Post on 08-Jan-2016
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EVALUATION OF URBAN FLOODS CONSIDERING CLIMATE CHANGE IMPACTS
Mohammad KaramouzProfessor, School of Civil Engineering, University of Tehran, Email: karamouz@ut.ac.ir
Ana HosseinpoorM.Sc. student, School of Civil Engineering, University of Tehran, Email:
ahoseinpour@ut.ac.ir
Sara NazifPh.D. candidate, School of Civil Engineering, University of Tehran, Email:
snazif@ut.ac.ir
Evaluation of urban floods considering climate change impacts 2
Introduction The urban floods could be very destructive in high population density
zone and in centers of economic and industrial activities.
The urbanization changes natural morphology of local rivers and often decreases their natural carrying capacity resulting from various activities and therefore intensifies the risk of urban floods.
The effects of climate change on hydrologic cycle have led to increased concerns about urban flood events especially in mega cities of the developing countries.
In this Study, the performance of drainage system of northern part of Tehran metropolitan area (capital of Iran) has been investigated
Evaluation of urban floods considering climate change impacts 3
Case studyThe The northeastern part of Tehran
•51º-22´ and 51 º-30´ longitudes
•35º -42´ and 35º -53´ latitudes
•Includes
•Darband sub-basin(zone 1)
•Golabdare sub-basin(zone 2)
•Velenjak sub-basin(zone 3)
•Sadabad sub-basin(zone 4)
•Kashanak sub-basin(zone 5)
•Jamshidie sub-basin(zone 6)
•Zones 7- 19
Evaluation of urban floods considering climate change impacts 4
zoneArea(hec)
12216.5
2639.8
3306.9
4803.16
5473
6188
71511.1
8424.5
9448.7
10242.9
11213.7
1240.46
13662.37
14734
15607.59
1622
17128.49
18913.68
19366.5
Evaluation of urban floods considering climate change impacts 5
Types of channels •Natural
•Man made
average slope: About 21%. The percentage of impervious area: 85%
The altitude: Between 1290 m and 3900 m.
Total drainage area: About 110 km²
Case study
Evaluation of urban floods considering climate change impacts 6
Data:
The rainfall data at Roodak station located in latitude 35º-51´ and longitude 51º-33´ with adequate recorded data which is out of the study area has been considered as a representative of the rainfall data of the study area.
The Ghasr station snow data has been used which is available between years 1975 and 1995.
Mehrabad (synoptic station ) is used as a source for wind and temperature
data which is about 10 Km away from the study area.
Case study
Evaluation of urban floods considering climate change impacts 7
Three scenarios have been considered for studied area drainage system
modeling as follows: Scenario 1: The surface water collection system in about 10 years ago.
•The model for this scenario is developed to evaluate the effectiveness of development projects done in the recent years.
Scenario 2: The present situation of surface water collection system.
Scenario 3: The future plans for improving and development of case study drainage system have been modeled in this scenario.
Case study
Evaluation of urban floods considering climate change impacts 8
Case study(a) Scenario 1
(Past)
(b) Scenario 2(Present)
)c (Scenario 3)Future(
Differences between considered scenarios
Added
abundant
Evaluation of urban floods considering climate change impacts 9
Case study
Percentage of
impervious area (%)
Number of detention
ponds
Total Capacity of detention
ponds (m3)
Natural channel
Man made closed channel
Man made open
channel
Scenario 1 :814 7500 17720 16940 45690
Scenario 2 85 59450 16170 21095 30650
Scenario 3 :90713380 16170 29915 30650
The characteristics of the different scenarios for water drainage system
Evaluation of urban floods considering climate change impacts 10
Case study
Governing Parameters in the scenarios:
The channel coverage and alignment
The number and placement of detention ponds
The land use and percentage of pervious area
Evaluation of urban floods considering climate change impacts 11
Methodology For evaluation of climate change effects on urban floods a statistical
downscaling model (SDSM) developed by wilby et al. (2004) is used.
The drainage system of the study area has been simulated using StormNET model.
The critical rainfall that may result in probable floods in the region are those which satisfy the following inequality:
Where Where μμіі and and σσіі are the average and standard division of rainfall in season i of the rainfall series, are the average and standard division of rainfall in season i of the rainfall series,
respectively. Rxi is considered the extreme rainfall in season irespectively. Rxi is considered the extreme rainfall in season i
iiiRx *2
Evaluation of urban floods considering climate change impacts 12
The effects of climate change on the magnitude and frequency of the extreme seasonal rainfalls in the future are evaluated.
The hydraulic model of the drainage system is calibrated.
