Review Article Effect of Land Use and Climate...
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Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2013, Article ID 471429, 14 pages http://dx.doi.org/10.1155/2013/471429 Review Article Effect of Land Use and Climate Change on Runoff in the Dongjiang Basin of South China Yanhu He, 1,2 Kairong Lin, 1,2 and Xiaohong Chen 1,2 1 Center for Water Resources and Environment, Sun Yat-Sen University, Guangzhou 510275, China 2 Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong Higher Education Institutes, Guangzhou 510275, China Correspondence should be addressed to Xiaohong Chen; [email protected] Received 15 February 2013; Revised 15 May 2013; Accepted 1 June 2013 Academic Editor: Yongping Li Copyright © 2013 Yanhu He et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Variability and availability of water resources under changing environment in a regional scale have been hot topics in recent years, due to the vulnerability of water resources associated with social and economic development. In this paper, four subbasins in the Dongjiang basin with a significant land use change were selected as case study. Runoffs of the four subbasins were simulated using the SCS monthly model to identify the quantitative impacts of land use and climate change. e results showed that (1), in the Dongjiang basin, temperature increased significantly, evaporation and sunlight decreased strongly, while precipitation showed a nonsignificant increase; (2) since the 1980s, land uses in the Dongjiang basin have experienced a significant change with a prominent increase in urban areas, a moderate increase in farmlands, and a great decrease in forest areas; (3) the SCS monthly model performed well in the four subbasins giving that the more significant land use change in each subbasin, the more runoff change correspondingly; (4) overall, runoff change was contributed half and half by climate change and human activities, respectively, in all the subbasins, in which about 20%∼30% change was contributed by land use change. 1. Introduction Environment Change (including land use change and climate change) and its impacts on water resources have always been the hot issues in recent years. e direct or indirect impacts on the hydrological regime brought by land use and climate change both have contributed to some water problems, such as water shortage, flooding, and water logging to different extent. Some researches have been conducted to study the impacts of land use and climate change on water resources in different basins [1–5]. Particularly in the humid region of south China, six hydrological models were used to simulate the hydrological impact of some climate change scenarios, and response strategies for water supply and flood control due to climate change were analyzed in the Dongjiang basin by Jiang et al. [6]. South China has identified an increasing trend of extreme rainfall events, and the correlation between such events and flood events was studied by Fu et al. [7]. Climate change makes flooding more frequent in some regions [8, 9]. Additionally, land use change also has notable impact on the hydrological cycle [10–12]. Overall, hydrological process and the variability and availability of water resources would change a lot due to land use change and climate change. As the biggest developing country in the world, China has experienced an explosive economic growth over a couple of decades, which results in the prominent land use change. is change can alter evaporation patterns and potentially affect water resources in a region. e impacts of climate change on water resources and agriculture in China were analyzed by Piao et al. [13], and the results indicated that agriculture relying on the resultant increase in glacier runoff, especially in western China, would face a challenge, although its climate trends remained moderate compared to natural variability [13]. Even worse was the more frequent occurrence of drought and flood extremes largely due to climate change in different parts of China [14]. Some researches have focused on the variability of runoff in the Dongjiang basin under the impacts of climate change and human activities, especially land use change in recent decades [15]. Definitely, there is an increasingly serious challenge in the availability of water
Transcript of Review Article Effect of Land Use and Climate...
Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2013 Article ID 471429 14 pageshttpdxdoiorg1011552013471429
Review ArticleEffect of Land Use and Climate Change on Runoff inthe Dongjiang Basin of South China
Yanhu He12 Kairong Lin12 and Xiaohong Chen12
1 Center for Water Resources and Environment Sun Yat-Sen University Guangzhou 510275 China2 Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong Higher Education InstitutesGuangzhou 510275 China
Correspondence should be addressed to Xiaohong Chen eescxhmailsysueducn
Received 15 February 2013 Revised 15 May 2013 Accepted 1 June 2013
Academic Editor Yongping Li
Copyright copy 2013 Yanhu He et alThis is an open access article distributed under theCreativeCommonsAttribution License whichpermits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Variability and availability of water resources under changing environment in a regional scale have been hot topics in recent yearsdue to the vulnerability of water resources associated with social and economic development In this paper four subbasins in theDongjiang basin with a significant land use change were selected as case study Runoffs of the four subbasins were simulated usingthe SCS monthly model to identify the quantitative impacts of land use and climate change The results showed that (1) in theDongjiang basin temperature increased significantly evaporation and sunlight decreased strongly while precipitation showeda nonsignificant increase (2) since the 1980s land uses in the Dongjiang basin have experienced a significant change with aprominent increase in urban areas amoderate increase in farmlands and a great decrease in forest areas (3) the SCSmonthlymodelperformed well in the four subbasins giving that the more significant land use change in each subbasin the more runoff changecorrespondingly (4) overall runoff change was contributed half and half by climate change and human activities respectively inall the subbasins in which about 20sim30 change was contributed by land use change
1 Introduction
Environment Change (including land use change and climatechange) and its impacts on water resources have always beenthe hot issues in recent years The direct or indirect impactson the hydrological regime brought by land use and climatechange both have contributed to some water problems suchas water shortage flooding and water logging to differentextent Some researches have been conducted to study theimpacts of land use and climate change on water resourcesin different basins [1ndash5] Particularly in the humid region ofsouth China six hydrological models were used to simulatethe hydrological impact of some climate change scenariosand response strategies forwater supply and flood control dueto climate change were analyzed in the Dongjiang basin byJiang et al [6] South China has identified an increasing trendof extreme rainfall events and the correlation between suchevents and flood events was studied by Fu et al [7] Climatechange makes flooding more frequent in some regions [8 9]Additionally land use change also has notable impact on
the hydrological cycle [10ndash12] Overall hydrological processand the variability and availability of water resources wouldchange a lot due to land use change and climate change
As the biggest developing country in the world Chinahas experienced an explosive economic growth over a coupleof decades which results in the prominent land use changeThis change can alter evaporation patterns and potentiallyaffect water resources in a region The impacts of climatechange on water resources and agriculture in China wereanalyzed by Piao et al [13] and the results indicated thatagriculture relying on the resultant increase in glacier runoffespecially in western China would face a challenge althoughits climate trends remained moderate compared to naturalvariability [13] Evenworse was themore frequent occurrenceof drought and flood extremes largely due to climate changein different parts of China [14] Some researches have focusedon the variability of runoff in the Dongjiang basin under theimpacts of climate change and human activities especiallyland use change in recent decades [15] Definitely there isan increasingly serious challenge in the availability of water
2 Mathematical Problems in Engineering
resources and its exploitation and management will be moreor less affected
As to a basin climate change and human activities bothcontribute to the hydrological cycle and this finding hasbeen supported by many studies [16ndash19] Many studies havebeen carried out to distinguish the roles of land use andclimate change on water resources The approach to thecalculation for the runoff change due to precipitation andpotential evaporationwas proposed [20ndash22] Based onwhichthe separated impacts of human activities and climate changeon natural runoff change in the Poyang basin from 1992to 2000 were analyzed quantitatively by Ye et al [23] Inrecent years much attention has been paid to analyze theseparated quantitative effects of land use and climate changeand some progress has been made although further researchstill needs to be carried out A simple approach to distinguishland-use and climate-change effects on water resources wasdeveloped with a coupled water-energy budget analysis in USMidwest area by Tomer and Schilling [11] Combined impactsof land cover and climate changes on hydrological processesof the Kejie watershed in the easternHimalayas were assessedwith a SWAT model which revealed that land-cover changehad more effects than those of climate change in the shortand middle terms [24] Furthermore in many river basinsof China many studies have been conducted to assess theimpacts of climate change and human activities on the runoffvariation As to Tarim River the impact of human activitieshad increased the runoffwith a ratio of 41sim75 for differentages [25] and similar research can be found in the WudingRiver [26] In addition some relative studies also took placein the Heihe catchment Chaobai River andMian River basin[27ndash29] which came to a conclusion that climate change andhuman activities have the separated impacts on the runoffchange varying from place to place There is no exceptionfor the Dongjiang basin [30] However few researches havebeen conducted to identify the quantitative effects of humanactivities and climate change on runoff in the study areaMoreover most of the previous studies focused on a largescale basin and had no cases for comparison which tendsto limit our understanding of the impacts of climate changeand human activities on water resources in the study areaThe quantitative effect of land use change on runoff of thebasin has not been revealed yet Therefore it is desirable toseparate the impacts of climate change and human activitiesspecifically the land use change on water resources under achanging environment in the study area
Hydrological models have been widely used to studymany practical and pressing issues that arise during planningdesign operation and management of water resources sys-tems [31 32] and also to quantify the impacts of land useand climate change on the hydrological cycle For examplea conceptual rainfall-runoff model was applied to the Rhinebasin for the purpose of modeling the effect of land usechange on the runoff The results suggested that increasedurbanization led to an increase in the lower peak runoffcompared to a considerable reduction of both the peakrunoff and the total runoff volume resulted from intensifiedforestation [33] Besides the hydrological model consideringother elements such as biogeochemistry was applied to reveal
how land use change affects hydrological regimes at thewatershed scale [34] According to the available climate andhydrological data and the hydrological characteristics of thebasin studied many conceptual or distributed hydrologicalmodels were introduced to analyze the hydrological responseunder land use and climate change [35ndash38] Trend analysisof climate variables is necessary to detect the variabilityof climate variables such as temperature and precipitation[39 40] which provides supports for study of the impactson the hydrological cycle of land use change and climatechange Overall hydrological model combined with statisticmethods has been a prevalent and useful tool to clarify suchan interesting phenomenon for a long time
The Dongjiang River which lies in south China is animportant fresh water source of the Pearl River Delta (one ofthe most developed areas in China) Specifically it supplies70 fresh water forHongKong However water shortage andwater pollution in theDongjiang basin appear to bemore andmore serious in recent years due to the fast and persistenteconomic development and urbanization Land use in thisregion has changed prominently since 1980s and contributedto hydrological response in the Dongjiang basin Meanwhileclimate change under the global warming also plays animportant role in the variation of hydrological processesThecombined effects of land use and climate changes lead to aseries of conflicts between water use and water supply Inthis paper four sub-basins the Shuntian Lantang Jiuzhouand Yuecheng within the Dongjiang basin are selected forstudy (Figure 1) Major climate variables were taken to trendanalysis by using the Mann-Kendall test method and runoffsin two different periods (natural and human activity periods)were simulated with the SCS monthly model for each basinThe aims of this study are to explore the temporal and spatialcharacteristics of land use change and climate variables ineach sub-basin to study the possible causes of the changemore specifically to identify the roles played by land usechange and climate change as well as other human activitieson the runoff change respectively A comparison between theindependent effect of land use and climate change in the foursub-basins will be conducted
2 Basic Knowledge and Data
21 Study Area TheDongjiang River (Figure 1) springs fromJiangxi Province and flows into the Pearl River estuary fromnortheast to southwest which forms the Dongjiang basinThe Dongjiang basin is located between 113∘521015840 and 115∘521015840E in longitude and 22∘381015840and 25∘141015840 N in latitude This basinhas a drainage area of 35340 km2 about 90 of which is inGuangdong Province The mainstream of the basin is about562 km long with an average slope of about 0039 [30]
The Dongjiang basin has a subtropical climate with amean annual temperature of 21∘C The annual rainfall overthe basin varies between 1500mm in the dry season fromOctober to March and 2400mm in the wet or monsoonseason fromApril to SeptemberThe basin has some differentsoil types and the dominated type is alluvial which iscentered largely in the central and southern part of the basin
Mathematical Problems in Engineering 3
Hydrological stationWater systemWater supply route
0 1 2 3 4(km)
NE
SW
24∘N
23∘N
22∘N
24∘N
D1
D2
D3
23∘N
22∘N
114∘E 115
∘E 116∘E
114∘E 115
∘E 116∘E
Figure 1 The sketch map of the Dongjiang Basin
The major land use type of this area is forest although theurban area has extended year by year with the fast pace ofurbanization since the 1980s Locations of the four sub-basinsare shown in Figure 1
22 Development of Economy and Society The Dongjiangbasin has experienced a fast development of economy andsociety over the recent 30 years Population and GDP (grossdomestic product) of the three regions (Huizhou Heyuanand Dongguan) within the basin from 1980 were analyzedDetailed information can be seen in Figure 4
Population and economy in the three regions have kepta rapid and persistent development due to Chinarsquos reformand opening policy Refering to Figure 4 population of eachregion has been expanding rapidly since 1980 In whichpopulation of Huizhou had increased from 192 million in1980 to 36 million in 2006 with the average growth rateof 108 The GDP of each region also increased rapidlyespecially Dongguan whose GDP increased from 8 billionChinese Yuan in 1980 to 2627 billion Chinese Yuan in 2006with the average growth rate of 1434There is no doubt thatthe growth of population and the development of economydepend largely on land resources Therefore we can inferthat land use has changed greatly for decades in accordancewith the social and economic development in the studyarea
23 Data The climatic data used in the study includingtime series of annual average precipitation evaporationand temperature from 1956 to 2008 of the 21 meteoro-logical stations in the Dongjiang basin was provided bythe Guangdong Meteorological Bureau The monthly runofftime series for 4 hydrological stations (Shuntian LantangJiuzhou and Yuecheng) from 1970 to 2008 were acquiredfromHydrological Bureau of Guangdong ProvinceThe dailyprecipitation evaporation and runoff time series of the mainrainfall and hydrological stations in theDongjiang basin from1970 to 1978 were extracted from Water Conservancy andElectric Power Bureau of Guangdong Province
Two multitemporal satellite sensor images Landsat The-matic Mapper (TM) imagery of the 1980s and 2000s weredownloaded from Global Land Cover Facility Based onthe images two periods (1980s and 2000s) of land use andvegetation covermaps of theDongjiang basin (Figure 2) weregained with the ArcGIS spatial analysis technique A digitalelevation model (DEM) with a spatial resolution of 30m andsoil type data with a spatial resolution of 90m (Figure 3)of the Dongjiang basin were downloaded from China SoilScientific Database (CSSD) and CGIAR-CSI respectively
3 Methodologies
31 Mann-Kendall Test for Time-Series Trend Developedby Mann and later improved by Kendall [41 42] highly
4 Mathematical Problems in Engineering
1980 2000
NW E
S
FarmlandGardenForestMeadow
UrbanWaterUnutilized
Figure 2 Land uses of two periods (1980 and 2000) in theDongjiang basin
DEMSoil type
Minimum infiltration rate(mmh)
73sim11438sim7313sim380sim13
1500
N
SEW
0
Value
Figure 3 Soil type and DEM of the Dongjiang basin
recommended for general use by the World MeteorologicalOrganization [43] the Mann-Kendall test was widely usedto detect time-series trends in hydrological and climatic datain many researches The Mann-Kendall test has some advan-tages including its simplicity ability to deal with nonnormaland missing data distributions and robustness to the effectsof outliers and gross data errors [44ndash46]
Firstly the Mann-Kendall test defined a variable 119878 as
119878 =
119899minus1
sum
119896=1
119899
sum
119895=119896+1
sgn (119909119894minus 119909
119895) (1)
Then the presence of a statistically significant trend isevaluated using the 119885 value
119885 =
119878 minus 1
radicVar (119878) 119878 gt 0
0 119878 = 0
119878 + 1
radicVar (119878) 119878 lt 0
(2)
Besides the standard normal cumulative distributionfunction 119865
