Browsing by Author "Rajapakse, RLHL"

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item: Conference-Extended-Abstract
An over view of water research and water related activities of its stakeholders
(2010) Bamunawala, RMJ; Rajapakse, RLHL; Wijesekera, NTS
Utilization of available water resources in needed to be optimized to meet the necessary capacity enhancements for future demands. In this context, water research plays a vital role, enabling rational decision making at national level. Present situation of said context is rather at poor level, thus leaving numerous concerns at researches. An over view of this situation is judicious for better utilization of effects and resources. Present situation of water research at national level was analyzed based on stakeholder points of view, recognized through a survey of explicit stakeholders. Responds were assessed to identify the efforts by different stakeholders as an aggregate value in a three step scale. The data can be further analyzed with a contribution based weight, so that a comparison can be made to indicate the difference of two indicators. Results of the survey showed, among other things, that the nation's present situation of water research is at a poor state, since 89.7% of the work related to surface water, 96.5% of the work related to climate changes and water and 98.9% of work related to water data and information are appear to being carried out without guidelines.
item: Thesis-Full-text
Analysis of hydroclimatic variability and adequacy of channel flows in an arid zone of Pakistan
(2019) Rashid, S; Rajapakse, RLHL
Water is becoming progressively scarce and effective usage of accessible supplies is of major concern. Globally, 15% ~ 21% of the water allocated for irrigation is lost due to poor management and non-optimized conveyance practices. Pakistan is an agricultural country which hosts one of the world’s largest irrigation networks, Indus Basin Irrigation System (IBIS). The system has been found to operate with an irrigation efficiency of a mere 35% ~ 50% which is abysmally low. It is thus vital to oversee the proper management of this scarce resource while limiting the losses within the system. The selected Hakra canal covers an irrigated area of 2031 km2 with a 92 km of total length and lies in the semi-arid region in Punjab, Pakistan. The aim of the present study is to evaluate the competence of the available irrigation channel flows to meet actual Crop Water Requirement (CWR) and variations in availability with climatic irregularities. For the detailed analysis of hydroclimatic variability and channel flow adequacy, data of daily channel flows and climatic parameters were obtained for the period of 2010~2017 while monthly rainfall data from 1978~2017 was used for long-term trend analysis. The CWR was estimated using CROPWAT 8.0. Observed deficit in supply is provided by groundwater abstraction and was estimated using root zone water balance approach. Mann-Kendall and the Sen's slope tests were used to detect the possible trend and its magnitude. An upstream rainfed basin is selected and used for the verification of observed climatic variations. Trend analysis depicted an increase in annual rainfall from 1978~2017 over the region with the estimated contribution of 13% to irrigation supply. Irrigation supplies are the dominating source of water and highly fluctuating. The seasonal shortfall has shown a variation of 7%~26% in Rabi season and 71% ~78% in Kharif season. Further analysis of data revealed an increasing trend in the maximum and minimum temperature values especially in the months where rainfall has also shown an increase i.e. June and September. The observed climatic variability in the downstream of IBIS is highly reliant on hydrological behaviour of upstream catchments. Four parameter ‘abcd’ lumped model with incorporated snow parameter ‘m’ for icy catchment is used to sensibly screen and verify the reaction of a catchment under the climate change scenario by evaluating the changes in hydrological processes. The better understanding of meteorological and hydrological conditions of the study area helped proper investigation and imitation of the actual situation. Unreliable supply of water in the irrigation system along with variability in climatic factors i.e. precipitation and temperature would disturb the dynamics of hydrological water cycle hampering crop yield. It would elevate the maximum soil moisture deficit that results in crop failure or low yield.
item: Thesis-Abstract
Analysis of the effect of climate change impacts on floods in Kelani river basin, Sri Lanka
(2023) Kulathunga, SPSP; Rajapakse, RLHL
Sri Lanka is highly vulnerable to climate change impacts, including rising land and sea temperatures, changing precipitation patterns, more extreme weather events, and sea-level rise. Notably, climate change has been observed to increase flood frequency, expand flood areas, and intensify flood damages. Previous research in Sri Lanka has mainly focused on rainfall estimation using weather models and examining climate change scenarios. This study aims to improve flood forecasting by analyzing climate change-induced changes in rainfall depths from Intensity-Duration-Frequency (IDF) curves and considering design sea levels. The objective is to gain insights into future flood characteristics, specifically the projected increases in discharges and water levels. The HEC-HMS Hydrological modelling tool was selected for the hydrological modelling of the entire Kelani Basin, while the HEC-RAS model was used for flood modelling in the Lower Kelani Basin which is downstream from Glencourse. HEC-HMS simulating discharges from rainfall inputs that served as boundary conditions for the HEC-RAS model. The verified models are utilized to simulate the 50-year design rainfall dataset lasting 3 days, incorporating published IDF equations from selected rain gauge locations along with the calibrated models. Rainfall depth multipliers of 1.100, 1.122, and 1.140 were applied to the design rainfall dataset for the RCP4.5, RCP6.0, and RCP8.5 projections, respectively. Simulations also considered sea-level rise values of 0.47 m, 0.48 m, and 0.63 m corresponding to the respective climate change projection scenarios. Calibration and validation of the three HEC-HMS models (Kelani Upper, Kelani Middle, and Kelani Lower) and the HEC-RAS Flood model for Lower Kelani (downstream to Glencourse) Basin were successfully calibrated using 2016 May and validated using 2017 May flood event data. The Nash Efficiency values during calibration were 0.79, 0.95, and 0.85 for the Kelani Upper, Kelani Middle, and Kelani Lower models, respectively. During validation, the Nash Efficiency values were 0.87, 0.85, and 0.25, respectively. The calibration Nash Efficiency values for the HEC-RAS model were 0.57, 0.56, and 0.52, and the validation Nash Efficiency values were 0.80, 0.57, and 0.53 for the respective models considering Hanwella Discharges, Hanwella Water Levels and Nagalagama Street Water levels, respectively. The research concluded that, under climate change projections, the Glencourse Peak Discharge is projected to increase by approximately 13.3% to 16.2%. Similarly, at Hanwella, the peak discharge is expected to increase by approximately 6.4% to 8.8%, while the maximum water level is anticipated to rise by approximately 3.1% to 4.2%. Moreover, the maximum water level at Nagalagama Street is likely to experience an increase of around 16.2% to 21.7% under climate change projections.