The impact of rainfalls with different return periods is evaluated running the hydraulic simulation model for the three pre-defined scenarios in the study area.
Methodology
Evaluation of urban floods considering climate change impacts 13
Methodology
Rainfall downscaling: SDSM carries five distinct tasks:
Screening of potential downscaling predictors
Assembly and calibration of model
Synthesis of ensembles of current weather data using observed predictors
Generation of ensembles of future weather data using GCM-derived predictor variables
Diagnostic testing/analysis of observed data and climate change scenarios
Evaluation of urban floods considering climate change impacts 14
Methodology
Rainfall downscaling:
SDSM model has been used for long-lead rainfall prediction and downscaling for an individual site on a daily time–scale, by using GCM outputs.
During the downscaling with the SDSM, a multiple linear regression model is developed using selected large-scale predictors and the local rainfall.
Large-scale relevant predictors are selected using correlation analysis, partial correlation analysis and scatter plots, considering the sensitivity between the selected predictors and rainfall for the region
Evaluation of urban floods considering climate change impacts 15
Methodology
Hydraulic modeling of urban drainage system :
The StormNET model developed by Boss International (2005) has been used for simulation of the urban drainage system.
StormNET is a link-node based model that performs hydrology, hydraulic, and water quality analysis of stormwater and wastewater drainage systems.
Evaluation of urban floods considering climate change impacts 16
Methodology
Hydraulic modeling of urban drainage system :The StormNET model needs some data on:
Sub-basin (total area, pervious and impervious area, manning’s roughness,…) Detention pond (shape of detention pond, elevation,…) Flow diversion Snow pack Rainfall hyetograph Channel and pipe links (shape, manning’s roughness,…)
Evaluation of urban floods considering climate change impacts 17
Methodology Hydraulic modeling of urban drainage system: It is important to consider the resulted runoff due to snow melting in
modeling of the drainage system.
The snow melt coefficient has been calculated as follows:
M is snowmelt runoff (mm), D is average number of degree day above zero (the snow melt base temperature has been determined 0°c for Tehran) and K is the snowmelt coefficient.
The following degree-day equation has been used to compute the melt rate:
Melt Rate = (Melt Coefficient) (Air Temperature - Base Temperature)
D
MK
D
MK
D
MK
Evaluation of urban floods considering climate change impacts 18
Methodology
Hydraulic modeling of urban drainage system : The SANTA BARBARA method :Simulation of sub-basin runoff
The KIRPICH method: Estimation of the basins time of concentration.
The Manning's roughness for pervious area 0.015
The Manning's roughness for impervious area .0149.
The soil property group D
CN of the pervious area varies between 76 and 84.
Evaluation of urban floods considering climate change impacts 19
Results> Downscaling Daily rainfall data at Roodak station has been transformed by the second
root function to better fit normal distribution The correlations between different combinations of available predictors and
daily rainfall have been calculated to find the most appropriate combination.
The combination of 3 predictors is selected 1) relative humidity at 850 hPa height, 2) near surface specific humidity3) near surface relative humidity.
The physical relation between the selected predictors and the rainfall of the study area has been implicitly considered by calculation of P-value between predictors and rainfall.
The model has been calibrated with rainfall data of 1977-1984 and validated for the remaining available data (1985-2000).
Evaluation of urban floods considering climate change impacts 20
Results Errors of rainfall prediction include errors of mean and maximum daily rainfall
and wet spells, during the validation period for NCEP( National Center For Environmental Prediction) and HadCM3(Second Hadley Centre Coupled Ocean-Atmosphere GCM)
Signal source variable MAE )Mean Absolute Error(
RMSE )Root Mean Square
Error(
NCEP Mean rainfall (mm)
0.07 2.08
Maximum rainfall (mm)
0.11 5.09
Wet spell (hr) 3.4 .48
HadCm3 Mean rainfall (mm)
0.19 2.65
Maximum rainfall (mm)
0.12 3.4
Wet spell (hr) 4.1 .62
Evaluation of urban floods considering climate change impacts 21
Results
0
5
10
15
20
25
30
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Rai
nfal
l (m
m)
Observed rainfall
Modeled rainfall using NCEP signals
•20 ensemble data of rainfall have been generated.
Evaluation of urban floods considering climate change impacts 22
Results YearNumber of extreme rainfalls Average of extreme rainfalls
Spring Summer Fall Winter Spring Summer Fall Winter
2007121101329.03 17.8 27.06 46.56
201711281749.7 33.46 48.42 42.45
2027231121722.18 76.99 49.45 38.61
203720191126.25 15.4 32.87 62.65
20471508826.12 048.6 50.77
2057180161631.24 037.94 40.27
20671809937.39 035.69 38.66
2077180121232.85 056 45.15
20871919940.1 7155.9 46.44
2097150141442.85 047.41 59.44
Evaluation of urban floods considering climate change impacts 23
Results The hydraulic model of the drainage system is calibrated with the observed
1995 flood hydrograph in Golabdareh (zone 2).