119899under the significance level 120572 is given by
119865
119899(119885
1205722) = 1205722 If |119885| gt 119885
1205722 the hypothesis of 119867
1for a
two-sided test can be accepted Positive value 119885 indicates anupward trend while negative value a downward trend Moredescriptions of this method can be found in many researches[47ndash49] In this paper trend analysis of climatic variablesand runoff in the Dongjiang basin were conducted with theMann-Kendall test based on over 50 years of climatic andhydrological data
In addition mutation detections of the climatic data werealso conducted by the Mann-Kendall mutation analysis testmethod a statistic variable of this method is
119878
119870=
119896
sum
119894=1
119903
119894 119896 = 2 3 119899
119903
119894=
+1 119909
119894gt 119909
119895
0 119909
119894le 119909
119895
119895 = 1 2 119894
(3)
where 119878119870is the counts for the 119909 series when 119909
119894is greater than
119909
119895119880119865
119870is the standard normal distribution and can be
calculated based on the 119909 series
119880119865
119870=
[119878
119870minus 119864 (119878
119870)]
radicvar (119878119870)
119896 = 1 2 119899 (4)
where 1198801198651=0 119864(119878
119870) and var(119878
119870) are the expected value and
variance of 119878119870which can be calculated on condition that the
119909 series is mutually independent with the same continuousdistribution
119864 (119878
119870) =
119899 (119899 + 1)
4
var (119878119870) =
119899 (119899 minus 1) (2119899 + 5)
72
(5)
32 SCS Rainfall-Runoff Model Developed by the Soil Con-servation Service of US Department of Agriculture (USDA)early in 1954 the SCS model is widely used in the USAand many other countries [50 51] Several advantages of thismodel are as follows (1) the characteristics of the land coversuch as soil slope vegetation and land use in a basin canbe considered with the SCS model the possible change onthe rainfall-runoff relationship can be preliminarily estimatedaccording to the change of land use and (2) it has theadvantages of simplicity in structure and convenience in usewith very low dependence on data
Mathematical Problems in Engineering 5
0
100
200
300
400
500
1980 1985 1990 1995 2000 2005Year
HuizhouHeyuanDongguan
HuizhouHeyuanDongguan
0
100
200
300
400
1980 1985 1990 1995 2000 2005Year
Popu
latio
n (m
illio
n)
GD
P (b
illio
n Yu
an)
Figure 4 Sketch map of economic and social development in the Dongjiang basin
Precipitation Evaporation
Soil moisture content zone
Ground water runoff
Surface runoff
Total runoff
P(t) EP(t)
SR(t)
R(t) = SR(t) + RG(t)
RG(t) = a times Z(t)
Z(t) = Z(t minus 1) + P(t) minus E(t)
+ SR(t) minus RG(t)
Figure 5 A schematic diagram of the water balance in a basin
The runoff yield for the SCS model is
119877 =
(119875 minus 119868
119886)
2
119875 + 119878 minus 119868
119886
119875 ge 119868
119886
0 119875 lt 119868
119886
(6)
where 119877 is the runoff P is the precipitation 119868119886is the initial
loss and 119878 is the present probable maximum retention in thebasin which is the top limit of the later loss
Initial loss 119868119886can be calculated by an empirical correlation
with S
119868
119886= 120572119878 (7)
where 120572 is the coefficient of the initial losses which is relatedto the initial soil water content of the basin
To eliminate the large variation scope of the 119878 valuethere is an empirical relation for CN (a non dimensionalparameter) and S
119878 =
25400
119862119873
minus 254 (8)
The curve number CN is a key and comprehensiveparameter within SCS model CN describes the watershedfeatures before a rain and is affected by AMC (antecedentmoisture condition) slope vegetation soil type and land use
condition with a value of 0sim100 AMC can be divided into3 classes AMC I-arid condition AMC II-normal conditionand AMC III-moist condition The specific basis for theclassification and the estimation of the CN value can be foundin related references [52]
Input by the observed monthly precipitation and evapo-ration the SCS model yields the monthly runoff A key issuehere is to calculate the actual evaporation by using the SCSmonthly model Based on the research results from the two-parameter monthly water balance model [53] the monthlyactual evaporation can be calculated by
119864 (119905) = 119862 times 119864119875 (119905) times tanh( 119875 (119905)
119864119875 (119905)
) (9)
where 119864(119905) is the actual monthly evaporation 119864119875(119905) is theobserved evaporation from the evaporating dish 119875(119905) is themonthly precipitation and 119862 is one of the parameters in themodel (nondimensional)
The total discharge consists of two parts the surface flow(119878119877(119905)) and the baseflow (119877119866(119905)) 119878119877(119905) can be gained by (6)while 119877119866(119905) can be calculated with
119877119866 (119905) = 119886 times 119885 (119905) (10)
where 119886 is the coefficient of the groundwater flow and 119885(119905) isthe soil moisture content which can be calculated by
119885 (119905) = 119885 (119905 minus 1) + 119875 (119905) minus 119864 (119905) + 119878119877 (119905) minus 119877119866 (119905) (11)
A schematic diagram for the water balance in a basinis shown in Figure 5 The SCS model is used to simulatethe monthly runoff process in this study There are twoparameters C and 120572 in the model
33 Approach to Distinguish the Respective Impact of LandUse and Climate Change to Water Resources The total runoffchange can be obtained by the difference between theobserved runoffs in two different periods respectively thatis the intensive human activities period and the low humanactivities period (natural condition) It is assumed that the
6 Mathematical Problems in Engineering
minus4
minus3
minus2
minus1
0
1
2
3
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(a) Precipitation
minus4
minus2
0
2
4
6
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(b) Temperature
minus5
minus4
minus3
minus2
minus1
0
1
2
3
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(c) Sunlight
minus4
minus2
0
2
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(d) Evaporation
Figure 6 Mann-Kendall test trend of four meteorological elements in the Dongjing basin
runoff change in the low human activities period is affectedonly by climate change
Therefore the impacts of climate change land use changeand other human activities on runoff change can be separatedaccording to the following calculations
Δ119877
119871= 119877
1198672minus 119877
1198671
Δ119877
119862= 119877
119861minus 119877
1198671
Δ119877
0= Δ119877
119879minus Δ119877
119862minus Δ119877
119871
Δ =
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
120583119871 =
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
Δ
times 100
120583119862 =
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
Δ
times 100
120583119877
0=
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
Δ
times 100
(12)
where Δ119877119871is the runoff change due to land use change from
time period of phase I to phase II 1198771198672
and 119877
1198671are the
simulated runoffs corresponding to the land uses of phase IIand phase I respectively and both of them can be calculatedwith the SCSmonthlymodelΔ119877
119862is the runoff change caused
by climate change 119877119861is the natural runoff of phase I Δ119877
119879is
the total runoff change Δ1198770is the runoff change due to other
human activities except for land use change 120583119871 120583119862 and 1205831198770
are the percentages for the roles played by land use changeclimate change and other human activities respectively
4 Results and Discussion
41 Time-Series Analysis The variation trends of the climaticvariables over 50 years in the study basin were analyzed withthe linear regression and Mann-Kendall trend test methodTable 1 listed the detailed results obtained by the Mann-Kendall trend test method Figure 6 demonstrated the resultsfor mutation analysis with the Mann-Kendall trend test andthe linear regression method respectively
It can be seen from Table 1 that each climatic variableshowed different degree of change in the Dongjiang basinduring the past 50 years (1959ndash2008) according to its statis-tics by the Mann-Kendall trend test method Precipitationshowed a nonsignificant increasing trend (119872 = 022) at 99confidence level which is largely due to local atmosphericcirculation and topography Temperature in the same periodshowed a significant increasing trend (119872 = 334) Whilesunlight showed a significant decreasing trend Meanwhilevery fast urbanization caused quick increase of impervious
Mathematical Problems in Engineering 7
Table 1 M-K trend analysis for meteorological elements in the Dongjiang basin (1958ndash2009)
StatisticsMeteorological elements
Precipitation Temperature Evaporation Humidity Sunlight(mm) (∘C) (mm) (gm3) (h)
119862 185292 2130 15724 781 1813119862V 016 002 005 003 009119862
119904
013 056 050 minus094 045119872 022 334 minus294 minus297 minus418
area in the study basin in the last 50 years These all con-tributed to a decreasing trend of evaporation Temperatureshowed an increasing trend with a distinct mutation takingplace around 1997 and sunlight and evaporation both hadan abrupt change in 1982 Overall the change of climaticvariables in the Dongjiang basin during the past 50 years wassignificant
It can be found from the119862V value of each climatic variablethat there was a significant internal variation for precipitationbut not for temperature It can be illustrated by both therainfall pattern and the atmospheric circulation in the studyarea Dongjiang basin is located in the southern humid regioninChina and deeply affected by themonsoon circulationwiththe rainfall patterns of frontal rain and convectional rainTherefore the internal variation of precipitation is significant
To clarify the relations among each climatic variable andthe runoff the correlation coefficients and relevancies wereanalyzed According to the spatial differences of land coverand climatic variables the Dongjiang basin was divided intothree parts the upper part centered with Longchuan markedD1 the middle part centered with Heyuan marked D2 andthe whole basin centered with Boluo marked D3 Tables2 and 3 listed the correlation coefficients and relevanciesrespectively It can be seen fromTable 2 that precipitationwaspositively related to runoff and their correlation coefficientwas the largest which revealed that runoff in the Dongjiangbasin depended mainly on precipitation In contrast tem-perature sunlight and evaporation were negatively related torunoff Among the three parts of the basin the correlationcoefficient of precipitation and runoff in D2 was the leastThe reason was that there located the biggest reservoir theXinfengjiang Reservoir (Figure 1) in D2 In addition morethan 20 middle and small sized reservoirs and hydraulicprojects were constructed in the same period which made amore significant change of land cover as compared to D1 andD3 Actually runoff in D2 is mainly controlled by regulationof the reservoir so precipitation was less correlation withrunoff in D2 Table 3 showed that the relevancy betweenprecipitation and runoff was the largest indicating thatprecipitation was the major driver for runoff change inthe whole study basin which is similar to the results ofcorrelation analysis
42 Land Use Change Analysis It has been found that theurban land and farmland increased in the study area [54]Based on the raster graphics for land use of two periods(1980 and 2000) temporal and spatial variations of land
use change in the Dongjiang basin were analyzed withthe ArcGIS spatial analysis technique Figure 2 showed themaps of land use in 1980 and 2000 respectively Table 4depicted the detailed information of the land use change inthe form of a comparison
It can be seen from Figure 2 that the dominant land usesin the study area in 1980 were mainly forest (widely dis-tributed in thewhole basin) and farmland (mainly distributedin the upper basin) accounting for 6456 and 2233respectively while garden meadow and water took a littlepart with the percentage of 594 471 and 228 respec-tively Urban land mainly distributed in the downstreambasin and the unutilized land took the least percentage in theDongjiang basinThe area of two types of land use urban landand farmland increased from 1980 along with the decreaseof garden (265)meadow (123) water (049) and forest(238) in 2000 while the dominant land use was still forestin 2000 In all since 1980s the landuse in theDongjiang basinhas been characterized with a prominent increase in urbanland a little increase in farmland and great decrease in forestarea while little change inwater area andunutilized landThisland use change due to fast social and economic developmenthad a significant impact on the hydrological response andthen contributed to the variability of water resources in theregion
43 Runoff Simulation and Runoff Change Analysis
431 The Value of CN CN (curve number) can reflect thecapacity of runoff yield for the land cover with a continuousspatial distribution The CN isocline represents the runoffyield capacities in the study basin
Based on land use maps of two periods (1980 and 2000)and soil type data of the Dongjiang basin CN distributionmaps (see Figure 7) of 3 AMC (antecedent moisture condi-tion) scenarios in the same periodswere obtainedwith spatialinterpolation Figure 8 showed the CN distribution maps forAMC II of the four sub-basins in the two periods
432 Model Calibration and Validation The SCS monthlymodel was calibrated in the period of 1970ndash1976 with climaticdata and then validated in the period of 1977-1978 by manualcalibration method with the acceptable set of parametersafter CN value analysis To measure the performance of themodel we chose Nash-Sutcliffe coefficient of efficiency (NSE)criterion [55] and relative error (RE) as objective function
8 Mathematical Problems in Engineering
Table 2 The correlation coefficient of each meteorological element to runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight HumidityD1 Upper Longchuan minus010 080 minus04 minus035 027D2 Midstream Heyuan minus023 069 minus028 minus039 035D The whole Basin Boluo minus008 088 minus054 minus057 026
Table 3 The relevancies between each meteorological element and runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight Humidity
D1 Upper Longchuan 04884 05503 04688 0449 04702Rank 2 1 4 5 3
D2 Midstream Heyuan 04857 05389 04659 04313 04861Rank 3 1 4 5 2
D The whole basin Boluo 0525 05968 04883 04495 05239Rank 2 1 4 5 3
Table 4 Comparison of land use in the Dongjiang basin during two different periods
Land use The year 1980 The year 2000Δ area (km
2) Ratio ()Area (km2) Ratio () Area (km2) Ratio ()
Farmland 608349 2233 727273 2669 118924 436Garden 161914 594 89670 329 minus72244 minus265Forest 1758688 6456 1693987 6218 minus64701 minus238Meadow 128274 471 94714 348 minus33560 minus123Built-up 3002 012 68225 25 65223 238Waters 61999 228 48012 179 minus13987 minus049Unutilized land 1738 006 2080 007 342 001
1980 1980 1980
2000 2000 2000
AMC I AMC II AMC III
Figure 7 Comparison of CN distribution under 3 AMC scenarios in the Dongjiang basin of two periods (1980 and 2000)
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Mathematical Problems in Engineering
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Differential EquationsInternational Journal of
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Applied MathematicsJournal of
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Discrete Dynamics in Nature and Society
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
2 Mathematical Problems in Engineering
resources and its exploitation and management will be moreor less affected
As to a basin climate change and human activities bothcontribute to the hydrological cycle and this finding hasbeen supported by many studies [16ndash19] Many studies havebeen carried out to distinguish the roles of land use andclimate change on water resources The approach to thecalculation for the runoff change due to precipitation andpotential evaporationwas proposed [20ndash22] Based onwhichthe separated impacts of human activities and climate changeon natural runoff change in the Poyang basin from 1992to 2000 were analyzed quantitatively by Ye et al [23] Inrecent years much attention has been paid to analyze theseparated quantitative effects of land use and climate changeand some progress has been made although further researchstill needs to be carried out A simple approach to distinguishland-use and climate-change effects on water resources wasdeveloped with a coupled water-energy budget analysis in USMidwest area by Tomer and Schilling [11] Combined impactsof land cover and climate changes on hydrological processesof the Kejie watershed in the easternHimalayas were assessedwith a SWAT model which revealed that land-cover changehad more effects than those of climate change in the shortand middle terms [24] Furthermore in many river basinsof China many studies have been conducted to assess theimpacts of climate change and human activities on the runoffvariation As to Tarim River the impact of human activitieshad increased the runoffwith a ratio of 41sim75 for differentages [25] and similar research can be found in the WudingRiver [26] In addition some relative studies also took placein the Heihe catchment Chaobai River andMian River basin[27ndash29] which came to a conclusion that climate change andhuman activities have the separated impacts on the runoffchange varying from place to place There is no exceptionfor the Dongjiang basin [30] However few researches havebeen conducted to identify the quantitative effects of humanactivities and climate change on runoff in the study areaMoreover most of the previous studies focused on a largescale basin and had no cases for comparison which tendsto limit our understanding of the impacts of climate changeand human activities on water resources in the study areaThe quantitative effect of land use change on runoff of thebasin has not been revealed yet Therefore it is desirable toseparate the impacts of climate change and human activitiesspecifically the land use change on water resources under achanging environment in the study area
Hydrological models have been widely used to studymany practical and pressing issues that arise during planningdesign operation and management of water resources sys-tems [31 32] and also to quantify the impacts of land useand climate change on the hydrological cycle For examplea conceptual rainfall-runoff model was applied to the Rhinebasin for the purpose of modeling the effect of land usechange on the runoff The results suggested that increasedurbanization led to an increase in the lower peak runoffcompared to a considerable reduction of both the peakrunoff and the total runoff volume resulted from intensifiedforestation [33] Besides the hydrological model consideringother elements such as biogeochemistry was applied to reveal
