Evaluation of climate elasticity of runoff based on observed rainfall/streamflow data and simulated future streamflow using swat model in Kelani ganga basin

Abstract

Kelani Ganga basin is the 7th largest watershed in Sri Lanka, spanning over 2,292 km2, with a length of 145 km, and annually discharging 4,225 MCM flow to the sea. The annual average rainfall varies from 2000 mm to 5700 mm while annual average temperature (Tavg) varies from 28 ⁰C to 30 ⁰C in the basin. The basin currently hosts over 19 % of the country’s population and is the primary source of drinking water to over 4 million people living in Greater Colombo. Hence, it is vital to investigate the potential effects of climate change on streamflow in the basin. The present study was undertaken to evaluate Climate Elasticity of runoff based on observed rainfall/ streamflow data and simulated future streamflow using SWAT Model in Kelani Ganga basin, targeting sustainable management of basin water resources in future. Hydro-meteorological data were collected for 41 rainfall, 10 temperature, and 3 streamflow gauging stations in and around the basin. The initial data checking was carried out and gap filling was performed based on regression analysis for streamflow and Inverse Distance Weighting (IDW) for rainfall and temperature. Root-mean-squared errors (RMSE) were calculated for each month and each percentile to determine the most suitable combination of Alpha of both rainfall and temperature. The α = 1 for rainfall and α = 5 for temperature were obtained as optimum parameters for the IDW. Additional statistical tests were carried out to identify trends on Climate change using Innovative Trend Analysis (ITA), Mann-Kendall and Sen’s Slope tests for rainfall, temperature and streamflow. Decadal averages and deviation from Mean were plotted for all rainfall stations in and around the basin. SWAT model was built to simulate streamflow for the selected duration of 1960 to 2016 and the model was calibrated and validated for the key hydrometric station at Glencourse. The runoff elasticity (ε) is assessed by two methods based on the impact assessment of climate change only and impacts of land surface and climate change, respectively for current and Future Pessimistic Climate Change Scenario for 2040 after incorporating the projected landuse for 2040. Annual average flow is reduced by 14% from the period of 1960-2016 to the period of 1980- 2016 at Glencourse. The runoff to rainfall ratio at Glencourse and Hanwella for the period of 1980 to 2016 are 53% and 55%, respectively. Among 41 rainfall stations, 20 exhibit positive trends, 17 show the negative trends for annual rainfall totals for the all three tests of ITA, Sen’s Slope and Mann-Kendall tests. The all selected three hydrometric gauging stations exhibit significant downward trends for the period of 1980 to 2016. An 80 % of the rain gauges in the middle and Upper basin, show significant decreasing trends for high to low rainfall totals for Yala season as ITA analysis for the period of 1980 to 2016. The model calibration and validation were completed at Glencourse for the period 1970 to 1980 and 1982 to 1992, respectively. Mass balance performance Error (Er), Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2) are used as multi-objective functions and 8.90 %, 0.65, 0.72 and 9.10 %, 0.69, 0.69 are obtained, respectively for the calibration and validation periods. 1 ⁰C of temperature increase causes 6.9 % and 7.4 % runoff decrease for current scenario and 0.4 % increase and 1.5 % decrease of runoff for Future Pessimistic Climate Change Scenario as evaluated by two methods, respectively. 1% of rainfall increase causes runoff increase of 0.002 % and 0.370 % for current scenario and runoff increase of 0.005 % and 0.360 % for 2040 as evaluated by two methods, respectively. The flow didn’t show significant increase for 2040 with projected landuse at Glencourse gauging station. As the water extraction quantity is significantly high for the districts, namely Colombo and Gampaha, with the highest residential densities with a majority (78%) are living in Kelani Ganga basin, it is recommended to further analyse the water allocation model for better results with practical implementations by considering identified trend after 1995 in future researches for planning and management of water resources in future.