0
50
100
150
200
250
300
0 0.5 1 1.5 2 2.5time(hr)
Q(c
ms)
Simulated hydrograph
Observed hydrograph
Evaluation of urban floods considering climate change impacts 24
Results The severity of wet and dry periods is increasing in the study area due to the
effects of climate change
The peak volumes of the floods are increasing
Increasing the peak volumes lead to considerable damaged and it is necessary
to revise the river training projects in the study area
Application of some new river training programs for dredging the channels and construction of new detention and retention ponds are needed.
Evaluation of urban floods considering climate change impacts 25
Results
No obvious trends in the volume and peak of floods due to climate change effects could be obseved.
The man-made channels have changed the characteristics of the drainage system. The positive effects are not uniform.
In response to the river training projects in the last 10 years, the flood peaks and volumes have been increased considerably.
As the capacity of the system increases, the overflow volumes variations are mixed.
Evaluation of urban floods considering climate change impacts 26
Conclusion In urban areas due to some special characteristics such as the population
concentration and limitations on the natural water systems, the effects of climate change are intensified.
One of the most important components of urban water cycle is urban runoff which is highly affected by climate change and urbanization.
In this study the effects of climate change on urban runoff in the northeast of Tehran is evaluated.
The downscaling model has been used to predict the future rainfall and then extreme rainfalls are identified.
Evaluation of urban floods considering climate change impacts 27
Conclusion The characteristics of the extreme rainfall of future years including the
frequency and the magnitude are evaluated.
It seems that the severity of wet and dry periods is increasing in the study area due to effects of climate change. Further study is needed.
The identified extreme rainfalls are applied in a hydraulic simulation model considering the existing and the future expansion of the system.
Evaluation of urban floods considering climate change impacts 28
Conclusion The results show that the peak volumes of the floods are increasing.
This may lead to considerable damaged and it is necessary to revise the current plans for river training projects of the drainage channels in the study area.
An integrated approach is needed to deal with the combined urban expansion and the climate change impacts.
Thank you for your Attention
For more information please contact:
Mohammad Karamouz: karamouz@ut.ac.ir
Tel: 0098-21-88555884
Fax:0098-21-88701507
Evaluation of urban floods considering climate change impacts 30
Methodology Hydraulic modeling of urban drainage system : The flow diverted through a weir flow diversion is computed through the
following equation:
is the diverted flow (m3/s), is weir coefficient, is weir height. f is a coefficient that is computed as follows:
Qin is inflow to the flow diversion, Qmin is the minimum flow at which flow diversion begins and Qmax is the maximum capacity of the channel.
All of the weirs in the system are assumed to be rectangular.
)*( wwdiv HfCQ divQ
wC wH
minmax
min
QQf in
Evaluation of urban floods considering climate change impacts 31
Results The extreme rainfall with different return periods are simulated by three
developed hydraulic models.
0
1000000
2000000
3000000
4000000
5000000
Vo
lum
e (m
^3)
140
160
180
200
220
240
260
Q (
cms)
Flood Volume
Overflow Volume
Flood Peak
0
1000000
2000000
3000000
4000000
5000000
2007
-20
2007
-200
2017
-100
2027
-50
2037
-20
2037
-200
2047
-100
2057
-50
2067
-20
2067
-200
2077
-100
2087
-50
2097
-20
2097
-200
Vo
lum
e (m
^3)
140
160
180
200
220
240
260
Q (
cms)
Flood Volume
Overflow Volume
Flood Peak
0
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
4500000
2007
-20
2007
-200
2017
-100
2027
-50
2037
-20
2037
-200
2047
-100
2057
-50
2067
-20
2067
-200
2077
-100
2087
-50
2097
-20
2097
-200
Vo
lum
e (
M^
3)
140
160
180
200
220
240
260
280
300
320
Q (
cm
s)
Flood Volume
Overflow Volume
Flood Peak
Evaluation of urban floods considering climate change impacts 32
Results
The average of long-term observed rainfall has been compared to the rainfall using NCEP signal and modeled rainfall using HADCM3
One of the predicted scenarios for future climate variation named HadCM3 (Second Hadley Centre Coupled Ocean-Atmosphere GCM) is used as the model input signal and rainfall is predicted