item: Thesis-Full-text
Analysis of the effect of loss and baseflow methods and catchment scale on performance of HEC-HMS model for Kelani river basin, Sri Lanka
(2018) Ud Din, AM; Rajapakse, RLHL
Hydrological models have become an indispensable tool for efficient water resource management which requires proper estimation of runoff in basins and recognition of appropriate catchment scale. The HEC-HMS (Hydrologic Engineering Center's Hydraulic Modeling System) is a reliable and freely available model. Different loss and baseflow estimation methods available in HEC-HMS have their own pros and cons. Lumping of model parameters over a large area reduces the model performance. In order to find the best loss and baseflow methods for simulating rainfall runoff and to check the possibility of further improvement in model performance by moving toward distributed modeling, Glencorse watershed in Kelani river basin of Sri Lanka was selected as the project area. Daily rainfall data from 2006/2007 to 2008/2009 and 2010/2011 to 2013/2014 for four rainfall stations in Glencorse watershed with daily stream flow data of Glencorse gauging station for the same duration were used for this study. Two different combinations of baseflow and loss methods for simulation of runoff were considered while Clark unit hydrograph method was used as transform model. In the First Option, the Deficit and Constant Method and Recession Method were used as loss and baseflow methods, respectively, while for the Second Option, the Soil Moisture Accounting (SMA) and Linear reservoir methods were used for continuous simulation. Glencorse watershed was divided into 3, 6, 9 and 16 sub divisions to assess the improvement in model performance by shifting toward distributed modelling. Manual calibration approach was used for with Mean Ratio of Absolute Error (MRAE) as the main objective function while another two statistical goodness of fit measures, Nash–Sutcliffe model efficiency coefficient (NASH) and percent error in volume were also checked as an additional observation. Soil Moisture Accounting as loss model and linear reservoir model as baseflow model simulated runoff more efficiently as compared to the other combination. Evaluation showed value of MRAE and NASH for Option 1 were 0.38 and 0.67 for calibration and 0.40 and 0.42 for verification, respectively. Option 2 evaluation showed MRAE and NASH as 0.31 and 0.70 for calibration and 0.34 and 0.57during verification, respectively. Soil Moisture Accounting and Linear Reservoir method used for distributed model showed improvement in model performance up to 6 sub-divisions after which the model performance started declining. Selection of appropriate method among different methods available in HEC-HMS should be in accordance with overall objective of study as it plays an important role in accurate estimation of runoff. Moving toward distributed modelling improves model performance but high resolution data and machine power is required..
item: Thesis-Full-text
Applicability of ABCD water balance model for the assessment of water resources in Kelani basin, Sri Lanka
(2018) Wangchuk, U; Rajapakse, RLHL
Water resources management in watersheds has become increasingly important due to rapid expansion of human settlements while pollution caused by industrial development has led to the part of the available precious water resources unusable for consumption, thus aggravating scarcity of fresh water resources. The impacts are further exacerbated due to global warming. The use of the multi-parameter, distributed hydrologic models for water resources assessment in the local basins are hindered due to scarcity of data and other resources. The lumped parameter rainfall runoff hydrologic models are widely applied to predict watershed response of small watersheds by simulating rainfall runoff generation and thus useful in water resource management in ungauged basins. This study aims at identifying distinct characteristics of one such widely used model, ABCD Water Balance Model, and studying its applicability to a selected sub basin in Kelani River Basin for simulating catchment response in terms of rainfall runoff. The model was subsequently applied to analyze surface and groundwater resources available in the basin, targeting effective and sustainable water resources development and management. The data required for the ABCD water balance model were precipitation, evapotranspiration, average temperature and minimum and maximum temperatures. The model was developed in Excel spread-sheet format focusing on the data period from 1994~2011 in the Kelani basin. For model calibration, precipitation and potential evapotranspiration data during the period 1994 to 2001 were used. The generated model streamflow was compared with observed streamflow at Glencorse station for the same period. For the validation of the model, the precipitation and potential evapotranspiration data in the latter 10-year period were used. For estimating the goodness-of-fit, Nash-Sutcliff efficiency coefficient method was used, while model response to four distinct parameters were assessed based on sensitivity analysis and parameter optimization. The calibrated model has shown that the model is less sensitive to parameters a (0.9) and b (20) while on the other hand, the model was highly sensitive to parameter c (0.68) and d (0.01). It was noted that even with the lesser amount of moisture infiltration from the upper soil zone, the aquifer was able to produce runoff. Hence, it proved that in the wet zone, the propensity of the area to produce runoff was largely independent of rainfall intensity. For the model calibration runs, the correlation or coefficient of determination (R2) between model flow and observed flow was 0.77 with NASH coefficient value of 0.71 and MRAE of 0.27. The model produced a better response to medium flows between 5% ~ 82% with NASH value of 0.78 and good response for high flows below 5% of percent exceedance with acceptable results (NASH = 0.62). The model could not response well for low flows (NASH = 0.45). This model with four parameters could adequately simulate the rainfall runoff response of the selected sub-watershed area in Kelani Basin (at Glencorse). Hence, this lumped parameter model was deemed suitable for streamflow forecasting and water resources assessment in Kelani basin and it can also be applied in areas elsewhere with similar hydrological characteristics.
