Evaluation of Climate Elasticity of Runoff based on Observed Rainfall, Streamflow and Simulated Future Streamflow using SWAT Model in Kelani Ganga Basin

Kelani Ganga basin is the 7th largest watershed in Sri Lanka, spanning over 2,292 km(2) and annually discharging 4,225 MCM flow to the sea. 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, the present study was undertaken to evaluate the Climate Elasticity of Runoff based on observed rainfall, streamflow data and simulated future streamflow using the SWAT Model in the Kelani Ganga basin, targeting sustainable management of basin water resources in future. The runoff elasticity (epsilon) is assessed by two methods for the present and 2040 scenarios. The 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 per Innovative Trend Analysis (ITA) for the period of 1980 to 2016. Mass balance performance error (Er), Nash-Sutcliffe Efficiency (NSE) and Coefficient of determination (R-2) are used as multi-objective functions and 8.90%, 0.65, 0.72 and 9.10%, 0.69, 0.69 are obtained for the above objective functions in SWAT model for the calibration and validation periods of 1970 to 1980 and 1982 to 1992, respectively. A 1 degrees C of temperature increase causes a 6.9% and 7.4% runoff decrease for the current scenario and it causes 0.4% increase and 1.5% decrease of runoff for Future Pessimistic Climate change Scenario as evaluated by the methods proposed by Zheng et al. [24] and Sankarasubramanian et al. [22], respectively. A 1% of rainfall increase causes a runoff increase of 0.002% and 0.370% for the current scenario and a runoff increase of 0.005% and 0.360% for 2040 as evaluated by the two methods, respectively. It is recommended to further analyse the water allocation model for better results with practical implementations by considering the identified trend after 1995 in future research for better planning and management of water resources in future.