Hydrological Response Assessment of an Upper Indus River Basin Under Diverse Climate Scenarios Using Data-Driven and Process-Based Models: Implications for Sustainable Development Goals

Climate change exerts a pronounced influence on streamflow regimes by altering precipitation characteristics and potential evapotranspiration, thereby affecting global water availability and hydrological functioning. This study investigates the hydrological behavior of the Upper Indus River Basin (UIRB), a strategically important transboundary mountainous watershed, under a range of future climate scenarios. An integrated modeling approach combining process-based simulation and data-driven techniques is employed to generate new insights relevant to the advancement of the Sustainable Development Goals (SDGs). The Soil and Water Assessment Tool (SWAT) and a Long Short-Term Memory (LSTM) neural network were calibrated and validated using daily streamflow observations spanning 1995–2014. During the calibration phase, SWAT yielded an R2 of 0.71, a Nash–Sutcliffe Efficiency (NSE) of 0.59, and a PBIAS of 20.3%. In comparison, the LSTM model demonstrated improved predictive performance, achieving an R2 of 0.72, an NSE of 0.71, and a PBIAS of −1.85%. Future discharge simulations were derived from bias-corrected climate projections obtained from 11 General Circulation Models under SSP245 and SSP585 scenarios for four future time slices (2015–2035, 2036–2055, 2056–2075, and 2076–2099), using 1995–2014 as the reference period. Under the high-emission SSP585 pathway, basin-wide precipitation is projected to increase by 14.7% by the late century, accompanied by substantial rises in maximum and minimum temperatures of 17.9% and 36.25%, respectively. SWAT simulations indicate streamflow increases of 7.1–9.9% under SSP245 and 10.1–11.7% under SSP585, whereas the LSTM model projects more pronounced increases of 17–25.6%. The outcomes of this research contribute significantly to multiple SDGs, with quantified impacts on SDG 6 (Clean Water and Sanitation, 35%), SDG 13 (Climate Action, 30%), SDG 2 (Zero Hunger, 15%), SDG 15 (Life on Land, 12%), and SDGs 8 and 9 (Economic Growth and Infrastructure, 8%). The proposed integrated modeling framework supports enhanced water security through optimized resource planning, reinforces climate resilience by strengthening adaptive capacity, promotes agricultural sustainability in irrigation-reliant regions, safeguards fragile mountain ecosystems under accelerating glacier retreat, informs the development of climate-resilient agricultural sustainability in irrigation-reliant regions, and informs the development of climate-resilient infrastructure. Collectively, these findings highlight the urgent necessity for adaptive water management policies to address climate-induced hydrological uncertainty in stressed transboundary river basins and offer a transferable framework for achieving water-related SDGs in climate-sensitive regions worldwide.