item: Thesis-Full-text
Application of 'abcd' monthly water balance model for Kalu Ganga and Gin Ganga basins and its application potential for water resources investigation
Gunasekara, DN; Rajapakse, RLHL
Only a limited number of mathematical models have been developed currently in Sri Lanka for water resources management purposes in Kalu and Gin River basins which predominantly provide water for the water supply schemes, irrigation and mini hydropower schemes. The developed models contain either a large number of parameters which increase the model complexity or less number of parameters which increase the amount of details in a parameter thus compromising the simulation accuracy. Based on available case studies, it is sufficient to have three to five parameters to reproduce most of the information in a hydrological record in monthly models for humid regions. Therefore, the “abcd” model which is a monthly lump hydrological model with four parameters was selected for the present research for the investigation of water resources in Kalu and Gin river basins considering Ellagawa and Thawalama sub catchments. For the corresponding watersheds, precipitation, streamflow and evaporation data were collected for the past 30 years and checked by visual comparison, single and double mass curve analysis and annual water balance budget to ensure data reliability, consistency and to identify suitable data periods for model calibration and validation. For Gin River, a 25 years data period was used, while 20 years of data were selected for Kalu River basin. For the model evaluation, Mean Ratio of Absolute Error (MRAE) was used as the objective function while Nash Sutcliff Efficiency coefficient was used for the comparison purposes. In addition, visual inspection of flow simulation with respect to the observed flow, annual water balance and flow duration curves were used for the model performance evaluation. The optimized a, b, c, and d parameters for Thawalama and Ellagawa watersheds are 0.961, 1066, 0.003, 0.813 and 0.998, 1644, 0.013, 0.741, respectively. The MRAE for the calibration of Thawalama and Ellagawa watersheds are 0.21 and 0.26, respectively while obtaining 0.23 and 0.43 for the validation which show satisfactory results. In both watersheds, low flows have been slightly over estimated while very high flows have been underestimated. But a balanced distribution of simulated flow results can be observed in intermediate flows. Comparatively high dispersion of simulation results can be observed in Ellagawa watershed than Thawalama watershed. In case of parameter sensitivity, parameter “a” and “b” are the most sensitive while parameter “d” is having the lowest sensitivity. As model outputs, monthly and annual variation of groundwater discharge, direct runoff, soil moisture storage and groundwater storage of the watersheds were obtained. For the overall discharge of both watersheds, the contribution from groundwater is very low. Therefore, the “abcd” hydrologic model can be recommended to use for streamflow simulations and water resources investigations in monthly temporal resolution for the watersheds which are having similar characteristics with parameter values in the ranges of a (0.961-0.998), b (1066-1644), c (0.003-0.013) and d (0.813-0.741). Key words: ‘abcd’ model, monthly water
item: Conference-Abstract
Application of a process-based, distributed, hydrological and material transport model to assess water resources and pollute transport in malwathu oya basin, sri lanka
Dahanayake, AC; Rajapakse, RLHL
The Water and Energy transfer Processes Model – WEP Model is a distributed, physically based hydrologic model that has been coupled with a material transport component. The model uses meteorological, geographical, hydrological data and, data relevant to anthropogenic activities and water quality simulation processes, as inputs. The model is capable of providing time series values of water and heat balance as well as water quality/material transport results for each grid, as outputs. It has been successfully applied to river basins in Japan, China, Korea and elsewhere to study the water resources management options and pollution caused by dissolved and particulate pollutants including the dispersal of excess Nitrogen and Phosphorous introduced by industrial effluents and chemical fertilizers. The present study incorporates a detailed modelling approach to the Nachchaduwa sub-catchment (598.74 km2) of the Malwathu Oya river basin, to study the water resources management options under the effect of varying rainfall patterns and impending climate change impacts. The model can be extended to study the fate and behaviour of the elements (Nitrogen and Phosphorous) which are added to the waterways as a result of the extensive use of agrochemicals in paddy lands in the upstream catchment area. This paper reviews the current state of the catchment as well as the suitability of applying the proposed model to Sri Lanka to assess this basin, which is seasonally stressed due mainly to over exploitation and water pollution. Apart from the water resources management, a quantitative analysis on the fate of excess amounts of agrochemicals used can also be concluded by studying the dispersal and accumulation behaviour of these elements after they have been added to the crop fields and waterways. The findings of the research study will be useful in identifying possible better water management scenarios and managing the fertilizer/agrochemical usage of this catchment in a more pragmatic manner. This study will set the baseline for commencing and continuing quantitative studies regarding studying the behaviour of the pollutants including their conveyance and spatial and temporal accumulation patterns after they have been added to the waterways, in the North Central Province of Sri Lanka
item: Conference-Full-text
An aquifer characteristic analysis for identifying ground water resource development alternatives in the wet zone of Sri Lanka
(Department of Civil Engineering, University of Moratuwa, 2011) Mayooran, S; Manarathna, SP; Gogulan, N; Rajapakse, RLHL; Ratnayake, N
A proper management system for groundwater resources in the wet zone of Sri Lanka is crucially needed to avoid further exploitation of the resource leading to deterioration of groundwater quality. This research study mainly targets on the assessment of groundwater in the wet zone of Sri Lanka by means of collecting and analysing available groundwater pumping and aquifer characteristic data towards the identification of best management practices. The pumping test data are collected from well locations in Kalutara district and transmissivity values are estimated using both Theis and Cooper Jacob methods. The estimated transmissivity values are used to identify the spatial variation of transmissivity. It is recognized that there is no particular pattern identifiable in the spatial distribution of estimated transmissivity values, however, with the limited data set available. The observation is in line with the fact that there exists significant groundwater anisotropy and heterogeneity even within the same locality or within a single distinct aquifer system. The transmissivity values are further analysed using statistical testing and Krasny's classification system, transforming the data set into log distribution and assigning an index value to identify best management practices for selecting suitable locations for both local water supply schemes and landfills. The places with positive anomalies are very suitable for locating local water supply schemes, and the places with negative anomalies are best to have toxic waste disposal sites or landfills.
