COMPARISION OF SOIL INFILTRATION UNDER … · 2018-09-04 · soil infiltration rates and compared...

CIVIL AND ENVIRONMENTAL ENGINEERING SOCIETY

79Proceedings of the Undergraduate Research Symposium on Recent Advances in Civil Engineering

6th January 2017

COMPARISION OF SOIL INFILTRATION UNDER DIFFERENT SURFACE CONDITIONS

T. Venukanan and T. N. Wickramaarachchi

ABSTRACT

Water penetrates into the soil is called infiltration. Determination of infiltration capacity is vital in designing of drainage systems and irrigation water supply systems. Infiltration depends on many factors such as soil parameters, vegetation, and initial moisture content. Hapugala area in Galle was the study area selected for the study. There are many models that can be used to estimate the infiltration capacity. In this study, measured infiltration in vegetation and non-vegetation lands was compared with model estimated values. Horton, Kostiakov and Green-Ampt models were analysed and field validation was checked. Double ring infiltrometer method was used to measure the field infiltration capacity. R2 (Correlation coefficient) and RMSE (Root Mean Square Error) values were calculated to select the best fit model. For the study area, Horton model was found as the best fit model for vegetation land and the Kostiakov model was found as the best fit model for non-vegetation land.

1. INTRODUCTION

Infiltration refers as water penetration into the soil downward. The rate of water moving into the soil in a particular time period is called infiltration rate. There are many factors that affect the infiltration. Soil texture, moisture content and vegetation cover are the most important factors.

Infiltration capacity can be measured by various methods. Double ring infiltrometer is a common filed method. The infiltration of water into the soil has important impact in the overall functioning of the variable land based activates. Therefore, infiltration is an important factor in the hydrologic modelling. Suitable infiltration models were selected for vegetation and non-vegetation lands in Hapugala area in this study by analyzing the measured and model estimated values. Galle features a tropical rainforest climate and soil type in the Galle including Hapugala area is laterite.

2. METHODOLOGY

Sieve analysis test and double ring infiltrometer test were conducted to analysis the soil infiltration capacity of Hapugala.

2.1 Sieve Analysis TestThe sieve analysis test was conducted to find the particle size distribution of soils in different places. Two sites were selected with different particle size distribution according to the sieve analysis test. Infiltration capacity was measured in these two sites with different soil textures.

2.2 Double Ring Infiltrometer Test Double ring infiltrometer was installed 5 cm into the ground without disturbing the soil in the selected sites. Initial moisture content was calculated before starting the infiltration measurement. Then the infiltration capacity was measured in various time intervals. Water was filled

to the inner ring, approximately 10 cm, without disturbing the surface soil. Infiltration measurement was stopped when infiltration rate became to constant rate or 15% of the initial infiltration capacity.

2.3 Measurements in Vegetation Land Green gram was planted inside the ring to make vegetation land. Green gram has been selected since it has quick growth and its root zone depth is similar to many other crop plants. The double ring infiltrometer test was conducted after two weeks of planting the crop when thecrops are having root zone depth of approximately 10 cm to 15 cm.

2.4 Infiltration ModelsThe infiltration capacity was compared for the two locations having different soil textures and different surface conditions. Also the initial infiltration rate wasinvestigated with the initial moisture content.The infiltration capacity was analyzed with Horton, Kostiakov and Green-Ampt models.

Horton model : fp = fc + (fo fc) e-

Kostiakov model : fp = Kk t

Green-Ampt model : fp = m +

In above empirical equations, fp is the infiltration capacity, fo is initial infiltration rate, fc is final constant infiltration rate, k , m and n are constant parameter depends on initial moisture content and soil texture, and t is time (Akinbile, 2010). According to Ogbe, Jayeoba & Ode (2011), R2 (Correlation coefficient) and RMSE (Root Mean Square Error) values were calculated for all three models to select the most suitable models for the study sites.



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3. RESULTS AND DISCUSSION

3.1 Selection of the SiteFive places were selected to carry out the sieve analysis test. First, one location (Location 1) was fixed considering the possibility of continuation of the experimental set up in future. Other location (Location 4) was selected with much different particle size distribution from the first location. Figure 1 shows the particle size distribution curves for all five sites where the sieve analysis tests were carried out.

3.2 Comparison of Infiltration CapacitiesInfiltration capacities were compared in the two locations selected. The infiltration capacity of the Location 4 is greater than that of Location 1 due to the soil texture. That is because the sand percentage of the Location 4 is higher than the Location 1. Figure 2 shows the difference between the infiltration capacities of the Location 1 and Location 4. Figure 3 shows the infiltration capacities in both vegetation and non- vegetation lands. Infiltration capacity of vegetation land is greater than the infiltration capacity in the non-vegetation land.

3.3 Infiltration Model AnalysisThe Horton, Kostiakov and Green-Ampt infiltration models were analyzed with the field data. R2 and RMSE

values were calculated for all three models to find the best fit model. The calculated average R2 and RMSE values are shown in Tables 1 and Table 2. Considering R2

and RMSE, Horton model is the best fit model for the vegetation land. For the non-vegetation land, Kostiakov is the best fit model.

Table 1: Average R2 and RMSE values for vegetation land

4. CONCLUSIONS

According to the results, the Horton infiltration model is the best fit model for vegetation land and Kostiakov infiltration model is the best fit model for non- vegetationland in Hapugala area. Soil texture is a major factor which affects the infiltration. Also crop vegetation cover increased the infiltration capacity due to disturbance to soil by penetrated roots.

REFERENCES

Advances in Applied Science Research, vol. 1, no.1, pp. 49-57.

Ogbe, VB, Jayeoba, OJ & Ode, SO 2011, Comparison of Four Soil Infiltration Models on A Sandy Soil in Lafia-Southern Guinea Savanna Zone of Nigeria , Publication of Nasarawa State University, Keffi, Nigeria. Available from: http://patnsukjournal.net/Vol7No2/p14.pdf[06th May 2016].

Figure 1: Particle size distribution curves

Figure 2: Comparison of infiltration capacities in Location 1 and Location 4

Figure 3: Comparison of infiltration capacities in vegetation and non-vegetation lands

Table 2: Average R2 and RMSE values for non-vegetation land



6th January 2017

COMPARATIVE ANALYSIS OF VERTICAL AND LATERAL INFILTRATION

R. Diluckshanaraj and T.N. Wickramaarachchi

ABSTRACT

Constant infiltration rates of different soils were analyzed at Hapugala area in Galle District. Experimental work was carried out in two locations in Hapugala with different soil textures. Study aimed at determining the vertical and lateralinfiltration rates of those different soils and comparing them with the infiltration rates obtained by Kostiakov, Hortonand Green-Ampt infiltration models. For getting best fit model for particular soil, the results obtained from various infiltration models were compared with observed field data. In this study, the ability of three models to fit vertical and lateral infiltration data was evaluated. Coefficient of Determination (R2) and Root Mean Square Error (RMSE) were considered in determining the optimum model. Study revealed that the Kostiakov model was the best fitting model toobserved field data in estimating both vertical and lateral infiltration rates at any given time with high degree of R2 and minimum RMSE.

1. INTRODUCTION

The water infiltration rate rolls in many situations such as agriculture and drainage issues. Soil infiltration is one of the vital components that needs to be considered in selecting particular irrigation method. Also for the irrigation purposes it is important to know the factors which are effecting the soil infiltration. Infiltration of water into the soil has important impact in all functions related to the land based activities. Hence it is required to determine vertical and lateral infiltration capacities of soil, separately.Many factors affect the infiltration rate. The sediment texture and structure, the condition of the sediment surface, the distribution of soil moisture or soil-moisture tension, the chemical and physical type of the water, head of the applied water, the depth to ground water table, time of application of water, biological activity, the temperature of the water and the sediments, the percentage of entrapped air in the sediments, and the atmospheric pressure (Lewis, 1937).Most probably, the ring infiltrometer method includes the perfect and accurate field methods in getting data on infiltration rates (Michelson & Muckel, 1937). The main objective of this research was to determine the most suitable model to estimate vertical and lateral infiltrationsfor the selected soil types (at different locations in Hapugala). From R2 value and RMSE value, the best fitted model was determined for vertical and lateral infiltration with high degree of R2 and minimum RMSE.

2. METHODOLOGY

For the experiment, two different locations were selected. As the first step, soil samples were collected in many places to find the soil texture. Then sieve analysis test was conducted to find out the percentage of the gravel, coarse sand and fine particles. Based on the soil texture, two different soils were selected in suitable areas in the faculty premises in Hapugala. In both locations, single ring and double ring infiltrometers were installed. Field

measurements were carried out to collected data on initial soil moisture content. Experimental data were analyzedby the Horton, Kostiakov and Green-Ampt models.Suitable models for vertical and lateral infiltrations in each location were determined based on the analysis considering the R2 value and RMSE value. For both locations, best fit models were investigated.


Comparison of vertical and lateral infiltration is shown in Figure 1. Figure 1 shows that the lateral infiltration is higher than the vertical infiltration for both locations. The infiltration tests performed during the dry season are preferable, as tests performed in the wet season are unlikely to reflect the stable soil characteristics that show the influence of antecedent soil water content on the measured infiltration capacity.

Figure 1: Comparison of vertical and lateral infiltration

Initial moisture content of the soil affects the infiltration capacity. Figure 2 shows the variation of initial soil moisture content with initial infiltration rate.



6th January 2017

Figure 2: Variation of initial soil moisture content with initial infiltration rate

Table 1: Comparison of R2 and RMSE values for lateral infiltration

ModelLocation 1 Location 2

R2 RMSE R2 RMSE

Horton 0.7639 0.2471 0.7688 0.5416

Kostiakov 0.9481 0.0709 0.9148 0.0563

Green-Ampt 0.7173 0.6501 0.8198 0.5417

As shown in Table 1, for the Kostiakov model in Location 1 and Location 2, R2 value is 0.9481 and 0.9148, respectively. According to Table 1, for the lateral infiltration for both locations, the Kostiakov model obtained the best results compared to the Horton and Green-Ampt models.

Table 2: Comparison of R2 and RMSE values for vertical infiltration

ModelLocation 1 Location 2

R2 RMSE R2 RMSE

Horton 0.7730 0.4728 0.7237 0.4348

Kostiakov 0.7972 0.196 0.8797 0.0641

Green-Ampt 0.5888 0.3306 0.8037 0.391

According to Table 2, high R2 and minimum RMSE are obtained for the Kostiakov model for both Location 1 and Location 2. Therefore, for the vertical infiltration, the Kostiakov model has been selected as the best fit model.

4. CONCLUSIONS

This study has experimentally determined the constant soil infiltration rates and compared them with the infiltration rates estimated by Kostiakov, Horton and Green-Ampt infiltration models.

Field measurements confirmed that the initial moisture content of the soil affects the infiltration capacity.

Based on the R2 values and RMSE values, it was revealed that the Kostiakov model is the best fitted model with high R2 and minimum RMSE for both vertical and lateral infiltration.

REFERENCES

Lewis, MR 1937, The rate of infiltration of water in irrigation-practiceAmerican Geophysical Union Transactions, v. 18, pp. 361-368.

Michelson, AT, & Muckel, DC 1937, Spreading water for storage underground United States Department of Agriculture (USDA) Technical Bulletin, 578, 80 p.



6th January 2017

INVESTIGATION OF LAND PREPARATION WATER MANAGEMENT PRACTICES IN MURUTHAWELA IRRIGATION SCHEME

W.P.M. Madusanka and T.N. Wickramaarachchi

ABSTRACT

Irrigation is the artificial application of water. Water demand for the agriculture is increasing with the increase of population. But the availability of water is limited. Therefore, proper water management practices in irrigation schemes are becoming important. This study is an attempt to identify the irrigation water management practices in Muruthawela irrigation scheme during Land Preparation (LP) and to compare it with the ID (Irrigation Department) guideline recommendations. For the study, areas fed by D8 and D9 Distributary canals in the Tract 2 of Muruthawelairrigation scheme have been selected. D8 and D9 Distributary canals supply water to 166 acres and 346 acres,respectively. Irrigation requirements were estimated by considering the system water losses. Study revealed that there exist significant differences between the water issues in the Distributary canals in comparison to the ID guidelinerecommendations. The existing water issues during the LP were much higher than the ID guideline recommended values and were 425 mm and 175 mm, on average during Maha and Yala seasons, respectively.

1. INTRODUCTION

Land Preparation (LP) lays the foundation for the whole cropping season and it is important in any situation to get the basics right. Water distribution by field channels, land levelling, and tillage operations are especially important for good water management during the LP. Water requirement for the LP during cultivations may be varied with some factors such as crop type, soil type, climate state, water losses of the system and existing conditions of the canal system. Also farmers preferred to commence their LP water issues with the start of the rainfall (with the onset of either north-east or south-west monsoon) since they like to capture more water in their allotments at the beginning of the LP because it facilitates the ploughing of farm lands (Wijesekara &Wickramaarachchi, 2003).

Muruthawela - Urubokka Oya irrigation system has been selected for this study. Muruthawela - Urubokka Oya system comprises of one major tank (Muruthawela), one medium tank (Udukiriwila), cascade system of six small tanks and seven anicut schemes along the stream. There are three main cultivation tracts in the Muruthawela. Areas fed by D8 and D9 Distributary canals in Muruthawela Tract 2 were selected for the investigation. Usually, during dry seasons, Tract 2 and Tract 3 farmers are unable to fulfill their water requirements. Also some lands are not cultivated due to the insufficiency of water supply. The water losses in the system had not been identified yet. Therefore, it is important to conduct thisstudy to investigate the problem. Determination of existing LP water issues with system water losses and comparison of those values with the ID guideline were the main objectives of this study.

2. METHODOLOGY

2.1 Questionnaire Surveys and System EvaluationsQuestionnaire surveys were carried out among irrigation officers and farmers to collect information on the system. Twenty-five farmers from D9 canal system and twenty farmers from D8 canal system were selected considering their farm locations such as head, middle and tail end of the canal system.

2.2 Seasonal Water IssuesThe existing water discharge data in the canals and rainfall data in the area were collected to analyse the existing system. The rainfall data and water discharge data in canals were extracted from the records available in the Irrigation Department. Water discharge was calculated using;

Q=3.33(L-0.2H) H3/2

where,Q Canal discharge (cfs)L - Width of the measuring gauge (ft)H Water issuing depth (ft)

2.3 System Water LossesIrrigation officers assumed system water loss valuesbased on their experience, when accounting water requirements for the cultivation season. 60% application efficiency and 75% conveyance efficiency were used at the farms.

In the existing system, the amounts of water issued at different locations of the main canal were used to

estimate the conveyance efficiency.

2.3 ID GuidelineThe water requirement for LP was described considering the land soaking and land tillage requirements in the IDguideline (Ponrajah, 1988). This LP water requirement



6th January 2017

depends upon the farm location and soil type. Field Irrigation Requirement (FIR) and Irrigation Requirement (IR) have been calculated as per the ID guideline.


3.1 Summary of Farmer Questionnaire Surveysand System EvaluationsAccording to the questionnaire surveys, the existing conditions of the canal system were not preferred to convey water with high efficiency. 50% of the farmers were not satisfied with the existing water issues during the LP period. Some canals were not properly designed to distribute water under gravity. Canal beds were eroded due to different reasons. Water wastage was high during the LP time.

3.2 Seasonal LP Water Releases

Figure 1: Comparison of existing water issues with the ID guideline during the LP

The water issues during the selected cultivation seasons were higher than the ID guideline recommendations(Figure 1). But many farmers in middle and tail ends of the canal were not satisfied with the water issues. Farmer questionnaire survey revealed that the status of LP water management in Tract 2 was not satisfactory. Head end farmers have the habit to block the water.

3.3 Seasonal Water Losses in MuruthawelaApplication loss was assumed as 40% with the irrigation

ance losses estimated in the Muruthawela scheme were 40% and 50% during Maha and Yala seasons, respectively while the recommend value by the ID guideline was 25%. With the seasonal rainfall, the water requirement is going to change. However, during high rainfall seasons also higher water issues had been observed due to high conveyance losses and improper design of canal layout.

Figure 2: Comparison of IR and water issues during entire cultivation season

IR varied with the system water losses. Higher amounts of water issues than IR during the entire cultivation season in the existing system as shown in Figure 2 were due to higher water losses in the existing system than theID guideline recommended values.

4. CONCLUSIONS

Study revealed that, the existing water issues during the LP were much higher than the ID guideline recommended values. LP water requirement according to the ID guideline was 295 mm. However, in the existing system, the average LP water issues were 720 mm and 470 mm during Maha and Yala seasons, respectively.

The average conveyance losses during Maha and Yala seasons were estimated as 40% and 50%, respectivelywhile 25% conveyance loss was recommended by the ID guideline. Due to high water losses in the conveyance system, more water had to be issued during the cultivation season. Therefore, the existing water issues in the system were always considerably higher than the estimated IR.

REFERENCES

Ponrajah, AJIrrigation Department Sri Lanka, Colombo.

Wijesekera, NTS &Water Use and Suggestions for Better Water Management, A Comparison of Two Schemes from Sri L Water Science & Technology, Journal of International Water Association (IWA), vol. 48, no. 7, pp. 197-206.



6th January 2017

INVESTIGATION OF IRRIGATION WATER USAGE FOR CROP GROWTH IN MURUTHAWELA IRRIGATION SCHEME

K.A.R. Madushanka and T.N. Wickramaarachchi

ABSTRACT

Agriculture is the main livelihood of people in dry zone of Sri Lanka. Water is the most limited resource for agriculture in the dry zone of Sri Lanka. Therefore, all possible efforts need to be taken to optimize the water usage in the area. There exists vital need to identify water requirement for crop growth and losses in irrigation systems. Such water requirements vary with type of crop, growth stage, soil type, evapotranspiration etc. Usually the irrigation water requirements are determined according to the ID (Irrigation Department) Guideline recommendations. Nevertheless, there exist a need for critical evaluation of available guidelines and present water issue practices in relation to crop yields, in order to achieve a significant water saving. The objective of this study was to evaluate the water issues in existing irrigation scheme (D8 and D9 Distributary canal fed areas in Tract 2 of Muruthwela left bank scheme) and the crop water requirements recommended by the ID Guideline. Study revealed that, significant quantity of excess water, i.e. 6 cm 53 cm per unit area, on average (in Maha season) and 22 cm per unit area, on average (in Yala season) have been issued in comparison to the ID Guideline recommendation.

1. INTRODUCTION

Muruthawela irrigation scheme is situated in Hambantota District (dry zone of Sri Lanka). In 1970, Muruthawela reservoir was made by blocking Urubokka Oya. It is one of the important reservoirs catering water to Weeraketiya, Tangalle and Ranna areas. Mainly reservoir water is used for agricultural and drinking purposes. Muruthawela reservoir on Urubokka Oya has 48 million m3 storage.The study area selected was Tract 2 in Muruthwela left bank scheme fed by D8 and D9 Distributary canals. Many studies have been conducted to investigate the irrigation water usage for the crop growth. Some of these compared the existing water issues in the systems withthe ID (Irrigation Department) Guidelinerecommendations. Those have shown that there exists a need to critically evaluate the available guidelines and present water issue practices in the systems, in order to achieve significant amount of water saving(Wickramaarachchi & Wijesekera, 2001; Wijesekera &Wickramaarachchi, 2003). The objective of this study was to evaluate the water issues in the existing system (D8 and D9 Distributary canal fed areas in Tract 2 of Muruthwela left bank scheme) and the crop water requirements recommended by the ID Guideline.

2. METHODOLOGY

2.1 Existing SystemThe existing system is the D8 and D9 canal fed areas in Tract 2 of Muruthwela left bank scheme. Annual rainfall of Muruthawela is about 1750 mm and annual pan evaporation measured at Hambantota is about 2000 mm.Tract 2 consists of 621 ha command area. Distributary canal D8 covers 68 ha and Distributary canal D9 covers 140 ha. Major type of soil in Muruthawela area is Reddish Brown Earth.

2.1.1 Data CollectionYala and Maha seasons water issue data and crop data were collected during 2013-2016. Lowland paddy was the main crop cultivated in both Yala and Maha seasons. 105day or 135-day lowland paddy were grown by all farmers.

2.1.2 Canal Details and Water Issue DetailsTract 2 area situated at a distance of 11.6 km-14.3 km in the Muruthawela left bank canal. During a cultivation season (land preparation and crop growth stages), water distributions in D8 and D9 canals are operated for 24 hours. Tract 2, D8 canal has 16 field canals and D9 canal has 33 field canals. The length of D8 canal is 618 m and D9 canal is 1017 m.

2.2 Irrigation Department Guideline

2.2.1 Data CollectionRequired data was collected to calculate crop water requirement according to the ID Guideline (Ponrajah, 1988). Crop water requirement (ETc) was calculated using;

ETc = ETo × Kc

where,ETo - Reference crop evapo-transpirationKc - Crop coefficient

Crop water requirements have been determined for the four growth stages of paddy; initial stage, crop development stage, mid-season stage and late stage as per the ID Guideline recommendations.

For the evaporation, data from the nearest evaporation station (Ridiagama station) was considered.

ID Guideline recommendations and existing system water issues (from 2013 to 2016) have been evaluated for both Maha and Yala seasons.



6th January 2017


Figure 1 and Figure 2 show the D8 canal existing water issues in Maha and Yala season, respectively, during 2013 2016. Also the ID Guideline recommended water requirements are shown in both figures.

Figure 1: Water issues in D8 canal for 135 day paddyin Maha season

Figure 2: Water issues in D8 canal for 135 day paddyin Yala season

Water usage amounts have been estimated for the ID Guideline recommendations and the existing system. It was realized that in the existing system, the water usage is higher than the ID Guideline recommendations. These excess water usages in D8 canal for 135 day paddy in Maha season and Yala season are shown in Table 1 and Table 2, respectively. Excess water usage in both D8 and D9 canals when cultivating 105 day low land paddy has also been estimated and found to be almost similar to the excess water usage for 135 day paddy.

Table 1: Excess water usage in D8 canal for 135 daypaddy in Maha season

Initialstage(mm)

Development stage (mm)

Midseason stage(mm)

Late stage (mm)

D8 Existing system (135 daypaddy in Maha)

760 741 532 241

ID Guideline (135 day paddy in

Maha)231 360 469 171

Excess water usage per unit

area 529 381 63 70

Table 2: Excess water usage in D8 canal for 135 day paddy in Yala season

Initial stage (mm)

Development stage (mm)

Midseason stage (mm)

Late stage (mm)

D8 Existing system (135 day paddy in Yala)

489 440 529 163

ID Guideline (135 day paddy in Yala)

269 467 545 229

Excess water usage per unit

area 220 - - -

4. CONCLUSIONS

Results revealed that, in D8 and D9 canal fed areas in Tract 2 of Muruthwela left bank scheme used more water (6 cm 53 cm per unit area, on average) than the ID Guideline recommendations, during all crop growth stages in Maha season. In Yala season, more water usage than the ID Guideline recommendations has been identified only during the initial growth stage and was 22cm per unit area, on average. It is evident that if the existing system water issue quantities and frequencies can be adjusted to match with the ID Guideline recommendations, a significant amount of water could be saved in the Muruthwela left bank scheme.

REFERENCES

Ponrajah, AJP 1988, Technical Guidelines for Irrigation Works , Irrigation Department Sri Lanka, Colombo.

Wickramaarachchi, TN &Irrigation Water Issue Options Case Study from System H of Mahaweli Development Programme', Journal of Tropical Agricultural Research, vol. 13, pp. 143-155.

Wijesekera, NTS & Wickramaarachchi, TN 2003, Reality of Irrigation Water Use and Suggestions for Better Water Management, A Comparison of Two Schemes from Sri Lanka Water Science &Technology, Journal of International Water Association (IWA), vol. 48, no. 7, pp. 197-206.



6th January 2017

SETTING UP OF HEC-HMS MODEL TO ASSESS HYDROLOGICAL RESPONSE OF GIN AND NILWALA RIVER BASINS OF SRI LANKA

A.V.D. Fernando, G.H.A.C. Silva and L.S. Sooriyabandara

ABSTRACT

The Gin and Nilwala Rivers are located entirely within the southern wet-zone of Sri Lanka and discharge considerable quantity of water to the sea, without being utilized. Lower basins of the rivers are subjected to frequently flooding while the adjacent Hambantota district is with the scarcity of water. The primary objective of this research is to setup a hydrological model for combine Gin-Nilwala River basins that constitute of the setting up, calibration and validation of a hydrological model which is a prerequisite to evaluate the hydrological potential of combined Gin Nilwala River basins. HEC-HMS hydrological modelling system with Muskingum routing method was used in set up of the hydrological model. The setup hydrological model has been calibrated and validated using observed rainfall and discharge data.

1. INTRODUCTION

The drainage areas of Gin & Nilwala Rivers are approximately 958 km2 and 971 km2 respectively. The regions of both Gin and Nilwala Rivers are basically at the South-West monsoonal area and frequent floods are experienced during monsoon periods. The average annual flow into the sea is about 1850 MCM and the mean annual rainfall is about 3300 mm in Gin River and about 1233 MCM of water reaches annually to the sea without being utilized through the Nilwala River with mean annual rainfall of 2920 mm (Arumugam 1969). Several studies have been done in the recent past to find the possibility of diverting the upper reaches of Nilwala to the Muruthawela reservoir. The project proposed to divert water of Gin River basin at Pitadeniya to Kotapola and Ampanagala in Nilwala River basin to existing Muruthawela tank through a series of tunnels (Consultancy services for review of feasibility study of Gin Nilwala Ganga diversion Project 2014). Diversion of Gin River to Nilwala River should also be considered to increase the reliability of flow during the dry weather periods. Previously the hydrological potential was evaluated based on sub catchment area ratio method (Sooriyabandara n.d.). However, a properly setup hydrological model can generate better outputs in computation of hydrological potential of each river basin.