how land use change affects hydrological regimes at thewatershed scale [34] According to the available climate andhydrological data and the hydrological characteristics of thebasin studied many conceptual or distributed hydrologicalmodels were introduced to analyze the hydrological responseunder land use and climate change [35ndash38] Trend analysisof climate variables is necessary to detect the variabilityof climate variables such as temperature and precipitation[39 40] which provides supports for study of the impactson the hydrological cycle of land use change and climatechange Overall hydrological model combined with statisticmethods has been a prevalent and useful tool to clarify suchan interesting phenomenon for a long time
The Dongjiang River which lies in south China is animportant fresh water source of the Pearl River Delta (one ofthe most developed areas in China) Specifically it supplies70 fresh water forHongKong However water shortage andwater pollution in theDongjiang basin appear to bemore andmore serious in recent years due to the fast and persistenteconomic development and urbanization Land use in thisregion has changed prominently since 1980s and contributedto hydrological response in the Dongjiang basin Meanwhileclimate change under the global warming also plays animportant role in the variation of hydrological processesThecombined effects of land use and climate changes lead to aseries of conflicts between water use and water supply Inthis paper four sub-basins the Shuntian Lantang Jiuzhouand Yuecheng within the Dongjiang basin are selected forstudy (Figure 1) Major climate variables were taken to trendanalysis by using the Mann-Kendall test method and runoffsin two different periods (natural and human activity periods)were simulated with the SCS monthly model for each basinThe aims of this study are to explore the temporal and spatialcharacteristics of land use change and climate variables ineach sub-basin to study the possible causes of the changemore specifically to identify the roles played by land usechange and climate change as well as other human activitieson the runoff change respectively A comparison between theindependent effect of land use and climate change in the foursub-basins will be conducted
2 Basic Knowledge and Data
21 Study Area TheDongjiang River (Figure 1) springs fromJiangxi Province and flows into the Pearl River estuary fromnortheast to southwest which forms the Dongjiang basinThe Dongjiang basin is located between 113∘521015840 and 115∘521015840E in longitude and 22∘381015840and 25∘141015840 N in latitude This basinhas a drainage area of 35340 km2 about 90 of which is inGuangdong Province The mainstream of the basin is about562 km long with an average slope of about 0039 [30]
The Dongjiang basin has a subtropical climate with amean annual temperature of 21∘C The annual rainfall overthe basin varies between 1500mm in the dry season fromOctober to March and 2400mm in the wet or monsoonseason fromApril to SeptemberThe basin has some differentsoil types and the dominated type is alluvial which iscentered largely in the central and southern part of the basin
Mathematical Problems in Engineering 3
Hydrological stationWater systemWater supply route
0 1 2 3 4(km)
NE
SW
24∘N
23∘N
22∘N
24∘N
D1
D2
D3
23∘N
22∘N
114∘E 115
∘E 116∘E
114∘E 115
∘E 116∘E
Figure 1 The sketch map of the Dongjiang Basin
The major land use type of this area is forest although theurban area has extended year by year with the fast pace ofurbanization since the 1980s Locations of the four sub-basinsare shown in Figure 1
22 Development of Economy and Society The Dongjiangbasin has experienced a fast development of economy andsociety over the recent 30 years Population and GDP (grossdomestic product) of the three regions (Huizhou Heyuanand Dongguan) within the basin from 1980 were analyzedDetailed information can be seen in Figure 4
Population and economy in the three regions have kepta rapid and persistent development due to Chinarsquos reformand opening policy Refering to Figure 4 population of eachregion has been expanding rapidly since 1980 In whichpopulation of Huizhou had increased from 192 million in1980 to 36 million in 2006 with the average growth rateof 108 The GDP of each region also increased rapidlyespecially Dongguan whose GDP increased from 8 billionChinese Yuan in 1980 to 2627 billion Chinese Yuan in 2006with the average growth rate of 1434There is no doubt thatthe growth of population and the development of economydepend largely on land resources Therefore we can inferthat land use has changed greatly for decades in accordancewith the social and economic development in the studyarea
23 Data The climatic data used in the study includingtime series of annual average precipitation evaporationand temperature from 1956 to 2008 of the 21 meteoro-logical stations in the Dongjiang basin was provided bythe Guangdong Meteorological Bureau The monthly runofftime series for 4 hydrological stations (Shuntian LantangJiuzhou and Yuecheng) from 1970 to 2008 were acquiredfromHydrological Bureau of Guangdong ProvinceThe dailyprecipitation evaporation and runoff time series of the mainrainfall and hydrological stations in theDongjiang basin from1970 to 1978 were extracted from Water Conservancy andElectric Power Bureau of Guangdong Province
Two multitemporal satellite sensor images Landsat The-matic Mapper (TM) imagery of the 1980s and 2000s weredownloaded from Global Land Cover Facility Based onthe images two periods (1980s and 2000s) of land use andvegetation covermaps of theDongjiang basin (Figure 2) weregained with the ArcGIS spatial analysis technique A digitalelevation model (DEM) with a spatial resolution of 30m andsoil type data with a spatial resolution of 90m (Figure 3)of the Dongjiang basin were downloaded from China SoilScientific Database (CSSD) and CGIAR-CSI respectively
3 Methodologies
31 Mann-Kendall Test for Time-Series Trend Developedby Mann and later improved by Kendall [41 42] highly
4 Mathematical Problems in Engineering
1980 2000
NW E
S
FarmlandGardenForestMeadow
UrbanWaterUnutilized
Figure 2 Land uses of two periods (1980 and 2000) in theDongjiang basin
DEMSoil type
Minimum infiltration rate(mmh)
73sim11438sim7313sim380sim13
1500
N
SEW
0
Value
Figure 3 Soil type and DEM of the Dongjiang basin
recommended for general use by the World MeteorologicalOrganization [43] the Mann-Kendall test was widely usedto detect time-series trends in hydrological and climatic datain many researches The Mann-Kendall test has some advan-tages including its simplicity ability to deal with nonnormaland missing data distributions and robustness to the effectsof outliers and gross data errors [44ndash46]
Firstly the Mann-Kendall test defined a variable 119878 as
119878 =
119899minus1
sum
119896=1
119899
sum
119895=119896+1
sgn (119909119894minus 119909
119895) (1)
Then the presence of a statistically significant trend isevaluated using the 119885 value
119885 =
119878 minus 1
radicVar (119878) 119878 gt 0
0 119878 = 0
119878 + 1
radicVar (119878) 119878 lt 0
(2)
Besides the standard normal cumulative distributionfunction 119865
119899under the significance level 120572 is given by
119865
119899(119885
1205722) = 1205722 If |119885| gt 119885
1205722 the hypothesis of 119867
1for a
two-sided test can be accepted Positive value 119885 indicates anupward trend while negative value a downward trend Moredescriptions of this method can be found in many researches[47ndash49] In this paper trend analysis of climatic variablesand runoff in the Dongjiang basin were conducted with theMann-Kendall test based on over 50 years of climatic andhydrological data
In addition mutation detections of the climatic data werealso conducted by the Mann-Kendall mutation analysis testmethod a statistic variable of this method is
119878
119870=
119896
sum
119894=1
119903
119894 119896 = 2 3 119899
119903
119894=
+1 119909
119894gt 119909
119895
0 119909
119894le 119909
119895
119895 = 1 2 119894
(3)
where 119878119870is the counts for the 119909 series when 119909
119894is greater than
119909
119895119880119865
119870is the standard normal distribution and can be
calculated based on the 119909 series
119880119865
119870=
[119878
119870minus 119864 (119878
119870)]
radicvar (119878119870)
119896 = 1 2 119899 (4)
where 1198801198651=0 119864(119878
119870) and var(119878
119870) are the expected value and
variance of 119878119870which can be calculated on condition that the
119909 series is mutually independent with the same continuousdistribution
119864 (119878
119870) =
119899 (119899 + 1)
4
var (119878119870) =
119899 (119899 minus 1) (2119899 + 5)
72
(5)
32 SCS Rainfall-Runoff Model Developed by the Soil Con-servation Service of US Department of Agriculture (USDA)early in 1954 the SCS model is widely used in the USAand many other countries [50 51] Several advantages of thismodel are as follows (1) the characteristics of the land coversuch as soil slope vegetation and land use in a basin canbe considered with the SCS model the possible change onthe rainfall-runoff relationship can be preliminarily estimatedaccording to the change of land use and (2) it has theadvantages of simplicity in structure and convenience in usewith very low dependence on data
Mathematical Problems in Engineering 5
0
100
200
300
400
500
1980 1985 1990 1995 2000 2005Year
HuizhouHeyuanDongguan
HuizhouHeyuanDongguan
0
100
200
300
400
1980 1985 1990 1995 2000 2005Year
Popu
latio
n (m
illio
n)
GD
P (b
illio
n Yu
an)
Figure 4 Sketch map of economic and social development in the Dongjiang basin
Precipitation Evaporation
Soil moisture content zone
Ground water runoff
Surface runoff
Total runoff
P(t) EP(t)
SR(t)
R(t) = SR(t) + RG(t)
RG(t) = a times Z(t)
Z(t) = Z(t minus 1) + P(t) minus E(t)
+ SR(t) minus RG(t)
Figure 5 A schematic diagram of the water balance in a basin
The runoff yield for the SCS model is
119877 =
(119875 minus 119868
119886)
2
119875 + 119878 minus 119868
119886
119875 ge 119868
119886
0 119875 lt 119868
119886
(6)
where 119877 is the runoff P is the precipitation 119868119886is the initial
loss and 119878 is the present probable maximum retention in thebasin which is the top limit of the later loss
Initial loss 119868119886can be calculated by an empirical correlation
with S
119868
119886= 120572119878 (7)
where 120572 is the coefficient of the initial losses which is relatedto the initial soil water content of the basin
To eliminate the large variation scope of the 119878 valuethere is an empirical relation for CN (a non dimensionalparameter) and S
119878 =
25400
119862119873
minus 254 (8)
The curve number CN is a key and comprehensiveparameter within SCS model CN describes the watershedfeatures before a rain and is affected by AMC (antecedentmoisture condition) slope vegetation soil type and land use
condition with a value of 0sim100 AMC can be divided into3 classes AMC I-arid condition AMC II-normal conditionand AMC III-moist condition The specific basis for theclassification and the estimation of the CN value can be foundin related references [52]
Input by the observed monthly precipitation and evapo-ration the SCS model yields the monthly runoff A key issuehere is to calculate the actual evaporation by using the SCSmonthly model Based on the research results from the two-parameter monthly water balance model [53] the monthlyactual evaporation can be calculated by
119864 (119905) = 119862 times 119864119875 (119905) times tanh( 119875 (119905)
119864119875 (119905)
) (9)
where 119864(119905) is the actual monthly evaporation 119864119875(119905) is theobserved evaporation from the evaporating dish 119875(119905) is themonthly precipitation and 119862 is one of the parameters in themodel (nondimensional)
The total discharge consists of two parts the surface flow(119878119877(119905)) and the baseflow (119877119866(119905)) 119878119877(119905) can be gained by (6)while 119877119866(119905) can be calculated with
119877119866 (119905) = 119886 times 119885 (119905) (10)
where 119886 is the coefficient of the groundwater flow and 119885(119905) isthe soil moisture content which can be calculated by
119885 (119905) = 119885 (119905 minus 1) + 119875 (119905) minus 119864 (119905) + 119878119877 (119905) minus 119877119866 (119905) (11)
A schematic diagram for the water balance in a basinis shown in Figure 5 The SCS model is used to simulatethe monthly runoff process in this study There are twoparameters C and 120572 in the model
33 Approach to Distinguish the Respective Impact of LandUse and Climate Change to Water Resources The total runoffchange can be obtained by the difference between theobserved runoffs in two different periods respectively thatis the intensive human activities period and the low humanactivities period (natural condition) It is assumed that the
6 Mathematical Problems in Engineering
minus4
minus3
minus2
minus1
0
1
2
3
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(a) Precipitation
minus4
minus2
0
2
4
6
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(b) Temperature
minus5
minus4
minus3
minus2
minus1
0
1
2
3
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(c) Sunlight
minus4
minus2
0
2
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(d) Evaporation
Figure 6 Mann-Kendall test trend of four meteorological elements in the Dongjing basin
runoff change in the low human activities period is affectedonly by climate change
Therefore the impacts of climate change land use changeand other human activities on runoff change can be separatedaccording to the following calculations
Δ119877
119871= 119877
1198672minus 119877
1198671
Δ119877
119862= 119877
119861minus 119877
1198671
Δ119877
0= Δ119877
119879minus Δ119877
119862minus Δ119877
119871
Δ =
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
120583119871 =
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
Δ
times 100
120583119862 =
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
Δ
times 100
120583119877
0=
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
Δ
times 100
(12)
where Δ119877119871is the runoff change due to land use change from
time period of phase I to phase II 1198771198672
and 119877
1198671are the
simulated runoffs corresponding to the land uses of phase IIand phase I respectively and both of them can be calculatedwith the SCSmonthlymodelΔ119877
119862is the runoff change caused
by climate change 119877119861is the natural runoff of phase I Δ119877
119879is
the total runoff change Δ1198770is the runoff change due to other
human activities except for land use change 120583119871 120583119862 and 1205831198770
are the percentages for the roles played by land use changeclimate change and other human activities respectively
4 Results and Discussion
41 Time-Series Analysis The variation trends of the climaticvariables over 50 years in the study basin were analyzed withthe linear regression and Mann-Kendall trend test methodTable 1 listed the detailed results obtained by the Mann-Kendall trend test method Figure 6 demonstrated the resultsfor mutation analysis with the Mann-Kendall trend test andthe linear regression method respectively
It can be seen from Table 1 that each climatic variableshowed different degree of change in the Dongjiang basinduring the past 50 years (1959ndash2008) according to its statis-tics by the Mann-Kendall trend test method Precipitationshowed a nonsignificant increasing trend (119872 = 022) at 99confidence level which is largely due to local atmosphericcirculation and topography Temperature in the same periodshowed a significant increasing trend (119872 = 334) Whilesunlight showed a significant decreasing trend Meanwhilevery fast urbanization caused quick increase of impervious
Mathematical Problems in Engineering 7
Table 1 M-K trend analysis for meteorological elements in the Dongjiang basin (1958ndash2009)
StatisticsMeteorological elements
Precipitation Temperature Evaporation Humidity Sunlight(mm) (∘C) (mm) (gm3) (h)
119862 185292 2130 15724 781 1813119862V 016 002 005 003 009119862
119904
013 056 050 minus094 045119872 022 334 minus294 minus297 minus418
area in the study basin in the last 50 years These all con-tributed to a decreasing trend of evaporation Temperatureshowed an increasing trend with a distinct mutation takingplace around 1997 and sunlight and evaporation both hadan abrupt change in 1982 Overall the change of climaticvariables in the Dongjiang basin during the past 50 years wassignificant
It can be found from the119862V value of each climatic variablethat there was a significant internal variation for precipitationbut not for temperature It can be illustrated by both therainfall pattern and the atmospheric circulation in the studyarea Dongjiang basin is located in the southern humid regioninChina and deeply affected by themonsoon circulationwiththe rainfall patterns of frontal rain and convectional rainTherefore the internal variation of precipitation is significant
To clarify the relations among each climatic variable andthe runoff the correlation coefficients and relevancies wereanalyzed According to the spatial differences of land coverand climatic variables the Dongjiang basin was divided intothree parts the upper part centered with Longchuan markedD1 the middle part centered with Heyuan marked D2 andthe whole basin centered with Boluo marked D3 Tables2 and 3 listed the correlation coefficients and relevanciesrespectively It can be seen fromTable 2 that precipitationwaspositively related to runoff and their correlation coefficientwas the largest which revealed that runoff in the Dongjiangbasin depended mainly on precipitation In contrast tem-perature sunlight and evaporation were negatively related torunoff Among the three parts of the basin the correlationcoefficient of precipitation and runoff in D2 was the leastThe reason was that there located the biggest reservoir theXinfengjiang Reservoir (Figure 1) in D2 In addition morethan 20 middle and small sized reservoirs and hydraulicprojects were constructed in the same period which made amore significant change of land cover as compared to D1 andD3 Actually runoff in D2 is mainly controlled by regulationof the reservoir so precipitation was less correlation withrunoff in D2 Table 3 showed that the relevancy betweenprecipitation and runoff was the largest indicating thatprecipitation was the major driver for runoff change inthe whole study basin which is similar to the results ofcorrelation analysis
42 Land Use Change Analysis It has been found that theurban land and farmland increased in the study area [54]Based on the raster graphics for land use of two periods(1980 and 2000) temporal and spatial variations of land
use change in the Dongjiang basin were analyzed withthe ArcGIS spatial analysis technique Figure 2 showed themaps of land use in 1980 and 2000 respectively Table 4depicted the detailed information of the land use change inthe form of a comparison