item: Thesis-Full-text
Assessment and regionalization of hydrological model parameters in neighboring Pho Chhu and Mo Chhu basins in Bhutan :
(2019) Choden, P; Rajapakse, RLHL
In the cold regions because of harsh climates, there exists no or an inadequate number of monitoring stations. It is indeed a challenge to generate the hydrographs of ungauged basins with scanty information from limited gauged basins. As a result, it has important implications for existing water resources systems as well as for future water resources planning and management since high elevation mountains are all important sources of water to the billions in the lowlands in these climatic regions. The Mo Chhu and Po Chhu catchments in Bhutan are used in this study to assess the regionalization of hydrological model parameters from one catchment to the other neighbouring catchment having similar characteristics using ABCD hydrological model incorporating snowmelt parameter. The Mo Chhu catchment was considered as the gauged catchment and its hydrological parameters were simulated through model calibration and validation, and then transferred to the neighbouring Pho Chhu catchment. For the corresponding watersheds, precipitation, streamflow and temperature daily data were collected for the 11 years from 2006~2017 from the National Centre for Hydrology and Meteorology in Bhutan and checked by visual comparison, single and double mass curve analysis and annual water balance to ensure data reliability, consistency and to identify suitable data periods for model calibration and validation. For the model performance evaluation, Root Mean Square Error (RMSE), Pearson correlation coefficient (r) and Coefficient of determination (R2) were used as the objective functions. The Pearson correlation values for calibration and validation of Mo Chhu basin are 0.84 and 0.88, respectively. When the same model parameters were transferred to Pho Chhu basin, Pearson value for validation was found to be 0.82, indicating good inter-basin parameter transferability and effective model regionalization. Comparing and analyzing the results of ABCD model with and without snow parameter "m", it can be concluded that the model with snow parameter performs better due to proper simulation of the major contribution to basin flow from snowmelt. Approximately, over 52% of the basin flows can be attributed to snowmelt during summer and spring and the incorporation of snow processes in the monthly ABCD model has thus significantly improved model performance in snow-covered areas in Bhutan
item: Conference-Full-text
Assessment of groundwater resource utilization in wet and dry zone aquifers in Sri Lanka and quantifying recharge losses due to urbanization and land-use change
(Department of Civil Engineering, University of Moratuwa, 2016-12) Dilhara, MAAR; Rajapakse, RLHL; Hettiarachchi, MTP
In Sri Lanka, almost all people have either direct or indirect connection to the groundwater resources. Rapid urbanization, deforestation and land use changes have recently incurred adverse impacts on groundwater recharge, leading to groundwater table decline and drying up of wells. A quantitative analysis of groundwater utilization and recharge loss due to urbanization and subsequent land use change was carried out in this research. Attanagaluoya (Dunamale catchment) and Kirindioyabasin (Thanamalwila catchment) were the study areas selected in wet and dry zones, respectively. The 4-parameter “abcd” monthly water balance model was developed to be compatible with the research objectives based on the gathered and simulated stream flow, groundwater and recharge data and the calibrated and validated model was then used in further analyses and quantitative assessment of recharge loss. The results indicate severe impact on groundwater recharge in dry zone in the future. Further, sustainable groundwater management and proper land use policies to overcome groundwater recharge loss in both wet and dry zones were proposed based on scenario analyses.
item: Conference-Abstract
Assessment of traditional water yield forecasting methods based on selected two dry zone basins in Sri Lanka
(Department of Civil Engineering, Faculty of Engineering, University of Moratuwa, 2022-12) Madusanka, WDP; Rajapakse, RLHL; Mallikarachchi, C
The majority of dry zone basins are still ungauged in Sri Lanka, and this has led to uncertainties in the planning and development of water management infrastructure. The Irrigation Guideline of Sri Lanka (IGM) has been widely in use to estimate the basin yield, but even so, there is insufficient evidence to evaluate the accuracy of the estimations under the changing climate conditions. Therefore a need exists for the comparison of available water yield models to close this gap and provide accurate yield estimations. In the current study, the observed streamflow yield data from Kirindi Oya and Maduru Oya basins were used to compare the yield estimates derived from the IGM and HEC-HMS models. Daily and 75% probable rainfall data were considered as the input data for the models and the model results were compared with the observed streamflow data. The evaluation has been carried out by considering the flow hydrographs, annual cumulative error, flow duration curves, runoff coefficients, and the Mean Ratio of Absolute Error (MRAE) value as an indicator. The two dry zone basins Thanamalwila and Padiyathalawa were considered for the study. The periods of comparison of the Thanamalwila and Padiyathalawa watersheds were from 2000-2015 and 2007-2015, respectively. Cumulative water yield error between observed and simulated yield, flow duration curves, and runoff coefficients were the critical elements used to compare simulation results with observations. Comparisons in the two selected basins show that the IGM is still the better model for estimating yield in watersheds in the dry zone, and it was found that rainfall is the dominant factor influencing yield. The comparison of the two models by using the 75% probable rainfall data as indicated in the IGM (Analysis 1) as the input data showed that it is the closest monthly yield evaluation model compared to observed data in the Padiyathalawa and Thanamalwila watersheds and annual differences in estimations were 47.9% and 39.8%, respectively. The HEC-HMS model results ended up with 83.9% and 83.8% annual differences for Padiyathalawa and Thanamalwila watersheds, respectively. In the comparison of the two models by using the actual rainfall data collected from the selected gauging stations (Analysis 2), for the Padiyathalawa watershed, HEC-HMS gives the closest monthly yield estimation with a 34.18% annual streamflow overestimation error. For the Thanamalwila watershed, the IGM model gives the closest monthly yield estimation, and the annual error was 32.2%. The HEC-HMS model gives overestimated values in the Padiyathalawa watershed in Analysis 2 while producing underestimated values in other cases. The IGM produces underestimated values for all cases. Due to the ambiguous variation of HECHMS yield results in each watershed in the same zone, it is recommended that the IGM model be used for yield estimations in the dry zone basins with similar characteristics.