2. METHODOLOGY

HEC-HMS hydrological model was setup to evaluate water availability in the upstream of Gin and NilwalaRiver basins at different locations (Figure 1). The model was calibrated using Thawalama discharge data (for Gin-River) and Pitabaddara (for Nilwala-River) and using precipitation data in several rainfall stations.Peak-weighted root mean square error method was used as the objective function (equation 01) in the calibration process of the HEC-HMS model.

Equation 01

Where; NQ is number of computed hydrograph ordinates; is observed flows; qs(t) is calculated flows, computed with a

is observed is mean of observed flows; qs (peak) is

calculated peak.


3.1 Gin River basin modelGin River basin model was calibrated using observed rainfall and discharge data from October to December 2006. Hiniduma, Deniyaya, Baddegama and Labuduwa precipitation gauging data and Thawalama discharge data were used to calibrate the model. Figure 2 and Figure 3illustrate the hydrograph comparison and the respective objective function obtained from the calibrated Gin River basin model. Figure 4 shows the validated hydrograph for the Gin River basin model.

Table 1 and Table 2 illustrate the optimized reach and basin parameters of the Gin River model respectively.

Figure 1: Locations of gauges (rainfall and discharge) in combined Gin-Nilwala River basins



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Table 1: Calibrated reach parameters for Gin River model

Table 2: Calibrated basin parameters for Gin River model

3.2 Nilwala River basin modelDeniyaya, Goluwawatta, and Mawarella precipitation gauging data and Pitabeddara discharge data were used to calibrate the model. Figure 5 and Figure 6 illustrate the hydrograph comparison and respective objective function obtained for the calibrated model for Nilwala River basin.

Figure 7 shows the validated hydrograph for the Nilwala river basin model.

4. CONCLUSIONS

Both Gin and Nilwala River basin models were setupsuccessfully. Observed and simulated hydrographs were shown a great matching in both calibration and validation processes and they were further endorsed by a reasonable objective function judgment.

The parameter optimization has been done for several upstream locations and using the optimized parameters now it is possible to use already setup models for further application such as investigation of hydrological potential at various upstream locations. Hence, more reliable discharge generation at un-gage upstream locations is possible for various storm events which would be a useful finding for combined Gin-Nilwala River basin applications.

REFERENCES

Arumugam, S., 1969, Water Resources of Ceylon, A Water Resources Board Publication, Colombo, Sri Lanka.

Consultancy services for review of feasibility study of Gin Nilwala Ganga diversion Project (2014), Mahaweli Consultancy Bureau (Pvt) Ltd, Ministry of Irrigation and Water Resources Management,Colombo, Sri Lanka.

Sooriyabandara, L.S., n.d., Nilwala Ganga Flood Protection Scheme, Department of Irrigation, Matara, Sri Lanka.

Figure 2: Calibration for Gin River model

Figure 3: Objective function for Gin River

Figure 4: Validation for Gin River model

Figure 5: Calibration for Nilwala River model

Figure 6: Objective function for Nilwala River

Figure 7: Validation for Nilwala River model



6th January 2017

DETERIORATION OF RIVER WATER QUALITY DUE TO IMPROPER HUMAN ACTIVITIES -A CASE STUDY FOR GIN RIVER BASIN

B.W.M.C.L. Wijekoon, G.H.A.C. Silva, G.G. Tushara Chaminda and S.K. Weragoda

ABSTRACT

The Primary aim of a catchment safety plan is to reduce risks within the catchment to protect the quality of drinking water sources at the intake point. Even effective arrangements for quality assurance and quality management have been established, unexpected deterioration in raw water can be affected to treated drinking water quality. Important steps of catchment safety plan include risk assessment, risk minimizing and monitoring effectiveness. In this study, correlation matrix was developed between water quality and land use patterns to assess the risk of water quality due to suspected improper human activities. Social survey was carried out in a pilot tributary area based on the primary observations of water quality parameters. Hazard analysis matrix was developed based on social survey outcome as a risk minimization procedure. The findings of this research would be the base for developing a proper catchment safety plan for the entireGin river basin.

1. INTRODUCTION

Supplying good and safe drinking water is a key issue in public health protection policies (Viera & Pinho, 2014).However more than one billion people around the world still lack access to safe water supplies. A substantial majority of these people are live in Asia (Saini, Khitoliya & Kumar 2014). Protection of raw water quality is one of paramount interest for ensuring the safe water in drinking water supply system. Thus potential sources which influence the pollution impacts should be clearly identified and monitored in order to ensure the raw water quality. Understanding the nature of sources of contamination and how these may enter the water supply is critical for assuring water safety. In this regard, catchment management is more important to identifypreventive measures at the point of absorption and to reduce cost and barriers in water safety plan compared to the treatment process. The aim of this study is toinvestigate possible correlation between water quality parameters and land use classes in which suspected improper fertilizer practices are practiced.

2. METHODOLOGY

Water quality risk assessment was done by characterizing catchment under geophysical, hydrological, water quality and sociological aspects. Seasonal variation was analyzed by considering a typical wet season (August, 2016) and compared with Central Environmental Authority (CEA) standards for drinking water with simple treatment (CEA2011 cited in Nagasinghe 2014). Study area and the geographical locations of sampling points are shown in Figure 1.The land acquisition patterns were identified by developing sub catchments related to each sampling point based on 2013 land use map with 1:10,000 resolution obtained from department of surveying, Sri Lanka.

Figure 1 : Sampling points and tributary catchments

Based on land use area and water quality data, a correlation matrix was developed using Pearson product -moment correlation coefficientMicrosoft Excel 2015). Social survey was conducted atThalangalu-Dola tributary catchment based on the initial water quality data. Comparison was done between Thalangalu-dola tributary catchment and the other 5 tributary catchments, with their water quality parameters to identify the entire Gin river catchment behavior. A trend analysis has also been done between Thalangalu-Dola tributary and other tributaries in Gin river basin for different cultivation types (land use types).


Water quality parameters measured at Gin river basin during the dry period shown in Figure 2. The highest COD has been detected at point G (Figure 2), at the outlet of Talangalu-Dola tributary. Therefore, the social survey was conducted within the Talangalu-dola tributary. The social survey reveals that the farmers use chemical fertilizers more than the recommended amount (Table 1).A correlation matrix between land use classes and water quality parameters was developed for the Thalangalu-Dola tributary (See Figure 4).

BE

ACDF

G

H

IJ

KL

M

N



6th January 2017

Figure 2 : COD variation along the main stream

Table 1: Usage of chemical fertilizer

Key:

Figure 3 : Correlation matrix

(a) Trend for Forest land use

(b) Trend for Paddy land use

Figure 4: Correlation of land use and water qualityfor Forest and Paddy

(c) Trend for Tea land use

(d) Trend for Home Garden land use

Figure 5: Correlation of land use and water qualityfor Tea and Home-Garden

The high COD value observed at the outlet of Talangalu-Dola (Figure 2) is due to high concentration of chemical fertilizer used at the tributary catchment (endorsed by social survey, Table 1). The general correlation matrix (Figure 3) developed for the pilot area also suggested that COD and TN concentrations are considerably high in paddy and tea cultivation compared to other land use classes. Figure 4(a) illustrates the trend of selected water quality parameters (TN and TP) are having identical and comparable trends in other tributaries for paddy cultivation land use. However, no clear trend can be seen for forest land use (Figure 4(b)). Figure 5 (a) and (b) illustrate similar trend in land use types tea and home-garden respectively.

4. CONCLUSIONS

Water quality is correlated with land use patterns to develop the correlation matrix. Colour, Turbidity, pH and DO can be identified as most sensitive parameters for land use changes. TN, TP and COD are proportionate with cultivated land areas including paddy, tea and home gardens. According to the social survey, farmers use over dosage of agro chemical for the cultivations compared with the recommended quantities. Controlling change of land use and usage of agro chemical seems as a viable solution in order to manage drinking water quality.

REFERENCES

Nagasinghe, I. U., 2014, Undergraduate research thesis on Evaluation of storm washoff quality in different urban land uses, Galle, s.n.

Viera, J. & Pinho, J., 2014. River water quality moddeling in developing a catchment water safety plan. New York city, USA, s.n.

Saini, H. K., Kitoliya, R. K. & Kumar, S., 2014, A study of water safety plan (WSP) for Environmental risk management of a modern North Indian city. ISOR Journal of environmental science, Toxicology and food technology, 8(9), pp. 101-113.

CEA standard



6th January 2017

MODELLING OF PHYTOPLANKTON AROUND COASTAL AREA OF SRI LANKA

N.R.Nirmal and H.P.V.Vithana

ABSTRACT

Phytoplankton is the primary producer in the marine eco-system and is considered to be one of the major influential factors for the existence of the entire planet earth. This eco-system (Phytoplankton) has the potential to indicate or forecast different environmental scenarios such as climate change, environmental pollution level, coastal related issues and etc. When it comes to the Indian Ocean, phytoplankton production rate is significantly influenced by the nutrient upwelling due to the current flow parallel to shore line, results in algal blooms in both spatially and temporally. This research focused on modelling the spatial variation of phytoplankton in a selected domain of the Indian Ocean through DELFT 3D software and the ultimate outcome is given by the water quality model. Hydrodynamics in the ocean (inside the modelled domain) is the pre-requisite for the water quality model and is achieved through DELFT3D FLOW model. Significant current flow was observed parallel to both from Western Indian and Western Sri Lankan coasts both of which converge towards southern coast of Sri Lanka. It was observed that a concentrated chlorophyll-a patch was blooming along southern coast throughout the modelled duration confirming the satellite derived spatial distribution of phytoplankton.

1. INTRODUCTION

that live in watery environments (both salty and fresh). Chlorophyll is the tool used by the phytoplankton to capture sunlight and then turn it into chemical energy through photosynthesis. Phytoplankton, like land plants, require nutrients such as nitrate, phosphate, silicate, and calcium at various levels depending on the species.

Historically, nitrogen has been considered to be the nutrient that limits phytoplankton growth in both coastal (Ryther and Dunstan 1971; Vince and Valiela 1973, cited in Bernhard and Peele 1997) and oceanic systems (Eppley et al. 1973; Goldman 1976, cited in Bernhard and Peele, 1997). According to (Schindler 1977, cited in Bernhard and Peele 1997), in freshwater systems, phosphorus is generally considered a limiting nutrient. Therefore, those major nutrients are playing a significant role in the spatial and temporal variation of phytoplankton in the salty waters.

River discharges are the major source of nutrients into the model domain originating from both Sri Lanka and India.Ocean currents transport those nutrient loads from one place to another and it affects the spatial distribution of phytoplankton in the ocean. Therefore, it is vital to investigate the ocean current directions to gain an understanding on where nutrients end up and accumulate in high concentrations.

This kind of a model is applicable at anywhere in the world to predict the spatial variation of phytoplankton in the ocean and the information obtained from this model is applicable for related purposes such as to predict fishery behavior in the ocean, climatic change, ocean pollution and etc.

The objectives of this study are to set up and calibrate the flow model to simulate hydrodynamics in the domain through DELFT3D software and couple hydrodynamics with the Water Quality model to simulate the spatial variation of a selected phytoplankton group typical of the Indian Ocean.

2. METHODOLOGY

Hydrodynamics in the Indian Ocean was first simulated before setting up the Water Quality model to investigatethe currents which transports the nutrient rich water. Delft 3D FLOW model facilitates simulation of hydrodynamics in the ocean following the bathymetry in the model domain.

2.1 Bathymetry dataHigh resolution bathymetry data provides an accurate 3D picture of the sea bottom to ensure the accurate representation of tide and current behavior inside the domain. Bathymetry data with reasonable resolution was extracted through Marine Geoscience Data System(IEDA).

2.2 Hydrodynamic model for tides propagationAn open boundary was defined at the Eastern boundary and with the tidal constituents for Colombo and Trincomalee as inputs. Tidal constituent data wereextracted from A. de Vos et al. (2014).

Then, the tidal constituents were adjusted until modelled tidal sea surface elevation tallied with measured data for the two stations.



6th January 2017

Table 1: Tidal constituents at two stations along the coastline of Sri Lanka

2.3 Coastal currentsTidal currents were extracted from the Hydrodynamic model for interested locations in the domain. In order to simulate the total current conditions, additional open boundary at the west was defined with currents given as a time series. Then the extracted tidal currents and total current values were compared with the actual (measured)conditions and they were found to exist in the allowable range. Actual tidal current values were in the range of 0.2m/s 0.3m/s while total current was in the range of 0.35m/s 0.45m/s.

2.4 Water Quality modelAfter successful setting up of the Hydrodynamic model it was coupled to the Water Quality model to simulate the phytoplankton growth and spatial variation. Relevant nutrient and other input boundary data were given for the model based on in-situ data.


Modelled water levels for Colombo and Trincomalee tallied well with measured tidal elevation for the same locations. Hydrodynamic model was observed to be stable after the successful calibration.

Dominant currents flowing towards Southern coast of Sri Lanka coming parallel to the Western Indian and Western Sri Lankan coasts were observed as shown in Figure 2. Both streams converge at the southern coast of Sri Lanka bringing nutrient rich water to the south.

Significant chlorophyll-a concentration (phytoplankton blooms) were observed near Hambanthota (a blooming patch) and in the Mannar basin (a static patch with high concentration). The final water quality model output is shown in Figure 3.

Figure 3: Modelled Phytoplankton distribution

4. CONCLUSIONS

Nutrient rich water accumulated at the Western Indian and Sri Lanka coasts due to the river discharges, aredriven towards the Southern coast of Sri Lanka as shown by the simulated current pattern. In addition, nutrient upwelling (moving nutrients to the surface layers from lower layers where nutrient concentration is high) occurs due to the currents parallel to the coast. These phenomena could be the reason for the chlorophyll-a patch nearHambanthota. Chlorophyll-a distribution with high concentration observed at the Mannar basin, may be due to the higher river inflows and shallow water effects in the area. The modelled phytoplankton distribution agreed well with the satellite derived data.

REFERENCES

Estuaries, 20(4), 759-769.

NASA. (2016)., Colorful and Plankton-Full Patagonian Waters, viewed 20 May 2016, from http://www.nasa.gov/content/colorful-plankton

Vos, A.D., Pattiaratchi, C.B. and Wijeratne, E.M.S., 2014. Surface circulation and upwelling patterns around Sri Lanka. Biogeosciences, 11(20), pp.5909-5930.

Figure 1: Current variation near Hambanthota

Figure 2: Modelled current flows

Hambantota

Mannar



6th January 2017

VALIDATION OF A PHYTOPLANKTON MODEL IN COASTAL OCEANAROUND SRI LANKA USING SATELLITE DATA

C.J.D.Yapa and H.P.V. Vithana

ABSTRACT

High phytoplankton production in the ocean can locally cause harmful algal blooms. Satellite ocean colour sensor data are broadly used for the exposure, mapping and monitoring of these blooms. This research focused on validating a phytoplankton model from satellite images using a chlorophyll-a algorithm. Here in-situ (cruise) data were compared with satellite images obtained from NASA ocean colour website to select a sensor with least error. Then monthly chlorophyll concentrations retrieved from the Indian Ocean using MODIS Aqua sensor for the period from January 2009 to September 2016 were analysed to find algal blooms around Sri Lanka. Also certain parameters which contributed to the bloom such as nutrients and ocean currents were identified. The information obtained indicate that despite the generally low chlorophyll concentration (0.01 0.1 mgm ) in these oligotrophic waters, there is a characteristic seasonal bloom in June August along the south coast of Sri Lanka concurrent with summer monsoonalcurrents.

1. INTRODUCTION

This study started from the background that the coastal zone is the most important part and the most intensively used area compared to all other areas settled by humans in the world. The rapid increase of population around the globe has caused the large-scale exploitation of coastal resources. Integrated Coastal Zone Management (ICZM) offers a means to balance the competing demands of different users to the same resources and to manage the resources in order to optimize the benefits to be derived on a sustagoals. One of the important tools in ICZM are ecological modelling and remotely sensed images. Ecological modelling makes an important platform in order to manage coastal resources and to gain quantities whileremotely sensed images helps to verify the results by providing the synoptic view of the landscape. Such a view is practically impossible to be obtained by conventional in-situ measurements. Since the start of the last century, Indian Ocean experiences eutrophication in its coastal zones due to elevated nutrient loads from rivers. In several studies, observed changes in phytoplankton biomass in the area have been coupled to an increase in anthropogenic nutrient loadings. Elevated phytoplankton primary production rates can locally lead to harmful situations such as a rapid increase of a

Ocean Color satellite measurements provide an important tool to monitor climate relevant changes like blooms in the oceans on a global scale. Nevertheless, it is necessary to validate remote sensing measurements with ground-truth data. Especially in the coastal ocean waters where the measurements are scarce.

So the main Objectives are:

Validate the water quality model using satellite data.

Identifying key parameters for chlor-a changes in the southern coast of Sri Lanka.

Previous studies that have been carried out to detectphytoplankton blooms in the southern coast of Sri Lanka identified possible nutrient upwelling concurrent with southwest monsoon period as a possible cause for their occurrence.

2. METHODOLOGY

Here SeaDAS software was used to derive mapped images from raw images downloaded from NASA ocean colour website. SeaDAS is a comprehensive image analysis package for the processing, display, analysis and quality control of ocean colour data. SeaDAS is intended to be used with all of the OBPG supported sensors: MODIS/Aqua, MODIS/Terra, SeaWiFS, OCTS, CZCS and OCM-2. The present processing sequence of SeaWiFS and MODIS Aqua in SeaDAS v.7.3.2 involves the conversion of level1b (L1B) data to level3 (L3) format. Image processing involves different processing methods along with atmospheric correction, flagging and masking.

To select a suitable sensor, the chlorophyll-a concentration data have been retrieved over the regions in the Indian ocean using SeaWIFS, MODIS Aqua, MODIS Terra sensor data and compared with in-situ data for the period from 01/01/1990 to 19/09/2016. Sampling locations lie inside the boundaries of 31.65° North, 9.8° South, 47.1° West and 111.8 East. After that, monthly chlorophyll concentrations retrieved from the Indian Ocean using MODIS Aqua sensor for the period from January, 2009 to September, 2016 were analyzed. Figure 1 shows a derived image of Chlor-a Concentrations for July, 2015 using SeaDAS.

Here annual and monthly variation of phytoplankton concentrations were plotted using the images derived from satellites to obtain spatial and temporal distribution of Chlor-a concentration. Figure 2 shows the process of validation.



6th January 2017

Figure 3: Chlor-a Concentration for July, 2015

Figure 4: Process of Validation

In addition to chlorophyll-a concentration, certain parameters such as existing nutrient condition, ocean currents and wind speed/direction were identified using Live Access Servers.


Table 1: Summary of Compared Data

SensorSatellite Range

(mg/m3)

In-situ Range

(mg/m3)# R2 RMSE

SeaWiFS0.12, 13.21 0.05, 13.64 41 0.865 0.287

MODIS Aqua

0.38, 8.39 0.20, 13.64 8 0.889 0.300

MODIS Terra

0.09, 1.88 1.00, 1.34 13 0.052 0.790

# - Number of SamplesR2 - Coefficient of DeterminationRMSE Root Mean Square Error

When selecting a suitable sensor, according to the regression analyses, SeaWiFS had relatively high coefficient of determination (R2 = 0.86521) and relatively low root mean square error (RMSE = 0.28726) followed by MODIS Aqua (R2 = 0.88902, RMSE = 0.3003), while MODIS Terra sensor had relatively low coefficient of determination (R2 = 0.05202) and relatively high root mean square error (RMSE = 0.79002). So there was notmuch difference between SeaWIFS and MODIS Aqua data but considering a number of samples which are included, SeaWiFS data were most reliable when considering locations near Indian Ocean.

The obtained information from monthly mapped chlorophyll concentration images indicated that average MODIS Aqua chlor-a concentrations for the period 20092016 were very low in the open sea (0.01 0.1 mgm-3), as expected. Higher values were observed near the coastal areas especially between coasts of Rameswaram and Manamelkudi in India and Jaffna and Mannar in Sri Lanka (1 15 mgm-3) because of low water depths in these areas. Most significant information is that there is a

characteristic seasonal bloom in June August in the South-West coast of India and in South coast of Sri Lanka. Live Access Server data also suggest high current and wind velocities resulting in nutrient upwelling in this area during this period.

4. CONCLUSIONS

In this paper, remotely-sensed chlor-a data from MODIS-Aqua were utilized to investigate the biological dynamics in the Indian Ocean. This investigation revealed a primary seasonal variability which consisted of a spring bloom in the Southern part of the India and Hambanthota area in Sri Lanka near the coast. The largest area of elevated chlor-a concentration occurred in the convergence zone created due to the circulation of currents from western coasts of India and Sri Lanka during summer monsoon.The existence of the zonal wind constituent and the total wind parallel to the coast with high variability ofchlorophyll-a in the water column also suggest the occurrence of possible upwelling in the area. The transport of nutrients into the surface layer through upwelling driven by alongshore winds, results in high phytoplankton concentrations. During July-September, there is relatively high nutrient concentration in the upper layer (0m-50m) of the ocean where phytoplankton normally exist. But there are considerably low concentrations in the middle layer (50m-125m). However, in the previous months high concentrations were observed in the mid layers with low concentration in the uppermost layer which indicates signs of upwelling.

High chlorophyll concentrations means high primary productivity in the southern coastal belt and in turn, couldsustain high fish production. Identification of these high production areas is very relevant to the sustainable management of fishing stocks.

REFERENCES

Banks, A.C. et al., 2012. A satellite ocean color observation operator system for eutrophication assessment in coastal waters. Journal of Marine Systems 94 (Suppl.), S2 S15.

Friedrich, A. S., Julian, P. M., 2001. The monsoon circulation of the Indian Ocean. Journal of Progress in Oceanography 51, 1 123.

Gabric, A.J. et al., 1990. Spatio-temporal variability in surface chlorophyll distribution in the central Great Barrier Reef as derived from CZCS imagery. Australian Journal of Marine and Freshwater Research 41, 313 324.

Yapa, K. K. A. S. et al., 2012. Effect of surface wind and wind vectors on sea surface chlorophyll-a distribution in the ocean waters surrounding Sri Lanka for the period 1999 2003. Journal of Natn. Sci.Foundation Sri Lanka 2012 40(3), 221-229.



6th January 2017

A STUDY ON TSUNAMI WAVE PENETRATION AFTER THECONSTRUCTION OF SETHUSAMUDRAM SHIP CANAL

C. Piruthevi and H.P.V.Vithana

ABSTRACT

This paper describes a study on tsunami wave penetration after the construction of the proposed Sethusamudram ship

canal project (SSCP). In order to fulfill this objective a hydrodynamic model set up based on linear shallow-water

equations was used to simulate tsunami propagation from the source to the shoreline around Sri Lanka. Numerical

model results were compared with data from field measurements and tide-gauge records for the existing condition. The

numerical simulation suggests that SSCP will have a minor impact in terms of tsunami wave penetration into the Gulf

of Mannar (i.e., 2-5% increase in wave amplitude compared to existing).

1. INTRODUCTION

Sethusamudram Shipping Canal Project (SSCP) was

proposed by India to establish a shipping route between

India and Sri Lanka in the depthless straits. The ocean

floor between India and Sri Lanka near the Mannar coast

is not navigable. It is very shallow and it does not allow

ships to pass. The total length of SSCP would be around

260 km; it was intended to have the depth of 12 m

enabling 10,000 to 12,000 GRT vessels to pass through.

The crossable path from Tuticorin to Adam s Bridge is

above 12 meters deep and hence it does not require

deepening. The canal will have 1:3 side slopes. The main

objective of this research is to estimate the impact of

Tsunami waves after the construction of the Canal using

hydrodynamic modelling.

There are several Hydrodynamic simulations done by

researchers in the SSCP area. s tsunami

simulation model has been accepted but it was corrected

by international tsunami authorities. The model explains

tsunami propagation in general terms, but fails to give us

a clear idea of tsunami wave action in Palk Bay area.

Tsunami simulation models by Steven N. Ward of

University of California, explains to us graphically the

way of tsunami waves action in Palk Bay on December

26, 2004. This research focused on developing a model

which will represent the tidal wave propagation and

tsunami penetration. Variations of Tsunami wave height

in Sethusamudram project area was studied to understand

the impact of the SSCP on Sri Lanka.

2. METHODOLOGY

To simulate the evolution of tsunami waves in coastal

oceanic areas the Delft3D-FLOW module was used. The

FLOW module of Delft3D computes wave propagation,

their interactions with seabed topography and energy

dissipation.

Figure 1: Schematic for Tsunami modelling

2.1 Bathymetry dataBathymetry data covering India and Sri Lanka were obtained from Marine Geo-science Data System at 60m, 240m and 1000m per node interval. After that computational grid and depth files for the relevant area were created.