It can be seen from Figure 2 that the dominant land usesin the study area in 1980 were mainly forest (widely dis-tributed in thewhole basin) and farmland (mainly distributedin the upper basin) accounting for 6456 and 2233respectively while garden meadow and water took a littlepart with the percentage of 594 471 and 228 respec-tively Urban land mainly distributed in the downstreambasin and the unutilized land took the least percentage in theDongjiang basinThe area of two types of land use urban landand farmland increased from 1980 along with the decreaseof garden (265)meadow (123) water (049) and forest(238) in 2000 while the dominant land use was still forestin 2000 In all since 1980s the landuse in theDongjiang basinhas been characterized with a prominent increase in urbanland a little increase in farmland and great decrease in forestarea while little change inwater area andunutilized landThisland use change due to fast social and economic developmenthad a significant impact on the hydrological response andthen contributed to the variability of water resources in theregion
43 Runoff Simulation and Runoff Change Analysis
431 The Value of CN CN (curve number) can reflect thecapacity of runoff yield for the land cover with a continuousspatial distribution The CN isocline represents the runoffyield capacities in the study basin
Based on land use maps of two periods (1980 and 2000)and soil type data of the Dongjiang basin CN distributionmaps (see Figure 7) of 3 AMC (antecedent moisture condi-tion) scenarios in the same periodswere obtainedwith spatialinterpolation Figure 8 showed the CN distribution maps forAMC II of the four sub-basins in the two periods
432 Model Calibration and Validation The SCS monthlymodel was calibrated in the period of 1970ndash1976 with climaticdata and then validated in the period of 1977-1978 by manualcalibration method with the acceptable set of parametersafter CN value analysis To measure the performance of themodel we chose Nash-Sutcliffe coefficient of efficiency (NSE)criterion [55] and relative error (RE) as objective function
8 Mathematical Problems in Engineering
Table 2 The correlation coefficient of each meteorological element to runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight HumidityD1 Upper Longchuan minus010 080 minus04 minus035 027D2 Midstream Heyuan minus023 069 minus028 minus039 035D The whole Basin Boluo minus008 088 minus054 minus057 026
Table 3 The relevancies between each meteorological element and runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight Humidity
D1 Upper Longchuan 04884 05503 04688 0449 04702Rank 2 1 4 5 3
D2 Midstream Heyuan 04857 05389 04659 04313 04861Rank 3 1 4 5 2
D The whole basin Boluo 0525 05968 04883 04495 05239Rank 2 1 4 5 3
Table 4 Comparison of land use in the Dongjiang basin during two different periods
Land use The year 1980 The year 2000Δ area (km
2) Ratio ()Area (km2) Ratio () Area (km2) Ratio ()
Farmland 608349 2233 727273 2669 118924 436Garden 161914 594 89670 329 minus72244 minus265Forest 1758688 6456 1693987 6218 minus64701 minus238Meadow 128274 471 94714 348 minus33560 minus123Built-up 3002 012 68225 25 65223 238Waters 61999 228 48012 179 minus13987 minus049Unutilized land 1738 006 2080 007 342 001
1980 1980 1980
2000 2000 2000
AMC I AMC II AMC III
Figure 7 Comparison of CN distribution under 3 AMC scenarios in the Dongjiang basin of two periods (1980 and 2000)
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Mathematical Problems in Engineering 3
Hydrological stationWater systemWater supply route
0 1 2 3 4(km)
NE
SW
24∘N
23∘N
22∘N
24∘N
D1
D2
D3
23∘N
22∘N
114∘E 115
∘E 116∘E
114∘E 115
∘E 116∘E
Figure 1 The sketch map of the Dongjiang Basin
The major land use type of this area is forest although theurban area has extended year by year with the fast pace ofurbanization since the 1980s Locations of the four sub-basinsare shown in Figure 1
22 Development of Economy and Society The Dongjiangbasin has experienced a fast development of economy andsociety over the recent 30 years Population and GDP (grossdomestic product) of the three regions (Huizhou Heyuanand Dongguan) within the basin from 1980 were analyzedDetailed information can be seen in Figure 4
Population and economy in the three regions have kepta rapid and persistent development due to Chinarsquos reformand opening policy Refering to Figure 4 population of eachregion has been expanding rapidly since 1980 In whichpopulation of Huizhou had increased from 192 million in1980 to 36 million in 2006 with the average growth rateof 108 The GDP of each region also increased rapidlyespecially Dongguan whose GDP increased from 8 billionChinese Yuan in 1980 to 2627 billion Chinese Yuan in 2006with the average growth rate of 1434There is no doubt thatthe growth of population and the development of economydepend largely on land resources Therefore we can inferthat land use has changed greatly for decades in accordancewith the social and economic development in the studyarea
23 Data The climatic data used in the study includingtime series of annual average precipitation evaporationand temperature from 1956 to 2008 of the 21 meteoro-logical stations in the Dongjiang basin was provided bythe Guangdong Meteorological Bureau The monthly runofftime series for 4 hydrological stations (Shuntian LantangJiuzhou and Yuecheng) from 1970 to 2008 were acquiredfromHydrological Bureau of Guangdong ProvinceThe dailyprecipitation evaporation and runoff time series of the mainrainfall and hydrological stations in theDongjiang basin from1970 to 1978 were extracted from Water Conservancy andElectric Power Bureau of Guangdong Province
Two multitemporal satellite sensor images Landsat The-matic Mapper (TM) imagery of the 1980s and 2000s weredownloaded from Global Land Cover Facility Based onthe images two periods (1980s and 2000s) of land use andvegetation covermaps of theDongjiang basin (Figure 2) weregained with the ArcGIS spatial analysis technique A digitalelevation model (DEM) with a spatial resolution of 30m andsoil type data with a spatial resolution of 90m (Figure 3)of the Dongjiang basin were downloaded from China SoilScientific Database (CSSD) and CGIAR-CSI respectively
3 Methodologies
31 Mann-Kendall Test for Time-Series Trend Developedby Mann and later improved by Kendall [41 42] highly
4 Mathematical Problems in Engineering
1980 2000
NW E
S
FarmlandGardenForestMeadow
UrbanWaterUnutilized
Figure 2 Land uses of two periods (1980 and 2000) in theDongjiang basin
DEMSoil type
Minimum infiltration rate(mmh)
73sim11438sim7313sim380sim13
1500
N
SEW
0
Value
Figure 3 Soil type and DEM of the Dongjiang basin
recommended for general use by the World MeteorologicalOrganization [43] the Mann-Kendall test was widely usedto detect time-series trends in hydrological and climatic datain many researches The Mann-Kendall test has some advan-tages including its simplicity ability to deal with nonnormaland missing data distributions and robustness to the effectsof outliers and gross data errors [44ndash46]
Firstly the Mann-Kendall test defined a variable 119878 as
119878 =
119899minus1
sum
119896=1
119899
sum
119895=119896+1
sgn (119909119894minus 119909
119895) (1)
Then the presence of a statistically significant trend isevaluated using the 119885 value
119885 =
119878 minus 1
radicVar (119878) 119878 gt 0
0 119878 = 0
119878 + 1
radicVar (119878) 119878 lt 0
(2)
Besides the standard normal cumulative distributionfunction 119865
119899under the significance level 120572 is given by
119865
119899(119885
1205722) = 1205722 If |119885| gt 119885
1205722 the hypothesis of 119867
1for a
two-sided test can be accepted Positive value 119885 indicates anupward trend while negative value a downward trend Moredescriptions of this method can be found in many researches[47ndash49] In this paper trend analysis of climatic variablesand runoff in the Dongjiang basin were conducted with theMann-Kendall test based on over 50 years of climatic andhydrological data
In addition mutation detections of the climatic data werealso conducted by the Mann-Kendall mutation analysis testmethod a statistic variable of this method is
119878
119870=
119896
sum
119894=1
119903
119894 119896 = 2 3 119899
119903
119894=
+1 119909
119894gt 119909
119895
0 119909
119894le 119909
119895
119895 = 1 2 119894
(3)
where 119878119870is the counts for the 119909 series when 119909
119894is greater than
119909
119895119880119865
119870is the standard normal distribution and can be
calculated based on the 119909 series
119880119865
119870=
[119878
119870minus 119864 (119878
119870)]
radicvar (119878119870)
119896 = 1 2 119899 (4)
where 1198801198651=0 119864(119878
119870) and var(119878
119870) are the expected value and
variance of 119878119870which can be calculated on condition that the
119909 series is mutually independent with the same continuousdistribution
119864 (119878
119870) =
119899 (119899 + 1)
4
var (119878119870) =
119899 (119899 minus 1) (2119899 + 5)
72
(5)
32 SCS Rainfall-Runoff Model Developed by the Soil Con-servation Service of US Department of Agriculture (USDA)early in 1954 the SCS model is widely used in the USAand many other countries [50 51] Several advantages of thismodel are as follows (1) the characteristics of the land coversuch as soil slope vegetation and land use in a basin canbe considered with the SCS model the possible change onthe rainfall-runoff relationship can be preliminarily estimatedaccording to the change of land use and (2) it has theadvantages of simplicity in structure and convenience in usewith very low dependence on data
Mathematical Problems in Engineering 5
0
100
200
300
400
500
1980 1985 1990 1995 2000 2005Year
HuizhouHeyuanDongguan
HuizhouHeyuanDongguan
0
100
200
300
400
1980 1985 1990 1995 2000 2005Year
Popu
latio
n (m
illio
n)
GD
P (b
illio
n Yu
an)
Figure 4 Sketch map of economic and social development in the Dongjiang basin
Precipitation Evaporation
Soil moisture content zone
Ground water runoff
Surface runoff
Total runoff
P(t) EP(t)
SR(t)
R(t) = SR(t) + RG(t)
RG(t) = a times Z(t)
Z(t) = Z(t minus 1) + P(t) minus E(t)
+ SR(t) minus RG(t)
Figure 5 A schematic diagram of the water balance in a basin
The runoff yield for the SCS model is
119877 =
(119875 minus 119868
119886)
2
119875 + 119878 minus 119868
119886
119875 ge 119868
119886
0 119875 lt 119868
119886
(6)
where 119877 is the runoff P is the precipitation 119868119886is the initial
loss and 119878 is the present probable maximum retention in thebasin which is the top limit of the later loss
Initial loss 119868119886can be calculated by an empirical correlation
with S
119868
119886= 120572119878 (7)
where 120572 is the coefficient of the initial losses which is relatedto the initial soil water content of the basin
To eliminate the large variation scope of the 119878 valuethere is an empirical relation for CN (a non dimensionalparameter) and S
119878 =
25400
119862119873
minus 254 (8)
The curve number CN is a key and comprehensiveparameter within SCS model CN describes the watershedfeatures before a rain and is affected by AMC (antecedentmoisture condition) slope vegetation soil type and land use
condition with a value of 0sim100 AMC can be divided into3 classes AMC I-arid condition AMC II-normal conditionand AMC III-moist condition The specific basis for theclassification and the estimation of the CN value can be foundin related references [52]
Input by the observed monthly precipitation and evapo-ration the SCS model yields the monthly runoff A key issuehere is to calculate the actual evaporation by using the SCSmonthly model Based on the research results from the two-parameter monthly water balance model [53] the monthlyactual evaporation can be calculated by
119864 (119905) = 119862 times 119864119875 (119905) times tanh( 119875 (119905)
119864119875 (119905)
) (9)
where 119864(119905) is the actual monthly evaporation 119864119875(119905) is theobserved evaporation from the evaporating dish 119875(119905) is themonthly precipitation and 119862 is one of the parameters in themodel (nondimensional)
The total discharge consists of two parts the surface flow(119878119877(119905)) and the baseflow (119877119866(119905)) 119878119877(119905) can be gained by (6)while 119877119866(119905) can be calculated with
119877119866 (119905) = 119886 times 119885 (119905) (10)
where 119886 is the coefficient of the groundwater flow and 119885(119905) isthe soil moisture content which can be calculated by
119885 (119905) = 119885 (119905 minus 1) + 119875 (119905) minus 119864 (119905) + 119878119877 (119905) minus 119877119866 (119905) (11)
A schematic diagram for the water balance in a basinis shown in Figure 5 The SCS model is used to simulatethe monthly runoff process in this study There are twoparameters C and 120572 in the model
33 Approach to Distinguish the Respective Impact of LandUse and Climate Change to Water Resources The total runoffchange can be obtained by the difference between theobserved runoffs in two different periods respectively thatis the intensive human activities period and the low humanactivities period (natural condition) It is assumed that the
6 Mathematical Problems in Engineering
minus4
minus3
minus2
minus1
0
1
2
3
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(a) Precipitation
minus4
minus2
0
2
4
6
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(b) Temperature
minus5
minus4
minus3
minus2
minus1
0
1
2
3
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(c) Sunlight
minus4
minus2
0
2
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(d) Evaporation
Figure 6 Mann-Kendall test trend of four meteorological elements in the Dongjing basin
runoff change in the low human activities period is affectedonly by climate change
Therefore the impacts of climate change land use changeand other human activities on runoff change can be separatedaccording to the following calculations
Δ119877
119871= 119877
1198672minus 119877
1198671
Δ119877
119862= 119877
119861minus 119877
1198671
Δ119877
0= Δ119877
119879minus Δ119877
119862minus Δ119877
119871
Δ =
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
120583119871 =
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
Δ
times 100
120583119862 =
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
Δ
times 100
120583119877
0=
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
Δ
times 100
(12)
where Δ119877119871is the runoff change due to land use change from
time period of phase I to phase II 1198771198672
and 119877
1198671are the
simulated runoffs corresponding to the land uses of phase IIand phase I respectively and both of them can be calculatedwith the SCSmonthlymodelΔ119877
119862is the runoff change caused
by climate change 119877119861is the natural runoff of phase I Δ119877
119879is
the total runoff change Δ1198770is the runoff change due to other
human activities except for land use change 120583119871 120583119862 and 1205831198770
are the percentages for the roles played by land use changeclimate change and other human activities respectively
4 Results and Discussion
41 Time-Series Analysis The variation trends of the climaticvariables over 50 years in the study basin were analyzed withthe linear regression and Mann-Kendall trend test methodTable 1 listed the detailed results obtained by the Mann-Kendall trend test method Figure 6 demonstrated the resultsfor mutation analysis with the Mann-Kendall trend test andthe linear regression method respectively
It can be seen from Table 1 that each climatic variableshowed different degree of change in the Dongjiang basinduring the past 50 years (1959ndash2008) according to its statis-tics by the Mann-Kendall trend test method Precipitationshowed a nonsignificant increasing trend (119872 = 022) at 99confidence level which is largely due to local atmosphericcirculation and topography Temperature in the same periodshowed a significant increasing trend (119872 = 334) Whilesunlight showed a significant decreasing trend Meanwhilevery fast urbanization caused quick increase of impervious
Mathematical Problems in Engineering 7
Table 1 M-K trend analysis for meteorological elements in the Dongjiang basin (1958ndash2009)
StatisticsMeteorological elements
Precipitation Temperature Evaporation Humidity Sunlight(mm) (∘C) (mm) (gm3) (h)
119862 185292 2130 15724 781 1813119862V 016 002 005 003 009119862
119904
013 056 050 minus094 045119872 022 334 minus294 minus297 minus418
area in the study basin in the last 50 years These all con-tributed to a decreasing trend of evaporation Temperatureshowed an increasing trend with a distinct mutation takingplace around 1997 and sunlight and evaporation both hadan abrupt change in 1982 Overall the change of climaticvariables in the Dongjiang basin during the past 50 years wassignificant
It can be found from the119862V value of each climatic variablethat there was a significant internal variation for precipitationbut not for temperature It can be illustrated by both therainfall pattern and the atmospheric circulation in the studyarea Dongjiang basin is located in the southern humid regioninChina and deeply affected by themonsoon circulationwiththe rainfall patterns of frontal rain and convectional rainTherefore the internal variation of precipitation is significant
To clarify the relations among each climatic variable andthe runoff the correlation coefficients and relevancies wereanalyzed According to the spatial differences of land coverand climatic variables the Dongjiang basin was divided intothree parts the upper part centered with Longchuan markedD1 the middle part centered with Heyuan marked D2 andthe whole basin centered with Boluo marked D3 Tables2 and 3 listed the correlation coefficients and relevanciesrespectively It can be seen fromTable 2 that precipitationwaspositively related to runoff and their correlation coefficientwas the largest which revealed that runoff in the Dongjiangbasin depended mainly on precipitation In contrast tem-perature sunlight and evaporation were negatively related torunoff Among the three parts of the basin the correlationcoefficient of precipitation and runoff in D2 was the leastThe reason was that there located the biggest reservoir theXinfengjiang Reservoir (Figure 1) in D2 In addition morethan 20 middle and small sized reservoirs and hydraulicprojects were constructed in the same period which made amore significant change of land cover as compared to D1 andD3 Actually runoff in D2 is mainly controlled by regulationof the reservoir so precipitation was less correlation withrunoff in D2 Table 3 showed that the relevancy betweenprecipitation and runoff was the largest indicating thatprecipitation was the major driver for runoff change inthe whole study basin which is similar to the results ofcorrelation analysis
42 Land Use Change Analysis It has been found that theurban land and farmland increased in the study area [54]Based on the raster graphics for land use of two periods(1980 and 2000) temporal and spatial variations of land
use change in the Dongjiang basin were analyzed withthe ArcGIS spatial analysis technique Figure 2 showed themaps of land use in 1980 and 2000 respectively Table 4depicted the detailed information of the land use change inthe form of a comparison