item: Thesis-Full-text
Climate extremes and precipitation trends in Kelani river basin, Sri Lanka and impact on streamflow variability under climate change
Dissanayaka, KDCR; Rajapakse, RLHL
The study region comprises a major river basin in the West of Sri Lanka namely Kelani River basin. The hydrological regime of this river differs significantly from that of the others because the basin features great geographical and climatic diversities over its latitudinal and longitudinal extent. Kelani River is the second largest river in Sri Lanka that originates from the central hills and flows to the west coast through Colombo city. The river basin is bound by northern latitudes from 6°47' to 7°05' and eastern longitudes from 79°52' to 80°13'. The river originates approximately 2,250 m above mean sea level and passes 192 km to reach the Indian Ocean. The river basin experiences an annual average rainfall of about 3,450 mm corresponding to a volume of about 7,860 MCM out of 43% discharges into the sea. However, changes in precipitation and temperature due to the climate change can cause more frequent extremes with extended droughts and floods with further impact to the reservoir storage resulting a significant threat to water resources. Therefore, the present study focuses on climate extremes with reference to the past, present and future behavior of rainfall, temperature and streamflow at watershed scale to identify climate change impact on the spatial and temporal variations of streamflow in the Kelani River Basin. For this research, basin-wide future hydrology is simulated by using downscaled temperature and precipitation outputs according to RCP Scenarios of the Canadian Earth System Model - version 2 (CanESM2), Statistical Downscaling Model (SDSM) and the Hydrologic Engineering Centre’s Hydrologic Modeling System (HEC-HMS). The case study further evaluates the long-term behaviour and trends of the climate extremes based on the observed historical temperature and precipitation data. The findings suggest that the temperature and precipitation extremes are on the rise while the annual average precipitation in the river basin is declining. It is also predicted with the application of statistical downscaling that temperature may rise annually for representative concentration pathways of RCP2.6, RCP4.5 and RCP8.5. The mean explained variance are 67, 86 and 13% for temperature maximum, temperature minimum and precipitation respectively, for calibration with NCEP predictors. During calibration, the R2 value of the monthly and seasonal sub-model of RCP 2.6, RCP 4.5 and RCP 8.5 scenarios are lies between 80.1% and 99.4% for both maximum and minimum temperature and 50 to 90% for precipitation. During validation, R2 value for both monthly seasonal sub-model followed by bias correction was between 76.9% and 99.2% for both maximum and minimum temperature, and 55% to 95.2% for precipitation. A detailed modelling approach is incorporated to Hanwella sub-watershed (1799.67 km2) of the Kelani River basin, to study the subsequent water resource management options with the varying streamflow of the Kelani River basin under the effect of the future (2020’s, 2050’s and 2080’s) rainfall and temperature as impending climate change impacts for RCP scenarios. The paper reviews the current state of the catchment as well as the suitability of applying the GCM’s rather than RCM’s to Sri Lanka to assess this river basin, according to monthly, seasonal and annual variations of the climatology. Apart from the water resources management, a quantitative analysis was conduct to assess the change in the amount of surface water within the selected river basin as a function of the expected variations in precipitation and temperature. This study will set the baseline for commencing and continuing quantitative studies incorporating the behaviour of the basin-wide climatology and streamflow variability with the use of general circulation models
item: Conference-Abstract
Combining water and environmental footprint methods for life cycle assessment of run of the river type mini/micro hydropower generation
(Department of Civil Engineering, University of Moratuwa, 2021-11) Pihillanda, VSB; Rajapakse, RLHL; Hettiarachchi, P
Hydropower is popular as one of the most environmentally friendly renewable energy sources. However, with the expansion of knowledge about footprint methods, it has been identified that there are considerable carbon, water and ecological footprints in hydropower schemes that are not adequately recognized based on commonly available tools and methods for overall impact assessment. Among these tools which assess the environmental impact quantitatively, the water footprint methods assess the water consumption (alias water loss) per unit of power produced at a hydropower plant. There are three methods of assessing the water footprint of hydropower plants namely, Gross Evaporation Method (WF1), Net Evaporation Method (WF2) and Net Water Balance Method (WF3). All three methods have been developed and used for hydropower plants connected to major reservoirs but have not been used for run-of-river (ROR) type mini/micro hydropower plants. Identifying this research gap, along with the fact that the Ceylon Electricity Board has planned to increase the mini/micro hydropower production in their Long-Term Generation Plan, this study has investigated the ability to apply the existing water footprint methods to ROR type mini/micro hydropower plants. Furthermore, their ability to relate to the Sri Lankan context as a viable tool in mini/micro hydropower plant designing phase is also investigated. The existing WF methods were applied to three selected mini hydropower plants in Seethawaka Ganga Sub-basin in the Kelani River Basin. To conduct the application, the daily streamflows at the weir locations were derived using a calibrated HEC-HMS model and available meteorological data. Then a correlation was synthesized between the daily streamflow at the weir and daily energy production of the mini hydropower plants based on the characteristics of the installed turbine and generator capacities. Simultaneously, the water losses were estimated using meteorological data and plant specific data which were extracted from project documents and using GIS tools. With the derived energy generation and estimated water losses, the daily, monthly, and annual WFs were calculated and their ability to reflect the ROR nature, the scale of the plant (i.e., mini/micro scale) and the Sri Lankan context were investigated. Based on the findings of the detailed analysis, it was concluded that the most appropriate water footprint method that reflects above-mentioned characteristics is the Mean Monthly Water Footprint of Gross Evaporation Method. Furthermore, a quantitative as well as a qualitative sensitivity analysis was carried out to identify all possible variations that may affect the outcome and the ability to integrate water footprint into ecological footprint evaluation is discussed. The study findings will be useful in the proper evaluation of overall impacts and for decision making in the implementation of future mini/micro hydropower generation plans.