A well-produced high resolution bathymetric data ensures the tsunami wave transformation is properly simulated in the model. Therefore, 60m resolution data was used in for the Gulf of Mannar area where SSCP project is to be located.

2.2 Hydrodynamic model for tsunamiThe time frame for tsunami model is 26/12/20004 08:00 am to 10:00am. The tsunami parameters; time, angular velocity, phase angle, distance, amplitude and wave height were calculated for this time frame.

2.3 Bathymetry of the CanalProposed ship canal coordinates, alignment, dredging segment length and dredging zone data were extracted from Sethusamudram Corporation Limited (SCL) of India. The width of the canal is 300m and depth is 12m. Bathymetry data used in this area had a horizontal resolution of 60m. The canal sea bed profile was inserted



6th January 2017

into the existing (pre-development) bathymetry using the coordinates provided by SCL.

Figure 2: Canal Bathymetry


3.1 Calibration of the tidal modelThe tidal constituents O1, M2, S2, and K1 were selected for Trincomalee and tidal elevation was plotted for several locations. The measured tidal data were extracted from the sea level database from the European Institute for Protection and Security of the Citizens. As shown in Figure 3, the modelled tidal elevation time series agrees reasonably well with the measured.

Figure 3: Calibration of Tide for Trincomalee

The constructed tidal flow model was calibrated by adjusting the calibration parameters. Manninroughness coefficient, horizontal eddy viscosities werechanged between -10% to 10 % but these calibrationparameters were not sensitive to changes. Therefore, values of tidal constituents were slightly changed to get the required agreement with the measured water levels.

3.2 Calibration of the Tsunami modelThe model was calibrated against the water levels observed during 2004 tsunami. The tide level and tsunami elevation were superimposed on the same time base as for the 2004 tsunami. The superimposed time series was used as the model boundary. Error between the modelled and observed tsunami water levels was less than 3%. Therefore, the model was considered sufficiently accurate to study the effect of the SSCP.

3.3 Hydrodynamic modelAfter the Canal creation in the existing bathymetry the model was run for post-construction scenario and the results were compared with the existing. Eastern, Southern and Western coastal areas were seen in aShadow zone, whilst Northern and Gulf of Mannar coasts were affected after the construction of the SSCP.

Figure 4: Left; Observation points (Jaffna and Gulf of Mannar) and Right; Maximum water level at pc5

after SSCP

Table 1: Variation of Tsunami water level

4. CONCLUSIONS

After construction of the proposed SSCP, the simulationswere carried out using the calibrated hydrodynamic model which gave a maximum water level of 3.04mMSLfor Jaffna. Water levels for other cities were: Batticaloa -6.13mMSL, Trincomalee - 5.14mMSL, Galle -5.02mMSL and Colombo - 2.63mMSL. Hydrodynamic simulations indicated that the Gulf of Mannar has a minor impact of 2%-5% in terms of water level increase due to tsunami wave penetration after construction of the Sethusamudrum Ship Canal.

REFERENCES

Kennedy, J., Ashmore, J., Babister, E. and Kelman, I., 2008. The evidence from post tsunami Aceh and

Sri Lanka. Journal of contingencies and crisis management, 16(1), pp.24-36.

Ramesh, R., 2005. Will to Disaster: Post-Tsunami Technical Feasibility of Sethusamudram Project. Economic and Political Weekly, pp.2648-2653.

Wijetunge, J.J., Wang, X. and Liu, P.L.F., 2008. Indian Ocean Tsunami on 26 December 2004: numerical modelling of inundation in three cities on the south coast of Sri Lanka. Journal of Earthquake and Tsunami, 2(02), pp.133-155.

Area Before SSCP After SSCP

Percentage increase

PC1 0.78 0.80 2.56%

PC2 0.92 0.96 4.34%

PC3 1.23 1.29 4.87%

PC4 1.90 1.98 4.21%

PC5 2.55 2.66 4.31%

Jaffna 2.98 3.04 2.00%

Mannar 0.60 0.61 1.67%

2.66 m



6th January 2017

STORM SURGE IMPACT ON SRI LANKA AFTER CONSTRUCTION OF SETHUSAMUDRAM SHIP CANAL

B. Sunthareswaran and H.P.V.Vithana

ABSTRACT

Sethusamudram shipping canal project (SSCP) was proposed by India to be located in shallow waters between Sri Lanka and India. Flooding of coastal areas occurs due to cyclone generated storm surges and combination of tides and waves. There is a need to predict the impact of the proposed canal on coastal flooding in the northern coast of Sri Lanka. In this research a storm surge model was set up using DLFT3D FLOW and WES. Two tropical cyclones occurred in 1964 and 1978 impacting north-eastern Sri Lanka were used to set up the model. , It was found that, when compared to the existing condition, the storm surge height increased by approximately 5% along the Jaffna and Mannar coasts after the construction of the SSCP.

1. INTRODUCTION

Setthusamudram shipping canal project (SSCP)envisaged dredging of the shallow sea bed of the Palk Bay and Adam's Bridge to a depth of 12 meters in good order to make navigation possible for ships. Sea surface temperature rise, because of the global warming might increase the intensity and recurrence frequency of the extreme weather phenomena such as tropical cyclones, flooding and torrential rain in the future. Storm surges are generated primarily by the extreme winds from low pressure atmospheric systems. Further, secondary factors such as atmospheric pressure drops, surface waves,

the intensity of the storm surge. Hence, a storm surge is a rise in sea water level above the predicted astronomical tide level, resulted from the combined effects of strong winds, reduced atmospheric pressure over a shallow water body and other secondary factors. Bay of Bengal is a place where cyclones are generally originated. As Sri Lanka is situated near Bay of Bengal these cyclones affect Sri Lanka as well. Storm surges and resulting flooding of land are indirect impacts of cyclones. The main objective of this research is to estimate the impact of storm surge events after the construction of the SSCPusing hydrodynamic modeling.

2. METHODOLOGY

The flow chart (Figure 1) shows the methodology followed in setting up the model. There are three no of input parameters. Those are meteorological inputs, oceanographic data and location specific data. Afterinputting those parameters model was obtained as .

Figure 1: Methodology in setting up the model

2.1 Bathymetry creationBathymetry data were collected from Marine Geo-science Data System Marine Geo-science Data System at 60m, 240m, 1000m per node interval. After that computational grid and depth files for the relevant area were created.

2.2 Wind file preparation The cyclone data was collected from Meteorological Department, India. The cyclone data (i.e., wind speed, pressure) related to 1978 Batticoloa and 1964 Trincomalee cyclones were used to set up the cyclone model (WES). The main input to the WES model was cyclone track file and wind/pressure input files. After the creation of the wind field as output from the WES model it was coupled to the hydrodynamic model.

2.3 Sethusamudram canal preparation The width of the canal is 300m. Therefore, bathymetry of the canal area should be of high resolution. Hence, 60m x 60m resolution bathymetry data were used in the Gulf of Mannar and Palk Strait as shown in Figure 2.



6th January 2017


3.1 Existing tidal model calibrationBefore setting up the cyclone model, the hydrodynamic model was calibrated for astronomical tides for the existing condition. Figure 3 shows the simulated tide for Trincomalee which agrees reasonably well with the measured. Consequently, hydrodynamic model can be used for other conditions such as cyclone modelling.

3.2 Hydrodynamic model for existing condition Hydrodynamic model (Delft3D FLOW) calibrated for tides was simulated coupled with the Cyclone wind field (WES) and bathymetry data with default physical parameters such as wind drag coefficient, viscosity and

roughness coefficient. The boundary was given astronomical tide conditions. Finally, the output water levels were calibrated and validated. Table 1 showsthe model calibration and validation for cyclone condition.

3.3 Hydrodynamic model after SSCP constructionHere existing bathymetry was altered to represent the 300m wide and 12m deep canal as shown in Figure 2. The calibrated model was re-run with the new bathymetry. Table 2 compares the storm surge heights before and after the construction of SSCP for Jaffna,Mannar as well as Thondi in India for this comparison.

4. CONCLUSIONS

After the SSCP is implemented, the storm surge is increased by approximately 5% along the Jaffna and Mannar coasts.

REFERENCES

Laknath D. P. C. , Kazunori Ito1, T.H. and T.T., 2014. Storm Surge Simulation Coastal Engineering Proceedings, 34, pp.1 10.in Nagasaki During the Passage of 2012 Typhoon Sanba.

Rashomi, S., 2005. Tropical cyclones and the Bay of Bengal. [Online] Available at: http://www.sundayobserver.lk/2005/11/27/fea08.html[Accessed 26 06 2015].

Vatvani, D. et al., 2012. Storm surge and wave simulations in the Gulf of Mexico using a consistent drag relation for atmospheric and storm surge models. Natural Hazards and Earth System Science, 12(7), pp.2399 2410.

Wijetunge, D. J. J., 2013. [Online] Available at: http://www.sundaytimes.lk/131229/sunday-times-2/cyclones-sri-lankas-underrated-hazard-77808.html[Accessed 29 December 2013].

Cyclone year

Location Simulated surge

height(m)

Measured Surge

height(m)1964 Mannar 5.5 4.6

Dhanushkodi 5.4 5.0

1978 Batticaloa 2.8 2.7

Thondi 3.4 4.0

Location Surge height with canal(m)

Surge height

without canal(m)

Increase %

Jaffna 1.9 2.0 5.26Mannar 2.0 2.1 5.0Thondi 3.4 3.5 2.94

Figure 3: Measured and modelled tide

Table 1: Measured and modelled surge heights

Table 2: Storm surge heights before and after the canal implementation

Figure 2: Sethusamudram canal between Sri Lanka and India



6th January 2017

A HYDRAULIC ANALYSIS OF ANCIENT BISOKOTUWA SLUICE-A COMPARATIVE STUDY

A.Y.Tharshikan and H.P.V.Vithana

ABSTRACT

sation, water was taken out of tanks by way of breaking bunds at suitable places. This is a primitive method that would not work for large tanks with high heads that were needed as the population grew. Our engineering predecessors constructed a novel sluice known as Bisokotuwa. This study analyses in detail the hydraulics of ancient Bisokotuwa sluice using a physical model and proceeds to compare it with modern sluices. Velocity and pressure measurement within the physical model showed that the Bisokotuwa outlet velocity is less than the inlet velocity and water pressure gradually decrease from Wewa (Tank) to outlet side. Because of thisBisokotuwa structure and Wewa bund are kept safe and erosion potential is less. In modern sluices outlet flow is not calm and high turbulence occur at the outlet side. This causes erosion on the outlet side and distribution canal downstream.

1. INTRODUCTION

The evolution of water resources planning took place in Sri Lanka during the last 2500 years. The growth of this hydraulic civilisation expanded with improved knowledge and developing new technology for water storage such as Wewas and flow control devices such as sluices. Sluice and sluice gate are one of the most important components in a Wewa and these components are control devices of Wewa. Control devices protect the Wewa bund without damaging the dam from velocity and pressure during outflow of water. The outgoing water from small village tanks was controlled by using temporary cuts in the earthen bunds. In medium size tanks this was done by using a technique called Keta Sorrowa. These simple methods are not useful to control the outflow of water in a much bigger Wewa because of the high head of water. As a solution for this situation our ancient engineers had invented Bisokotuwa. Bisokotuwa could help to control water effectively without exerting high velocity and high pressure on the Wewa bund.

2. METHODOLOGY

In our preliminary studies we identified some Bisokotuwa sites. They were in Anuradhapura, Polonnaruwa and Vavuniya. There are no Bisokotuwas functioning in Sri Lanka at the moment and most are completely abandonedall over the Sri Lanka. We also did not have any structural drawings with dimensions shown of Bisokotuwas. During our field visit to Bhu Wewa it was found that the Bisokotuwa is still in good condition and therefore, we were able to measure the dimensions for our analysis and physical model study. Thereafter,dimensional analysis was carried out for Bhu Vewa Bisokotuwa. For the dimensional analysis, suitable dimensions were selected based on laboratory 2D flume.The physical model was constructed at 1:15 scale to understand the flow behaviour of Bisokotuwa.

Velocity and pressure heads within the Bisokotuwa structure were measured for different reservoir heads. Velocities were measured using velocity meter. Pressures on the Bisokotuwa, inlet and outlet were measured using piezometers made with plastic tubes vented to the atmosphere.


3.1 Hydraulics of BisokotuwaVelocities were measured at inlet and outlet sections of the physical model. Figure 2 shows the inlet (P1) and outlet velocity (P3) of Bisokotuwa. It was observed that the outlet velocity of Bisokotuwa is smaller than the inlet velocity. The measurement locations P1 and P3 are shown in Figure 1.

Figure 1: Experimental setup

P1P2P3



6th January 2017

Figure 2: Graph of Velocity Vs Reservoir head

Figure 3 shows the pressure heads obtained from Piezometers. In the Bisokotuwa inlet and chamber water pressure gradually increased with an increase of reservoir head. However, the pressure at outlet (P3) is mostly constant for increasing reservoir head.

Figure 3: Pressure head Vs Reservoir head

Figure 4 shows the total energy head. Inlet energy head gradually increased with an increase of reservoir head. However, the total energy of outlet is mostly constant for increasing reservoir head.

3.2 Hydraulics of modern sluice

3.2 Hydraulics of modern sluicesWhen the sluice gate is gradually opened, the hydraulic jump also gradually moves forward in the modern sluice structures. At full supply, the jump will be formed near the sluice outlet, therefore, under full water supply condition the water flow is not calm. As a result, the sluice outlet channel and the tank bund face the risk oferosion.

3.3 Comparison of Bisokotuwa with modern sluicesIn Bisokotuwa, most of energy losses occur inside the chamber and, thus, the outflow is calm. But in modern sluices, the hydraulic jump dissipates energy on the outlet side of the sluice. This causes turbulence in the flow. In hydraulic jump kinetic energy is converted to potential energy. However, at the location of hydraulic jump erosion will occur. To prevent this, special hydraulic structures are constructed at the outlet of the sluice.

4. CONCLUSIONS

The Bisokotuwa outlet velocity is less than inlet velocity and also water pressure is gradually decreased from Wewa to the outlet. The pressure of the outlet structure slightly reduces and chamber pressure increases for increasing reservoir heads. This confirms the widely established view that the Bisokotuwa acts to regulate pressure at the outlet.

The total energy of the outlet structure is also mostly constant for increasing reservoir heads and significantly less than that of the inlet. The reduction in total energy at the outlet could be due to a significant energy loss withinthe chamber which was not recognised before as an important phenomenon contributing to reduced turbulence at the outlet.

REFERENCES

Lanka Reservoirs: The Bisokotuwa Sluice'

Parker, H., 1909. Ancient Ceylon (Vol. 41). Asian educational services, pg (377-411).

Ponrajah, A.J.P., 1988. Technical guidelines for irrigationworks. Department of Irrigation, Colombo, Sri Lanka: Department of Irrigation.

Figure 4: Total energy head Vs Reservoir head



6th January 2017

CFD SIMULATION OF FLOW THROUGH AN ANCIENT BISOKOTUWA SLUICE

S.G.L.M. Fernando and H.P.V. Vithana

ABSTRACT

In this study, laboratory measurements of the water surface profile, approach flow velocity, piezometer heads and flow rate were carried out over seven different reservoir head scenarios. Experimental investigations were carried out to study the flow behaviour in the physical model which was constructed at the Hydraulic and Coastal Laboratory. The velocity of the channel flow at the inlet was measured using a propeller type velocity meter. The measured horizontal velocity at the reservoir outlet of the physical model was used as boundary condition for the numerical model. The flow was then numerically simulated using the CFD software ANSYS fluent v.17.0 by solving the governing equations. In the numerical solution of the governing equations, the standard turbulence model was used to define the turbulent viscous dissipation. Velocities and pressure throughout the structure was determined and compared with physical model results. Comparison of experimental and numerical results showed that the simulations predict flow behaviour within Bisokotuwa reasonably well.

1. INTRODUCTION

Ancient Sri Lanka has been known as a hydraulic civilization. Sri Lanka has a great history with agriculture based society. Our ancestors needed to manage the irrigation system to cultivate paddy fields. They built a large network of reservoirs and tanks in order to fulfil their needs. The numerous tank and reservoirs found all over Sri Lanka are a classic evidence of this ancient irrigation system. In the early days water was taken out of small tanks by way of breaking tank bunds at suitable places. However this system clearly would not work with bigger reservoirs. According to the ancient writings, there were some sluices called as Mohole sluice, Keta sorovva etc. Despite all these methods when the volume of water within the reservoir increases as with tank holding up to 20-30ft of water it generates a severe pressure that above mentioned less sophisticated sluices could not safely handle. In such situations our ancestor irrigation engineers had invented a marvellous structure to overcome the above task which is a finest example of ingenuity of the Sri Lankan irrigation engineering known as n s-(Parker, 1909).

There are many past research that only describe the technology behind the Bisokotuwa. No past research described the flow behaviour within the Bisokotuwa. This research was conducted to fill that gap using a computer model. ANSYS Fluent is the software which is used to solve complex fluid mechanics problems. Many types of laminar and turbulent fluid flows can be modelled and analysed by using this software. The software hasdifferent abilities which allow the user to model various geometries with different mathematical models. Finite volume approach is the method which is used for solvinggoverning equations.

2. METHODOLOGY

During the preliminary survey we have found a feasible Bisokotuwa site for research - Bhuwewa in Polonnaruwa.That is the only scientifically excavated Bisokotuwa in Sri Lanka without causing any damage to the structure. There are a number of ancient Bisokotuwas all over Sri Lanka but all of them are abandoned and no structural drawings are available with the Irrigation Department.During the field visit to the site all dimensions required to construct a physical model was measured. Then drawings were developed and a model was scaled down to 1:15 according to the limitations of the available flume in the Hydraulic and Coastal Laboratory. Perspex boards were selected to construct the physical model and some dimensions were slightly changed without affecting hydraulic behaviour of the Bisokotuwa based on dimensions of the available 2D tilting flume.

First verification of the velocity meter was carried out. Discharge was measured using the Weir of the tilting flume. Using this discharge, theoretical velocities at inlet was calculated and it was compared with velocity meter reading. Calibration graph showed that velocity meter works accurately.

Thereafter physical model was tested for different reservoir water heights on the inlet side. Available height of the flume is 250mm. Therefore, the testing was started from 200mm decreasing by 20mm down to 80mm. Velocities at inlet, chamber (Bisokotuwa) and outlet were measured and piezometer water heads were observed and relevant discharge was measured using the flow reading device in the flume.

Thereafter CFD simulations were done using ANSYS Fluent software. CFD modelling methodology is shown in Figure 1.



6th January 2017

Figure1: CFD modelling methodology

Inlet was defined as velocity inlet, then the measured velocity was given as an input. Measured water height at inlet side was converted to a pressure head and inputgiven as an initial gauge pressure. Chamber of the structure was selected as the outlet-vent and the input gauge pressure as zero because operating pressure is zero. The outlet was selected as a pressure outlet. It is already given as a default.


Seven tests for different water levels at inlet side were carried out. Inlet side water level was maintained in a constant level to mimic the tank (reservoir). Then velocities and pressure variation were plotted.Verification was done using the averaged outlet velocities from the CFD model and the physical model. Figure 2shows the comparison between measured velocities from the physical model and CFD model velocities.

Figure 2: Outlet velocity comparision

Observed velocities from the CFD model were compared at inlet and outlet. Figure 3 shows that outlet velocities are lower than inlet velocities in all seven reservoir heads.

Figure 3: Modelled inlet and Outlet velocities

Pressure at the outlet from CFD model was comparedwith that of the physical model in order to clarify the pressure behaviour in the Bisokotuwa.

Figure 4: pressure comparision at outlet pizeometer

4. CONCLUSIONS

CFD model results shows that pressure and velocities of the outlet were reduced in Bisokotuwa. Here inlet cross section is larger than the outlet cross section. One would expect when the flow is steady for the outlet velocity to be higher than the inlet velocity. However, the average velocity at the outlet is lower than that at the inlet. The reason for this phenomenon could be that there is significant energy loss within Bisokotuwa due to turbulence.

REFERENCES

Sirirnimal lakdusinghe felication volume, 173-189.

Calomino, F. & Lauri -D Underflow of a sluice gate at a Journal of

Civil Engineering and Urbanism, Vol 4, Issue 5, 501-508.

Parker, H., 1909, Ancient Ceylon, Asian Educational Services, New

Delhi.

Geometry creation

Mesh generation

Fluid physics setup

Processingg and Results



6th January 2017

HYDROLOGICAL IMPACT ASSESSMENT OF LAND USE CHANGES ON RUNOFF IN THE UPPER NILWALA BASIN USING HYDROLOGICAL

MODELLING

N. A. S. S. Nishshanka, B. M. L. A. Basnayake, and W. M. K. R. T. W. Bandara

ABSTRACT

human activities such as urbanization, mining, agriculture.Hydrological systems and their related processes are affected due to these changes. Better understanding on land use change on runoff is essential for proper watershed management. This study aims to investigate the effects of land usechange on runoff in the Upper Nilwala basin. HEC-HMS model was developed to quantify the runoff generation for land use in 1983 and 2011 using the Soil Conservation Service-Curve Number (SCS-CN) method. Analysis of results shows that the surface runoff has increased in 2011 by 1141 mm than that in 1983 due to the land use change in the Upper Nilwala basin.

1. INTRODUCTION

Human needs have led changes in land cover such as forests, water surfaces, agricultural lands, etc. Changing the type of land use has a considerable impact on the runoff and hydrological related issues. For example, with urbanization, evapotranspiration, infiltration, and interception may decrease increasing the surface runoff.Usually, urbanization increases peak discharge and runoff volume, and shortens the time of concentration (Weng, 2001). Assessment of land use change on runoff is a recent research interest (Liu and De Smedt, 2005). The objective of this research is to evaluate the impacts of changes in land use on the generation of runoff in the Upper Nilwala basin.

2. STUDY AREA

Nilwala river basin (Figure 1) is mainly located in MataraDistrict of Sri Lanka.

Figure 1: Nilwala basin and river network

It starts at Panilkanda area, near Deniyaya, which is located at an altitude of 1,050 m and flows to the Indian Ocean at Matara. The area of the Nilwala river basin is approximately 1,073 km2 while the study area which the catchment area above Pitabeddara is ~380 km2.

2. METHODOLOGY

Firstly, land use maps were developed using ArcGIS to evaluate the land use change over years. Secondly, HEC-HMS model (Figure 2) was developed to quantify the runoff change due to land use change.

Figure 2: HEC-HMS model set up of the Upper Nilwala catchment

Datasets used to develop the model includes; land usemaps, soil maps, topography, rainfall, and discharge data.Topography, represented by 30-meter resolution Digital Elevation Model (DEM) acquired from the United States

Dataset. Land use map layer was obtained from the department of survey in Sri Lanka. Rainfall data and

from theobtainedwerePitabeddaradischarge data atMeteorological Department Department,Irrigationandrespectively.

Anninkanda

Mawarella

Mapalana

Arpthop

Legend

River network

Upper Nilwala Catchment

Nilwala Catchment0 10 205 km



6th January 2017


Table 1 presents the variation of land use from 1983 to 2011.

Table 1: Land use area (%) classification of the Upper Nilwala catchment in 1983 and 2011

According to the land use classification data in the watershed, land use has been mainly changed from agricultural and forest to build up and bare areas. Agricultural and forest areas have been reduced by 28.5% and 4.0%, respectively to form of build-up and bare areas.This clearly indicates that the impervious area of the catchment has increased from 1983 to 2011.

Surface runoff generated in the catchment for land use in 2011, in general, was equivalent to 57% of rainfall water, while surface runoff for land use in 1983 was equivalent to 45%. This implies a surface runoff increase of 12%from 1983 to 2011. Results of hydrological modelsupport the hypothesis that a decrease in pervious layer results in increase of runoff.

4. CONCLUSIONS

In this study, SCS Curve Number method was used to estimate the effect of land use changes on runoff in the Upper Nilwala basin. It is estimated that the annual surface runoff generated in the watershed is increased in 2011 by 1141 mm than that in 1983 due to the land use change in the Upper Nilwala basin.

REFERENCES

Journal of Environmental Modeling and Assessment, 9(4), pp227-235.

urface runoff with Environmental

Management, 28(6), pp.737-748.

Land Use 1983 2011

Agricultural 70.927 42.477

Bare Area 4.089 13.245

Build Up Area 0.075 23.193

Forest 24.060 20.065

Rock 0.017 0.015

Water 0.832 1.006



6th January 2017

FLOOD FREQUENCY ANALYSIS UNDER CHANGING ENVIRONMENT

K. M. K. C. Rodrigo, B. M. L. A. Basnayake, and W. M. K. R. T. W. Bandara

ABSTRACT

Flood frequency analysis is required in designing hydrological structures. Traditional flood frequency analysis is based on the stationary assumption. However, climate change and land use change are affected hydrological cycle and thereby stationary assumption may not be valid for some catchments. In such a case, non-stationary flood frequency analysis may provide a proper flood frequency analysis rather than traditional approach. In this research validity of the stationary and non-stationary flood frequency analysis for Upper Nilwala basin is investigated. Validity of the stationary flood frequency analysis depends on changes in the land use, rainfall, temperature, wind pattern etc. In this research, changes in the rainfall are considered in the non-stationary flood frequency analysis. HEC-HMS model was developed to the Upper Nilwala basin to estimate runoff for the non-stationary approach. Land use is assumed to be constant in the entire period. Results show that non-stationary method is more appropriate for the Upper Nilwala basin.