It can be seen from Figure 2 that the dominant land usesin the study area in 1980 were mainly forest (widely dis-tributed in thewhole basin) and farmland (mainly distributedin the upper basin) accounting for 6456 and 2233respectively while garden meadow and water took a littlepart with the percentage of 594 471 and 228 respec-tively Urban land mainly distributed in the downstreambasin and the unutilized land took the least percentage in theDongjiang basinThe area of two types of land use urban landand farmland increased from 1980 along with the decreaseof garden (265)meadow (123) water (049) and forest(238) in 2000 while the dominant land use was still forestin 2000 In all since 1980s the landuse in theDongjiang basinhas been characterized with a prominent increase in urbanland a little increase in farmland and great decrease in forestarea while little change inwater area andunutilized landThisland use change due to fast social and economic developmenthad a significant impact on the hydrological response andthen contributed to the variability of water resources in theregion
43 Runoff Simulation and Runoff Change Analysis
431 The Value of CN CN (curve number) can reflect thecapacity of runoff yield for the land cover with a continuousspatial distribution The CN isocline represents the runoffyield capacities in the study basin
Based on land use maps of two periods (1980 and 2000)and soil type data of the Dongjiang basin CN distributionmaps (see Figure 7) of 3 AMC (antecedent moisture condi-tion) scenarios in the same periodswere obtainedwith spatialinterpolation Figure 8 showed the CN distribution maps forAMC II of the four sub-basins in the two periods
432 Model Calibration and Validation The SCS monthlymodel was calibrated in the period of 1970ndash1976 with climaticdata and then validated in the period of 1977-1978 by manualcalibration method with the acceptable set of parametersafter CN value analysis To measure the performance of themodel we chose Nash-Sutcliffe coefficient of efficiency (NSE)criterion [55] and relative error (RE) as objective function
8 Mathematical Problems in Engineering
Table 2 The correlation coefficient of each meteorological element to runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight HumidityD1 Upper Longchuan minus010 080 minus04 minus035 027D2 Midstream Heyuan minus023 069 minus028 minus039 035D The whole Basin Boluo minus008 088 minus054 minus057 026
Table 3 The relevancies between each meteorological element and runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight Humidity
D1 Upper Longchuan 04884 05503 04688 0449 04702Rank 2 1 4 5 3
D2 Midstream Heyuan 04857 05389 04659 04313 04861Rank 3 1 4 5 2
D The whole basin Boluo 0525 05968 04883 04495 05239Rank 2 1 4 5 3
Table 4 Comparison of land use in the Dongjiang basin during two different periods
Land use The year 1980 The year 2000Δ area (km
2) Ratio ()Area (km2) Ratio () Area (km2) Ratio ()
Farmland 608349 2233 727273 2669 118924 436Garden 161914 594 89670 329 minus72244 minus265Forest 1758688 6456 1693987 6218 minus64701 minus238Meadow 128274 471 94714 348 minus33560 minus123Built-up 3002 012 68225 25 65223 238Waters 61999 228 48012 179 minus13987 minus049Unutilized land 1738 006 2080 007 342 001
1980 1980 1980
2000 2000 2000
AMC I AMC II AMC III
Figure 7 Comparison of CN distribution under 3 AMC scenarios in the Dongjiang basin of two periods (1980 and 2000)
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Mathematical PhysicsAdvances in
Complex AnalysisJournal of
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Discrete Dynamics in Nature and Society
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Decision SciencesAdvances in
Discrete MathematicsJournal of
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
4 Mathematical Problems in Engineering
1980 2000
NW E
S
FarmlandGardenForestMeadow
UrbanWaterUnutilized
Figure 2 Land uses of two periods (1980 and 2000) in theDongjiang basin
DEMSoil type
Minimum infiltration rate(mmh)
73sim11438sim7313sim380sim13
1500
N
SEW
0
Value
Figure 3 Soil type and DEM of the Dongjiang basin
recommended for general use by the World MeteorologicalOrganization [43] the Mann-Kendall test was widely usedto detect time-series trends in hydrological and climatic datain many researches The Mann-Kendall test has some advan-tages including its simplicity ability to deal with nonnormaland missing data distributions and robustness to the effectsof outliers and gross data errors [44ndash46]
Firstly the Mann-Kendall test defined a variable 119878 as
119878 =
119899minus1
sum
119896=1
119899
sum
119895=119896+1
sgn (119909119894minus 119909
119895) (1)
Then the presence of a statistically significant trend isevaluated using the 119885 value
119885 =
119878 minus 1
radicVar (119878) 119878 gt 0
0 119878 = 0
119878 + 1
radicVar (119878) 119878 lt 0
(2)
Besides the standard normal cumulative distributionfunction 119865
119899under the significance level 120572 is given by
119865
119899(119885
1205722) = 1205722 If |119885| gt 119885
1205722 the hypothesis of 119867
1for a
two-sided test can be accepted Positive value 119885 indicates anupward trend while negative value a downward trend Moredescriptions of this method can be found in many researches[47ndash49] In this paper trend analysis of climatic variablesand runoff in the Dongjiang basin were conducted with theMann-Kendall test based on over 50 years of climatic andhydrological data
In addition mutation detections of the climatic data werealso conducted by the Mann-Kendall mutation analysis testmethod a statistic variable of this method is
119878
119870=
119896
sum
119894=1
119903
119894 119896 = 2 3 119899
119903
119894=
+1 119909
119894gt 119909
119895
0 119909
119894le 119909
119895
119895 = 1 2 119894
(3)
where 119878119870is the counts for the 119909 series when 119909
119894is greater than
119909
119895119880119865
119870is the standard normal distribution and can be
calculated based on the 119909 series
119880119865
119870=
[119878
119870minus 119864 (119878
119870)]
radicvar (119878119870)
119896 = 1 2 119899 (4)
where 1198801198651=0 119864(119878
119870) and var(119878
119870) are the expected value and
variance of 119878119870which can be calculated on condition that the
119909 series is mutually independent with the same continuousdistribution
119864 (119878
119870) =
119899 (119899 + 1)
4
var (119878119870) =
119899 (119899 minus 1) (2119899 + 5)
72
(5)
32 SCS Rainfall-Runoff Model Developed by the Soil Con-servation Service of US Department of Agriculture (USDA)early in 1954 the SCS model is widely used in the USAand many other countries [50 51] Several advantages of thismodel are as follows (1) the characteristics of the land coversuch as soil slope vegetation and land use in a basin canbe considered with the SCS model the possible change onthe rainfall-runoff relationship can be preliminarily estimatedaccording to the change of land use and (2) it has theadvantages of simplicity in structure and convenience in usewith very low dependence on data
Mathematical Problems in Engineering 5
0
100
200
300
400
500
1980 1985 1990 1995 2000 2005Year
HuizhouHeyuanDongguan
HuizhouHeyuanDongguan
0
100
200
300
400
1980 1985 1990 1995 2000 2005Year
Popu
latio
n (m
illio
n)
GD
P (b
illio
n Yu
an)
Figure 4 Sketch map of economic and social development in the Dongjiang basin
Precipitation Evaporation
Soil moisture content zone
Ground water runoff
Surface runoff
Total runoff
P(t) EP(t)
SR(t)
R(t) = SR(t) + RG(t)
RG(t) = a times Z(t)
Z(t) = Z(t minus 1) + P(t) minus E(t)
+ SR(t) minus RG(t)
Figure 5 A schematic diagram of the water balance in a basin
The runoff yield for the SCS model is
119877 =
(119875 minus 119868
119886)
2
119875 + 119878 minus 119868
119886
119875 ge 119868
119886
0 119875 lt 119868
119886
(6)
where 119877 is the runoff P is the precipitation 119868119886is the initial
loss and 119878 is the present probable maximum retention in thebasin which is the top limit of the later loss
Initial loss 119868119886can be calculated by an empirical correlation
with S
119868
119886= 120572119878 (7)
where 120572 is the coefficient of the initial losses which is relatedto the initial soil water content of the basin
To eliminate the large variation scope of the 119878 valuethere is an empirical relation for CN (a non dimensionalparameter) and S
119878 =
25400
119862119873
minus 254 (8)
The curve number CN is a key and comprehensiveparameter within SCS model CN describes the watershedfeatures before a rain and is affected by AMC (antecedentmoisture condition) slope vegetation soil type and land use
condition with a value of 0sim100 AMC can be divided into3 classes AMC I-arid condition AMC II-normal conditionand AMC III-moist condition The specific basis for theclassification and the estimation of the CN value can be foundin related references [52]
Input by the observed monthly precipitation and evapo-ration the SCS model yields the monthly runoff A key issuehere is to calculate the actual evaporation by using the SCSmonthly model Based on the research results from the two-parameter monthly water balance model [53] the monthlyactual evaporation can be calculated by
119864 (119905) = 119862 times 119864119875 (119905) times tanh( 119875 (119905)
119864119875 (119905)
) (9)
where 119864(119905) is the actual monthly evaporation 119864119875(119905) is theobserved evaporation from the evaporating dish 119875(119905) is themonthly precipitation and 119862 is one of the parameters in themodel (nondimensional)
The total discharge consists of two parts the surface flow(119878119877(119905)) and the baseflow (119877119866(119905)) 119878119877(119905) can be gained by (6)while 119877119866(119905) can be calculated with
119877119866 (119905) = 119886 times 119885 (119905) (10)
where 119886 is the coefficient of the groundwater flow and 119885(119905) isthe soil moisture content which can be calculated by
119885 (119905) = 119885 (119905 minus 1) + 119875 (119905) minus 119864 (119905) + 119878119877 (119905) minus 119877119866 (119905) (11)
A schematic diagram for the water balance in a basinis shown in Figure 5 The SCS model is used to simulatethe monthly runoff process in this study There are twoparameters C and 120572 in the model
33 Approach to Distinguish the Respective Impact of LandUse and Climate Change to Water Resources The total runoffchange can be obtained by the difference between theobserved runoffs in two different periods respectively thatis the intensive human activities period and the low humanactivities period (natural condition) It is assumed that the
6 Mathematical Problems in Engineering
minus4
minus3
minus2
minus1
0
1
2
3
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(a) Precipitation
minus4
minus2
0
2
4
6
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(b) Temperature
minus5
minus4
minus3
minus2
minus1
0
1
2
3
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(c) Sunlight
minus4
minus2
0
2
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(d) Evaporation
Figure 6 Mann-Kendall test trend of four meteorological elements in the Dongjing basin
runoff change in the low human activities period is affectedonly by climate change
Therefore the impacts of climate change land use changeand other human activities on runoff change can be separatedaccording to the following calculations
Δ119877
119871= 119877
1198672minus 119877
1198671
Δ119877
119862= 119877
119861minus 119877
1198671
Δ119877
0= Δ119877
119879minus Δ119877
119862minus Δ119877
119871
Δ =
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
120583119871 =
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
Δ
times 100
120583119862 =
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
Δ
times 100
120583119877
0=
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
Δ
times 100
(12)
where Δ119877119871is the runoff change due to land use change from
time period of phase I to phase II 1198771198672
and 119877
1198671are the
simulated runoffs corresponding to the land uses of phase IIand phase I respectively and both of them can be calculatedwith the SCSmonthlymodelΔ119877
119862is the runoff change caused
by climate change 119877119861is the natural runoff of phase I Δ119877
119879is
the total runoff change Δ1198770is the runoff change due to other
human activities except for land use change 120583119871 120583119862 and 1205831198770
are the percentages for the roles played by land use changeclimate change and other human activities respectively
4 Results and Discussion
41 Time-Series Analysis The variation trends of the climaticvariables over 50 years in the study basin were analyzed withthe linear regression and Mann-Kendall trend test methodTable 1 listed the detailed results obtained by the Mann-Kendall trend test method Figure 6 demonstrated the resultsfor mutation analysis with the Mann-Kendall trend test andthe linear regression method respectively
It can be seen from Table 1 that each climatic variableshowed different degree of change in the Dongjiang basinduring the past 50 years (1959ndash2008) according to its statis-tics by the Mann-Kendall trend test method Precipitationshowed a nonsignificant increasing trend (119872 = 022) at 99confidence level which is largely due to local atmosphericcirculation and topography Temperature in the same periodshowed a significant increasing trend (119872 = 334) Whilesunlight showed a significant decreasing trend Meanwhilevery fast urbanization caused quick increase of impervious
Mathematical Problems in Engineering 7
Table 1 M-K trend analysis for meteorological elements in the Dongjiang basin (1958ndash2009)
StatisticsMeteorological elements
Precipitation Temperature Evaporation Humidity Sunlight(mm) (∘C) (mm) (gm3) (h)
119862 185292 2130 15724 781 1813119862V 016 002 005 003 009119862
119904
013 056 050 minus094 045119872 022 334 minus294 minus297 minus418
area in the study basin in the last 50 years These all con-tributed to a decreasing trend of evaporation Temperatureshowed an increasing trend with a distinct mutation takingplace around 1997 and sunlight and evaporation both hadan abrupt change in 1982 Overall the change of climaticvariables in the Dongjiang basin during the past 50 years wassignificant
It can be found from the119862V value of each climatic variablethat there was a significant internal variation for precipitationbut not for temperature It can be illustrated by both therainfall pattern and the atmospheric circulation in the studyarea Dongjiang basin is located in the southern humid regioninChina and deeply affected by themonsoon circulationwiththe rainfall patterns of frontal rain and convectional rainTherefore the internal variation of precipitation is significant
To clarify the relations among each climatic variable andthe runoff the correlation coefficients and relevancies wereanalyzed According to the spatial differences of land coverand climatic variables the Dongjiang basin was divided intothree parts the upper part centered with Longchuan markedD1 the middle part centered with Heyuan marked D2 andthe whole basin centered with Boluo marked D3 Tables2 and 3 listed the correlation coefficients and relevanciesrespectively It can be seen fromTable 2 that precipitationwaspositively related to runoff and their correlation coefficientwas the largest which revealed that runoff in the Dongjiangbasin depended mainly on precipitation In contrast tem-perature sunlight and evaporation were negatively related torunoff Among the three parts of the basin the correlationcoefficient of precipitation and runoff in D2 was the leastThe reason was that there located the biggest reservoir theXinfengjiang Reservoir (Figure 1) in D2 In addition morethan 20 middle and small sized reservoirs and hydraulicprojects were constructed in the same period which made amore significant change of land cover as compared to D1 andD3 Actually runoff in D2 is mainly controlled by regulationof the reservoir so precipitation was less correlation withrunoff in D2 Table 3 showed that the relevancy betweenprecipitation and runoff was the largest indicating thatprecipitation was the major driver for runoff change inthe whole study basin which is similar to the results ofcorrelation analysis
42 Land Use Change Analysis It has been found that theurban land and farmland increased in the study area [54]Based on the raster graphics for land use of two periods(1980 and 2000) temporal and spatial variations of land
use change in the Dongjiang basin were analyzed withthe ArcGIS spatial analysis technique Figure 2 showed themaps of land use in 1980 and 2000 respectively Table 4depicted the detailed information of the land use change inthe form of a comparison
It can be seen from Figure 2 that the dominant land usesin the study area in 1980 were mainly forest (widely dis-tributed in thewhole basin) and farmland (mainly distributedin the upper basin) accounting for 6456 and 2233respectively while garden meadow and water took a littlepart with the percentage of 594 471 and 228 respec-tively Urban land mainly distributed in the downstreambasin and the unutilized land took the least percentage in theDongjiang basinThe area of two types of land use urban landand farmland increased from 1980 along with the decreaseof garden (265)meadow (123) water (049) and forest(238) in 2000 while the dominant land use was still forestin 2000 In all since 1980s the landuse in theDongjiang basinhas been characterized with a prominent increase in urbanland a little increase in farmland and great decrease in forestarea while little change inwater area andunutilized landThisland use change due to fast social and economic developmenthad a significant impact on the hydrological response andthen contributed to the variability of water resources in theregion
43 Runoff Simulation and Runoff Change Analysis
431 The Value of CN CN (curve number) can reflect thecapacity of runoff yield for the land cover with a continuousspatial distribution The CN isocline represents the runoffyield capacities in the study basin
Based on land use maps of two periods (1980 and 2000)and soil type data of the Dongjiang basin CN distributionmaps (see Figure 7) of 3 AMC (antecedent moisture condi-tion) scenarios in the same periodswere obtainedwith spatialinterpolation Figure 8 showed the CN distribution maps forAMC II of the four sub-basins in the two periods
432 Model Calibration and Validation The SCS monthlymodel was calibrated in the period of 1970ndash1976 with climaticdata and then validated in the period of 1977-1978 by manualcalibration method with the acceptable set of parametersafter CN value analysis To measure the performance of themodel we chose Nash-Sutcliffe coefficient of efficiency (NSE)criterion [55] and relative error (RE) as objective function
8 Mathematical Problems in Engineering
Table 2 The correlation coefficient of each meteorological element to runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight HumidityD1 Upper Longchuan minus010 080 minus04 minus035 027D2 Midstream Heyuan minus023 069 minus028 minus039 035D The whole Basin Boluo minus008 088 minus054 minus057 026
Table 3 The relevancies between each meteorological element and runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight Humidity
D1 Upper Longchuan 04884 05503 04688 0449 04702Rank 2 1 4 5 3
D2 Midstream Heyuan 04857 05389 04659 04313 04861Rank 3 1 4 5 2
D The whole basin Boluo 0525 05968 04883 04495 05239Rank 2 1 4 5 3
Table 4 Comparison of land use in the Dongjiang basin during two different periods
