Coupling Remote Sensing and Hydrological Model for Evaluating the Impacts of Climate Change on Streamflow in Data-Scarce Environment

The Kabul River Basin (KRB) in Afghanistan is densely inhabited and heterogenic. basin’s water resources are limited, climate change anticipated to worsen this problem. Unfortunately, there a scarcity of data measure the impacts on KRB’s current resources. objective study introduce methodology that couples remote sensing Soil Water Assessment Tool (SWAT) for simulating impact existing KRB. Most biophysical parameters required SWAT model were derived from sensing-based algorithms. SUFI-2 technique was used calibrating validating with streamflow data. stream-gauge stations monitoring not only sparse, but also scarce limited. Therefore, we selected properly being monitored. During calibration period, coefficient determination (R2) Nash–Sutcliffe Efficiency (NSE) 0.75–0.86 0.62–0.81, respectively. validation period (2011–2013), NSE R2 values 0.52–0.73 0.65–0.86, validated then evaluate potential streamflow. Regional Climate Model (RegCM4-4) extract scenarios (RCP 4.5 8.5) CORDEX domain. results show most tributaries KRB would decrease by maximum 5% 8.5% under RCP 8.5 scenarios, However, Nawabad tributary increase 2.4% 3.3% To mitigate reduced/increased surface availability, model, when combined data, can be an effective tool support sustainable management strategic planning Furthermore, methodological approach applied any data-scarce regions around world.