1. INTRODUCTION

Flood frequency analysis is a statistical method of prediction using historical storm events which determines the probabilities of occurrence of these events in the future. The primary objective of the flood frequency analysis is to relate the magnitude of extreme events to their frequency of occurrences through the use of probability distributions. The results of flood frequency analysis can be used for many engineering purposes such as for the design of dams, bridges, culverts and flood control structures, to determine economic value of flood control projects, to delineate flood plains, and to determine the effect of encroachments on the flood plain.

In general, flood frequency analysis is based on the stationary assumption. It assumes that flood series data are independent and identically distributed, in other words, time series data are free of trends and abrupt changes. The use of long historical records for flood frequency analysis brings in question of flood stationary due to climate and land use changes (Machado et al. 2015). Validity of the stationary assumption depends on the significance of the changes. Yet, the application of non-stationary concepts in engineering community became as a rather challenging due to the limited number of non-stationary models and scarce long term flood records to test the behavior of such a modal.

Nilwala river basin which is subjected to frequent flooding is selected in this research to compare the applicability of traditional approach with the non-stationary approach.

2. STUDY AREA

Nilwala river basin (Figure 1) is mainly located in Matara District of Sri Lanka.

Figure 1: Nilwala basin and river network

It starts at Panilkanda area, near Deniyaya, which is located at an altitude of 1,050 m and flows through 72 km. Nilwala river basin is approximately 1,073 km2 while the study area which the catchment area above Pitabeddara is ~380 km2. The mean annual rainfall of upper basin is above 3000 mm and lower river basin receives about 1900 mm.

3. METHODOLOGY

Most commonly used probability distributions in the hydrology are considered in the flood frequency analysis(Table 1). Chi-Squired goodness of fit test was used to identify the best fitted distribution function.

In the non-stationary flood frequency analysis, rainfallvariance was considered with the time while land use is assumed to be a constant. HEC-HMS rainfall-runoff model was used to estimate the annual discharge data.



6th January 2017

Table 1: Most commonly used probability density functions in hydrology

Distribution Probability density function

Normal

Lognormal

Where

Exponential

Gamma

Where

Pearson type

Where

Log Pearson

Where

Weibull


Table 1 shows the Chi-squared test statistics of the stationary and non- stationary flood frequency analysis.

Table 1 : Chi-squared test statistics of the stationary and non-stationary flood frequency analysis (FFA)

Distribution Stationary FFA Non-stationary FFA

Lognormal (3P) 0.332 3.815

Gamma 0.344 4.768

Log-Pearson 3 0.636 0.058

Gumbel Max 0.722 3.945

Weibull 1.169 5.487

Lognormal 1.522 4.013

Weibull (3P) 2.259 4.042

Normal 2.500 6.082

Gamma (3P) 4.296 4.015

Lognormal (3P) type is the best fitted probability distribution in the stationary flood frequency analysis which provides a chi-squared value of 0.332. However, non-stationary method gave a chi squared value of 3.815 for the Lognormal distribution function. Log-Pearson

type 3 provided the least chi-squared value which is less than that of the best fitted function in the stationary approach. This implies that the non-stationary method provides the best results in the flood frequency analysis.

5. RESULTS AND CONCLUSIONS

Flooding has been one of the most costly disasters in terms of both property damage and human in Sri Lanka.According to the past records, Nilwala basin is subjected to frequent flooding, causing several damages to the properties, people and surrounding area. In this research, stationary and no-stationary flood frequency analysis is considered for the Upper Nilwala basin. Rainfall is only considered in non-stationary method. Results show that non-stationary method is more appropriate for the Upper Nilwala basin.

REFERENCES

Machado, M. J, Botero, B. A, Lopez, J. Frences, F, Diez-Herrero, A. & Benito, G., 2015, 'Flood frequency analysis of historical flood data under stationary and non-stationary modelling', Hydrol. earth Syst. Sci. Discussion.

CIVIL AND ENVIRONMENTAL ENGINNERING SOCIETY

107Proceeding of Undergraduate Research Symposium on Recent Advances in Civil Engineering

6th January 2017

PRESNTING REAL TIME WATER QUALITY DATA USING FUSION TABLES

H.S. Priyadarshana and Cyril Kariyawasam

ABSTRACT

Conventional data management systems used currently outdated storage mechanisms. Google Inc. introduced new experimental cloud based data management system which is much easier to display and manage data. Fusion tables enable users to upload tabular data files currently up to 250 MB. The system enables users to visualize data withcharts, maps and timelines. The system supports merging, sharing and commenting on data sets. This new experimental technology was used to publish water quality data of Galle and Hambantota districts. The important aspect of this work is data can be imported in real time basis. Real time data are uploaded using relevant sensors and transmitted to the server. User can access the server and retrieve the real time water quality data.

1. INTRODUCTION

Google launched on an experimental basis, fusion table technique in June 2009.Until then there was no easy user friendly data management system to handle large amounts of water information which were locked away in private computers. It is a new experimental online research and data organizing tool. (Dickinson B., 2011.)

The new Google technology provides users to share data, probe them, organize information and generate design elements charts, graphs and maps that translate complex information into much more digestible trends. The intent is to enable users to study and understand the

crisis is among them. Fusion Tables can be used to tell stories, offer insights, and propose solutions. (Parker, 2009)

Google Fusion Tables making it easy for the people to upload, to merge data sets, to discuss the data, to create visualizations and then to take these visualizations and

access to data on the Web. (Gonzalez, 2010)

2. METHODOLOGY

Water quality data of two hundred and thirty-twonumbers of wells around Galle and Hambantota districts were presented using the latitude and longitude of each well. Google fusion table technology was used to publish the data. However, water quality is dynamic variable. So it is important to make real time water quality data available for users. This task was achieved using Nodemcu and relevant sensors and transmitter connected server.

We obtained water quality data of two hundred thirty-twonumbers of wells with different locations with corresponding latitude and longitude of each well. Table 2.1 shows selected water quality parameters.

Table 2.1: Selected water quality parameters

As the data are stored in the cloud sharing, collaborating and visualizing data is much easier.

Google Maps API was used embed the fusion table map on the web interface. It is an Application Programming Interface which allows different software components to communicate with each other and library that includes tools, variables, data structures, object classes, etc. Web version utilizes JavaScript. So the Google map created using fusion tables and other visualizations of charts, tables and graphs can be embedded in a web interfacewith more other information which fusion table is not capable of handling. Another advantage is data can be updated using table ID. (Google inc., 2016).

Real time data can be uploaded to a server by relevantsensor and microcontroller. To demonstrate this NodeMCU v1.0 and DS18B20 temperature sensor were used. When internet access and power supplied to the microcontroller it will upload real time temperature of the relevant water body to ThingSpeak.com.


Figure 3.1 shows the feature map produced using Google fusion tables from water quality data of Galle and Hambantota districts. Each icon on the map represent a

Water quality parameters

Fe2+ SO42- Mg Fe Cd

CaCO3 NO3- Ca Ni Pb

Electrical

conductivity Na2+ Al Cu V

pH NH4+ Cr Zn Alkalinity

Cl- K+ Mn As SiO2

CIVIL AND ENVIRONMENTAL ENGINNERING SOCIETY

108Proceeding of Undergraduate Research Symposium on Recent Advances in Civil Engineering

06th January 2017

location of well. The user can retrieve real time water quality data by clicking the icon. An important aspect of this work is that cloud can be updated so that map will be automatically updated.

Figure 3.1: Visualization of data using fusion tables

Figure 3.2 shows the variation of real time temperature with respect to time. By this method, continuously updating real time temperature of a water body was presented to public.

Figure 3.2: Real time temperature of a waterbody uploaded to sever

4. CONCLUSIONS

Google fusion tables is cloud based new era data management system for majority mass who does not know about data management systems and have data and want to visualize and get value out of data. (Hector,2010)There many examples in the web that journalists used this new technology and embed their data in web so the readers can visualize them. Another important aspect is another one can merge their data set and make the project into a collaborative effort. Users can keep the data private, share it with a selected set of collaborators, or make it public so that data is crawlable by search engines. The discussion feature of Fusion Tables allows collaborators to conduct detailed discussions of the data at the level of tables and individual rows, columns. The Google map API used to develop further and embed the fusion table map in the web.

Water quality monitoring is essential to understanding the impact humans have on the environment. Clean water is important to the health of plants and animals and the quality of life for all people. So it is a common sense today that real-time water quality monitoring is vital to efficiently operate water plants and manage sources.

There are many water quality sensors on the market.Available sensors include temperature, conductivity, dissolved oxygen, pH, turbidity, chlorophyll A, and blue-green algae.

REFERENCES

Dickinson, B., 2011. How to visualize data using Google Fusion Tables. [Online] Available at: http://www.zdnet.com/article/how-to-visualize-data-using-google-fusion-tables/[Accessed 16 May 2016].

Google inc., 2016. About Fusion Tables. [Online] Available at: https://support.google.com/fusiontables/answer/2571232?hl=en[Accessed 18 May 2016].

Hector Gonzalez, A. H. C. S. J., 2010. Google Fusion Tables: Data Management, Integration and. ACM, 11 JUNE, 45(6), p. 6.

Hector, G. et al., 2010. Google Fusion Tables: Web-Centered Data Management and Collaboration. [Online] Available at: http://research.google.com/pubs/pub36257.html[Accessed 18 May 2016].

Kidon, J. G., 2010. Fusion Tables : new ways to collaborate on structured data. [Online] Available at: http://hdl.handle.net/1721.1/60999

Parker, A. A., 2009. Google Brings Water Data to Life. [Online] Available at: http://www.circleofblue.org/2009/world/google-brings-water-data-to-life/[Accessed 15 May 2016].



6th January 2017

PUBLISHING GIS DATA ON GOOGLE MAPS USING FUSION TABLE TECHNOLOGY

B.S.M.T Hirantha and C. Kariyawasam

ABSTRACT

There are many mapping tools that are available in the market to prepare Geographical maps. But they require a lot of money and expert knowledge. But Google recently introduced fusion table technology which has become revolutionary to users who interest on preparing GIS maps to publish their data. Capability of publishing real time data is a remarkable feature of fusion tables. Using fusion tables, it is easy to publish the GIS data and to allow access the data. Water quality data of wells in Galle and Hambantota districts have been selected here to publish on GIS maps using fusion table technology. The goal of Fusion Tables is not to replace traditional database management

to effectively enable new users and uses of data management technology.

1. INTRODUCTION

Fusion tables are capable of filtering and summarizinghundreds of thousands of rows associated with data. All the data have inserted in tabular form is automatically saved and stored in Google Drive. Then it is able to insert and formulate charts, maps, network graphs, or custom layouts and embed or share it over web site. It enables to use without creating hundreds of copies of data depend on hard drives. Data is saved in bigtables and megatables in Google cloud. Data can be easily imported as

file (Gonzalez, 2010). To illustrate the publishing of GIS data on Google maps using fusion tables, water quality data of wells around the Galle and Hambantota districts were used. It is very important to know the water quality before use. GIS map enables to identify the distribution of water quality within the selected area. The server embedded map and visualizations will allow public to identify the quality of water with aid of Google maps.

2. METHODOLOGY

Water quality data of 232 wells around the Galle and Hambantota districts were selected to publish water quality on Google maps. For each well 25 no of water quality parameters were considered, including pH, F, Cl and etc. Location of wells imported in to Google maps by their latitudes and longitudes. It is important to create server to publish the GIS map and other visualizations allowing filtering and sharing, to access data by large community. Basic GIS maps were created using existing data and embedded into a server. Water quality is a dynamic variable; real time data system was prepared to publish most recent data continuously. It is accomplished by relevant sensors and transmitter connected to server. A API is generated by fusion table for each visualization including the maps created by fusion tables. Through that API maps can be embedded in a web site as required. HTTP requests are sent through SQL to programmatically update the tables and visualizations. NODEMCU circuit and Temperature sensor are used to demonstrate the real time data management system. This technology is

illustrated here using water quality data however can be used with any other time series data. Figure 1 shows the process of manipulating real time data.

Figure 1: Real time data uploading process


Creating maps and visualizations from GIS data, publish them on a server and updating the server in real time basis are the major results achieved through the research.

3.1 Creating effective maps and visualizationsFigure 2 shows a featured map created by Google fusion tables. Each icon in the map represent a well and by clicking on it details of the particular well are viewed. Icons were given to particular well considering the concentration of relevant parameter. Figure illustrate the Cl concentration of wells, the colour and type of icon change according to the concentration as given in legend.

Figure 2: Feature map for well data in Galle and Hambantota district

Icon represent the wells which have exceeded the maximum allowable concentration for drinking. At a glance user able to identify where the water sources which not suitable for drinking or to be filtered before drink.



6th January 2017

Heatmaps display colors on the map to represent the density of points from a table. The optional Weight adjusts each point's importance by multiplying its intensity by the specified column value (Google inc,2016). Weight can be changed according to the parameter needs to be considered. Heat map created by Google fusion table in figure 3 shows the spatial distribution weighted by pH. It enables to analyze spatial variance ofparticular parameter within particular region.

Figure 3: Heat map for distribution of pH values

Charts give a clear view of comparison of concentration of parameters in each local areas of Galle and Hambantota districts. Likewise altering and filtering data many charts can be generated for compare each parameter. Figure 4a and 4b show the comparison of parameters F and NH3 for average concentration and maximum concentration with respect to local areas. Morecharts can be created and published for minimum and maximum concentration of any parameter as well.

Figure 4a: Average concentrations of F and NH3 in local areas

Figure 4b: Maximum concentrations of F and NH3 in local area

3.2 Publish GIS data on web serverAll the data have set accessible for public and anybody interested on data can access the web site. There is an option to comment on data considering their validity. Each and every visualization on web server is updated in real time basis, so users are able to see most recent data.

A fusion table API is generated for each map created by fusion tables. Through that API map can be embedded in a web site as required. As well tables, charts, cards can be embedded into a web site through the API.

3.3 Real time data systemCircuit for the real time basis data system was prepared with sensors and microcontrollers to keep the data updated. The set of devices set to take measurements can be controlled remotely through connectivity of Wi-Fi. So no need of manual engage with the circuit except for maintenances. If the delay per reading want to be manipulated it can be done remotely. Transmitted data into thingspeak cloud can be imported as CSV file which contain all the data taken since the very first data. This information are used to identify the variation of particular parameter with respect to time.

4. CONCLUSIONS

More than just publishing GIS data on books, magazines and storage devices it is effective and reliable to share them through fusion tables as GIS maps and visualizations. Most important thing is publishing real time data on Google maps. As the fusion table is updated with real time data simultaneously maps and visualizations embedded on web server will be updated.Then the users will able access most recent data and get the advantages in to day to day life. Millions of data can be published on Google maps to provide more information. Feature map can include every data in exact location. Data can be categorized and displayed on map highlighting specific of the data category and data included in the particular category. Just clicking on the representing icon every detail related to considered thing can be viewed. As a summary data can be manipulated in many mays through the visualizations.

REFERENCES

Blasch, E.P., Deignan, P.B., Dockstader, S.L., Pellechia, M., Palaniappan, K. and Seetharaman, G., 2011, July. Contemporary concerns in geographical/geospatial information systems (GIS) processing. In Aerospace and Electronics Conference (NAECON), Proceedings of the 2011 IEEE National (pp. 183-190). IEEE.

Gonzalez, H., Halevy, A., Jensen, C.S., Langen, A., Madhavan, J., Shapley, R. and Shen, W., 2010, June. Google fusion tables: data management, integration and collaboration in the cloud. In Proceedings of the 1st ACM symposium on Cloud computing (pp. 175-180). ACM

Google inc., 2016. About Fusion Tables. [Online] Availableat: https://support.google.com/fusiontables/answer/2571232?hl=en.]



6th January 2017

GIS BASED SUITABILITY ANALYSIS FOR MUNICIPAL WASTEWATERTREATMENT PLANT: A CASE STUDY FOR PUTTALAM URBAN

COUNCIL

S.I.S. Wijesingha, W.M.K.R.T.W. Bandara, B.M.L.A. Basnayake, and Terrance M. Rengarasu

ABSTRACT

One of major issue in municipal planning and development is finding the most appropriate site for a wastewater treatment plant (WWTP). This research was aimed to identify the suitable site for the Puttalam Municipal Council. An appropriate site selection of is an important for the sustainable treatment and reuse of municipal domestic wastewater and reduces the awkward environmental and social cultural impact. Environmental aspect, social and cultural aspect,and technical aspect were included as major criteria in the research. The Analytical Hierarchal Process (AHP) was used to determine the priority weight of main criterion and sub criteria. AHP and the GIS were an integrated technique used to assess suitable site for wastewater treatment plant (WWTP) in Puttalam municipal council area. According to the field verification procedure the more appropriate land was selected beside from the not suitability land for construction of the WWTP.

1. INTRODUCTION

One important applications of Geographic Information System (GIS) is site suitability mapping and analysis (Brail & Klosterman 2001). One of the possibilities of GIS system is analysis of map overlays. This ability is one of the fundamental analysis functions in GIS so that multiple information layers can be overlaid to reveal optimal locations through application of logical and mathematical operators. In this research, overlay process was used to analysis.

Puttalam town is located in the Eastern shore of PuttalamLagoon in Puttalam district, North Western province ofSri Lanka. High population density in the town and discharge of sewage to the drains has caused health hazards in the area. Use of unprotected water sources is an additional cause for the poor hygiene conditions available in the area. In this background, municipal wastewater treatment plant is important for Puttalam town to treat and reuse of municipal wastewater.

A wastewater treatment plant should reduce the social and environmental impacts, and there should be technical feasible site to reduce technical environment. Site suitability analysis is applied to identify suitable sites for a domestic wastewater treatment plant. The criteria involve include technical aspects, social aspects, and environmental aspects (Meinzinger 2003).

In addition, appropriate site selection avoids or reducesmany of the environmental problems inherent in WWTPsuch as: Reduce the need for technically based environmental and health risk mitigation measures and costly on-going management measures; Result in substantial savings in establishment and operation of sewerage systems; Reduce levels of public concern.

The main objective of this research is to identify an optimal site for a domestic wastewater treatment plant for

Puttalam municipal council. This main objective consist with following two specific objectives:

To develop a criteria for WWTP site selection suitability analysis.To evaluate and assign the weights for site suitability factors by using AHP decision-making method.

2. METHODOLOGY

Figure 1 shows the research design chart.

2.1 Define Appropriate Criteria

By considering previous researches and legislative framework in Sri Lanka, affected criteria was fixed. Data availability also affected for criteria. Then, suitability data layers of the study area were obtained from several sources.

From Literature Reviews

Apply Basic Theories

Define Appropriate Criteria

Conclusion

Digital Data

Field Verification

Assign Weights

Suitable Site for Treatment Plant

Figure 1: Research design chart.



6th January 2017

2.3 AHP AnalysisIn this process, the weights of the each suitability criteria were calculated using AHP weighting method. As all dataare not equally important, they need to be weighted based on their importance in this land use suitability process. The questionnaires survey was conducted to produce best result for AHP weighing analysis. These were taken from multiple experts in the field. The 20 samples were obtained for this research. As a result of this survey, final pair-wise comparison judgement sheet of all suitability criteria i.e. main and sub criteria were prepared for AHP weight computation.

2.4 Weighted Overlay ProcessGIS model was used to the weighted overlay process.

After the weighted overlay of the reclassified data layers; the common layers were created for main criteria as technical, environmental, and social and cultural aspect. Finally, main three common layers were weighted overlaid.


3.1 Affected Criteria for Site Suitability AnalysisThis research provides fundamental concept about

the suitability criteria (Figure 2) which could beused in the site selection of the Municipal wastewater treatment plant.

3.2 Weightage of Criteria for Site SelectionAccording to AHP analysis topography, surface water, and residential area have higher weightage of sub criteria, and social & cultural aspect has higher weightage of main criteria. All weightage values are shown in Table 1.

Table 1: Weightage of each criterion

3.3 Final suitability mapUsing GIS model, final suitability map (Figure 3) was created. Approximately 1200 hectare wasidentified as suitable area.

Figure 3: Final Suitability map

4. CONCLUSIONS

Figure 2: Selected site for WWTP

To identify an optimal site for domestic WWTP for Puttalam municipal council was main objective of this research thesis. Therefore, domestic wastewater treatment site suitability (Figure 4) has been achieved accurately and effectively due to the application of GIS and AHP decision-making results.

REFERENCES

Brail, R. K. and R. E. Klosterman., 2001, planning support systems: Integrating geographic information systems, models and visualization tools Redlands, CA: ESRI Press.

Meinzinge, F., 2003, GIS Based Site Identification for the Land Application of Wastewater, Linclon University.

Main CriteriaWeights

(%)Sub Criteria

Weight(%)

Technical 10.8Soil 25

Topography 75

Environmental 35.9

Surface water

83.3

Ground water

16.7

Social and cultural

53.3

Land use 38.9

Road 10

Residential area

51.1

Wastewater treatment plant

Technical Aspect

Soil

Topography

Environmental Aspect

Surface water

Ground water

Social And cultural Aspect

Land use

Road

Residential area

Figure 2: Affected criteria for site suitability analysis



06th January 2017

GIS BASED SITE SUITABILITY ANALYSIS FOR WASTEWATER TREATMENT PLANT: A CASE STUDY FOR UNAWATUNA AREA

N.A. Nusky, W.M.K.R.T.W. Bandara, B.M.L.A. Basnayake, and Terrance M. Rengarasu

ABSTRACT

Identifying a site for domestic waste water treatment plant requires a comprehensive evaluation to identify the best available location(s) that can simultaneously meet the requirements of regulations and minimise economic, environmental, health, and social costs. While GIS has been a powerful tool to handle spatial data in site suitability analysis, application of this tool alone could not overcome the issue of inconsistency in expert opinion when trying to judge and assign relative importance to each of many criteria considered in a suitability analysis. To address this issue, the Analytical Hierarchy Process method is used in combination with the GIS tool. This study presents how the integrated tool has handled effectively a site suitability analysis for Unawatuna tourist area which considered simultaneously 8 different sub criteria under 3 different main criteria such as climate, soil texture, topography, surface water, ground water, land use, residential area, and roads.

1. INTRODUCTION

In the wastewater 99% of water and only one percentage is solid wastes. Wastewater is generated from domestic, industrial, agricultural sources, and surface run-off due to rain. Eventually, it goes down to the drainage and end up in wastewater treatment facility. Hence, it is necessary to take effective steps toward achievement of environmental goals of sustainability through developing treatment plants in suitable sites. However, finding a suitable site for this purpose involves considering wide range of criteria which makes decision making complicated. It includes consideration not only inherent capacity of a land unit to support a specific land use for a long period of time without deterioration, but also the socio-economic and environmental feasibility. Therefore, when selecting appropriate site selection, the technical, social, environmental aspects need to be considered as main criteria during analysis. The criteria influencing the site selection were mainly determined by temperature, wind direction and speed, rainfall soil, topography, ground water, surface waters, land use, residential area, and roads (Meinzinger, 2003; Munasinghe, 2015). In spatial multi-criteria decision analysis (MCDA), geographical data are gathered, processed and transformed into a decision. And for that we have to adopt a technique that allows an estimation of the weights. Analytic hierarchy process (AHP) was applied to assign weights for the selected influence criteria with combination of GIS analysis tools to provide effective and efficient site identification promising results. The selected study area is Unawatuna tourist area in the southern region of Sri Lanka.

2. METHODOLOGY

Research procedures can be mainly categorized as defining site suitability criteria, AHP analysis, and weighted overlay. Defining site suitability criteria was

done by referring previous studies and laws on conservation. Relevant GIS maps were created using ArcGIS. For AHP analysis, questionnaire survey was conducted among experts such as Galle irrigation chief engineer, engineers, doctors, undergraduates and public in the study area. The weights derived from the AHP analysis was used for weighted overlay process using ArcGIS. The weighted overlay was done in two phases, among the sub criteria and main criteria. Finally, field verification was carried out. The design flow chart isshown in Figure 1.

Figure 1 : Design Flow Chart

The digital layers used for spatial analysis were 1: 10,000 map obtained from the Department of Surveying, Sri Lanka. The ground water map was created using the ArcGIS tools from the data around the study area. Ultimately, based on the above procedures the final suitability map was created.


The criteria and the suitability classification with scores were developed which is primary procedure in identifying the optimal site for municipal WWTP for Unawatuna(Table 1). The weightage of criteria is shown in table 2.



6th January 2017

Table 1: Suitability Criteria

Main Criteria

Sub Criteria Class

Technical Aspects

SoilSoil Texture

Red-yellow Podzolic

3

Regosol 2

Bog and half dog

1

TopographySlope[%]

0 15 215 30 330 < 1

EnvironmentalAspects

Groundwater

Depth[m]

0 1.5 11.5 2.0 22.0 < 3

Surface Waters

Buffer[m]

0 60 160 100 2100 < 3

Social and Cultural Aspects

Building/ Residential Areas

Buffer[m]

0 15 1

15 30 2

30 < 3

Land Use Type

Built-up area

1

Boggy areaForest areaCloud areaCultivation areaRock areaWater areaSand area 2Bare area 3

Major Roads

Buffer[m]

0 400 1400 600 3600 < 2

Minor Roads

Buffer[m]

0 50 150 100 3100 < 2

3- suitable 2- Moderate 1- Unsuitable

Table 2 : Weightage of Criteria

Main criteria Weight Sub-criteria WeightTechnical Aspects

0.090Soil Texture 0.750Slope 0.250

Environmental Aspects

0.303Ground Water 0.250Surface Waters 0.750

Social and Cultural Aspects

0.607Land use 0.303Residential Area 0.607Roads 0.090

Criteria which have highest weights influence more in the output overlaid map. Here, among main criteria, social and cultural aspects influence around 61%. In the overlay of social and cultural suitability, residential area factor influences about 61% (Table 2).