Land use The year 1980 The year 2000Δ area (km
2) Ratio ()Area (km2) Ratio () Area (km2) Ratio ()
Farmland 608349 2233 727273 2669 118924 436Garden 161914 594 89670 329 minus72244 minus265Forest 1758688 6456 1693987 6218 minus64701 minus238Meadow 128274 471 94714 348 minus33560 minus123Built-up 3002 012 68225 25 65223 238Waters 61999 228 48012 179 minus13987 minus049Unutilized land 1738 006 2080 007 342 001
1980 1980 1980
2000 2000 2000
AMC I AMC II AMC III
Figure 7 Comparison of CN distribution under 3 AMC scenarios in the Dongjiang basin of two periods (1980 and 2000)
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Operations ResearchAdvances in
Journal of
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Decision SciencesAdvances in
Discrete MathematicsJournal of
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Mathematical Problems in Engineering 5
0
100
200
300
400
500
1980 1985 1990 1995 2000 2005Year
HuizhouHeyuanDongguan
HuizhouHeyuanDongguan
0
100
200
300
400
1980 1985 1990 1995 2000 2005Year
Popu
latio
n (m
illio
n)
GD
P (b
illio
n Yu
an)
Figure 4 Sketch map of economic and social development in the Dongjiang basin
Precipitation Evaporation
Soil moisture content zone
Ground water runoff
Surface runoff
Total runoff
P(t) EP(t)
SR(t)
R(t) = SR(t) + RG(t)
RG(t) = a times Z(t)
Z(t) = Z(t minus 1) + P(t) minus E(t)
+ SR(t) minus RG(t)
Figure 5 A schematic diagram of the water balance in a basin
The runoff yield for the SCS model is
119877 =
(119875 minus 119868
119886)
2
119875 + 119878 minus 119868
119886
119875 ge 119868
119886
0 119875 lt 119868
119886
(6)
where 119877 is the runoff P is the precipitation 119868119886is the initial
loss and 119878 is the present probable maximum retention in thebasin which is the top limit of the later loss
Initial loss 119868119886can be calculated by an empirical correlation
with S
119868
119886= 120572119878 (7)
where 120572 is the coefficient of the initial losses which is relatedto the initial soil water content of the basin
To eliminate the large variation scope of the 119878 valuethere is an empirical relation for CN (a non dimensionalparameter) and S
119878 =
25400
119862119873
minus 254 (8)
The curve number CN is a key and comprehensiveparameter within SCS model CN describes the watershedfeatures before a rain and is affected by AMC (antecedentmoisture condition) slope vegetation soil type and land use
condition with a value of 0sim100 AMC can be divided into3 classes AMC I-arid condition AMC II-normal conditionand AMC III-moist condition The specific basis for theclassification and the estimation of the CN value can be foundin related references [52]
Input by the observed monthly precipitation and evapo-ration the SCS model yields the monthly runoff A key issuehere is to calculate the actual evaporation by using the SCSmonthly model Based on the research results from the two-parameter monthly water balance model [53] the monthlyactual evaporation can be calculated by
119864 (119905) = 119862 times 119864119875 (119905) times tanh( 119875 (119905)
119864119875 (119905)
) (9)
where 119864(119905) is the actual monthly evaporation 119864119875(119905) is theobserved evaporation from the evaporating dish 119875(119905) is themonthly precipitation and 119862 is one of the parameters in themodel (nondimensional)
The total discharge consists of two parts the surface flow(119878119877(119905)) and the baseflow (119877119866(119905)) 119878119877(119905) can be gained by (6)while 119877119866(119905) can be calculated with
119877119866 (119905) = 119886 times 119885 (119905) (10)
where 119886 is the coefficient of the groundwater flow and 119885(119905) isthe soil moisture content which can be calculated by
119885 (119905) = 119885 (119905 minus 1) + 119875 (119905) minus 119864 (119905) + 119878119877 (119905) minus 119877119866 (119905) (11)
A schematic diagram for the water balance in a basinis shown in Figure 5 The SCS model is used to simulatethe monthly runoff process in this study There are twoparameters C and 120572 in the model
33 Approach to Distinguish the Respective Impact of LandUse and Climate Change to Water Resources The total runoffchange can be obtained by the difference between theobserved runoffs in two different periods respectively thatis the intensive human activities period and the low humanactivities period (natural condition) It is assumed that the
6 Mathematical Problems in Engineering
minus4
minus3
minus2
minus1
0
1
2
3
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(a) Precipitation
minus4
minus2
0
2
4
6
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(b) Temperature
minus5
minus4
minus3
minus2
minus1
0
1
2
3
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(c) Sunlight
minus4
minus2
0
2
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(d) Evaporation
Figure 6 Mann-Kendall test trend of four meteorological elements in the Dongjing basin
runoff change in the low human activities period is affectedonly by climate change
Therefore the impacts of climate change land use changeand other human activities on runoff change can be separatedaccording to the following calculations
Δ119877
119871= 119877
1198672minus 119877
1198671
Δ119877
119862= 119877
119861minus 119877
1198671
Δ119877
0= Δ119877
119879minus Δ119877
119862minus Δ119877
119871
Δ =
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
120583119871 =
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
Δ
times 100
120583119862 =
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
Δ
times 100
120583119877
0=
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
Δ
times 100
(12)
where Δ119877119871is the runoff change due to land use change from
time period of phase I to phase II 1198771198672
and 119877
1198671are the
simulated runoffs corresponding to the land uses of phase IIand phase I respectively and both of them can be calculatedwith the SCSmonthlymodelΔ119877
119862is the runoff change caused
by climate change 119877119861is the natural runoff of phase I Δ119877
119879is
the total runoff change Δ1198770is the runoff change due to other
human activities except for land use change 120583119871 120583119862 and 1205831198770
are the percentages for the roles played by land use changeclimate change and other human activities respectively
4 Results and Discussion
41 Time-Series Analysis The variation trends of the climaticvariables over 50 years in the study basin were analyzed withthe linear regression and Mann-Kendall trend test methodTable 1 listed the detailed results obtained by the Mann-Kendall trend test method Figure 6 demonstrated the resultsfor mutation analysis with the Mann-Kendall trend test andthe linear regression method respectively
It can be seen from Table 1 that each climatic variableshowed different degree of change in the Dongjiang basinduring the past 50 years (1959ndash2008) according to its statis-tics by the Mann-Kendall trend test method Precipitationshowed a nonsignificant increasing trend (119872 = 022) at 99confidence level which is largely due to local atmosphericcirculation and topography Temperature in the same periodshowed a significant increasing trend (119872 = 334) Whilesunlight showed a significant decreasing trend Meanwhilevery fast urbanization caused quick increase of impervious
Mathematical Problems in Engineering 7
Table 1 M-K trend analysis for meteorological elements in the Dongjiang basin (1958ndash2009)
StatisticsMeteorological elements
Precipitation Temperature Evaporation Humidity Sunlight(mm) (∘C) (mm) (gm3) (h)
119862 185292 2130 15724 781 1813119862V 016 002 005 003 009119862
119904
013 056 050 minus094 045119872 022 334 minus294 minus297 minus418
area in the study basin in the last 50 years These all con-tributed to a decreasing trend of evaporation Temperatureshowed an increasing trend with a distinct mutation takingplace around 1997 and sunlight and evaporation both hadan abrupt change in 1982 Overall the change of climaticvariables in the Dongjiang basin during the past 50 years wassignificant
It can be found from the119862V value of each climatic variablethat there was a significant internal variation for precipitationbut not for temperature It can be illustrated by both therainfall pattern and the atmospheric circulation in the studyarea Dongjiang basin is located in the southern humid regioninChina and deeply affected by themonsoon circulationwiththe rainfall patterns of frontal rain and convectional rainTherefore the internal variation of precipitation is significant
To clarify the relations among each climatic variable andthe runoff the correlation coefficients and relevancies wereanalyzed According to the spatial differences of land coverand climatic variables the Dongjiang basin was divided intothree parts the upper part centered with Longchuan markedD1 the middle part centered with Heyuan marked D2 andthe whole basin centered with Boluo marked D3 Tables2 and 3 listed the correlation coefficients and relevanciesrespectively It can be seen fromTable 2 that precipitationwaspositively related to runoff and their correlation coefficientwas the largest which revealed that runoff in the Dongjiangbasin depended mainly on precipitation In contrast tem-perature sunlight and evaporation were negatively related torunoff Among the three parts of the basin the correlationcoefficient of precipitation and runoff in D2 was the leastThe reason was that there located the biggest reservoir theXinfengjiang Reservoir (Figure 1) in D2 In addition morethan 20 middle and small sized reservoirs and hydraulicprojects were constructed in the same period which made amore significant change of land cover as compared to D1 andD3 Actually runoff in D2 is mainly controlled by regulationof the reservoir so precipitation was less correlation withrunoff in D2 Table 3 showed that the relevancy betweenprecipitation and runoff was the largest indicating thatprecipitation was the major driver for runoff change inthe whole study basin which is similar to the results ofcorrelation analysis
42 Land Use Change Analysis It has been found that theurban land and farmland increased in the study area [54]Based on the raster graphics for land use of two periods(1980 and 2000) temporal and spatial variations of land
use change in the Dongjiang basin were analyzed withthe ArcGIS spatial analysis technique Figure 2 showed themaps of land use in 1980 and 2000 respectively Table 4depicted the detailed information of the land use change inthe form of a comparison
It can be seen from Figure 2 that the dominant land usesin the study area in 1980 were mainly forest (widely dis-tributed in thewhole basin) and farmland (mainly distributedin the upper basin) accounting for 6456 and 2233respectively while garden meadow and water took a littlepart with the percentage of 594 471 and 228 respec-tively Urban land mainly distributed in the downstreambasin and the unutilized land took the least percentage in theDongjiang basinThe area of two types of land use urban landand farmland increased from 1980 along with the decreaseof garden (265)meadow (123) water (049) and forest(238) in 2000 while the dominant land use was still forestin 2000 In all since 1980s the landuse in theDongjiang basinhas been characterized with a prominent increase in urbanland a little increase in farmland and great decrease in forestarea while little change inwater area andunutilized landThisland use change due to fast social and economic developmenthad a significant impact on the hydrological response andthen contributed to the variability of water resources in theregion
43 Runoff Simulation and Runoff Change Analysis
431 The Value of CN CN (curve number) can reflect thecapacity of runoff yield for the land cover with a continuousspatial distribution The CN isocline represents the runoffyield capacities in the study basin
Based on land use maps of two periods (1980 and 2000)and soil type data of the Dongjiang basin CN distributionmaps (see Figure 7) of 3 AMC (antecedent moisture condi-tion) scenarios in the same periodswere obtainedwith spatialinterpolation Figure 8 showed the CN distribution maps forAMC II of the four sub-basins in the two periods
432 Model Calibration and Validation The SCS monthlymodel was calibrated in the period of 1970ndash1976 with climaticdata and then validated in the period of 1977-1978 by manualcalibration method with the acceptable set of parametersafter CN value analysis To measure the performance of themodel we chose Nash-Sutcliffe coefficient of efficiency (NSE)criterion [55] and relative error (RE) as objective function
8 Mathematical Problems in Engineering
Table 2 The correlation coefficient of each meteorological element to runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight HumidityD1 Upper Longchuan minus010 080 minus04 minus035 027D2 Midstream Heyuan minus023 069 minus028 minus039 035D The whole Basin Boluo minus008 088 minus054 minus057 026
Table 3 The relevancies between each meteorological element and runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight Humidity
D1 Upper Longchuan 04884 05503 04688 0449 04702Rank 2 1 4 5 3
D2 Midstream Heyuan 04857 05389 04659 04313 04861Rank 3 1 4 5 2
D The whole basin Boluo 0525 05968 04883 04495 05239Rank 2 1 4 5 3
Table 4 Comparison of land use in the Dongjiang basin during two different periods
Land use The year 1980 The year 2000Δ area (km
2) Ratio ()Area (km2) Ratio () Area (km2) Ratio ()
Farmland 608349 2233 727273 2669 118924 436Garden 161914 594 89670 329 minus72244 minus265Forest 1758688 6456 1693987 6218 minus64701 minus238Meadow 128274 471 94714 348 minus33560 minus123Built-up 3002 012 68225 25 65223 238Waters 61999 228 48012 179 minus13987 minus049Unutilized land 1738 006 2080 007 342 001
1980 1980 1980
2000 2000 2000
AMC I AMC II AMC III
Figure 7 Comparison of CN distribution under 3 AMC scenarios in the Dongjiang basin of two periods (1980 and 2000)
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
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Mathematical Problems in Engineering
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Differential EquationsInternational Journal of
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Stochastic AnalysisInternational Journal of
6 Mathematical Problems in Engineering
minus4
minus3
minus2
minus1
0
1
2
3
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(a) Precipitation
minus4
minus2
0
2
4
6
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
(b) Temperature
minus5
minus4
minus3
minus2
minus1
0
1
2
3
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(c) Sunlight
minus4
minus2
0
2
4
1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009
UfUB
(d) Evaporation
Figure 6 Mann-Kendall test trend of four meteorological elements in the Dongjing basin
runoff change in the low human activities period is affectedonly by climate change
Therefore the impacts of climate change land use changeand other human activities on runoff change can be separatedaccording to the following calculations
Δ119877
119871= 119877
1198672minus 119877
1198671
Δ119877
119862= 119877
119861minus 119877
1198671
Δ119877
0= Δ119877
119879minus Δ119877
119862minus Δ119877
119871
Δ =
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
+
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
120583119871 =
1003816
1003816
1003816
1003816
Δ119877
119871
1003816
1003816
1003816
1003816
Δ
times 100
120583119862 =
1003816
1003816
1003816
1003816
Δ119877
119862
1003816
1003816
1003816
1003816
Δ
times 100
120583119877
0=
1003816
1003816
1003816
1003816
Δ119877
0
1003816
1003816
1003816
1003816
Δ
times 100
(12)
where Δ119877119871is the runoff change due to land use change from
time period of phase I to phase II 1198771198672
and 119877
1198671are the
simulated runoffs corresponding to the land uses of phase IIand phase I respectively and both of them can be calculatedwith the SCSmonthlymodelΔ119877
119862is the runoff change caused
by climate change 119877119861is the natural runoff of phase I Δ119877
119879is
the total runoff change Δ1198770is the runoff change due to other
human activities except for land use change 120583119871 120583119862 and 1205831198770
are the percentages for the roles played by land use changeclimate change and other human activities respectively
4 Results and Discussion
41 Time-Series Analysis The variation trends of the climaticvariables over 50 years in the study basin were analyzed withthe linear regression and Mann-Kendall trend test methodTable 1 listed the detailed results obtained by the Mann-Kendall trend test method Figure 6 demonstrated the resultsfor mutation analysis with the Mann-Kendall trend test andthe linear regression method respectively
It can be seen from Table 1 that each climatic variableshowed different degree of change in the Dongjiang basinduring the past 50 years (1959ndash2008) according to its statis-tics by the Mann-Kendall trend test method Precipitationshowed a nonsignificant increasing trend (119872 = 022) at 99confidence level which is largely due to local atmosphericcirculation and topography Temperature in the same periodshowed a significant increasing trend (119872 = 334) Whilesunlight showed a significant decreasing trend Meanwhilevery fast urbanization caused quick increase of impervious
Mathematical Problems in Engineering 7
Table 1 M-K trend analysis for meteorological elements in the Dongjiang basin (1958ndash2009)
StatisticsMeteorological elements
Precipitation Temperature Evaporation Humidity Sunlight(mm) (∘C) (mm) (gm3) (h)
119862 185292 2130 15724 781 1813119862V 016 002 005 003 009119862
119904
013 056 050 minus094 045119872 022 334 minus294 minus297 minus418
area in the study basin in the last 50 years These all con-tributed to a decreasing trend of evaporation Temperatureshowed an increasing trend with a distinct mutation takingplace around 1997 and sunlight and evaporation both hadan abrupt change in 1982 Overall the change of climaticvariables in the Dongjiang basin during the past 50 years wassignificant
It can be found from the119862V value of each climatic variablethat there was a significant internal variation for precipitationbut not for temperature It can be illustrated by both therainfall pattern and the atmospheric circulation in the studyarea Dongjiang basin is located in the southern humid regioninChina and deeply affected by themonsoon circulationwiththe rainfall patterns of frontal rain and convectional rainTherefore the internal variation of precipitation is significant