item: Thesis-Full-text
Continuous hydrological modelling using soil moisture accounting for water resources assessment in Kelani river basin, Sri Lanka
(2018) Nasimi, MN; Rajapakse, RLHL
The assessment of water resources in a river basin for fulfilling various needs in the present and future requires a proper estimation of water availability. This is possible through hydrological modelling. The Kelani river basin in Sri Lanka experiences water stress under the current water uses, development, and urbanization effects. It requires a continuous hydrological model for the assessment of its water resources, focusing on impending climate change impacts. Continuous hydrological models, unlike event-based models, simulate longer periods that include both dry and wet conditions. Soil moisture accounting (SMA) model in the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) is chosen to simulate the streamflow. However, the SMA loss model requires precise and updated soil and land use data for parameter estimation, which is not available for the study area. In addition, the lumped nature of the model comparing to distributed models is also in question. This research discusses the development, parametrization and calibration methodologies for the 14 parameters of the HEC-HMS model with the SMA algorithm by considering a catchment divided into several sub-catchments. This division is based on the maximum drainage area method to improve the model accuracy in a scarce soil data situation. The SMA loss model requires 14 parameters to be set. Among these, the impervious percentage is calculated from a land use map; the groundwater 1 and 2 storage as well as the groundwater 1 and 2 coefficients are calculated through the streamflow recession analysis. The maximum infiltration, soil storage, tension storage, and soil percolation rate are calculated from the similar studies; and the groundwater 1 and 2 percolation with four initial parameters are calculated only through a calibration procedure. The model is calibrated using daily data from 2007 to 2012 and validated from 2012 to 2017. The mean ratio of absolute error (MRAE) is used as a primary objective function. The coefficient of determination (R2), percent volume error (PVE), and Nash-Sutcliffe efficiency (NSE) are also used to compare and evaluate the model performance. The results indicate that the performance of the rainfall-runoff model significantly improves when the basin is subdivided into three to eight sub-catchments and the optimum result is found with the five sub-catchments. For the calibration period, the performance of the model is adequate with a R2 of 0.83, a NSE of 0.82, a PVE of 5.3%, and a MRAE = of 0.38. Similarly, adequate results are also retrieved for the validation period, with a R2 of 0.81, a NSE of 0.80, a PVE of 13.1%, and a MRAE of 0.36. The results of the statistical analysis indicate that the simulated and observed flows are reasonably well correlated. The parameter analysis shows that the soil percolation and tension zone storage rates are the most sensitive and second storage of ground water (GW2) is the least sensitive parameters. Furthermore, for the Kelani river basin up to the Hanwella catchment, the simple surface, simple canopy, ModClark, recession and Muskingum methods are found to be the most suitable methods alongside the SMA model. The model performance can potentially be improved through further calibration using hourly climatic input data instead of daily data and with using multiple gauging stations instead of single gauge station. In the future, the validated HEC-HMS model can be employed with seasonal climate forecasts under long-range land use and climate projections. Besides, radarbased precipitation data can be used to represent the climatic variability on a grid-based scale.
item: Conference-Full-text
Daily and monthly lumped parameter hydrologic models for analysis of small watersheds in Sri Lanka
(2018-05) Perera, GMCA; Rajapakse, RLHL; Chathuranga, D
Water resource management has become vital with the increase of demand for fresh water and modelling of ungauged basins under the conditions of data scarcity has always been a challenge. The two-parameter (2-P) and fourparameter (4-P) models have been used in this study to simulate the response of two river basins Maha Oya and Kelani River in Sri Lanka in an attempt to investigate the potential of these lumped parameter models. Both daily and monthly rainfall and streamflow data sets have been used to evaluate the model performance. Two key performance indices, Pearson Correlation Coefficient (PC) and Mean Relative Error (MRE) have been used as objective functions to compare goodness of fit of the observed and simulated streamflow. The two models were calibrated and validated for 2011~2014 and 2008~2010 periods, respectively. Based on the comparison of the results, it was found that the 4-P model provides a greater accuracy for the evaluation of the streamflow of the two selected river basins with a PC > 0.75 in both basins with both daily and monthly data. Even the 2-P model provided results with PC > 0.70 when used with monthly and daily data and within the acceptable range.