Figure 2: Final Suitability Map

The final suitability map (Figure 2) was created from weighted overlaid map and majority filtering processes.The particular sites A, B, C, D were identified from field verification and land area requirement.

Land Area RequirementClient Requirement (NWSDB Galle-Experience) 16000m2

4. CONCLUSIONS

The defined criteria were more reliable for selected study area. AHP method is superior for multi- criteria decision making technique. GIS is greater flexibility and accurate tool for domestic wastewater site suitability analysis. Hence, the integration of AHP technique and GIS analysis provided the efficient result of suitability analysis of the domestic wastewater treatment plant. Authorities can easily apply this new approach as it is fastand high accurate. The approach applied in this study can be adopted in other part of Sri Lanka for sustainable future development.

REFERENCES

-based site identification for the land application of wastewater: Christchurch

Munasinghe, D.S., Pussella, P.G.R.N.I. and Gunathilaka, M.D.E.K.,

Domestic Wastewater Treatment Plant: A Case Study of Akkaraipattu In Proceedings of International Forestry and

Environment Symposium (Vol. 20).



6th January 2017

FEASIBILITY OF HYBRID REACTOR FOR REMOVAL OF HEAVY METAL IN WASTEWATER

G.S. Nallaperuma, W.M.K.R.T.W Bandara and G.G.T. Chaminda

ABSTRACT

A UASB reactor and an activated sludge process have combined to form a hybrid reactor for the removal of heavy metals in wastewater. The system was operated with synthetic wastewater at a flow rate of 20 ml/min and a 7 hrs of HRT. Pb, Cd, Zn, and Cu was added to the wastewater separately, each in three different concentrations. The average COD removal efficiency of 84% was obtained for each case. Heavy metal removal efficiencies achieved for Pb and Cu were above 80%, for Cd it is above 75% and for Zn removal efficiency was above 90%. It was found that the hybrid reactor is feasible for heavy metal removal from wastewater and the heavy removal from the wastewater increase in the order of Cd<Cu<Pb<Zn.

1. INTRODUCTION

The elements with atomic weight between 63.5 and 200.6 and a specific gravity greater than 5.0 are known to be heavy metals (Srivastava & Majumder 2008). Heavy metals in wastewater come from industries and municipal sewage, and they are one of the main causes of water and soil pollution. The most common heavy metals contaminants are: Cadmium (Cd), Chromium (Cr), Copper (Cu), Iron (Fe), Lead (Pb), Nickel (Ni), Zinc (Zn), and Arsenic (As) (Dhokpande & Kaware 2013).

Most of the heavy metal ions present in the environment are known to be toxic or carcinogenic. There are various treatment processes available for wastewater with heavymetals. These technologies can be divided into three categories like biological, chemical, and physical. Currently, the major methods of industrial wastewater treatment involve physical and/or chemical processes. Because of the high cost and disposal problems, many of these conventional methods for treating wastewater have not been widely applied at large scale. In practice, a combination of different processes is often used to achieve the desired water quality in the most economical way (Ahmaruzzaman 2011).

Biological treatment is often the most economical alternative when compared with other processes.Biological treatment can be divided into two classes, aerobic and anaerobic which constitute the main units of most wastewater treatment plants. Although, there were so many researches for the removal of heavy metals from the wastewater, the researches which were focused on combination of aerobic and anaerobic (hybrid) systems are less. There was not a research which used upflow anaerobic sludge blanket (UASB) for hybrid system. Therefore, this study was designed to study the feasibility of UASB and aerobic reactor on the removal of heavy metals during the wastewater treatment stage and compare it with other methods.

2. METHODOLOGY

The general arrangement of lab scale hybrid reactor consists a combination of UASB reactor with anaerobic granular sludge having a working volume of 8.5 L.Aeration tank has a working volume of 20 L and theSedimentation tank has a working volume of 13 L.Synthetic wastewater was used as the influent to the reactor. First a baseline was established without adding any heavy metal. Then, the reactor was operated with Pb, Zn, Cd, and Cu separately and each in three different concentrations at 7 hrs. of HRT. pH and temperature of the system was observed daily in order to maintain favorable conditions for the anaerobic process. COD and the heavy metal concentrations in the influent and effluent was measured to find the treatment efficiencies. The sludge volume of the decanted sludge was estimated by the volumetric method using Imhoff cones.


COD removal efficiency, sludge volume, and the heavy metal removal efficiency of the hybrid reactor are shown in figure 1, figure 2, figure 3, and figure 4, respectively.

Lead (Pb) was introduced to the system in 0.1 mg/l, 0.25mg/l, and 0.5 mg/l concentrations and above 80% Pb removal efficiency was obtained from the hybrid reactor.Heavy metal removal efficiency has increased with the influent concentration.

Zinc (Zn) was introduced to the wastewater in 1 mg/l, 2mg/l, and 3mg/l concentrations and above 90% Zn removal efficiency was obtained from the hybrid reactor.Cadmium (Cd) was introduced to the wastewater in 0.1 mg/l, 0.25 mg/l, and 0.5 mg/l concentrations and above 75% removal efficiency was obtained. The removal efficiency of Cd is less compared to other heavy metals because of its high solubility.

Copper (Cu) was introduced to the wastewater in 0.5mg/l, 1 mg/l, and 1.5 mg/l concentrations and above 80%



6th January 2017

Cu removal efficiency was obtained from the hybrid reactor.

Figure 1: COD removal and heavy metal removal efficiencies of the hybrid reactor, and the sludge

volume for the wastewater containing Pb


volume for the wastewater containing Zn


volume for the wastewater containing Cd


volume for the wastewater containing Cu

4. CONCLUSIONS

The reactor was operated over 110 days by maintaining a flow rate of 20 ml/min where HRT of UASB reactor is 7 hrs. at ambient temperature of 32°C. Results showed that the T-COD removal efficiency is more than 80% for Lead (Pb) and Copper (Cu); more than 75% for Cadmium (Cd) and more than 90% for Zinc (Zn). It can conclude that the reduction of heavy metal contents has increased in the order of Cd<Cu<Pb<Zn. The removal efficiencies are directly proportional to the initial concentration.

REFERENCES

Ahmaruzzaman, M., 2011, 'Industrial wastes as low-cost potential adsorbents for the treatment of wastewater', Advances in Colloid and Interface Science 166, pp. 36-59.

Dhokpande, S. R. & Kaware, J. P., 2013, 'Biological Methods for Heavy Metal Removal-A Review', International Journal of Engineering Science and Innovative Technology (IJESIT) 2(5), pp. 304-309.

Srivastava, N. K. & Majumder, C. B., 2008, 'Novel biofiltration methods for the treatment of heavy metals' , Journal of Hazardous Materials 151, pp. 1-8.

100

110

120

130

140

150

160

0.1 0.25 0.570

75

80

85

90

95

Influent Pb concentration (mg/l) Pb

Sludge volume COD removal Pb removal

100

150

200

250

300

350

1 2 384

86

88

90

92

94

96

Influent Zn concentration (mg/l) Zn

Sludge volume COD removal Zn removal

100

150

200

250

300

350

0.1 0.25 0.570

75

80

85

90

Influent Cd concentration (mg/l) Cd

Sludge volume COD removal Cd removal

100

200

300

400

500

0.5 1 1.582

84

86

88

90

Influent Cu concentration (mg/l) Cu

Sludge volume COD removal Cu removal



6th January 2017

FEASIBILITY OF UASB REACTOR FOR REMOVAL OFHEAVY METAL IN WASTEWATER

U.L.N.C. Jayathileke, W.M.K.R.T.W. Bandara and Thushara Chaminda

ABSTRACT

Accumulation of heavy metals into wastewater has increased with rapid urbanization. Therefore, treatment methods to remove heavy metals are essential. Upflow Anaerobic sludge blanket (UASB) reactor uses sludge granules rich with microbes as treatment media. A lab scale reactor was operated with synthetic wastewater influent at HRT of 7 hours.Heavy metals were added to the influent wastewater at 3 different concentrations and one heavy metal was added at a time. COD, Biogas production rate, pH, temperature, and heavy metal concentration were measured for the analysis. The analyzed results shows that Zn and Cd are toxic for the granules and Cu and Pb are not toxic. It is also shows thatPb has high removal efficiency. Although Cu showed low removal efficiency this may be improved by changing HRT. Even if Zn and Cd were toxic there was considerable removal efficiency.

1. INTRODUCTION

Environment contamination with toxic heavy metals hasbecome one of the major concerns for human kind in thecurrent era of globalization and rapid industrialization.Discharge of heavy metal contaminated wastewatercauses the accumulation of heavy metals to the water bodies, soil, and crops. Heavy metals are naturally occurring substances that have a high atomic weight and a density at least 5 times greater than that of water (Tchounwou et al. n.d.).

Although there are numerous methods for removal of heavy metals, new methods with less cost and less sludge production are required. UASB reactor is an attractivetreatment method because of its compactness, lowoperational cost, low sludge production, and productionof bio methane. (Mudhoo & Kumar 2013). However, the feasibility of the UASB reactor for the removal of heavy metals has not been taken into consideration. Therefore,the objective of this study is to identify whether the UASB reactor is feasible for the removal of heavy metals and to identify the removal efficiency. The effect heavy metals on wastewater treatment process are also considered inthis study.

2. METHODOLOGY

A lab scale UASB reactor with a height 110 cm; diameter10 cm; working volume 8.5 L was used for this study. A synthetic wastewater was used as the influent to the reactor. First, a baseline was established for the performance of the reactor by running the reactor without adding any heavy metals. Then, four heavy metals Pb, Zn, Cd, and Cu was added to the influent at one heavy metal a time in 3 different concentrations and the reactor was operated at 7 HRT. The influent and effluent wastewater samples were collected to test the parameters. The pH and temperature of the influent and inside UASB was tested to ensure the proper anaerobic conditions inside the

UASB reactor. The COD and the heavy metal concentrations in the influent and effluent were measured to identify the removal efficiencies. The gas volume generated through the treatment inside the reactor and its composition was also measured.


3.1 Pb removalPb was added to wastewater in 3 concentrations which are 0.1 mg/l, 0.25 mg/l, and 0.5 mg/l. Figure 1 shows the COD removal efficiency and the biogas production for the Pd addition. Both parameters has increased with the increase of Pb concentration in the influent wastewater. 63% - 83% of Pb removal efficiency was obtained.

3.2 Zn removalZn was added to wastewater in 3 concentrations which are 1 mg/l, 2 mg/l, and 3 mg/l. As shown in the Figure 2, COD removal efficiency and the biogas production has decreased with Zn concentration. Removal efficiency between 68% -74% was achieved.

Pb concentration (mg/l)

COD removal Pb removal

Biogas production

Figure 1: Analyzed parameters for Pb addition



6th January 2017

Figure 2: Analyzed parameters for Zn addition

3.3 Cd removalCd was added to wastewater in 3 concentrations which are 0.1, 0.25, and 0.5mg/l. As shown in the Figure 3, COD removal efficiency and the biogas production has increased and then decreased with Cd concentration. Removal efficiency between 61-71% was achieved.

Figure 3: Analyzed parameters for Cd addition

3.4 Cu removalCu was added to wastewater in 3 concentrations which are 0.5 mg/l, 1 mg/l, and 1.5 mg/l. Figure 4 shows thatCOD removal efficiency and the biogas production hasnot change significantly with Cu concentration. Removalefficiency between 61% - 68% was achieved.

Figure 4: Analyzed parameters for Cu addition

4. CONCLUSIONS

It was possible to remove the heavy metals using UASB reactor. The removal efficiencies are different based on the heavy metal type and the concentration. The efficiency was between 63% - 83%, 68% -74%, 61-71%, and 61% - 68% for Pb, Zn, Cd, and Cu, respectively. The other objective of this research was to identify whether there is an effect on the wastewater treatment parameters from the heavy metals. From the results it can be concluded that the COD removal is enhanced by the increased Pb concentration. However, there is a negative effect on the COD removal by the Cd and Zn. The effect is more significant when it comes to Cu. However, in each case at least 50% removal efficiency can be achieved. This study can be developed considering the removal efficiency of heavy metals when there is more than one heavy metal in influent wastewater and fordifferent HRT values for better analysis.

REFERENCES

factors on anaerobic digestion processes and biogas production from 1398.

Tchounwou, P. B., Yedjou, C. G., Patlolla, K. A. & Sutton, D.J., n.d.,

Molecular, Clinical and Environmental Toxicology. s.l.:Birkhäuser Basel, pp. 133-164.

Zn concentration (mg/l)

COD removal Zn removal Biogas production

Cd concentration (mg/l)

COD removal Cd removalBiogas production

Cu concentration (mg/l)

COD removal Cu removal

Biogas production



6th January 2017

FEASIBILITY OF USING MIXED PLANT CULTURES FOR REMOVAL OF NUTRIENTS IN WASTE WATER: LAB SCALE EXPERIMENTS

W.C.S. Perera and K.C. Ellawala

ABSTRACT

This study was investigated the feasibility of removing nutrients using mixed plant combinations of Limnocharis flava:Pistia stratiotes and Limnocharis flava:Ipomea aquatica which are common invasive plants in Sri Lanka. The reduction of nitrogen and phosphorus in waste water by continuous flow constructed wetlands was observed using glass tanks (60cm×30cm×30was included waste water in feeding tank (TN- 50.22ppm, TP 2.84ppm). The removal efficiency of nutrients were investigated under mixed culture of Limnocharis flava:Pistia stratiotes (3:1) at two different HRT values. At HRT of 1 day resulted low nutrient removal efficiency with maximum 5.8% and 40.07% TN, TP removal respectively. At HRT of 5 days resulted maximum 8.95% and 31.81% TN, TP removal respectively. It was concluded that there is no benefit of increasing HRT further more. Therefore, the attention of another possible candidate for further experiment had become essential and Ipomea aquatica was selected as substitution, which is highly available in Sri Lanka. At HRT of 5 days with Limnocharis flava: Ipomea aquatica (3:1) resulted higher nutrient removal such as maximum 35.81% TN and 67% TP removal respectively. The removal efficiency obtained from this research indicated that, mixed culture with Limnocharis flava: Ipomoea aquatica had a great potential in removing nutrients from nutrient enriched water with HRT of 5 day.

1. INTRODUCTION

There is a growing demand for the development of appropriate and affordable wastewater management technologies particularly in developing countries such as Sri Lanka to reduce the pollution of fresh water resources from unacceptable ways of wastewater discharges. Compared to conventional wastewater treatment technologies, constructed wetlands offer low cost, easy to operate, efficient and robust treatment and have become a widely use technology recently in many parts of the world with good results(Weerakoon et al. 2011)

There are many research have been done to remove contaminants from waste water by using aquatic macrophytes. Basically, most of the research were done in temperate countries. But constructed wetlands are low cost technology which is highly applicable to tropical countries, since most of them are developing countries and sunlight is available throughout the year for plant growth. In addition, most of studies on competition have been done either for emergent emergent, submerged-submerged or floating floating plant species. Less studies have been done for their combinations. But in this study, it is investigated the feasibility of using mixed plant cultures of emergent (Limnocharis flava) floating (Pistia stratiotes, Ipomoea aquatica) plants in order to understand the removal of nutrients in waste water.

TP uptake rate of mixed culture system was significantly higher (p<0.05) compared with monoculture systems when it is having constant nutrient concentration. L. flavaalways performed better in mixed culture than monoculture. The inter-specific competition is significantly influenced in TP uptake rate of L. flava and P. stratiotes than intra-specific competition. P. stratioteswas less effective in monocultures; but when it was

together with L. flava, contributed to increase nutrient removal efficiency in mixed culture system (Kodithuwakku et al. 2016).

The Objective of this research is to investigate the feasibility of removing nutrients using mixed plant combinations. (Limnocharis flava:Pistia Stratiotes, Limnocharis flava:Ipomea aquatica)

2. METHODOLOGY

Same age, same size and young healthy Limnocharisflava, Pistia stratiotes and Ipomoea aquatica plants for the experiment were manually collected and the experiment was conducted in glass tanks

for making structure of constructed wetland. At the first experiment, the continuous flow system was arranged by using commercially available fertilizer as waste water. The fertilizer will be diluted up to the typical TN (Total Nitrogen) and TP (Total Phosphorus) values (TN-50.22ppm/ TP 2.84). The plants were grown in mixed culture, density with 3:1 (L. flava: P. stratiotes) which was found from one of past studies related to this study.The different HRT values were found according to past literature to determine the efficient HRT in removing nutrients in nutrient rich waste water. The initial TN/TP values, final effluent TN/TP values are tested and until it gives efficient HRT value. Experimental setup is shown in Figure 1.



6th January 2017

Figure 1: Experimental Setup

2.1 TN AnalysisThe filtered water samples were used to measure TN in water by using per sulphate digestion and second derivative spectroscopy. The absorbance was measured at 220nm and 275nm by UV spectrophotometer.

Corrected Absorbance=Abs220nm-2×Abs275nm

2.2 TP AnalysisThe filtered water samples were used to measure TP in water by using Molybdenum blue method after per sulphate digestion. The absorbance was measured at830nm by UV spectrophotometer.


According to the experiment 1, there was no successfulnutrient uptake. Maximum TN and TP removal efficiency from experiment 1 was 5.8% and 40.07% respectively.Depending on plant species used, type of wastewater treated, and nutrient loading rates, plant nutrient uptake has been shown to account for between 3% and 47% of N removal and 3% to 60% of P removal. (Greenway, M.,et al. 2000)

The treatment 2 was done using Limnocharis flava:Pistia stratiotes(3:1) plant ratio for 5 day HRT. Maximum TN, TP removal efficiency in this treatment was 8.95% and 31.81% respectively. So, this results shows that the uptake rate for TN cannot be easily measured using a hydroponic system. This could be due to the high concentration of nitrates, production of nitrates by some living species, the slow decrease in TN concentration, or some sort of uncontrolled nitrate sources affecting the systems due to a change in related atmospheric chemical species (Nathan 2014)

Although the TN removal efficiency was increased in treatment 2, TP removal efficiency was decreased. Intreatment 3 with Limnocharis flava: Ipomea aquatica, 3:1for same nutrient concentration at HRT of 5 day, themaximum TN, and TP removal efficiency was 35.81%, 67% respectively. Results of treatment 3 is shown below.

Figure 2: TN Removal efficiency (%) in Treatment 3

Figure 3: TP Removal efficiency (%) in Treatment 3

4. CONCLUSION

The removal efficiency obtained from this research indicated that, mixed culture with Limnocharis flava: Ipomoea aquatica had a great potential in removing nutrients from nutrient enriched water. So, this research is an application of continuous flow CW for nutrient removal in nutrient enriched water using emergent-floating plant combination of Limnocharis flava: Ipomea aquatica (3:1) at HRT of 5 day.

REFERENCES

Greenway, M., Wolley, A. (2000). Changes in plant biomass and nutrient removal over 3 years in a constructed free water surface flow wetland in Cairns Australia. In Proceedings of the Seventh International Conference on Wetland Systems for Water Pollution Control, International Water Association , Lake Buena Vista, Florida, 11-16 November, 707-718.

Kodithuwakku H.,Sewwandi S.H.I., Ellawala K.C.,2016,Efficiency of removing phosphorus in water by Limnocharis flava and Pistia stratiotes,Department of Civil and Environmental Engineering,University of Ruhuna.

Nathan D,Ide A. D. P., Steve J. R.,2014. Phytoremediation of Phosphates and Nitrates in the Lake Macatawa Watershed Using Wetland Plants. 8.

Weerakoon, G. M. P. R., , M. I. M. M., , G. B. B. H. & Jinadasa, A. K. B. S. N. 2011. A Comparison Of Vertical Sub-Surface Flow And Horizontal Subsurface Flow Constructed Wetland Mesocosms In Tropics.



6th January 2017

EVALUATION OF THE INFLUENCE OF THE CONSUMER AWARENESS ON DRINKING WATER TREATMENT PROCESS ON HOUSEHOLD

WATER CONSUMPTION

T.K.G Wijesiri and K.C. Ellawala

ABSTRACT

Water is one of the most important resources. The effect of the consumer awareness of water treatment in household water consumption is less concern in the world. The main reason is that in the developing country the people do not have an idea about water treatment process. So the people are misusing the potable water. In this research, questionnaire survey was conducted to obtain the relationship between consumer awareness about water treatment process and their average daily consumption. Using cluster analysis, three awareness groups were developed and average water consumption of these three groups were compared. The results show the awareness on drinking water treatment process is influential on the household water consumption. Further improvement of water saving technologies can reduce the consumption of water and also it is important to find the alternative water sources for landscape maintenances and for vehicle washing.

1. INTRODUCTION

We can't imagine a world with life without water, becausewater is a primary necessity for all forms of life on the Earth. Fresh water sources are very scarce in the world because of that water treatment is very important process to supply potable water for the consumer from raw water obtained from water source. It is important to ensure water quality not only relate to the treatment of the water, but to its conveyance and distribution after treatment. There is lots of time consuming and costly processes are in connection with water treatment process. Householdsare the smallest consumers of water, but have a large potential impact and also they are the responsible people,who need to develop water saving habits in household level. In developed countries most of the peoples are having the idea about water treatment process. By increasing awareness about treatment process the water misusing can be reduced. The objective of this research is to collect data on consumer awareness on drinking water treatment process on household water consumption and to identify the effect of consumer awareness on drinking water treatment process on household water consumption quantitatively and qualitatively.

2. METHODOLOGY

In this research we checked the consumer awareness on drinking water treatment process on household water consumption in Sri Lanka. Data used for the study were collected by questionnaire survey. In this survey consumer awareness was checked under following topics, the reasons for the limited water supply, cost for the water supply, regular processes which needed to be done in distribution of water, awareness about unit treatment process, one unite treatment cost and the attitude of the consumer. Data were clustered using hierarchical cluster analysis using Ward's method. Gower's distance matrix method was used for calculating distances. All the

analysis was carried out using R statistical software package.


The questionnaire survey was completed and 219 numbers of data was collected from households in Galle and Matara districts and 64 householders are water board employers. Three-year water consumption data was collected from National Water Supply and Drainage Board, which related to that households water consumption. Analyses have been done and there we could identify three main clusters and the average water consumption was compared with their awareness about the main factors that we address from the questionnaire survey in these three clusters.

Figure 1: Awareness about the reason for the limited water supply



6th January 2017

Figure 2: Awareness about the cost for the water supply

Figure 3: Awareness about the regular processes which needed to be done in water distribution

Figure 4: Awareness about the attitude factors

Cluster 1 name as LOW cluster always has less awareness about water treatment process, cluster 3 name as MODERATE has moderate awareness about water treatment process and cluster 2 name as HIGH always has high awareness about water treatment process.

Figure 5: Average water consumption in three clusters

Resulting from the clustering shows that end use water consumption in households varies with the consumer awareness of drinking water treatment process. There the low awareness group (LOW cluster) is having average consumption of 145.9 L/p/d, high awareness group (HIGH cluster) is having average consumption of 128.1 L/p/d and the moderate awareness group is having 134.3 L/p/d.

Awareness percentage is high in HIGH cluster compare with other two clusters about one unit treatment cost and also the awareness about unit treatment process also high in the HIGH cluster. Less number of water board employers in the LOW cluster.

4. CONCLUSIONS

The result from this research provide the people have high awareness about water treatment process have less average water consumption that they aware about the water treatment process and they always try to use alternative water sources activity like gardening and

The results from this research provide water consumption is effected by the awareness about water treatment process on household water consumption. The awareness programme should be targeted to obtain highest effective household water saving. Significant water saving can be achieved by giving the clear image of the water treatment process. The research method could also be applied to investigate relationship between awareness of consumer about water treatment process to consumption and to the conservation of potable water in the commercial and industrial sectors.

REFERENCES

Understandingbehaviour to inform water supply management in developed nations A review of literature, conceptual model and research agenda Environmental Management, 91, 47 56.

Beal, C. D., Gurung, T. R. & Ste -side management for supply- Sustainable Production andConsumption, 6,1-2.

Crampton, A. & Ragusa, A. T., 2Behaviors about Drinking Water in Australia and New Zealand: Is It

hydrology,3(8).



6th January 2017

EVALUATION OF THE INFLUENCE OF ENVIRONMENTAL ATTITUDES ON HOUSEHOLD WATER CONSUMPTION

De Silva A.S.R. and C.K. Ellawela

ABSTRACT

Drinking water is a scarce resource. Production of potable water is costly operation. Therefore, minimization of wastage and hence reducing the demand is an important aspect. This study is aimed to evaluate the relationship between environmental attitudes and water consumption. A questionnaires survey was conducted to evaluate the environmental attitudes of the consumer living in Galle and Matara water supply areas. Consumers were clustered based on their environmental attitudes and their daily average water consumption was compared. It was found that there is no correlation with the environmental attitude of the people and their water consumption.