To clarify the relations among each climatic variable andthe runoff the correlation coefficients and relevancies wereanalyzed According to the spatial differences of land coverand climatic variables the Dongjiang basin was divided intothree parts the upper part centered with Longchuan markedD1 the middle part centered with Heyuan marked D2 andthe whole basin centered with Boluo marked D3 Tables2 and 3 listed the correlation coefficients and relevanciesrespectively It can be seen fromTable 2 that precipitationwaspositively related to runoff and their correlation coefficientwas the largest which revealed that runoff in the Dongjiangbasin depended mainly on precipitation In contrast tem-perature sunlight and evaporation were negatively related torunoff Among the three parts of the basin the correlationcoefficient of precipitation and runoff in D2 was the leastThe reason was that there located the biggest reservoir theXinfengjiang Reservoir (Figure 1) in D2 In addition morethan 20 middle and small sized reservoirs and hydraulicprojects were constructed in the same period which made amore significant change of land cover as compared to D1 andD3 Actually runoff in D2 is mainly controlled by regulationof the reservoir so precipitation was less correlation withrunoff in D2 Table 3 showed that the relevancy betweenprecipitation and runoff was the largest indicating thatprecipitation was the major driver for runoff change inthe whole study basin which is similar to the results ofcorrelation analysis
42 Land Use Change Analysis It has been found that theurban land and farmland increased in the study area [54]Based on the raster graphics for land use of two periods(1980 and 2000) temporal and spatial variations of land
use change in the Dongjiang basin were analyzed withthe ArcGIS spatial analysis technique Figure 2 showed themaps of land use in 1980 and 2000 respectively Table 4depicted the detailed information of the land use change inthe form of a comparison
It can be seen from Figure 2 that the dominant land usesin the study area in 1980 were mainly forest (widely dis-tributed in thewhole basin) and farmland (mainly distributedin the upper basin) accounting for 6456 and 2233respectively while garden meadow and water took a littlepart with the percentage of 594 471 and 228 respec-tively Urban land mainly distributed in the downstreambasin and the unutilized land took the least percentage in theDongjiang basinThe area of two types of land use urban landand farmland increased from 1980 along with the decreaseof garden (265)meadow (123) water (049) and forest(238) in 2000 while the dominant land use was still forestin 2000 In all since 1980s the landuse in theDongjiang basinhas been characterized with a prominent increase in urbanland a little increase in farmland and great decrease in forestarea while little change inwater area andunutilized landThisland use change due to fast social and economic developmenthad a significant impact on the hydrological response andthen contributed to the variability of water resources in theregion
43 Runoff Simulation and Runoff Change Analysis
431 The Value of CN CN (curve number) can reflect thecapacity of runoff yield for the land cover with a continuousspatial distribution The CN isocline represents the runoffyield capacities in the study basin
Based on land use maps of two periods (1980 and 2000)and soil type data of the Dongjiang basin CN distributionmaps (see Figure 7) of 3 AMC (antecedent moisture condi-tion) scenarios in the same periodswere obtainedwith spatialinterpolation Figure 8 showed the CN distribution maps forAMC II of the four sub-basins in the two periods
432 Model Calibration and Validation The SCS monthlymodel was calibrated in the period of 1970ndash1976 with climaticdata and then validated in the period of 1977-1978 by manualcalibration method with the acceptable set of parametersafter CN value analysis To measure the performance of themodel we chose Nash-Sutcliffe coefficient of efficiency (NSE)criterion [55] and relative error (RE) as objective function
8 Mathematical Problems in Engineering
Table 2 The correlation coefficient of each meteorological element to runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight HumidityD1 Upper Longchuan minus010 080 minus04 minus035 027D2 Midstream Heyuan minus023 069 minus028 minus039 035D The whole Basin Boluo minus008 088 minus054 minus057 026
Table 3 The relevancies between each meteorological element and runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight Humidity
D1 Upper Longchuan 04884 05503 04688 0449 04702Rank 2 1 4 5 3
D2 Midstream Heyuan 04857 05389 04659 04313 04861Rank 3 1 4 5 2
D The whole basin Boluo 0525 05968 04883 04495 05239Rank 2 1 4 5 3
Table 4 Comparison of land use in the Dongjiang basin during two different periods
Land use The year 1980 The year 2000Δ area (km
2) Ratio ()Area (km2) Ratio () Area (km2) Ratio ()
Farmland 608349 2233 727273 2669 118924 436Garden 161914 594 89670 329 minus72244 minus265Forest 1758688 6456 1693987 6218 minus64701 minus238Meadow 128274 471 94714 348 minus33560 minus123Built-up 3002 012 68225 25 65223 238Waters 61999 228 48012 179 minus13987 minus049Unutilized land 1738 006 2080 007 342 001
1980 1980 1980
2000 2000 2000
AMC I AMC II AMC III
Figure 7 Comparison of CN distribution under 3 AMC scenarios in the Dongjiang basin of two periods (1980 and 2000)
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Mathematical Problems in Engineering
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Differential EquationsInternational Journal of
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Applied MathematicsJournal of
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Mathematical Problems in Engineering 7
Table 1 M-K trend analysis for meteorological elements in the Dongjiang basin (1958ndash2009)
StatisticsMeteorological elements
Precipitation Temperature Evaporation Humidity Sunlight(mm) (∘C) (mm) (gm3) (h)
119862 185292 2130 15724 781 1813119862V 016 002 005 003 009119862
119904
013 056 050 minus094 045119872 022 334 minus294 minus297 minus418
area in the study basin in the last 50 years These all con-tributed to a decreasing trend of evaporation Temperatureshowed an increasing trend with a distinct mutation takingplace around 1997 and sunlight and evaporation both hadan abrupt change in 1982 Overall the change of climaticvariables in the Dongjiang basin during the past 50 years wassignificant
It can be found from the119862V value of each climatic variablethat there was a significant internal variation for precipitationbut not for temperature It can be illustrated by both therainfall pattern and the atmospheric circulation in the studyarea Dongjiang basin is located in the southern humid regioninChina and deeply affected by themonsoon circulationwiththe rainfall patterns of frontal rain and convectional rainTherefore the internal variation of precipitation is significant
To clarify the relations among each climatic variable andthe runoff the correlation coefficients and relevancies wereanalyzed According to the spatial differences of land coverand climatic variables the Dongjiang basin was divided intothree parts the upper part centered with Longchuan markedD1 the middle part centered with Heyuan marked D2 andthe whole basin centered with Boluo marked D3 Tables2 and 3 listed the correlation coefficients and relevanciesrespectively It can be seen fromTable 2 that precipitationwaspositively related to runoff and their correlation coefficientwas the largest which revealed that runoff in the Dongjiangbasin depended mainly on precipitation In contrast tem-perature sunlight and evaporation were negatively related torunoff Among the three parts of the basin the correlationcoefficient of precipitation and runoff in D2 was the leastThe reason was that there located the biggest reservoir theXinfengjiang Reservoir (Figure 1) in D2 In addition morethan 20 middle and small sized reservoirs and hydraulicprojects were constructed in the same period which made amore significant change of land cover as compared to D1 andD3 Actually runoff in D2 is mainly controlled by regulationof the reservoir so precipitation was less correlation withrunoff in D2 Table 3 showed that the relevancy betweenprecipitation and runoff was the largest indicating thatprecipitation was the major driver for runoff change inthe whole study basin which is similar to the results ofcorrelation analysis
42 Land Use Change Analysis It has been found that theurban land and farmland increased in the study area [54]Based on the raster graphics for land use of two periods(1980 and 2000) temporal and spatial variations of land
use change in the Dongjiang basin were analyzed withthe ArcGIS spatial analysis technique Figure 2 showed themaps of land use in 1980 and 2000 respectively Table 4depicted the detailed information of the land use change inthe form of a comparison
It can be seen from Figure 2 that the dominant land usesin the study area in 1980 were mainly forest (widely dis-tributed in thewhole basin) and farmland (mainly distributedin the upper basin) accounting for 6456 and 2233respectively while garden meadow and water took a littlepart with the percentage of 594 471 and 228 respec-tively Urban land mainly distributed in the downstreambasin and the unutilized land took the least percentage in theDongjiang basinThe area of two types of land use urban landand farmland increased from 1980 along with the decreaseof garden (265)meadow (123) water (049) and forest(238) in 2000 while the dominant land use was still forestin 2000 In all since 1980s the landuse in theDongjiang basinhas been characterized with a prominent increase in urbanland a little increase in farmland and great decrease in forestarea while little change inwater area andunutilized landThisland use change due to fast social and economic developmenthad a significant impact on the hydrological response andthen contributed to the variability of water resources in theregion
43 Runoff Simulation and Runoff Change Analysis
431 The Value of CN CN (curve number) can reflect thecapacity of runoff yield for the land cover with a continuousspatial distribution The CN isocline represents the runoffyield capacities in the study basin
Based on land use maps of two periods (1980 and 2000)and soil type data of the Dongjiang basin CN distributionmaps (see Figure 7) of 3 AMC (antecedent moisture condi-tion) scenarios in the same periodswere obtainedwith spatialinterpolation Figure 8 showed the CN distribution maps forAMC II of the four sub-basins in the two periods
432 Model Calibration and Validation The SCS monthlymodel was calibrated in the period of 1970ndash1976 with climaticdata and then validated in the period of 1977-1978 by manualcalibration method with the acceptable set of parametersafter CN value analysis To measure the performance of themodel we chose Nash-Sutcliffe coefficient of efficiency (NSE)criterion [55] and relative error (RE) as objective function
8 Mathematical Problems in Engineering
Table 2 The correlation coefficient of each meteorological element to runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight HumidityD1 Upper Longchuan minus010 080 minus04 minus035 027D2 Midstream Heyuan minus023 069 minus028 minus039 035D The whole Basin Boluo minus008 088 minus054 minus057 026
Table 3 The relevancies between each meteorological element and runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight Humidity
D1 Upper Longchuan 04884 05503 04688 0449 04702Rank 2 1 4 5 3
D2 Midstream Heyuan 04857 05389 04659 04313 04861Rank 3 1 4 5 2
D The whole basin Boluo 0525 05968 04883 04495 05239Rank 2 1 4 5 3
Table 4 Comparison of land use in the Dongjiang basin during two different periods
Land use The year 1980 The year 2000Δ area (km
2) Ratio ()Area (km2) Ratio () Area (km2) Ratio ()
Farmland 608349 2233 727273 2669 118924 436Garden 161914 594 89670 329 minus72244 minus265Forest 1758688 6456 1693987 6218 minus64701 minus238Meadow 128274 471 94714 348 minus33560 minus123Built-up 3002 012 68225 25 65223 238Waters 61999 228 48012 179 minus13987 minus049Unutilized land 1738 006 2080 007 342 001
1980 1980 1980
2000 2000 2000
AMC I AMC II AMC III
Figure 7 Comparison of CN distribution under 3 AMC scenarios in the Dongjiang basin of two periods (1980 and 2000)
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
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Mathematical PhysicsAdvances in
Complex AnalysisJournal of
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OptimizationJournal of
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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
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Discrete Dynamics in Nature and Society
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
8 Mathematical Problems in Engineering
Table 2 The correlation coefficient of each meteorological element to runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight HumidityD1 Upper Longchuan minus010 080 minus04 minus035 027D2 Midstream Heyuan minus023 069 minus028 minus039 035D The whole Basin Boluo minus008 088 minus054 minus057 026
Table 3 The relevancies between each meteorological element and runoff in the Dongjiang basin
Basin units Basin scope Gauge stations Temperature Precipitation Evaporation Sunlight Humidity
D1 Upper Longchuan 04884 05503 04688 0449 04702Rank 2 1 4 5 3
D2 Midstream Heyuan 04857 05389 04659 04313 04861Rank 3 1 4 5 2
D The whole basin Boluo 0525 05968 04883 04495 05239Rank 2 1 4 5 3
Table 4 Comparison of land use in the Dongjiang basin during two different periods
Land use The year 1980 The year 2000Δ area (km
2) Ratio ()Area (km2) Ratio () Area (km2) Ratio ()
Farmland 608349 2233 727273 2669 118924 436Garden 161914 594 89670 329 minus72244 minus265Forest 1758688 6456 1693987 6218 minus64701 minus238Meadow 128274 471 94714 348 minus33560 minus123Built-up 3002 012 68225 25 65223 238Waters 61999 228 48012 179 minus13987 minus049Unutilized land 1738 006 2080 007 342 001
1980 1980 1980
2000 2000 2000
AMC I AMC II AMC III
Figure 7 Comparison of CN distribution under 3 AMC scenarios in the Dongjiang basin of two periods (1980 and 2000)
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Mathematical Problems in Engineering 9
Table 5 Calibration and validation of the SCS monthly model
Sub-basins Runoff coefficient Calibration NSE RE EvaluationData lengthyears 119886 119888 Data lengthyears NSE RE
Shuntian 0596 7 0699 0858 816 10 2 925 minus97Yuecheng 0658 7 0592 0604 840 09 2 860 111Lantang 0515 7 0601 0832 830 16 2 940 minus18Jiuzhou 0571 7 0674 0821 823 minus05 2 793 209
Shuntian Yuecheng LantangJiuzhou
1980 1980 1980 1980
2000 2000 2000 2000
Figure 8 Comparison of the CN distribution under AMC II scenario for the four sub-basins in the Dongjiang basin of two periods (1980and 2000)
0
200
400
600
800
1000050
100150200250300
Prec
ipita
tion
(mm
)
Month
PrecipitationObserved runoffSimulated runoff
Runo
ff (m
3s
)
1 7 13 19 25 31 37 43 49 55 61 67
Figure 9 Comparison of simulated and observed runoffs in thecalibration period (1970ndash1976) in the Shuntian subbasin
The results of simulation were listed in Table 5 Thecomparisons between simulated and observed runoffs ofthe calibration and validation periods in Shuntian sub-basin were illustrated in Figures 9 and 10 respectively Thesimulated results by the SCSmonthlymodel were comparablewith the observations in the four sub-basins Nash-Sutcliffecoefficients were above 08 andREwaswithin the pale of 002for those all four sub-basins in the calibration period It can beinferred from Figures 9 and 10 that the simulated hydrograph
0200400600800100012000
50100150200250300
1 3 5 7 9 11 13 15 17 19 21 23Pr
ecip
itatio
n (m
m)
Month
Runo
ff (m
3s
)
PrecipitationObserved runoffSimulated runoff
Figure 10 Comparison of simulated and observed runoffs in thevalidation period (1977ndash1978) in the Shuntian sub-basin
matched well with the observed one and the peak flowswere coincided in both the calibration and validation periodsOverall model performance was acceptable within the studydomain and reliable to be extended to reconstruct the naturalrunoff
433 Runoff Simulation in Human Activity Period Based onthe CN value of land use in the first phase (before 1980)
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
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Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
10 Mathematical Problems in Engineering
Table 6 Monthly runoff changes of natural and human activity periods in the four sub-basins (108 m3)
Sub-basin Natural period 119877119873
119877HR Δ119877
119879
Human activity periodLand use change Climate change Other human activities
Δ119877
119871
120583119871 () Δ119877
119862
120583119862 () Δ119877
0
120583119877
0
()Shuntian 112 116 004 008 2411 minus015 4460 011 3129Yuecheng 055 053 minus001 003 1954 minus008 5474 004 2572Lantang 073 077 003 005 2994 minus007 4051 005 2955Jiuzhou 034 034 minus001 002 2550 minus005 5322 002 2127
and climatic data in the second phase (precipitation andevaporation from 1980 to 2000) in the four sub-basins thenatural monthly runoff I and its process in the human activityperiod were simulated by using the SCSmonthly model Andthemonthly runoff II was obtained under the land use changecondition (with the CN value of land use in 2000 as its input)by the same method The difference between the simulatedrunoffs in the two phases was the runoff change due to landuse change
The simulated monthly runoff change due to land usechange from 1980 to 2000 for each sub-basin was shownin Figure 11 It can be found that the runoff change variedfrom sub-basin to sub-basin and the changes in Yuechengsub-basin and Jiuzhou sub-basin were less than those of inShuntian and Lantang which was relevant to the variationscope of the CN value in the basins
434 The Quantitative Effect due to Climate and Land UseChanges The analysis of quantitative impacts on runoff dueto human activities particularly land use and climate changeswas carried out in the four sub-basinsThe runoff change dueto land use change was obtained from the simulated runoffby the SCS model in the two periods (human activity andnatural periods) The quantitative impacts of climate changeand human activities were identified by themethod presentedin (12) and the results were shown in Table 6
It can be seen from Table 6 that take Shuntian sub-basinfor instance as compared to natural period the runoff inhuman activity period increased by 4 times 106m3 The 2411increase of runoffwas contributed by the land use change Onthe contrary climate change contributed the 446 decreaseto runoff which was superior to that of land use changeA meaningful clue has been found for explaining such aresult as two most important factors of the runoff changeprecipitation showed an insignificant increasing trend whichwas different from that of temperature (significant increasingtrend) and the compound effects led to the reduction ofthe total runoff Other factors including natural and humanaspects accounted for 3129 to the runoff change Overall allthe driving factors can make the runoff change to a differentlevel among which the role played by climate change tooknearly the half for each sub-basin This was in accordancewith the result of identifying the quantitative effect of landuse and climate change on runoff in the high flow period inthe Dongjiang basin [30]
The impact of land use change on the total runoff changein Lantang sub-basin was the highest (2994) among thefour sub-basins while the impact ratios of climate change and
other human activities were 4051 and 2955 respectivelyIn summary human activities contributed 5949 to runoffchange which revealed that human activities were the majordriver for runoff change
