Metrics Assessment and Streamflow Modeling under Changing Climate in a Data-Scarce Heterogeneous Region

Abstract

Due to many uncertainties in hydrological data and modeling, the findings are frequently regarded as unreliable, especially in heterogeneous catchments such as the Kabul River Basin (KRB). Besides, statistical methods to assess the performance of the models have also been called into doubt in several studies. We evaluated the performance of the Soil and Water Assessment Tool (SWAT) model by statistical indicators including the Kling-Gupta efficiency (KGE), Nash–Sutcliffe efficiency (NSE), and the coefficient of determination (R2) at single and multi-outlets in the KRB and assessed the streamflow under changing climate scenarios i.e., Representative Concentration Pathways (RCP) 4.5 and 8.5 (2020–2045). Because of the heterogeneous nature of the KRB, NSE and R2 performed poorly at multi-outlets. However, the KGE, as the basic objective function, fared much better at single-outlet. We conclude that KGE is the most crucial metric for streamflow evaluation in heterogeneous basins. Similarly, the mean and maximum annual streamflow is projected to decrease by 15.2–15.6% and 17.2–41.8% under the RCP 4.5 and 8.5, respectively.