1. INTRODUCTION

Domestic water consumption is very important in potable water production, because it is one of the major aspects in water supply. Preparation of potable water from raw water obtained from a water body is a costly and time-consuming process. Constructions of infrastructure for water purification plants are also high. Some water supply schemes in Sri Lanka are unable to supply water even if the full capacity of the treatment plant is obtained. However household consumption of water is not limited to necessary requirements of pure water. That problem can be minimized by reducing amount of house hold water consumption. Peoples attitude on the environment and water conservation can do major change in these patterns (Coelho et al., 2016)

2. METHODOLOGY

In this research, our main objective is to identify arelationship (if exists) between environmental attitude & consumption of water. Hence, the parameters which depend for house hold of water consumption were identified and house hold water conservation technique were also identified by studying researches that are publish in previously. Then, questions that can be get information about people attitude for water consumption and conservation were created using those parameters which depend for house hold end use of water consumption. Next, a questionnaires survey is done using in Galle and Matara areas. n= 233 sample was collected in this questionnaires survey. Using questionnaires survey, we collected information about people awareness of household end use of water conservation and way of water consumption (Willis et al., 2011). Data wereclustered using hierarchical cluster analysis using Ward's method. Gower's distance matrix was used for calculatingdistances. All the analysis was carried out using R statistical software package.


According to the awareness of environmental attitude, our

software. Those data were clustered in three group and there are denoted as High, Moderate and Low according to the awareness of environmental attitude. The HIGH cluster donates the group of households with a very high level of awareness about environmental attitude. MODERATE cluster represents the group with the moderate level of awareness about environmental attitude. Finally, LOW cluster donates the group of households with a low level of awareness about environmental attitude. In this case, low awareness group (Low Cluster) included 56 (24.03%) data set. Moderate cluster included 71 (30.47%) data set. High cluster included 106 (45.49%) data set. The average per capita water consumptions were determined separately for clusters using data sets of low, moderate and high clusters. The low cluster average total water use was 128.62 L/p/d, moderate cluster was 132.44 L/p/d and high cluster was 127.23 L/p/d.

Figure 1: Avg per capita water consumption distribution against with Environmental attitude

awareness Clusters

According to the distribution of water consumption against with clusters of awareness of environmental attitude, you can see water consumption is not



6th January 2017

significantly change. It means, awareness of environmental attitude is not directly affect for the water consumption rather than other social and economicfactors. Hence, when improving environmental attitude from low to high, water consumption cannot be reduced significantly because those parameters are not significantly inter relationship and other factors, such as social and economic factors can be influenced to the amount of water consumption. Hence we cannot predict negative relationship between environmental attitude and water consumption

The consumer income also mainly influences to the water consumption. Consumers who have high awareness for environmental attitude have high income (Positive relationship). When consumer income increases, then their water consumption rate also increase. It was expected that, when environmental attitude is positive, their water consumer rate to be reduced (Coelho et al.,2016). Water consumption of moderate cluster is litter bit high as final result because both environmental attitude and economic factors affect for final result. Combination of influence of both factors, distribution of final result not significantly change.income against with awareness of environmental attitude represent bellow chart in figure.2

Figure 2: Consumer Income distribution

Income rage of less than 25000, 25000-50 000, 50000-75000,75000-100000 and more than 100000 is weight as 1,2,3,4,5 respectively. Then, average expected income weight value for low, moderate and high are 2.57, 2.88 and 3.14. It means, low awareness cluster consumers average income is medium range of 25000-50000, moderate awareness cluster consumers average income is upper range of 25000-50 000 and high awareness cluster consumers income is lower range of 50000-75000. Hence when increase income of consumers; their awareness of environmental attitude also increases. The level of education also increases against with awareness of environmental attitude. It also represents following chart in Figure 3.

Figure 3: Level of Education distribution

4. CONCLUSIONS

In this result you can see many relationships among factors. When level of education increases both consumer income and environmental attitude also increase. It means, level of education and both consumer income and environmental attitude have positive relationship. The consumer income and water consumption also have positive relationship. But the awareness of environmental attitude and water consumption has negative relationship.When consider water consumption against with other independence factors. Environmental attitude not only influence to the water consumption, but also influence consumer income. Those two factors influence to the water consumption significantly. But they affect negative and positive way. Hence water consumption variation against with environmental attitude is low and the moderate awareness people have consumed little bit high amount rather than other people who have low and high awareness of environmental attitude. Hence final result of water consumption against with environmental attitude have moderate in like that developing country, especially south province because influence of consumer income is high these countries.

REFERENCES

Coelho J. A.P.M., Gouveia, V. V. , de Souza G. H. S., Milfont, T. L., Barrosa, B. N. R.,2016, Emotions toward water consumption: Conservation and wastage, Revista Latinoamericana de Psicología, 48( 2), 117 126.

Hurlimann, A., Dolnicar, S., Meyer,P., 2009, Understanding behavior to inform water supply management in developed nations A review of literature, conceptual model and research agenda, Environmental Management, 91, 47 56.

Willis, R. M., Stewart, R. A., Panuwatwanich, K., Williams, P. R Hollingsworth, A. L., 2011, 'Quantifying the influence of environmental and water conservation attitudes on household end use water consumption.' Environmental Management, 92, 1996-2009.



6th January 2017

THE INFLUENCE OF CONSUMER BEHAVIOUR ON HOUSEHOLD WATER CONSUMPTION

Y. Wasala and K.C. Ellawala

ABSTRACT

Water is a key element for human survival and it is becoming a scarce resource in the world. Fully understanding consuming patterns and water conservation among different social groups will help in implementing more effective water conservation programs worldwide. Authorities related to water resources are working so hard to ensure that there is enough water to meet demand in the face of common issues like drought, population growth and predictions of reduced supply due to change in climate. In order to develop effective household demand management programs, water managers need to understand the factors that influence the household water usage. Consequently they investigated water use patterns, water conservation practices, attitudes, and barriers to water conservation by randomly surveying household users. The collected data from questionnaire survey in household level was used to create models. And those models were used to identify relationship between the consumption of water.

1. INTRODUCTION

It is a well-known fact that water is a critical resource. It supports human life and culture, ecological functions and economic activities. Significant differences between the availability of quality water sources and demand for consumption can occur due to many reasons like population increase, water pollution, urban development, agricultural irrigation, climate change and drought occurrence. Which simply implies that demand is not satisfied with the available resources. Waste, dumping of industrial pollutants and fertilizer runoff are common hazards for freshwater sources. Past research has determined that water consumption within household is dependent on various factors, which include: the number of people in the house, the age ranges of house residents, education levels of residents, size of properties, total income of household responsible persons, efficiency of water consuming appliances (i.e. clothes washers, showers, taps, dishwashers and toilets) and the attitudes, beliefs and behaviors of consumers. Peoples attitude on the environment and water conservation can do major change in these patterns. For example time of bathing, running washing machine in full capacity, fitting water saving bathroom appliances can reduce the consumption of water. Further socioeconomic characteristics like number of occupants, family composition, Ages of family members, income level, educational level, etc. may be influential on the consumer behavior. Therefore this study is aimed to explore the relationship between consumer behavior and water consumption.

2. METHODOLOGY

In this research, our main objective is to build statistical relationship between water. Hence, the parameters that depend for household end use of water consumption will be identified and household water conservation technique will also be identified by studying researches that are publish in

previously. Then, questions that can be used to get information about people attitude for water consumption and conservation will be created using those parameters, which depend for household end use of water consumption. Research activities were carried out by development, application and statistical analysis of an attitudinal and demographic questionnaire survey. The surveys were distributed to households and it is important to note that only one questionnaire survey was completed per household. The target is to conduct the questionnaire survey among 250 respondents. Asking 25 questions per each person to cover the required fields of researchcollects the data. A four-point Likert-type measurement

attitudinal items, with 1 representing strongly agree and 4 representing strongly disagree. Data obtained from the survey are compiled into statistical software for the purpose of statistical analysis. Data are clustered using hierarchical cluster analysis using Ward's method. Gower's distance matrix method is used for calculating distances. All the analysis was carried out using R statistical software package.


We conducted our questionnaire survey in areas likeAmbalangoda, Hikkaduwa, Rajgama, Baddegama, Galle town, Hapugala, Matara town, Pamburana, Weligama area. There we collected the last month consumption of the household and there water bill account number. First we selected two groups as general public and water board employers. So we could distribute 233 number of data collection forms to both groups. 72 among water board employers and 161 among general public. For the completed 217 data we got monthly consumption data up to month of January 2013 from national water supply and drainage board. Eight consumption behaviours were selected for the analysis and additionally demographic data (family composition, Age, Gender, Income, Education level) and availability of alternative water sources for consumers also questioned.



6th January 2017

Table 1: Consumer behaviours selected for the analysis

In analysis 1 we observed that water board employees` group had high awareness about those behaviours and their consumption was low. And second group was general public where the awareness is moderate and it was observed that their water consumption is comparatively high.

Figure 1: Consumption variation between water board employers and general public

In analysis 2, we observed that water board employees` group had high awareness about those behaviours and their consumption was low. But after clustering general public the high aware cluster showed relatively high average consumption while low aware cluster showed relatively low consumption. However these consumption values were not significantly different among groups. We identified that use of alternative water sources and income had affected the two clusters to differ from usual consumption pattern. Finally we analysed the data with dry and wet weather conditions but there was no significant change of water consumption of three groups during dry and wet weather conditions.

Figure 2: Consumption variation between water board employers and general public in two clusters

4. CONCLUSIONS

This research is highlighting consumption tendencies of different consumers. It help to identify what actions they can simply take to reduce water wastage while reducing the water bill and finally achieve universal goal of water conservation. Peoples attitude on the environment and water conservation can do major change in these patterns. For example time of bathing, running washing machine in full capacity, fitting water saving bathroom appliances can reduce the consumption of water. Further socioeconomic characteristics like number of occupants, family composition, Ages of family members, income level, educational level, etc. may be influential on the consumer behavior. The results from this research provide water consumption is effected by the awareness about common water consuming behaviours in household level. In future the targeted areas can be broadened to industrial and irrigation water consumption as well.

REFERENCES

Bea -side management for supply- Sustainable Production and Consumption, 6,1-2.

De Miranda Coelhoa J.A.P., Gouveiab V.V., de Souzac G,H,S., Emotions toward water

Revista Latinoamericana de Psicología,10,RLP 21.

behaviour to inform water supply management in developed nations -A review of literature Journal of Environmental Management, 91 (1), 47-56].

Willis, R.M., Stewart, R.A., Panuwatwanich, K., Williams, P.R.,

and water conservation attitudes on household end use water Journal of Environmental Management, 92, 1996-2009.

Common behaviours Uncommon behaviours

1.) Take short baths 5.) Use native drought tolerant plants for gardening

2.) Wash dirty clothes at once

6. ) Watering gardens less frequently

3.) Avoiding use of running water when washing fruits and vegetables

7.) Frequent checking for leakages in faucets and drips

4.) Washing all cooking utensils in a basin at once

8.) Prevent children from playing with water unnecessarily



6th January 2017

FIELD- SCALE LOW-COST MIXED-MEDIA PERMEABLE REACTIVE BARRIER (PRB) SYSTEM TO TREAT ORGANIC COMPOUNDS AND

NUTRIENTS OF GROUND WATER CONTAMINATED BY LANDFILL-LEACHATE

D. M. Kankanige and W. K. C. N. Dayanthi

ABSTRACT

Permeable Reactive Barrier (PRB) is a potential treatment method for ground water contaminated with land fill leachate. This study was focused on a mixed-media PRB system with Dewatered Alum Sludge (DAS), Washed Quarry Dust (WQD), Washed Sea Sand (WSS), Red Soil (RS), Bio Char (BC) and Saw Dust (SD) as reactive materials to treat organic compounds and nutrients of leachate contaminated by ground water. The influent to the system was from a lysimeter modelling a landfill. The system responded with satisfactory treatment results among which the mean removal efficiencies of BOD5 (88.2+5.7%), COD (84.2+9.6%), NH3-N (95.6+8.2%) and TP (77.8+22.2%) became significant. Thus, these reactive materials have the potential to be used as filter media in other leachate treatment units as well.

1. INTRODUCTION

Landfill leachate, the aqueous effluent generated as a consequence of rainwater percolating through wastes(Bagchi, 2004), consists of a variety of contaminants, and they can be hazardous in the form of both organic and inorganic compounds (Snow, 1999). Organic compoundssuch as phenols, esters, ethanes, propanes etc. are abundantly found in it. Among the inorganic compounds nitrogenous and phosphorous compounds are dominant nutrients. Due to the contamination of groundwater with the landfill-leachate, the quantity of safe ground water on earth is getting reduced rapidly, which is already limited at the moment. Thus, at present, when leachate has become a dominant factor of polluting ground water, it is of highest importance to investigate a remediation technique to treat the contaminated ground water. That technique being economical and practically feasible is quite essential when considering its application in the developing countries. PRB is such a novel in-situ technique widely applied to treat the contaminated groundwater. As revealed by literature, the type and packing configuration of the reactive media are significant factors that affect the treatment efficiency of PRB. If low-cost/waste materials can be used as PRB-reactive media, it will make PRB more applicable in terms of cost, and it will also be a reuse application for the waste materials. Since the sequential arrangement of the reactive materials in a multi-media reactive bed gives construction difficulties, mixed arrangement seems more feasible. This study focused on investigating the removal efficiencies of landfill-leachate contaminants, namely organic materials and nutrients, by a PRB system in which two mixed-media PRBs were connected in series. The reactive materials were DAS, WSS, WQD, RS, SD and BC. The experiments were carried out in a field scale experimental set-up for a total duration of 140 days. The changes in the physical and mechanical properties of the

reactive materials subjected to the interaction with landfill-leachate were also studied.

2. METHODOLOGY

Two mixed-media PRB units were connected in series in the field scale experimental set-up. PRB unit 1 was loaded with DAS, WQD, WSS and RS, mixed in equal weights whereas PRB unit 2 was loaded similarly with SD and BC. A high degree of compaction was provided when loading the reactive materials into each PRB unit, in order to reduce the hydraulic conductivity and thereby increase the hydraulic retention time. The measuredparameters were BOD5, COD, Nitrate-Nitrogen, Total Nitrogen, Ammonia-Nitrogen (NH3-N), Orthophosphate-Phosphorous (PO4

3 P) and Total Phosphorous (TP). Table 1 shows the loading criteria on each PRB unit.

The removal efficiencies of each parameter were determined based on the influent and effluent concentrations. Additionally, physical and mechanical properties of reactive media were tested prior to and after the experimental run to investigate the variation of those properties with the interaction of the leachate. The measured properties were particle size, porosity, hydraulic conductivity and shear strength.

Table 1: Loading criteria of PRB reactors

Hydraulic parameter PRB 1 PRB 2Hydraulic Loading Rate (HLR) (m3/m2. d)

0.172 0.152

Hydraulic Retention Time (HRT) (d)

5.4 7.7

Organic Loading Rate (OLR)(kg BOD/m3.day)

0.05 0.01

OLR (kg COD/m3. d) 0.088 0.039OLR (kg N/m3. d) 0.014 0.007



6th January 2017


3.1 Overall analysisThe values of the average influent concentrations and the means and standard deviations of removal efficiencies ofeach measured parameter are given in Table 2.

Table 2: Influent characteristics and removal efficiencies

ParameterAverage influent

concentration (mg/L)

Removal efficiency (%)

Mean SDBOD5 437 88.2 5.7COD 765.2 84.2 9.6

NH3 - N 1.98 95.6 8.2TN 100.5 67.1 21.3

PO43-- P 0.03 76.5 7.6

TP 0.48 77.8 22.2

3.2 Removal of BOD5 and CODFigure 1 shows the overall removal efficiencies of BOD5

and COD in the mixed-media PRB system. Accordingly, both removal efficiencies have remained around 80%. Both biodegradation and adsorption could be the major treatment mechanisms of organic materials. At the initial stages, the adsorption could be dominant while at the latter stages, biodegradation could be dominant according to the theoretical explanations of both the mechanisms.

3.3 Removal of nutrientsFigure 2 indicates the overall removal efficiencies ofNH3-N, TN, PO3-

4-P and TP. As interpreted by these graphical results, the highest treatment was obtained for NH3-N removal which could most probably be attributed to the NH3 adsorption which may have effectively taken place in the system (Bagchi 2004). TN removal efficiency has dropped in the latter stage, most probably due to the less availability of adsorbent phases in the reactive media. TP and PO3-

4-P removal efficiencies were around 70% with the major contribution from PRB 1, the reactive media of which contained DAS, a well-known phosphorus adsorbent as per the past research.

3.4 Changes of the physical and mechanical properties of reactive mediaThe hydraulic conductivity of the reactive media in both PRBs had a slight reduction which was by 10-3 order of magnitude. The cohesion of the reactive media in PRB 1 and 2 decreased from 3.8 kPa and 0.5 kPa to 3.2 and 0.3 kPa, respectively. The internal friction angle of the reactive media in PRB 1 and 2 increased from 34 and 2.4 degrees to 36 and 2.9 degrees, respectively. Since both shear strength parameters have not decreased, there is no high reduction in shear strength of reactive media in both the reactors during the experimental run.

Figure 1: Removal efficiencies of organic compounds

Figure 2: Removal efficiencies of nutrients

4. CONCLUSIONS

DAS, WQD, WSS, RS, BC and SD in mixed-media PRB system have a high potential to treat BOD5 (88.2+5.7%), COD (84.2+9.6%) and NH3 (95.6+8.2%). The properties of these reactive materials have not been subjected to significant variations due to the interaction of leachate during the 4-month long experimental period. Moreover, not only can these reactive materials be used as PRB reactive media, but also they will effectively be able to replace the expensive filter media in other leachate treatment units. As future recommendations, it is important to do more studies on the long-term performances of these reactive materials in order to identify the limitations of their application.

REFERENCES

-122.



6th January 2017

FIELD-SCALE LOW-COST MIXED-MEDIA PERMEABLE REACTIVE BARRIER (PRB) SYSTEM TO TREAT THE HEAVY METALS OF THE

GROUNDWATER CONTAMINATED BY LANDFILL-LEACHATE

A.M. Disanayaka and W.K.C.N. Dayanthi

ABSTRACT

Permeable Reactive Barrier(PRB) is a potential treatment method for the ground water contaminated by landfill-leachate. This study focused on the applicability of waste or low-cost, locally and readily available materials as reactive media in PRBs to treat heavy metals found in the groundwater contaminated by landfill-leachate. Field scale experimental set-up consisted of two PRB units (1 and 2) filled with reactive materials such as Dewatered Alum Sludge (DAS), Washed Quarry Dust (WQD), Washed Sea Sand (WSS) and Red Soil (RS) in PRB 1 and Saw dust (SD) and Biochar (BC) in PRB 2. During 140- day long experimental run, the removal efficiencies of heavy metals (Cu, Pb, Cd, Mn and Fe) were quite consistent at considerable values. Hence, it can be concluded that the selected PRB treatment system can effectively be used to treat the groundwater contaminated by landfill-leachate.

1. INTRODUCTION

Direct land filling of solid wastes creates nuisance owing to the generation of highly contaminated leachate.Leachate is generated as a result of rainwater receivingboth biological materials and chemical constituents of wastes while percolating through solid wastes (Turanet. al. 2013). Ground and surface water can be potentially contaminated by landfill leachate which contains higher concentrations of heavy metals. Hence it requires proper treatment to control such situations.

The traditional methods used to treat ground water contaminated by landfill-leachate belong to the category of

technologies. In this category, thecontaminated groundwater is pumped up to the ground surface to do treatments, which is not economically effective. The latest technology is the Permeable Reactive Barriers (PRBs). In this method, reactive materials with different chemical capabilities are selected to treat the contaminated water. These reactive materials are placed in the subsurface of the ground as a reactive wall so that the contaminated ground water passes through it, and undergoes treatments in the meanwhile(Powell et. al. 2002).

The principle behind the PRBs is that its reactive media make contaminant degrade into harmless or easily degradable compounds. There are several parameters which should be known for a successful design and implementation of PRB to remediate the ground water. They are contaminant concentrations, the degradation rate with the proposed reactive media, preferential flow paths through the substrate, and plume depth and width. Thisinformation allows designers to determine the contaminants time in the reactive zone andsubsequently the barrier thickness as well as how long and deep it must be (Snow 1999).

In this study, waste/ low cost, locally and readily available reactive materials were used for the reactive media bed of PRBs. The usage of these materials makes the PRBs more

cost-effective. Hence the study is significant as it would introduce a low-cost treatment system for the contaminated groundwater which is a serious issue at the present time. The objectives were to obtain the removal efficiencies of heavy metals and to check the variation of the physical and mechanical properties of reactive materials after contacting with the landfill-leachate.

2. METHODOLOGY

2.1 Preparation of reactive materialsWaste materials, namely BC, SD, WQD, DAS, RLS and WSS were selected as reactive materials based on the past research and availability. Materials of high particle densities, namely WQD, DAS, WSS and RS were selectedfor PRB 1 while the materials with low particle densities, namely BC & SD were selected for PRB 2. The required quantities of these materials were collected from surrounding areas. These samples were then washed and dried well. WQD, DAS, RLS and WSS were sieved before mixing them together. BC was broken in to small pieces to ensure good compaction.

2.2 Field-scale experimental runThe field-scale experimental set-up consisted of a lucimeter to produce leachate which was used as the influent to the PRB treatment system. Leachate from the lysimeter first drained into a receiving tank from which it

was pumped on to an overhead storage tank (1st). Field-scale experimental set-up is shown in the Figure 1. There were two PRB units constructed in such a way that the leachate was passed through the reactive media bed as in a real situation. Both PRB units were with 2m×1m×1m dimensions. There were two compartments with 0.25m length in each PRB unit facilitating the storage of influent and effluent. The two PRB units (PRB 1 and 2) were connected in series and each unit consisted of a mixture of reactive materials. In PRBs, there was a layer of coarse aggregates in between the reactive media bed and the



6th January 2017

effluent compartment. This granular layer preventedwashing out of reactive materials.

Figure 1: Field scale experimental setup

The leachate from the 1st overhead tank was flown into the PRB unit 1 and its effluent was then pumped onto anoverhead tank (2nd) via a temporary storage tank. Next the leachate was flown gravitationally into the influent compartment of the PRB2. Its effluent was recirculated on to the lisymeter via a temporary storage tank. From the 98th

day onwards, the influent was artificially added with the selected heavy metals so that their individual concentrations increased by several folds.

The influent and effluent samples were collected in two-week periods. Heavy metals, namely Cu, Mn, Cd and Pbwere analysed using the atomic absorption spectrometerand Fe was measured by the UV visible spectrophotometer. Both total dissolved solids (TDS) and oxidation reduction potential (ORP) were also analysed.

2.3 Analysis of physical and mechanical properties of reactive materialsPhysical properties such as particle size distribution by sieve analysis test and void volume ratio were obtained. Mechanical properties such as hydraulic conductivity and shear strength were also measured.


Figure 2 shows the overall removal efficiencies for the selected heavy metals. The possible treatment mechanismsthat could cause the treatment are absorption, biological uptake, cation and anion exchange reactions, dilution, filtration and precipitation.

Figure 2: Overall removal efficiencies of heavy metals

The results show that the artificial addition of heavy metals in the influent has not caused any reduction in the removal efficiencies (Figure 2). It implies that the PRB system is still effective in treating even high concentrations of the selected heavy metals.

The specific gravity of the reactive media in both PRBs hasslightly increased with the interaction of leachate while the void volume ratio has slightly decreased. This indicates that during the treatment process, filtration, precipitation and adsorption have taken place. The effective size of the PRB 1 reactive media has decreased due to the interaction with the leachate. It could be due to the attachment of impurities to the soil particles. The effective size of PRB 2 reactive media has decreased. It could be due to the degradation of reactive materials with the progression of the treatment process.

There was a slight reduction in the hydraulic conductivity in both PRB 1 and PRB 2 reactive media. This could be due to the pores being clogged by contaminants andinsoluble gases. Cohesion has slightly increased and friction angle has slightly decreased implying that the shear strength of the reactive media has not considerably changed during the experimental run.

4. CONCLUSIONS

Considering the influent and effluent characteristics of the PRB units, it can be concluded that the PRB system described in the study, has the ability to treat heavy metals of the groundwater contaminated by landfill-leachate to a considerable degree. The study also proved that this treatment system is capable of withstanding higher heavy metal loading rates. There was no significant change in the physical and mechanical properties of the reactive media with the interaction of leachate. This proves that the reactive materials have not degraded during 4-month long period. However further experiments should be conducted to find out the effective life time of the reactive media beds in the PRB system.

REFERENCES

Powell, R.M., Powell, P.D. &Puls, R.W., 2002, Economic Analysis of the Implementation of Permeable Reactive Barriers for Remediation of Contaminated Ground Water, National Risk Management Research Laboratory, Office of Research and Development, U.S. Environmental, Protection Agency, Cincinnati, Ohio 45268.

To: Dr. Jones, N., Civil Engineering Dept., BYU

Turan, N.G., Gumusel, E.B. & Ozgonenel, O., 2013, Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique, The ScientificWorld Journal, pp.1-6.