It was obvious that climate change with increased pre-cipitation and decreased evaporation caused the increase ofrunoff in the study area Furthermore changes of inner-annual distribution precipitation also affected the runoffchange Seven pairs of simulated runoff under nearly equalamount of precipitation were shown in Table 7 It can befound from Table 7 that the greater the percentage of pre-cipitation in flood season the greater the simulated runoffin Shuntian sub-basin except for 1985 and 1987 It was alsoimplied that precipitation was the major driver for runoffchange in Shuntian sub-basin
To analyze the impact of land use change we dividedannual precipitation into four classes as under 1500mm1500ndash1800mm 1800ndash2000mm and above 2000mm in thefour sub-basins The total runoff change due to land usechange in each class was shown in Figure 12 It can be foundthat under larger precipitation the runoff (to be flattened)of flood season was less as compared with that of droughtseason and the whole year in the four sub-basins This wasattributed to land cover conversion due to construction ofreservoirs which storedmuch water in flood season for floodprevention andwater use In addition runoff yield changed tobemuch quick andmore sensitive to precipitation alongwiththe land cover conversion from forest to urban areas or othervegetation typesThe impact of land use change on runoffwasmore distinctive when the precipitation was larger
Finally it can be concluded that the runoff change wasaffected by many factors and the contribution ratio of eachfactor was different Climate change and human activities(especially the land use change) were the two dominantdrivers which contributed about 40sim50 each to the runoffchange Particularly the land use change whose impact onthe runoff change in flood season under large precipitationshould not be neglected The role played by climate changeand human activities including land use change should beconsidered respectively in the analysis of variability andavailability of water resources and then reasonable measuresand policies should be taken
5 Conclusions
Based on land usemaps of two time periods in the Dongjiangbasin this study identified the quantitative effects of landuse and climate change on the runoff which revealed some
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Mathematical Problems in Engineering 11
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(a) Shuntian
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(b) Lantang
0
300
600
900
1200minus20
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(c) Jiuzhou
minus20
0
300
600
900
1200
0
20
40
60
1 31 61 91 121 151 181 211 241Month
PrecipitationRunoff change
Prec
ipita
tion
(mm
)
Runo
ff ch
ange
(m3s
)
(d) Yuecheng
Figure 11 Processes of the simulated monthly runoffs change in the four sub-basins due to land use change from 1980 to 2000
003 002 0
minus024
091 095 10128
094 097 10 104
minus060
061218
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(a) Shuntian
minus004 minus008 minus009 minus013
025 035 038 049020 028 029 037
minus040
0408
P (mm)15
00ndash1
800
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(b) Yuecheng
006 005
minus003 minus015
026051 062
081033 057 058 066
minus040
040812
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
Flood seasonDry seasonAnnual
(c) Lantang
Flood seasonDry seasonAnnual
010 008 004
minus001
018 028 034 043029 035 038 042
minus040
04
08
P (mm)
1500
ndash180
0
1800
ndash200
0
lt1500
gt20
00ΔRL
(108m
3)
(d) Jiuzhou
Figure 12 Average annual runoff change due to land use change under different precipitation classes in the four sub-basins
interesting results with the application of the SCS monthlymodel
(1) The climate experienced significant changes in thebasin over the past 50 years and the changes were detectedusing the Mann-Kendall test method with the results ofnonsignificant increase in precipitation significant increasein temperature while decrease in evaporation and sunlight
(2) Land use has experienced a significant change sincethe 1980s in the Dongjiang basin with the characteristicof spatial distribution for the CN value under three AMCscenarios in two periods The average value of CN increased
and the CN value varied in each sub-basin due to differentland use patterns In particular expansion of urban area in thesouth part of the study area (downstream) and deforestationin the whole area provided contributory factors that affectedhydrological processes and subsequently increased runoff
(3) The SCS monthly model performed well in the foursub-basins of the Dongjiang basin and the results showedthat the runoff change in each sub-basin during two timeperiods was different The runoff change in Yuecheng sub-basin was less than that of Shuntian sub-basin and Lantangsub-basin which was in good correlation to the variation
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
12 Mathematical Problems in Engineering
Table 7 Simulated runoff yielded by similar amount of precipitations in the three sub-basins
Subbasins Year Precipitation (mm) Simulated runoff (108 m3)Annual Flood season Percentage of flood season ()
Shuntian
2004 1274 110810 8657 7561999 1279 110750 8700 8412002 1421 107961 7600 8122003 1425 125616 8817 9801985lowast 1639 121740 7427 11831987lowast 1643 118557 7214 13151982 1811 139643 7711 13041984 1813 159217 8783 1470
Lantang 1986 1628 125960 7739 7961998 1631 114810 7039 877
Jiuzhou
1981 1754 142700 8135 4001982 1752 139810 7979 3481984 1577 149850 9502 3871989 1575 131670 8361 351
Annual precipitation for Yuecheng subbasin varies greatly all the years as compared with other sub-basins and no similar amount of precipitations can befound in different years The impact of inner-annual distribution of precipitation on the variation of runoff in Yuecheng subbasin was neglected
scope of theCNvalueThemore land use changed the greaterthe CN value changed which resulted in the greater variationof the runoff under the same climatic condition
(4) The separated quantitative effect of land use andclimate change on the runoff showed that climate changeand human activities (including land use) contributed halfand half respectively to runoff change While land usechange independently contributed 20sim30 to the totalrunoff change Moreover the effect of land use on runoffchange was in different level under different amounts ofprecipitation The effect of climate change on runoff changehad a different inner-annual distribution even under a sameamount of annual precipitation
Further research is required to acquire the regional futureclimate scenarios coupled with the hydrological model of abasin scale under GCMs (general circulation models) withthe downscaling technique so as to further quantify the rela-tions between runoff and climatic variables In addition thespace-time distribution of floods and droughts resulted fromthe runoff change should also be studied to provide scientificframework for basin-scale water resources management
Acknowledgments
The research is financially supported by the National Nat-ural Science Foundation of China (Grant no 51210013)the Public Welfare Project of Ministry of Water Resources(Grant no 201301071-02 201301002-02) the project fromGuangdong Science and Technology Department (Grantno 2010B050300010) the project from Guangdong WaterResources Department (Grant no 2009-39) Key Projectof Chinese National Programs for Fundamental Researchand Development (973 program) (Grant no 2013CB0364062010CB951102) and the Pearl-River-New-Star of Science
and Technology supported by Guangzhou City (Grant no2011J2200051)
References
[1] A Bronstert D Niehoff and G Brger ldquoEffects of climate andland-use change on storm runoff generation present knowledgeandmodelling capabilitiesrdquoHydrological Processes vol 16 no 2pp 509ndash529 2002
[2] D Legesse C Vallet-Coulomb and F Gasse ldquoHydrologicalresponse of a catchment to climate and land use changes inTropical Africa case study south central Ethiopiardquo Journal ofHydrology vol 275 no 1-2 pp 67ndash85 2003
[3] B Zimmermann H Elsenbeer and J M De Moraes ldquoTheinfluence of land-use changes on soil hydraulic propertiesimplications for runoff generationrdquo Forest Ecology andManage-ment vol 222 no 1ndash3 pp 29ndash38 2006
[4] D Mao and K A Cherkauer ldquoImpacts of land-use changeon hydrologic responses in the Great Lakes regionrdquo Journal ofHydrology vol 374 no 1-2 pp 71ndash82 2009
[5] N A Adnan and P M Atkinson ldquoExploring the impactof climate and land use changes on streamflow trends in amonsoon catchmentrdquo International Journal of Climatology vol31 no 6 pp 815ndash831 2011
[6] T Jiang Y D Chen C-Y Xu X Chen X Chen and V PSingh ldquoComparison of hydrological impacts of climate changesimulated by six hydrological models in the Dongjiang BasinSouth Chinardquo Journal of Hydrology vol 336 no 3-4 pp 316ndash333 2007
[7] G B Fu J J Yu X B Yu et al ldquoTemporal variation of extremerainfall events in China 1961ndash2009rdquo Journal of Hydrology vol487 pp 48ndash59 2013
[8] G A Meehl F Zwiers J Evans T Knutson L Mearns and PWhetton ldquoTrends in extremeweather and climate events issuesrelated to modeling extremes in projections of future climate
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Mathematical Problems in Engineering 13
changerdquo Bulletin of the American Meteorological Society vol 81no 3 pp 427ndash436 2000
[9] S Wang S Kang L Zhang and F Li ldquoModelling hydrologicalresponse to different land-use and climate change scenariosin the Zamu River basin of northwest Chinardquo HydrologicalProcesses vol 22 no 14 pp 2502ndash2510 2008
[10] M Verbunt M Groot Zwaaftink and J Gurtz ldquoThe hydrologicimpact of land cover changes and hydropower stations in theAlpine Rhine basinrdquo Ecological Modelling vol 187 no 1 pp 71ndash84 2005
[11] M D Tomer and K E Schilling ldquoA simple approach todistinguish land-use and climate-change effects on watershedhydrologyrdquo Journal of Hydrology vol 376 no 1-2 pp 24ndash332009
[12] E-S Chung K Park and K S Lee ldquoThe relative impacts ofclimate change and urbanization on the hydrological responseof a Korean urban watershedrdquo Hydrological Processes vol 25no 4 pp 544ndash560 2011
[13] S Piao P Ciais Y Huang et al ldquoThe impacts of climate changeon water resources and agriculture in Chinardquo Nature vol 467no 7311 pp 43ndash51 2010
[14] P Zhai X Zhang H Wan and X Pan ldquoTrends in totalprecipitation and frequency of daily precipitation extremes overChinardquo Journal of Climate vol 18 no 7 pp 1096ndash1108 2005
[15] Y Q Chen Q Zhang X H Chen and P Wang ldquoMulti-scalevariability of runoff changes in the Pearl River basin ChinardquoQuaternary International vol 226 pp 44ndash53 2010
[16] C O Wilson and Q Weng ldquoSimulating the impacts of futureland use and climate changes on surface water quality in theDesPlaines River watershed ChicagoMetropolitan Statistical AreaIllinoisrdquo Science of the Total Environment vol 409 no 20 pp4387ndash4405 2011
[17] L Cuo T K Beyene N Voisin et al ldquoEffects of mid-twenty-first century climate and land cover change on the hydrologyof the Puget Sound basin Washingtonrdquo Hydrological Processesvol 25 no 11 pp 1729ndash1753 2011
[18] J I Lopez-Moreno S M Vicente-Serrano E Moran-Tejeda JZabalza J Lorenzo-Lacruz and J M Garcıa-Ruiz ldquoImpact ofclimate evolution and land use changes on water yield in theebro basinrdquo Hydrology and Earth System Sciences vol 15 no 1pp 311ndash322 2011
[19] L M Mango A MMelesse M E McClain D Gann and S GSetegn ldquoLand use and climate change impacts on the hydrologyof the upper Mara River Basin Kenya results of a modelingstudy to support better resource managementrdquo Hydrology andEarth System Sciences vol 15 no 7 pp 2245ndash2258 2011
[20] J C I Dooge M Bruen and B Parmentier ldquoA simple modelfor estimating the sensitivity of runoff to long-term changes inprecipitationwithout a change in vegetationrdquoAdvances inWaterResources vol 23 no 2 pp 153ndash163 1999
[21] R D Koster and M J Suarez ldquoA simple framework forexamining the interannual variability of land surface moisturefluxesrdquo Journal of Climate vol 12 no 7 pp 1911ndash1917 1999
[22] P C DMilly andK A Dunne ldquoMacro-scale water fluxes waterand energy supply control of their inter-annual variabilityrdquoWater Resources Research vol 38 p 1206 2002
[23] X C Ye Q Zhang and J Liu ldquoImpact of climate change andhuman activities on runoff of Poyang Lake Catchmentrdquo Journalof Glaciology and Geocryology vol 31 no 5 pp 835ndash842 2009(Chinese)
[24] X Ma J Xu and M van Noordwijk ldquoSensitivity of streamflowfrom a Himalayan catchment to plausible changes in land coverand climaterdquo Hydrological Processes vol 24 no 11 pp 1379ndash1390 2010
[25] X Hao Y Chen C Xu and W Li ldquoImpacts of climate changeand human activities on the surface runoff in the Tarim RiverBasin over the last fifty yearsrdquo Water Resources Managementvol 22 no 9 pp 1159ndash1171 2008
[26] J Wang Y Hong J Gourley P Adhikari L Li and F SuldquoQuantitative assessment of climate change and human impactson long-term hydrologic response a case study in a sub-basinof the YellowRiver Chinardquo International Journal of Climatologyvol 30 no 14 pp 2130ndash2137 2010
[27] Z Li W-Z Liu X-C Zhang and F-L Zheng ldquoImpacts ofland use change and climate variability on hydrology in anagricultural catchment on the Loess Plateau of Chinardquo Journalof Hydrology vol 377 no 1-2 pp 35ndash42 2009
[28] G Wang J Xia and J Che ldquoQuantification of effects of climatevariations and human activities on runoff by a monthly waterbalance model a case study of the Chaobai River basin innorthernChinardquoWater Resources Research vol 45 no 7 ArticleID W00A11 2009
[29] J Fan F Tian Y Yang S Han and G Qiu ldquoQuantifying themagnitude of the impact of climate change and human activityon runoff decline in Mian River Basin Chinardquo Water Scienceand Technology vol 62 no 4 pp 783ndash791 2010
[30] D Liu X Chen Y Lian and Z Lou ldquoImpacts of climate changeand human activities on surface runoff in the Dongjiang Riverbasin of ChinardquoHydrological Processes vol 24 no 11 pp 1487ndash1495 2010
[31] K Lin S GuoW Zhang and P Liu ldquoA new baseflow separationmethod based on analytical solutions of the Horton infiltrationcapacity curverdquo Hydrological Processes vol 21 no 13 pp 1719ndash1736 2007
[32] K Lin Q Zhang and X Chen ldquoAn evaluation of impacts ofDEM resolution and parameter correlation on TOPMODELmodeling uncertaintyrdquo Journal of Hydrology vol 394 no 3-4pp 370ndash383 2010
[33] Y Hundecha and A Bardossy ldquoModeling of the effect of landuse changes on the runoff generation of a river basin throughparameter regionalization of a watershed modelrdquo Journal ofHydrology vol 292 no 1ndash4 pp 281ndash295 2004
[34] K Y Li M T Coe N Ramankutty and R D Jong ldquoModelingthe hydrological impact of land-use change in West AfricardquoJournal of Hydrology vol 337 no 3-4 pp 258ndash268 2007
[35] G Parkin G OrsquoDonnell J Ewen J C Bathurst P E OrsquoConnelland J Lavabre ldquoValidation of catchment models for predictingland-use and climate change impacts 2 Case study for aMediterranean catchmentrdquo Journal of Hydrology vol 175 no1ndash4 pp 595ndash613 1996
[36] J K Loslashrup J C Refsgaard and D Mazvimavi ldquoAssessing theeffect of land use change on catchment runoff by combined useof statistical tests and hydrological modelling case studies fromZimbabwerdquo Journal of Hydrology vol 205 no 3-4 pp 147ndash1631998
[37] D Niehoff U Fritsch and A Bronstert ldquoLand-use impactson storm-runoff generation scenarios of land-use change andsimulation of hydrological response in a meso-scale catchmentin SW-Germanyrdquo Journal of Hydrology vol 267 no 1-2 pp 80ndash93 2002
[38] B Troy C Sarron J M Fritsch and D Rollin ldquoAssessment ofthe impacts of land use changes on the hydrological regime of a
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
14 Mathematical Problems in Engineering
small rural catchment in South Africardquo Physics and Chemistryof the Earth vol 32 no 15ndash18 pp 984ndash994 2007
[39] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[40] D H Burn ldquoClimatic influences on streamflow timing in theheadwaters of theMackenzie River Basinrdquo Journal of Hydrologyvol 352 no 1-2 pp 225ndash238 2008
[41] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 no 7 pp 245ndash259 1945
[42] M G Kendall Rank CorrelationMethods Griffin London UK1975
[43] J M Mitchell B Dzerdzeevskii H Flohn et al ldquoClimatechangerdquoWMOTechnical Note 79WorldMeteorological Orga-nization 1966
[44] E Kahya and S Kalayci ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 no 1ndash4 pp 128ndash1442004
[45] Z X Xu K Takeuchi H Ishidaira and J Y Li ldquoLong-termtrend analysis for precipitation in Asian Pacific FRIEND riverbasinsrdquo Hydrological Processes vol 19 no 18 pp 3517ndash35322005
[46] R Modarres and V de Paulo Rodrigues da Silva ldquoRainfalltrends in arid and semi-arid regions of Iranrdquo Journal of AridEnvironments vol 70 no 2 pp 344ndash355 2007
[47] F-W Gerstengarbe and P C Werner ldquoEstimation of thebeginning and end of recurrent events within a climate regimerdquoClimate Research vol 11 no 2 pp 97ndash107 1999
[48] T Jiang and Q Zhang ldquoClimatic changes driving on floods inthe Yangtze Delta China during 1000ndash2002rdquo European Journalof Geography Cybergeo vol 296 pp 1ndash21 2004
[49] M C Karabork ldquoTrends in drought patterns of Turkeyrdquo Journalof Environmental Engineering and Science vol 6 no 1 pp 45ndash52 2007
[50] D RamakrishnanA Bandyopadhyay andKNKusuma ldquoSCS-CN and GIS-based approach for identifying potential waterharvesting sites in the KaliWatershedMahi River Basin IndiardquoJournal of Earth SystemScience vol 118 no 4 pp 355ndash368 2009
[51] R K Sahu S K Mishra and T I Eldho ldquoComparative evalu-ation of SCS-CN-inspired models in applications to classifieddatasetsrdquo Agricultural Water Management vol 97 no 5 pp749ndash756 2010
[52] D G DurbudeM K Jain and S KMishra ldquoLong-term hydro-logic simulation using SCS-CN-based improved soil moistureaccounting procedurerdquoHydrological Processes vol 25 no 4 pp561ndash579 2011
[53] L H Xiong and S L Guo Distributed Hydrological ModelChina Water Power Press 2004
[54] X H Chen and Z L Wang ldquoLand use change and its impacton water resources in east river basin south Chinardquo Journalof Beijing Normal University vol 46 no 3 pp 311ndash316 2010(Chinese)
[55] J E Nash and J V Sutcliffe ldquoRiver flow forecasting throughconceptual models part Imdasha discussion of principlesrdquo Journalof Hydrology vol 10 no 3 pp 282ndash290 1970
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttpwwwhindawicom
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom
Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Stochastic AnalysisInternational Journal of
![Land Use and Climate Interactions [i.e. the role of land ... · Land Use and Climate Interactions [i.e. the role of land use within the climate system] ... shortwave ADRF, and shortwave](https://static.fdocuments.us/doc/165x107/5b5c36f17f8b9aa1428ba805/land-use-and-climate-interactions-ie-the-role-of-land-land-use-and-climate.jpg)