item: Thesis-Full-text
The Effect of antecedent moisture condition on HEC-HMS model performance : a case study in Kelani river basin, Sri Lanka
(2018) Dorji, KY; Rajapakse, RLHL
Among all observed natural hazards, water-related disasters are the most frequent and they pose major threats to people and while hindering socio-economic development. Flood forecasting is one the most challenging and difficult problems in hydrology. However, it is also one of the most important problems in hydrology due to its critical contribution in reducing economic damages and loss of life losses. In many regions of the world, flood forecasting is one among the few feasible options to manage floods. In Soil Conservation Service Curve Number (SCS-CN) method, Antecedent Moisture Condition (AMC) of the soil plays a very consequential role because the curve number varies according to the soil, land cover and soil moisture content, and that is considered while estimating runoff depth. Soil water represents only a minimal part of the water on our planet, but it is certainly one of the most imperative factors when it comes to flood forecasting since soil saturation directly affects runoff generation. Kelani river basin was selected for the study because of the nature of the basin with respect to the vulnerability to floods and availability of data at finer resolution. Ten years of daily rainfall, streamflow and evaporation data from 2007 to 2017 water year were used for the study. Events separation was carried out using Minimum Inter-event Time (MIT) method. There are 38 selected events, out of which the first half events were used for model calibration and the second half events were used for model verification. The univariate gradient search method was applied to optimize the parameters by minimizing the Sum of Absolute Residual Error (SARE) objective function. Manual calibration was carried out using Nash-Sutcliffe model efficiency coefficient (NASH) as an objective function for comparison. The average NASH value in model calibration and validation were 0.63 and 0.62 while the lowest Root Mean Square Error (RMSE) obtained in model calibration and validation were 1.31 and 2.82 respectively. The closer the model efficiency is to NASH value of 1, the more accurate the model is. The calibration data set performed better than the model verification data set as depicted by lower RMSE value. Random events were selected to incorporate different soil moisture conditions to check the model performances. It has been observed that the events that falls in Maha season performs better when AMC III is applied whereas the model performance neither improves nor deteriorate when the events falls in Yala season. The present work reveals and confirms that while conducting event rainfall-runoff modelling for flood management using HEC-HMS, AMC should be considered in order to improve the model efficiency and performance. The study findings are applicable to other hydrologically similar basins in the same region or elsewhere and the findings from model sensitivity analysis are useful for fine tuning model performance and opting for better flood management strategies.
item: Conference-Abstract
Effect of climate change on monthly pond storage variation - a case study in Jaffna, Sri Lanka
(2019) Thilakarathne, JASI; Rajapakse, RLHL; Wijayaratna, TMN
Due to various anthropogenic interventions, the inherent natural function of water has been disturbed and distorted. Proper water management is vital to reduce flood damages and also to increase water availability in the dry season. The Jaffna peninsula in the northernmost part of Sri Lanka makes use of its existing pond systems to have an enhanced water functionality. However, due to the climate change, the rainfall pattern in the region has changed and currently, the peninsula is experiencing water scarcity especially during the dry period (January~September) while frequent flash floods occur in the wet season (October~January). The study attempts to determine the effect of rainfall pattern variability on pond water availability. Moreover, the study illustrates the variation of pond water availability using the Average Storage Index (ASI) during the study period of 16 years. Taking the monthly precipitation data for the period of 2002~2017, the pond storage variation of Paalkulam pond in the Jaffna Municipal Council (JMC) area was modelled. Monthly rainfall data, evaporation data, pond physical data and catchment data were used for this analysis. Pond simulations were carried out using the HEC-ResSim computer application. Whit the monthly rainfall data, the model simulation results show that the pond storage variation is becoming even critical during the dry period. The ASIs for 2002 are 0.681 and 0.996 for the dry period and wet period, respectively. However, for the year 2017, these indices change to 0.497 and 1.000. Study results show that due to the changes in rainfall pattern in the JMC area, the pond water availability is decreasing in the dry period. Furthermore, when looking at the yearly variation of ASI of Paalkulam pond, it clearly shows that the water availability is strongly driven by the precipitation to the peninsula. Therefore, for more adverse rainfall patterns, the water availability in the region would be much more serious. When the study results are taken into considerations, it can be concluded that the ASI of Jaffna ponds is getting decreased in the dry period due to the change of rainfall pattern which shows a noticeable reduction of water availability and rehabilitation and proper maintenance of pond storage play a critical role in addressing water scarcity issues.
item: Conference-Abstract
Effect of different methods for spatial interpolation of rainfall data for hydrological modeling in dry zone Mi Oya Basin, Sri Lanka
Karunarathne, HMADSS; Rajapakse, RLHL
For water resource management in ungauged basins, rainfall runoff hydrological modelling is applied to predict or estimate the response of watershed or drainage basin to rainfall by simulating the rainfall runoff generation. As climate data, mainly rainfall or precipitation is the given input to the model, and thus even a minor variability in the rainfall dataset would cause negative effects in the model causing the predictions and estimations in the hydrological system to infer less accurate results. Therefore, in the present study, the spatial variability of rainfall is taken into account via different spatial interpolation and computational methods and their effect is reviewed. The basin is selected as to study the variation of accuracy of simulation with different spatial interpolation methods through a model which takes precipitation as input and produces streamflow as output. The model is calibrated for a four-year period. Further, the validation is assessed for consecutive four-year period using the calibrated parameter values. Subsequently, the calibrated and validated model with the selected most suitable spatial interpolation method can be used in watersheds with similar catchment characteristics, and in our study, IDW method considerably outperforms other methods for rainfall runoff simulation at daily time-steps.