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0 50 100 150

Cu

Pb

Cd

Mn

FeBefore adding heavy metals

After adding heavy metals



6th January 2017

LABORATORY-SCALE STUDY OF LOW-COST ANAEROBIC FILTERS WITH COMBINED MEDIA TO TREAT THE ORGANIC COMPOUNDS

AND NUTRIENTS FOUND IN LANDFILL-LEACHATE

H. M. L. V. K. Herath, W. K. C. N. Dayanthi and W. M. K. R. T. W. Bandara

ABSTRACT

Anaerobic-filters are quite expensive due to the high-cost of artificial filtration media. Hence introducing alternative low-cost filtration media will make anaerobic-filters more economical. The aim of this study was to investigate the performances of several low-cost/waste materials as filtration media in anaerobic-filters to treat organic compounds and nutrients found in landfill-leachate. The experimental set-up consisted of four down-flow anaerobic-filter columns, two of which were control columns while the others were experimental columns. Control columns were filled with granular activated carbon (GAC) and plastic pall rings (PPR) as single media. Experimental columns were filled with a mixture of dewatered alum sludge (DAS), washed sea sand (WSS), firewood charcoal (FWC), while the other with the same materials as layers. The overall removal efficiencies of layered-media configuration were 73%, 84%, 61%, 55%, 76% and 79% for COD, BOD5, TN, Ammonia-N (NH3-N), TP and Orthophosphate-P (PO4

3- -P), respectively. Mixed-mediaconfiguration gave overall removal efficiencies of 59%, 87%, 49%, 26%, 71% and 78% for COD, BOD5, TN, NH3-N, TP and PO4

3- -P, respectively.

1. INTRODUCTION

Landfill-leachate is generated as a result of percolation of liquid and moisture through waste in landfills. The leachatemay have several contaminants like, COD, organic matter, nitrogenous and phosphorus compounds and heavy metals(Moulin et. al, 2007). It can cause severe damage and pollution to the ecological systems. Therefore landfill-leachate treatment is very essential to protect the entire environment. Anaerobic filters are one of the commonly applied treatment methods. However due to the high cost of the traditional filtration media, anaerobic filters have become an expensive treatment method. An introduction of efficient waste/low-cost, locally and readily available filtration materials as packing media in anaerobic filters will enhance its applicability in landfill-leachate treatment.The aim of this study was to investigate the removal efficiencies of organic and nutrients found in the landfill-leachate using down-flow anaerobic filters filled with waste/low-cost, locally and readily available materials such as DAS, FWC and WSS as filtration media.

2. METHODOLOGY

The experimental set-up (Figure 1) consisted of four laboratory-scale down-flow anaerobic filter columns. PVC pipes with 90 mm diameter were used for 1.5 m high columns with a media height of 1.2 m (Figure 2).

Two columns were used as control columns while others were experimental columns. One experimental column was filled with a mixture of DAS, FWC, WSS, and the other was filled with the same filtration materials as layers. Control units were filled with GAC and PPR individually.The material properties were checked for all the filter columns at the beginning before the experimental run.

Figure 1 : Experimental set-up

Influent was 10% diluted leachate collected from the Galle Municipal Council dumpsite. The influent was stored in an overhead storage tank. The influent flowed from the overhead tank to four columns under the gravity. The influent COD, BOD5,TN and TN concentrations were 313,35,348 and 0.3 mg/L, respectively.

Influent and effluent samples were collected every 5-day period and tested for nutrients and organic matters. The flow rate of the influent was maintained at approximately 0.025 mL/s using control valves. The hydraulic retention time (HRT) and hydraulic loading rate for the filter columns were 2 days and 0.283 m3/m2. d, respectively. The duration of the experimental run was 115 days. At the end the experimental run, final material properties were tested. Overall removal efficiencies were obtained by conducting mass balance analyses.



6th January 2017

Figure 2 : Cross Section of a filter column


Organic matter removal efficiencies were determined in terms of BOD5 and COD. Average COD removal efficiencies for mixed-media and layered-media columnswere (60±9.1) % and (73±7.1) %, respectively. Mixed-media and layered-media columns showed (84±14.2) %and (83±10.9) % for average BOD5 removal efficiencies,respectively(Figure3).

According to Metcalf and Eddy (2003), adsorption could be the dominant treatment mechanism initially. Anaerobic decomposition may also have taken place with the progression of time, thus contributing to the removal ofbiodegradable organic matters to a great extent. The removal of nutrients was evaluated considering nitrogenous compound and phosphorus compounds. The possible treatment mechanisms for nitrogenous removal could be ammonia adsorption and denitrification (Figure 4).Table 1 shows the overall removal efficiencies calculated from the mass balance analyses.

The effective diameter of WSS and DAS slightly decreased while that of FWC slightly increased due to the interaction with leachate. Increment of effective diameter could be explained by the wearing process of the particles. There could also be particle breaking to small pieces during the leachate run. The reduction of effective diameter could happen due to coagulation, flocculation and sedimentation of particles with the leachate interaction.The specific gravity of all the experimental low-cost materials slightly increased with the interaction of leachate.

The hydraulic conductivity also decreased in 103- order of magnitude due to the interaction with the leachate. Thecohesion of DAS and WSS increased slightly, whereas the friction angle of them slightly decreased, implying that there was no much change in the shear strength of those materials subjected to the leachate interaction.

Figure 3 : BOD5 removal efficiencies

Figure 4 : TN removal efficiencies

Table 1: Overall Removal Efficiencies

ParameterOverall Removal Efficiency (%)

Mixed Layered GAC PPR

COD 59 73 88 12BOD5 87 84 79 72

TN 49 61 92 12TP 71 76 - 70

PO43--P 78 79 - 79

NH3-N 26 55 92 16

4. CONCLUSIONS

Overall, the treatment capability of both mixed and layered-media experimental set-ups were on a par with that of expensive GAC, and phenomenal compared to that of traditional PPR. Hence the selected low-cost filtration materials can effectively be used in anaerobic filters to treat nutrients and organic matters found in landfill-leachate. During the experimental run of 115 days, these materials did not undergo significant degradation. However further studies have to be conducted to evaluate the limitations of the selected filtration materials on long run.

REFERENCESMoulin, P., Renou, S., Givaudan, J. G., Poulain, S. and Dirassouyan, F.,

Materials 150(2008), pp. 468-493.

Metcalf & Eddy, 2003, Wastewater Engineering: Treatment & Reuse, 4th ed., Tata McGraw-Hill, Inc.



6th January 2017

LABORATORY-SCALE STUDY OF LOW-COST ANAEROBIC FILTERS WITH COMBINED MEDIA TO TREAT THE HEAVY METALS FOUND IN

LANDFILL-LEACHATE

K.H.S.S. Tharanga, W.K.C.N. Dayanthi and W.M.K.R.T.W. Bandara

ABSTRACT

Though the anaerobic filters are effective in treating landfill-leachate, it is an expensive treatment method mainly due to the expensive filter materials. If low-cost, locally and readily available materials can effectively be utilized as filter media, anaerobic filters can be made suitable for the day-to-day practice in developing countries. The cost can be reduced by using waste/ low-cost and readily available materials as filter media in anaerobic filters. The aim of this study was to find out the removal efficiencies of heavy metals found in the landfill-leachates by using anaerobic filters with firewood charcoal (FWC), washed sea sand (WSS) and dewatered alum sludge (DAS) as filter media. The experimental systemcontained two experimental columns and two control columns. Each of two experimental columns was filled with DAS, FWC and WSS as a mixture and in layers, respectively. Each of two control columns was filled with expensive granular activated carbon (GAC) and plastic pall rings (PPR), a traditional expensive filter material, respectively. During the application of 10 % diluted landfill-leachate within a period of 115 days, the experimental columns showed significant removal efficiencies of around Pb (38%), Cd (48%), Cu (49%) and Mn (58%). The experimental system could also withstand low and high heavy metal loading rates equally.

1. INTRODUCTION

Landfill-leachate generally contains high concentrations of ammonium, organic substances, toxic compounds and heavy metals (Mojiri et.al, 2013). Therefore treatment of the leachate is essential because of the high pollution level.Though anaerobic filters are widely used to treat the landfill-leachate, they are usually expensive as a result of expensive filter media. Hence the aim of this study was to assess the removal efficiencies of the heavy metals found in landfill-leachate by anaerobic filters filled with waste/low-cost, locally and readily available filtermaterials. The study had the following objectives: to determine the treatment efficacies of selected filter media for heavy metals; to compare the treatment efficiencies of the selected filter media with those of the conventional expensive filter media, and to study the variation of the physical and mechanical properties of the selected filtermedia with time.

2. METHODOLOGY

The experimental system was composed of an overhead influent storage tank, four filter columns and effluent tanks. The overhead tank was placed at a higher elevation because the columns were operated in the downward direction under the gravity. First filter column (mixed) was filled with a mixture of FWC, WSS and DAS. Second filter column (Layered) was prepared by packing in layers FWC, DAS and WSS, respectively from the top of the column. Above materials were taken according to 1:1:1 proportion on volume basis. Third and fourth filter columns were filled with GAC and PPR, respectively. Figure 1 shows the schematic diagram of the experimental system.

Figure 1: Schematic diagram of the experimental system

After setting out the experimental system, leakages were checked by circulating the clean water for 2-3 days. Then leachate was applied to each filter column at the least possible flow rate (0.025mL/s) with this system to achieve a hydraulic retention time (HRT) of approximately2 days which is the least effective HRT in anaerobic filters in usual practice. The effluent was collected and analyzed every five -day period. The influent was also analyzed in every 10-day period. After 80 days, the selected heavy metals were artificially added to the influent in order to increase the heavy metals concentrations in the influent by several folds so that they would be comparable with the heavy metal concentrations of the typical raw leachate. Table 1 shows the heavy metal loading rates while Table 2 shows the influent characteristics. At the end of 115 long experimental period, physical and mechanical propertiesof the filter materials were tested. Mass balance analyses were also conducted for each measured parameter to find out the overall removal efficiencies.



6th January 2017

Table 1: Heavy metal loading rates before and after the addition of heavy metals artificially

Loading rate(µg/m2. d)

Before adding heavy metals


Pb 2.5 20.2Cd 0.3 17.9Cu 5.4 187.1Mn 11.7 80.1

Table 2: Influent characteristics

ParameterInfluent Characteristic

Before adding heavy metals


ORP (mV) 372.1 368.7Conductivity

(mS/cm)3.7 4.6

TDS (mg/l) 1.1 1.1Pb (µg/l) 7.2 58.4Cd (µg/l) 0.7 51.8Cu (µg/l) 15.8 541.4Mn (µg/l) 33.9 231.7


Table 3 shows the overall removal efficiencies of each experimental column. Figure 2,3 and 4 depict the variation of the removal efficiencies of Cd, Cu and Mn, respectively.The treatment performances of the mixed and layered experimental columns were comparatively good. Both the columns surpassed the performances of the column with PPR. Their performances lagged behind the column with GAC for measured heavy metals, but not for TDS. The increase of the heavy metal loading rates by several folds did not affect the treatment efficiencies (Figure 2,3 and 4).

With the leachate interaction, the specific gravity of all the experimental materials slightly increased with the decrease of void volume ratio. Further the effective sizes of WSS and DAS slightly decreased while that of FWC slightly increased. The hydraulic conductivity also decreased slightly proving the occurrence of coagulation, flocculation, sedimentation, filtration and adsorption inside the filter media. The shear strength in terms of cohesion and friction angle of these materials did not undergo a notable change.

Figure 2: Cd Removal efficiency with time

Figure 3: Cu Removal efficiency with time

Figure 4: Mn Removal efficiency with time

Table 3: Overall removal efficiencies

Parameter

Overall Removal Efficiencies(%)

TDS 58 54 - 31

Pb 40 37 80 5

Cd 48 54 71 15

Cu 41 45 69 5

Mn 52 57 71 9

4. CONCLUSIONS

Filter materials, namely DAS, WSS and FWC showedreasonable removal efficiencies for heavy metal comparedwith those of the expensive traditional filter materials. Both layered and mixed arrangement of above filter materials can effectively be utilized in anaerobic filters.The filters with these filter materials can withstand both low and high loading rates giving a consistent removal efficiency. The useful application of waste material such as DAS in anaerobic filters is a way of reusing it, which would have otherwise caused issues in disposing.

REFERENCES

Mojiri, A., Aziz, H.A. and Aziz, S.Q., 2013. Trends in physical-chemical methods for landfill leachate treatment. Int J Sci Res Environ Sci, 1, pp.16-25.



6th January 2017

FIELD-SCALE LOW-COST COMBINED-MEDIA ANAEROBIC FILTER SYSTEM FOR THE TREATMENT OF ORGANIC COMPOUNDS AND

NUTRIENTS FOUND IN LANDFILL-LEACHATE

Fernando D.M.T.P and Dayanthi W.K.C.N

ABSTRACT

Anaerobic filter(AF) is a major concern in the treatment of landfill-leachate and one major drawback is the usage of expensive filter media. Hence investigations on the applicability of waste/low-cost materials as efficient filter materials in anaerobic filters are timely and crucial. Thus, the present study was focused on assessing the applicability of waste/low -cost materials as filter media in a field-scale anaerobic filter treatment system in which two AFs (AF1 and AF2) were connected in series. AF1 was filled with dewatered alum sludge (DAS) and washed sea sand (WSS) while AF2 was with saw dust (SD) and bio char (BC). Removal efficiencies of organic compounds and nutrients, and the variation of physical and mechanical properties of filter media subjected to the contacts with leachate were obtained. Average overall treatment efficiencies of BOD5 and COD were 43.6 ± 17.7 % and 54.6 ± 17.0%, respectively. Average treatment efficiencies of TN and TP were 61.5 ± 15% and 68.9 ± 16%, respectively. The physical and mechanical properties of the filter materials did not undergo a significant variation as a result of the interaction with the landfill-leachate.

1. INTRODUCTION

One of the major pollution problems caused by the municipal solid waste (MSW) landfill is the leachate, which is generated as a result of mixing water from precipitation and surface run-off with the MSW. There are many efficient treatment methods to treat leachate, and AF is one such method. One major drawback of the AF is the usage of expensive filter materials. Past research provedthat several waste/low-cost and locally available materials can effectively replace the expensive conventional filtermaterials in AF units. Hence the present study was conducted to find out the treatment performances of an AF system filled with dewatered alum sludge (DAS), washed sea sand (WSS), saw dust (SD) and bio char (BC) as filter materials. The first objective was to find out the removal efficiencies of the organic compounds in terms of BOD5

and COD, and nutrients in terms of ammonia nitrogen(NH3-N), total nitrogen (TN), total phosphorus (TP) and orthophosphate phosphorus (PO4

3- -P). Thesecond objective was to find out the changes in the physical and mechanical properties of the filter materials due to it being interacted with the leachate.

2.METHODOLOGY

2.1 Field-scale experimental unitThe experimental unit consisted of a lisymeter, a receiving tank, two overhead storage tanks, two effluent storage tanks and two AFs (AF1 and AF2) connected in series. The lisymeter generated the leachate which was the influent to the AF treatment system. The leachate was collected in to a receiving tank and then pumped into an overhead storage tank from which it drained onto AF1 under gravity. The effluent of AF1 was collected in a storage tank and was pumped into another overhead storage tank from which it drained onto AF2. The effluent of AF2 was collected temporary in a storage tank before being recirculated on to

the lysimeter. The height and the diameter of the cylindrical anaerobic filter columns were 2 m and 600 mm,respectively. An image and the isometric view of the field-scale experimental unit are shown in Figure 1.

Figure 1: Image and the isometric view of the field-scale experimental unit.

AF1 and AF2 consisted of a bed of coarse aggregates at the bottom in order to collect the drained effluent through the filter bed, and direct toward the effluent port. Figure 2 depicts the packing configurations of AF1 and AF2. In AF1, filter materials with relatively higher particle densities, DAS and WSS, were filled as layers. In AF2, filter materials with relatively lower particle densities, BC and SD, were filled in layers. The layer height of each filter material was 670 mm.



6th January 2017

Figure 2: The filter materials arrangement of AF1 and AF2

2.2 Experimental runThe hydraulic loading rates on to AF1 and AF2 were 0.2 m3/m2.d. Water samples were collected from the influent of the AF1(S1) and the effluent lines of both AF 1 (S2) and AF 2 (S3) once in two weeks throughout 126 days of experiment period (Figure 2). The target wastewater parameters were organic compounds (BOD5 and COD), nitrogenous compounds {Total Nitrogen, Ammonia Nitrogen and Nitrate Nitrogen} and phosphorous compounds {Total Phosphorus and Ortho Phosphates Phosphorus}. Core samples of the filter media bed were collected before applying the influent and at the end of the experimental runin order to find out the variation of the physical and mechanical properties of the filter media with the progression of the treatment.


Lesser BOD5 removal efficiencies were obtained at the initial stage due to the in the attached growth system and then with time, overall removal efficiency of BOD5 in the AF system wasincreased as 43.6±17.7%. COD removal efficiency wascomparatively higher in AF 1 as a result of the adsorption process that could most probably happen in the anaerobic filters. The overall removal efficiency of COD in the AF system was 54.7±17.0%. Treatment of TN and NH3-N are expected in AF units due to the adsorption at the initial stage and the denitrification process at the latter stage9Metcalf & Eddy, 2003). Hence the average overall efficiencies of 61.5±15% and 80.0±12.2% were obtained for TN and NH3-N removal, respectively. The averageremoval efficiencies of TP and in AF 1 were 68.9±16% and 75.4±14.5%, respectively. According to the past research (Razali et al, 2007), DAS is an effective absorbent for phosphorus compounds. With the foregoing result, the present study verified that DAS was a suitable adsorbent for phosphorus compounds in the leachate with the Sri Lankan field conditions.

Table 1 shows the physical and mechanical properties of the filter materials before and after loading the influent on

to the system. The physical properties of the filter media did not undergo much change during the 4 month long experimental run. The slight changes of these materials could be due to the occurrences of treatment mechanisms such as coagulation, flocculation, sedimentation, filtration, adsorption and ion exchange. In addition, a slight wearingoff of the materials could cause these variations in the properties of the filter materials.

Table 1: Physical and mechanical properties of filter materials

Filter media

Porosity Hydraulic conductivity(cm/s)

Initial Final Initial FinalDAS 0.663 0.697 0.0038 0.0036WSS 0.401 0.392 0.0069 0.0065SD 0.756 0.807 0.0038 0.0032

BC 0.541 0.446 0.0041 0.0036

4. CONCLUSIONS

The key feature of this study was the use of waste / low -cost, locally available materials instead of the expensive filter media in a system of two anaerobic filters connected in series to treat the landfill-leachate. The above system responded quite positively in treating BOD5, COD, TN and TP in the landfill-leachate. The study verified that DAS was efficient in removing phosphorus of landfill-leachate, under anaerobic conditions even in field scale. Experiments with alternative filter bed configurations with these materials and different hydraulic conditions applied for longer experimental durations are future recommendations.

5. REFERENCES

th

edition, McGraw-Hill, Inc., New York, chapter 9, pp 888-889,2003.

Effectiveness of a Drinking-Water Treatment Sludge in Removing Different Phosphorus Species from

Separation and purification technology, Vol. 55, No. 03, July, 2007, pp.300-306.



6th January 2017

FIELD-SCALE LOW-COST COMBINED-MEDIA ANAEROBIC FILTER SYSTEM FOR THE TREATMENT OF HEAVY METALS FOUND IN

LANDFILL-LEACHATE

K.G.D. Chamenuka and W.K.C.N. Dayanthi

ABSTRACT

Though anaerobic filters are commonly used for the treatment of landfill-leachate, its application is sometimes limited owing to the expensive filter materials. Therefore, a research on assessing the applicability of waste/low-cost materials in the filter bed of anaerobic filters is significant. In this study, the feasibility of several such materials as anaerobic filter bed media were investigated in a field-scale anaerobic filter system. The anaerobic filter system consisted of two anaerobic filters (AF1 and AF2) connected in series. The filter bed of AF1 contained dewatered alum sludge (DAS) and washed sea sand (WSS) in layers whereas that of AF2 contained saw dust (SD) and bio char(BC). During the experimental period of 120 days, influent and effluent were characterized in terms of total dissolved solids(TDS) and several heavy metals. The mean values of the overall removal efficiencies of the AF system for Cu, Fe, Mn, Pb and Cdwere 85%,79%,74%,72% and 67 %, respectively.

1. INTRODUCTION

Generation of leachate is a severe problem to surface and ground water. Leachate is highly contaminated due to organic compounds, ammonium ions, heavy metals and other contaminants. Therefore, it is a must to treat leachate to mitigate environmental risks and to protect the ecology of water bodies. Anaerobic filters have emerged as a promising technology to treat the landfill-leachate. However, its application has been limited due to the requirement of expensive filter media. If low-cost and waste material can effectively be utilized as filter media in anaerobic filters, it is effective and more advantageous to a developing country like Sri Lanka.

Hence the aim of the study was to assess the treatment potential of heavy metals in landfill-leachate using a system of two anaerobic filters filled with waste/low-cost, locally and readily available materials and connected in series. The objectives of the study were to obtain the removal efficiencies of both heavy metals and TDS found in landfill-leachate, and to investigate the effects of the interaction with the leachate on the physical and mechanical properties of the filter materials.

2. METHODOLOGY

The field-scale experimental set-up (Figure 1) includes a sequence of components connected to each other in the following order: a lisymeter, a receiving tank, an overhead storage tank, an anaerobic filter filled with filter materials of high specific gravity (DAS and WSS), a storage tank, an overhead storage tank, an anaerobic filter filled with filter materials of low specific gravity (SD and BC) and a storage tank. The leachate was generatedinside the lysimeter due to the rain water and recirculated effluent onto the lysimeter. Figure 2 depicts the packing configurations of the filter beds of AF1 and AF2.The leachate was applied on the anaerobic filters in the down-

flow direction. The height of each filter material layerwas 67 cm.

Figure 2: Packing configurations of anaerobic filter beds

After 98 days of the experimental run, the influent was added with the selected heavy metals artificially to increase the heavy metals concentrations in the influent by several folds, aiming at finding the capability of the treatment system to bear high loading rates. Table 1 shows the heavy metal loading rates before and after the addition of heavy metals synthetically.

(a)(b)

Figure 1: Isometric view (a) and the photograph (b) of the experimental set-up



6th January 2017

Wastewater samples were collected from the influent of the AF 1 and the effluents of both AF 1 and AF 2, once in two-week period and analyzed in terms of target wastewater parameters. In addition, the effects on the physical and mechanical properties (porosity and hydraulic conductivity) of filter materials due to the interaction with the leachate were investigated.

Table 1: Heavy metal loading rates before and after the addition of heavy metals artificially

Parameter

Surface loading rate (mg/m2.d)Without adding heavy metals synthetically

After adding heavy metals synthetically

Cu 4.7 35.9

Pb 11.0 2.5

Cd 0.1 3.1

Mn 0.8 9.3

Fe 0.3 27.7

TDS 169.0 266.4


The mean values of the overall removal efficiencies of the AF system for Cu, Fe, Mn, Pb, Cd and TDS were 85%,79%,74%,72%, 67 % and 47 %, respectively. Figure 2, 3 and 4 depict the variation of the removal efficiencies of Cu, Fe and Mn with the progression of the experiment.

Figure 2: Variation of Cu removal efficiency

Figure 3: Variation of Fe removal efficiency

Figure 4: Variation of Mn removal efficiency

TDS removal is mainly caused by adsorption, precipitation, filtration, and decomposition (Metcalf and Eddy, 2003). Presence of coagulants such as alum, iron salts, and organic polymers in DAS can enhance the removal of heavy metals from influent as hydroxide precipitation. The sulphides available in the filter media can react with heavy metal ions and form insoluble precipitates. The precipitates such formed can be separated from the influent by sedimentation or filtration as it flows through sea sand. Adsorption could also contribute to the removal mechanism of heavy metals in filter columns. Further BC and SD contain various organic compounds (lignin, cellulose and hemicellulose) with polyphenolic groups that could bind heavy metalions through different mechanisms. Another cause for the treatment of heavy metals can be due to the ion-exchange reactions. Presences of zeolites, silicate minerals in sea sand has ability to exchange its cations with the heavy metal ions and remove heavy metals from the influent.

There was no significant difference in physical and mechanical properties of filtration materials due to the interaction with leachate.

4. CONCLUSIONS

The anaerobic filter treatment system described in this study had the potential to treat heavy metals in the landfill-leachate with significant efficiencies. There was no significant difference of the physical and mechanical properties of filtration media due to the interactions with leachate. The AF treatment system could withstand high heavy metal loading rates. It is recommended to conduct further experiments with increased packing densities and the increased hydraulic retention times in order to obtain better results. Chemically modified filter materials will also provide higher efficiencies for the removal of heavy metals.

REFERENCESth

edition, McGraw-Hill, Inc., New York, chapter 9, pp 888-889,2003.



6th January 2017

AN ASSESMENT OF IRRIGATION WATER QUALITY IN HAMBANTOTA DISTRICT

M.G.B.S Kumari., G.G.T Chaminda, T.N. Wickremaarchchi and L. Ramanayaka

ABSTRACT

Irrigation water quality of Hambantota district has become a question with prevailing CKDu in some part of the Hambantota. Therefore, this study was carried out to evaluate the irrigation water quality Hambantota District. The water quality parameters such as pH, EC, TDS, salinity, SAR, COD, F- and heavy metals (Cd, As and Pb) in irrigation water and sediments from field canals were analysed in two sampling sessions. It has been recorded that maximum Cd, As and Pb as 0.8 µg/l, 4.4 µg/l and 0.96 µg/l respectively and heavy metal mobility towards sediment is high. Furthermore, with recorded TDS and EC salinity hazard can be seen in Bandagiriya field water and no issue about other parameters. Furthermore, all heavy metals, the values recorded at the second sampling session were higher than the values recorded at the first sampling session. This might be due to the accumulation of agrochemicals such as pesticides in irrigation water. Therefore, it is recommended to extend this study by increasing the sampling points and frequency of sampling.

