Performance Assessment Comparison between Physically Based and Regression Hydrological Modelling: Case Study of the Euphrates–Tigris Basin

This paper presents two hydrological models developed for the Euphrates–Tigris Basin in Turkey. The first model is a linear regression-based allowing estimation of streamflow based on available hydroclimatic data (precipitation, temperature, evapotranspiration, etc.) with use clustering analysis. second consists an elevation-based semi-distributed (HBV model), process-based modelling watershed. A set performance metrics identified HBV as best terms predicting (NSE = 0.752), while RCA4-EU regression CORDEX showed most robust performance. results show potential from computational and point view being integrated into physically wherein hybrid approach might be beneficial. comparison conceptual statistical analyses shows analysis when regions are clustered hydro-meteorologically homogeneous groups. employment also provides significantly region, which especially important estimating hydropower region’s near future.