item: Thesis-Full-text
Effect of watershed subdivision and antecedent moisture condition on HEC-HMS model performance in the Maha Oya basin, Sri Lanka
Kamran, M; Rajapakse, RLHL
Effect of Watershed Subdivision and Antecedent Moisture Condition on HEC-HMS Model Performance in the Maha Oya Basin, Sri Lanka Rainfall-Runoff models such as Hydrologic Modeling System (HEC-HMS) are used for predicting the hydrologic response of watersheds. Due to the effect of discretization, the model accuracy increases with number and watershed sub-divisions and the inferred level of soil saturation in the model. Therefore, an important issue that must be addressed by all users of these models is the determining of an appropriate level of watershed subdivision and Antecedent Moisture Condition (AMC) for runoff simulation. The present research study was conducted in an attempt to find appropriate answers for the above two modelling issues. As a case study, the Badalgama watershed is selected as study area in the Maha Oya Basin in Sri Lanka. Spatial extent of Badalgama watershed is 1272 km2 with an upstream river length of 96 km. Four rainfall stations and one river gauge station are selected in Badalgama watershed. Daily rainfall and streamflow data were used for calibration period from 2005 ~ 2008 and for validation period from 2010 ~ 2013. River basin was divided into 3, 6, 9, and 16 number of subdivisions based on critical threshold area method using ArcGIS 10.5. Nash–Sutcliffe (NASH) and Mean Ratio of Absolute Error (MRAE) objective functions were selected as the evaluation criteria of the model. HEC-HMS modeling was carried out for different subdivisions and varying AMC conditions. The result shows that with MRAE objective function, the accuracy of the model increased by 4.5% up to six subdivisions and with NASH, the accuracy increased by 4.2% with respect to the same lumped model. The accuracy of the model found to decrease for the model with six subdivisions to sixteen sub-divisions. The accuracy of the model with Antecedent Moisture Condition with AMC-III was found to increase by 12.04% as compared to AMC-II. With the above findings, it is concluded that subdivision of watershed for modeling results in no more than modest improvements in prediction of low flow and medium flow simulation. As the result shows in the AMC analysis AMC-III produced improved accuracy of 12.04% in calibration period and 6.60% for validation period as compared to AMC-II. The event-wise estimation of AMC led to further increase in model accuracy. In this research, the recession method was considered for the base flow simulation which led to a mass balance error exceeding 20%. Therefore, it is recommended apply linear reservoir method as base flow simulation method to further improve the modelling accuracy by conserving the water balance.
item: Conference-Abstract
Enhancing streamflow prediction in Sri Lankan River Basins using AI models: A comparative study of wet and dry zones
(Department of Civil Engineering, University of Moratuwa, 2024) Karunarathna, SMSD; Rajapakse, RLHL; Pasindu, HR; Damruwan, H; Weerasinghe, P; Fernando, L; Rajapakse, C
Artificial Intelligence (AI) techniques have gained significant attention in recent years for their application in various engineering domains, including hydrology. Groundwater modelling, streamflow prediction, precipitation forecasting, temperature forecasting, and time series generation for rainfall are some of the hydrological applications that have benefited from AI techniques. In Sri Lanka, water resource management is challenging due to the country's geographical characteristics, seasonal rainfall patterns, and growing water demands. Traditional methods used in water resource management have limitations and rely on complex parameters, which often result in less accurate predictions of rainfall-runoff, flood events, and drought conditions, impeding effective water resource management. To enhance water resource management practices in Sri Lankan River basins, AI methodologies were integrated into hydrological modelling. Two river basins were chosen as representatives of the wet and dry zones in Sri Lanka: the Ellagawa sub-basin from the Kalu River basin for the wet zone, and the Thanamalwila sub-basin from Kirindi Oya basin for the dry zone, covering the period from October 1, 2000, to September 30, 2011. The pivotal recurrent neural network (RNN) architectures such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) are highly effective for modelling time series data, especially when it comes to streamflow prediction. These models are excellent at capturing temporal dependencies, which is significant for streamflow as it depends on previous data and weather. In this study, both the physically-based semi-distributed HEC-HMS hydrological model and AI models such as RNN-LSTM and RNN-GRU were applied to evaluate their predictive capabilities in streamflow forecasting. The performance of these models was assessed using objective criteria including Nash-Sutcliffe Efficiency (NSE), Mean Ratio of Absolute Error (MRAE), and the coefficient of determination (R²). The observed and predicted streamflow hydrographs and flow duration curves (FDC) were generated to evaluate model goodness of fit and time series graphical comparability. The study findings indicate that the LSTM model is superior to both the GRU and HEC-HMS models in predicting streamflow, with an MRAE of 0.42 and NASH of 0.82 for the LSTM model in wet zone river basins. The LSTM algorithm used the best values of R2, which were 0.88 and 0.87 for the testing and training phases, respectively. The proposed model may be used to develop other basins in the wet zone. However, for the Thanamalwila sub-basin, the results of both AI and physical-based models were poor, likely due to inaccurate input features and inherent mismatches between rainfall and streamflow. Better input features are essentially required to improve the model training and simulation process. Therefore, the integration of AI techniques presents an opportunity for Sri Lanka to overcome existing limitations in hydrological modelling and enhance its resilience to water-related challenges. By embracing innovative approaches and leveraging available data, Sri Lanka can strengthen its capacity for water resource management and adaptation to climate change impacts, ultimately fostering sustainable development and resilience in the face of evolving environmental conditions.