1. INTRODUCTION

Sri Lanka has two main pattern of agriculture, irrigated and rain fed. Majorly in dry zone their cultivation pattern is depends on the irrigated water supply and this has a great history which runs up to centuries. From the resent past there is an issue about the irrigated water quality of Sri Lanka. Combine with this issue a question was raised whether the rice, vegetables, fruits and food crops that people daily consumed are safe or not for the human health and regular exposure to the irrigated water is harmful or not for the farmers. For an example in dry zone, such as Anuradhapura district there is a serious issue about quality of the irrigation water getting low day by day with the use of agrochemicals and due to agrochemicals heavy metals; arsenic, lead and cadmium are come to the water and this lead to serious health problems among people. Moreover, recently Hambantota district has identified as one of the Chronic Kidney Disease of Unknown etiology (CKDu) prevailing district.

Furthermore, it should consider about the path of the irrigation water from source (river, lake, reservoir and tank) to paddy fields as along this path irrigation water can be cross contaminated. Therefore, evaluation of the irrigation water quality is a national requirement and no past research has been conducted on this matter especiallywithin Southern province. This is collaborative research with Southern province irrigation department to evaluate water quality and heavy metals in irrigation waterHambantota district.

2. METHODOLOGY

collected from 3 main cultivated areas (Bandagiriya (B), Sooriyawewa (S) and Angunukolapalassa (A)) which were identified as issues with irrigation water quality. Samples were taken from a tank, a field canal and a paddy field of each selected area in two sampling sessions. From each tank, field canal and field water

samples were collected and sediment samples were collected from the canal from a depth of 0-20 cm.

Samples were collected using polyethylene bottles which were cleaned using conc.HNO3 and then using distilled water. At the collection point prior to sampling bottles were washed out using samples. Collected samples were filtered, acidified and stored in refrigerator for further analysis of heavy metals using atomic adsorption spectrometer. Before preservation pH, electric conductivity, F-, Ca2+, Mg2+, Na- and COD were measured.

The heavy metal levels and water quality parameters were compared to the maximum permissible levels set for the irrigation water by the Food and Agricultural Organization (FAO) and ambient water quality parameters set by Central Environmental Authority (CEA).


According to the proposed ambient water quality standards for island water in Sri Lanka by CEA water with electric conductivity less than 700 µs/cm is good for irrigation purposes. For the first and second sample collection session minimum and maximum conductivity values were found as 227 µS/cm, 712 µS/cm, 384 µS/cm and 985 µS/cm respectively. For the TDS less than 500 mg/l is considered as good for irrigation purposes and according to FAO guide lines water with TDS greater than 2000 mg/l is considered as not suitable for irrigation. For the first and second sample collection session minimum and maximum TDS values were found as 184 mg/l, 492 mg/l, 427 mg/l and 528 mg/l respectively.

Therefore, it can identify that in some areas of Hambantota district TDS and EC values are exceed the standards and specially at Bandagiriya area both TDS and EC were exceed the standards. It indicates that there is salinity hazard at that area. Even though there is small amount of dissolved salts presence in the irrigation water



6th January 2017

with the supplying water quantity, this small amount can make grate impact. In late season there is less amount of water supply. Therefore, with the ions that presence it shows high EC. These ions originated from dissolution of rocks and soils or agrochemicals that added in various growth stages.

Figure 1 and 2 shows the average heavy metal (Cd and Pb) concentrations for collected irrigation water samples in two sampling sessions.

Figure 1: Cd concentrations of irrigation water samples

Figure 2: Pb concentrations of irrigation water samples

It was noticed that maximum Cd, As and Pb as 0.8 µg/l (Sooriyawewa field water), 4.4 µg/l (Bandagiriya field canal) and 0.96 µg/l (Bandagiriya field canal) respectively. According to the guide lines for irrigation water quality by FAO and figure 1 and figure 2 it can be noticed that Cd and Pb concentration of the collected water samples are below the maximum allowable concentration for irrigation water. However, in the late season stage of paddy growth (second sampling session)both Cd and Pb concentration has increased. For the asthis variation of increment of heavy metal concentration from crop development stage to late season stage can be seen. Therefore, this level is considered as not harmful but long term exposure to this much of level also can cause health problems. Main source of heavy metal to the irrigation water in this areas can be considered as

agrochemicals as sampling points were not much urban areas and are not highly industrialized areas. Furthermore,water for tanks comes from its main sources from a long way and at the way the water contaminated as they pass large no of irrigated areas.

The other parameters that were evaluated were under the maximum permissible limits set by CEA and FAO for irrigation water. Only Bandagiriya tank water exceed the maximum pH value for irrigation water and possible reason can be the hardness of the water at that area as both field water and field canal water pH values much closer to the maximum standard values.

4. CONCLUSIONS

This study shows that the water quality parameters such as Na+, Ca2+, sodium absorption ratio (SAR) and concentrations of heavy metals such as Cd, As and Pb for the irrigation water of selected areas are within the permissible limits. However, pH, TDS and EC slightly exceed the permissible limits for the irrigation water in some collection points. Results showed that maximum Cd, As and Pb as 0.8 µg/l (Sooriyawewa field water), 4.4 µg/l (Bandagiriya field canal) and 0.96 µg/l (Bandagiriya field canal) respectively and heavy metal mobility towards sediment is high. Furthermore, all heavy metals, the values recorded at the second sampling session were higher than the values recorded at the first sampling session. That showed the possible accumulation of agrochemicals such as pesticides has been a reason for increment of heavy metal concentration in irrigation water. Therefore, it is recommended to extend this studyby increasing the sampling points and frequency of sampling.

REFERENCES

Ayers, R.S. & Westcot. D.W., 1985, Water quality for agriculture: FAO irrigation and drainage paper 29, 2nd edn., Food and Agriculture organization of United Nations, Italy. Conley, TG and Galeson, DW 1998, 'Nativity and wealth in mid-nineteenth century cities', Journal of Economic History, vol. 58, no. 2, pp. 468-493.

Gunatilake, S., Samaratunga, S. & Rubasinghe, R., 2014, 'Chronic Kidney Disease (CKD) in Sri Lanka - Current Research Evidence Justification:', Sabaragamuwa University Journal 13(2), pp. 31-58.

Jayasumana, M.A.C.S., Pranagama, P.A., Amarasinghe, M.D., Wijewardane, K.M.R.C., Dahanayake, K.S., Fonseka, S.I., Rajakaruna, K.D.M.L.P., Mahamithawa, A.M.P., Samarasinghe, U.D. & Senanayake, V.K., 2013. 'Possible link of Chronic arsenic toxicity with Chronic Kidney Disease of unknown etiology in Sri Lanka.' Journal of Natural Sciences Research 3(1), pp. 64-73.



6th January 2017

AN ASSESSMENT OF IRRIGATION WATER QUALITY IN GALLE AND MATARA DISTRICTS

Y.B.P. Kahatagahawatte., G.G.T. Chaminda, T.N. Wickramaarachchi and L. Ramanayaka

ABSTRACT

This research was conducted to evaluate the irrigation water quality in Matara and Galle districts. Water samples were collected from irrigation tank/anicut, field canal and field in Pottewela, Makawita and Kitharaliya in Matara district and Dorape in Galle district. Field canal sediment samples were analyzed to evaluate the sediment-water heavy metal interaction. Water samples were analyzed for pH, COD, Total dissolved solids (TDS), Electrical Conductivity (EC), Salinity hazard, Sodium hazard, Fluoride, arsenic, cadmium and lead. It was found that Matara district irrigation water was base and that in Galle district was acidic. COD is comparatively high in all the locations. EC and TDS has increased in second stage in both districts. Na+, Mg2+ and Ca2+ concentrations have reduced in harvesting stage due to the low usage of fertilizers compare to that in initial stage. There is no sodium hazard or salinity hazard in two districts. It was further noticed that Fluoride concentration was also not significant and As, Cd and Pb concentrations were within the permissible level in irrigated water in Galle and Matara.

1. INTRODUCTION

The irrigated water quality in Sri Lanka is of vital importance since paddy cultivation is mainly depend on the irrigation water. The deterioration of water quality effects on human safety, soils and crops and itsmanagement. High quality crops can be produced only by using high-quality irrigation water keeping other inputs optimal (Islam and Shamsad, 2009).

In Sri Lanka there were limited researches conducted to investigate irrigation water quality and there was no any detailed research done for the irrigation water quality for wet zone and intermediate zone like Galle and Matara districts. CKDu is a severe health hazard which can be cause due to the quality of the irrigated water. Currently there is a risk that CKDu is spreading towards the Southern province as well. Besides affecting to the human health, irrigation water quality can affect crop productivity, fertility needs, irrigation system performance and longevity, and the water requirement due to the salinity hazard, Sodium hazard, etc.Consequently, this research was conducted to evaluate theirrigation water quality in Galle and Matara districts.

2. METHODOLOGY

2.1 Study areaStudy area of the research was depicts in Figure 1. Total no of 12 water samples were collected from Pottewela, Makawita and Kitharaliya in Matara district and Dorapein Galle district. Three water samples were taken from each location by representing irrigation tank or anicut, field canal and the field for higher accuracy. One sediment sample was collected from the field canal in each location in order to analyze the heavy metal interaction with water and sediment.

Figure 1: Sampling Locations

2.2 Sampling frequencyTwo set of samples were collected in Yala season at crop development stage and late season stage. Fertilizers were added for crop growth from the crop development stage to the half of mid-season. After that, fertilizer usage is comparatively low. When it comes to late season,pesticides were sprayed to the rice grains and water get polluted by those contaminants. Therefore, it was more conservative to analyze water quality in two different crop growth stages to evaluate the variation of irrigated water quality.

2.3 Analytical parametersSamples were analyzed for pH, EC, TDS, COD, Calcium, Magnesium, Sodium, Fluoride, Arsenic, Cadmium and Lead concentrations at the Environmnetal Engineering Laboratary of Faculty of Engineering, University of Ruhuna.


Irrigation water quality were compared with the standards of Central Environmental Authority (CEA) and Food and Agricultural Organization of United Nations (FAO) and evaluate the variation of irrigated water quality in two stages (initial and later). Matara district irrigation water showed basicity while Galle district water showed acidity



6th January 2017

in both stages while values lie within the standard limits of 8.5 and 6. COD concentrations varied from 22 ~ 95 mg/l and have exceeded the minimum quality waterconcentration in Makawita and Dorape. This may due to the higher population and the urbanization of two districts. According to the obtained results, Fluoride wasnegligible compared to the dry zone. Na+, Ca2+ and Mg2+

concentrations have decreased in the late season stage due to the low usage of fertilizers in that stage (Amarasiri 1972). SAR values were calculated by using Na+, Ca2+

and Mg2+ ion concentrations. Intensity of Sodium hazard was classified as shown in table 1 by evaluating SAR values and electrical conductivity in each locations.

Table 1: Intensity of Sodium hazard

LocationSodium hazard

Crop development stage

Late season stage

Pottewela Moderate Moderate

Makawita Moderate Moderate

Kitharaliya Moderate Moderate

Dorape High Moderate

Salinity hazard was determined by using EC and TDS values which were shown in Figure 2. Recommended maximum values were 700 S/cm and 500 mg/l for EC and TDS respectively.

Figure 2: Variation of EC and TDS concentration

There was a slight increment of EC and TDS in lateseason stage than crop development stage due to the dilution effect. Moreover, both EC and TDS in one location were not exceeded the standard value. Therefore,there was no salinity hazard in Matara and Galle districts in both stages. The average Arsenic, Cadmium, Lead concentrations of irrigation water in any location at two stages varied from 0.4 g/l, 0.1 0.6 g/l and 0.5 3.6 g/l respectively. These concentrations were well below the recommended maximum values by the CEA. But all the above mentioned heavy metal concentrations were increased in late season stage. This can be mainly attributed to the usage of agro chemicals in late season stage.

The heavy metal mobility in irrigated canal water towards the sediments was characterized by the exchange factor of water-sediments (Kouame et al, 2014) which was shown in Table 2. Exchange factor was lower for Pb than As and Cd. That means large portion of lead in water interacted with sediment. As a whole heavy metal concentration in sediment was significantly high in Galle and Matara districts rather than Hambanthota district. This can be due to the heavy rainfall, temperature and other geological features in the ground.

Table 2: Exchange factor of water-sediments

Parameter (x10-3)

As Stage

Cd Stage

Pb Stage

Location 1 2 1 2 1 2

Pottewela 2 2 50 133.3 0.6 0.6

Makawita 4 4.2 25 50 0.6 0.4

Kitharaliya 6 6.1 40 120 1.2 1.2

Dorape 1 1.4 10 10 0.1 0.1

4. CONCLUSIONS

Currently there is no big issue with the irrigation water quality in Matara and Galle districts and can be used for irrigation purpose with the suitable management practices. However, water quality parameters like salinity hazard, sodium hazard and COD has reached its maximum standard limits in Pottewela, Makawita and Dorape. Moreover, heavy metals and electrical conductivity has increased and Na+, Mg2+, Ca2+ has decreased at the late season stage. Therefore, continuous monitoring should be conducted in the area by increasing no of sampling points and especially concerning about the downstream irrigation schemes of the area.

REFERENCES

Water Quality of major Irrigation tanks in Sri Lanka

Islam, M.S. and Bangladesh J. Agril. Res. 34(4), 597-

608.

Kouamé, M.K., Safiatou, C., Boua,C.A., Essetchi, P.K.,of heavy metals concentrations in water and Sediments of the estuary

International Journal of Research In Earth & Environmental Sciences, Vol. 1, No.3.



6th January 2017

EVALUATION OF HEAVY METALS IN SELECTED SOIL AND CROPS AT IRRIGATED AREAS IN GALLE, MATARA AND HAMABANTOTA

S.M.T.L. Samarakoon, G.G.T. Chaminda, T.N. Wickramaarachchi and L. Ramanayake

ABSTRACT

This study was aimed to evaluate soil and crop quality in irrigated lands in southern province. Total 66 soil and paddy crop samples were collected in two stages (initial and later) of paddy growth and analyzed for the total concentrations of Cd, As, Pb and F-. Paddy soil of Galle, Matara are found as acidic while Hambanthota is alkaline because of chemical parameters of the soil profile of underneath. Pb in soil is exceeded in Galle 36.60mg/kg and Matara26.08mg/kg districts (>17) which is having high absorption rate (7mm-10mm per day) while other were below the maximum permissible levels. Average Cd level in rice grains are exceeded WHO recommended level in Hambanthota district (0.391 > 0.2 mg/kg). However, all other rice grains consisted of As, Pb and F- which are less than permissible levels. Furthermore, it was noted that accumulation of heavy metals in Soils and rice grains but apparently no issue inirrigated water quality in Bandagiriya, Agunukolapalassa and Poththewela irrigated areas due to the usage of different type of Agrochemicals in different quantities.

1. INTRODUCTION

Most of the past studies show that use of heavy metal contaminated water for irrigation, over long period of time increases the heavy metal contents of soils and plants above the permissible limitations (Lente et al, 2014). The direct transfer routes of heavy metals to human body are the parts that we take for daily diet such as the rice grain, which may consequently become a threat to human health (Satpathy et al. 2014). However,there are some cases reported within Asian countries like Japan, China, Thailand and India due to pollutant toxicity in irrigated water, soil and rice grains due to use of excess amount of fertilizers (Silva 2014).

Furthermore, the endemic chronic kidney disease has been identified in some of the certain regions for few years back now spreading towards the southern Sri Lanka (Silva 2014). There is a hypothesis that irrigation water can be one of the reason (etiology). Hence the objective of this study was to evaluate soil and crop quality in southern province as a collaborative research with Southern Provincial irrigation department.

2. METHODOLOGY

2.1 Study AreaThe Study area located in Southern province of Sri Lanka. Results of the Department of agriculture Soil survey the soils are classed to three major soil types, Reddish brown earth and low humic gley soils in Hambanthota district, (pH 7.5-6) Reddish brown earth and non-calcic brown soils (6.5-7) in Mathara District andRed yellow podzolic (5.5-6) in Galle district. Soil structure are mostly granular fragments and debris, color is generally brown-red.

2.2 SamplingTotal 66 soil and paddy crops samples were collected in two stages of paddy growth (Crop development stagestage 1 and late stage stage2) in Yala season (May to September) and sampling was carried out at 7 different locations in each districts which are recommended by Irrigation department. See Figure 2.1.

Figure 1: Sampling locations

At each sampling site, three replicate samples were randomly collected. Samples were prepared foranalyzing, following US methods 3456 and 3051a anddigested in a microwave digester (CEM-MARS 6).

2.3 Analytical Procedure and EvaluationThe pH values were measured using pH meter. The extracts were analyzed for F- by iron selective electrode and Cd, As and Pb by atomic absorption spectrometer.Observed values were evaluated with WHO guidelines for paddy crops and Euro community standards (ECS) for paddy soils.



6th January 2017


3.1 Variation of pH valuesConsidering the paddy soil samples of both crop development stage and late stage, values of soil inHambantota district earns the maximum pH values which can be categorized as alkaline soil. (See Figure 2)

Figure 2: observed pH values in paddy soil

The rest of areas are slightly acidic soils which are less than pH value of 6.6. Moreover, the pH values of stage 2 is considerably less than the values of stage 1. The reason for the variation of pH values of stage 1 and stage 2 could be the nitrogen fertilizers. The greater the nitrogen fertilization rate, the greater the soil acidification (Lente et al. 2014).

3.2 Variation of Heavy Metals in Paddy Soil and Paddy CropsIt was noted that at the both stages there were no issue inaverage Lead concentrations values of soils in both stagesin Hambanthota (2.64 mg/kg) district while Mathara(26.08 mg/kg) and Galle (36.60 mg/kg) districts exceeded maximum permissible level Pb in soil (>17 mg/kg ECS)specially in Poththewela area (40.5 mg/kg). The reason can be absorption rate of soil of these areas relatively high (7mm-10mm per day).

Average Cadmium concentration in rice grains in Hambanthota district (0.391mg/kg) is exceeded the maximum permissible level in Cd (>0.2mg/kg WHO) inpaddy grains, especially in Bandagiriya (0.390mg/kg),Agunukolapalassa (0.45mg/kg) and Sooriyawewa(0.34mg/kg). The reason could be the usage of fertilizers,consisted of different concentration of heavy metals (Rosemary et al .2014) and the past studies show that Cd in phosphate fertilizers, are above the maximum permitted levels of Sri Lankan standards (Weerakoon2012).

3.3 Variation of Heavy metals in Rice grains in different Growth stagesRice grain samples in Bandagiriya were collected when the crop met the 85 days after the initial stage. The analysis given as following Table 2.

Table 2: Heavy metals in Rice grains

The results suggested that when rice grain comes to late stage (harvesting stage) accumulation of heavy metal concentration was high.

4. CONCLUSIONS

Results suggested that the field soil of the Hambanthota area is more alkaline and the field soil of the Galle and Matara areas more acidic and the reason depends on the type of the soil and the chemical parameters of the soil profile of underneath. Furthermore, average Cd level in 3 locations in Hambanthota district exceeded the WHO recommended level in rice grains (0.391mg/kg > 0.2mg/kg). It was also noted that accumulation of Pb in paddy soils in Galle (36.60mg/kg >17mg/kg) and Matara (26.08mg/kg> 17 mg/kg) Districts. The reason for most of the cases can be the type of soil and the usage of different type of Agrochemicals in different quantities in different agricultural practices.

Therefore, it is recommended to continues monitoring of soil and crop quality particularly in Hambatota district and should be continued for the other type of land uses as well. Moreover. Bio availability of Cd, when TSP is applied to soils, especially in Bandagiriya, Agunukolapalassa and Sooriyawewa areas need to be determined.

REFERENCES

Journal of Applied Ecology 22(1), 41 58.

Rosemary, F. & Witharana, U.W. A., 2014Metals in Selected Land

Metals Contamination in Paddy Soil, Plants, and Grains (Oryza sativa 4

(2014), 11.

-3.

Weerakoon W.M.W., A. Abeysekara & C. Wijesundara., 2012, to increase rice yields in Sri L ournal of

research and development center Bombuwela.

Research, 25(4),512-522.

Concn (mg/kg) Pb Cd AsStage 1 0.13 0.012 0.04Stage 2 0.29 0.390 0.08



6th January 2017

WATER QUALITY MODELING OF GIN RIVER DOWNSTREAM

W.M.S.D Jayasena, G.G.T. Chaminda and G.H.A.C. Silva

ABSTRACT

This study was aimed to evaluate the water quality of Gin River downstream using QUAL2k water quality (WQ) modeling software. The model was calibrated and validated for dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total Nitrate (TN) and total phosphate (TP) as the key water quality parameters. Calibrated model was used to predict the water quality along the Gin River downstream. Predicted water quality along the river downstream were compared with the available WQ standard (central environment authority, WHO). Calibrated model showed that Lankagama to Batuwangala had a good WQ for drinking with a simple treatment while that for Batuwangala to Keppetiyagoda had average WQ and Keppetiyagoda to Wakwella had minimum WQ. It was also noticed that for washing and bathing, Lankagama to Thawalama except Neluwa has a good WQ while Thawalama to Wakwella had average WQ. As a further improvement of the research, user-friendly software was developed separately which can visualize the model results clearly in any location between the upstream (Lankagama) and downstream (Wakwella). In spite of some limitations, it is recommended to use calibrated QUAL2k model for water future resources management in Gin River downstream.

1. INTRODUCTION

Rivers are the major source of supplying water to human being all around the world. Gin River is the source which supplies water to Galle District which has the total length of 116 km. According to NWS&DB, it has a requirement of applying a better water management system to particularly to Gin River downstream for planning of their future activities in Gin River.

This research was aimed to evaluate water quality using QUAL2kw water quality modeling software. Assessment of water quality of Gin River downstream was done using calibrated QUAL2kw model. The study area was limited to 83 km from Lankagama to Wakwella. (Figure 1)

2. METHODOLOGY

Overview of the research methodology has displayed in the following figure 2.

Figure 2: Overview of the Research Methodology

QUAL2k model requires water quality, hydrological, geometrical, climatic data and kinetic parameters for its calculation. Necessary secondary data were collected from NWS&DB, Irrigation department, surveyingdepartment and Metrological department. For water quality, sampling was done for two different periods in dry days for the calibration and validation. Samples were analyzed in-situ and laboratories of faculty of Engineering and NWS&DB. The study area of the river was divided into 12 reaches for QUAL2k modeling purpose. Within this study area 8 major tributaries were selected as point sources in to the main River. QUAL2k was run for simulation after enter the all necessary data and with the default values. Then by adjusting kinetic parameters such as Re aeration Coefficient (Ka), BOD Oxidation rate (Kdc) and SOD within the allowable limit,

Figure 1: Study Area



6th January 2017

calibration was done. Calibrated model was verified through validation before use for water quality predictions.


Calibration results for DO and BOD5 are shown below Figure 3 and Figure 4 respectively.

Figure 3: Calibrated Graph for DO

Figure 4: Calibrated Graph for BOD5

QUAL2k model was simulated for DO, BOD5, TN, TP,COD, pH and Conductivity. When it calibrates mainly focused on the DO and BOD5 as they are critical water quality parameters.

Predicted River water quality was exceeded the CEAstandards only for DO and COD (Figure 5 and Figure 6).Calibrated model showed that Lankagama to Batuwangala had a good WQ for drinking with a simple treatment while that for Batuwangala to Keppetiyagoda had average WQ and Keppetiyagoda to Wakwella had minimum WQ. It was also noticed that for washing and bathing, Lankagama to Thawalama except Neluwa has a good WQ while Thawalama to Wakwella had average WQ.

4. CONCLUSIONS

Calibrated QUAL2k WQ model was used to predict water quality along the Gin River downstream. Results showedthat for drinking with a simple treatment; Lankagama to Batuwangala has a good quality while Batuwangala to Keppetiyagoda average quality and Keppetiyagoda to Wakwella minimum quality.

When it consider water Quality for washing and bathing; Lankagama to Thawalama except Neluwa has a good quality while Thawalama to Wakwella has average quality.Water Quality for Agriculture is still in the better quality along Gin River downstream. The calibrated QUAL2k model can be effectively used for future water resources management in Gin River downstream.

REFERENCESChaminda, G.G.T. (n.d) 'Assesment of water quality of Kelelani River using qual2k model.

Chapra, S., pelletier, G. and tao, H. (2012) qual2k (a modeling frame work for Simulating river and stream water quality).

Kalburgi, P.B., shivayogimath, C.B. and purandara, B.K. (2010) 'environmental Science and engineering', application of qual2k for water quality modelling of River gataprabha(India), vol. 4, dec.

Wijesiri, I.D., chaminda, G.G.T. and silva, G.H.A. (2015) 'catchment protection of Gin ganga (river) as part of water safety plan (wsp)', 6th international conference on Structural engineering and construction management 2015, Kandy.

Figure 5: DO comparisons with CEA standards

Figure 6: COD comparisons with CEA standards

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