Remotely sensed evapotranspiration-based ensemble streamflow modeling in an ungauged watershed under climate and land...

Hydrological assessment in ungauged watersheds is challenging due to the lack of streamflow observations, and remote sensing (RS) products have emerged as viable in such regions. However, previous studies have relied on a single optimal parameter set and have not considered uncertainty into scenario based simulations. To address this gap, this study evaluated the applicability of an RS-evapotranspiration (ET)-based calibration framework using the Soil and Water Assessment Tool (SWAT), incorporating multiple behavioral parameter sets to explicitly account for equifinality. Six scenarios were evaluated against a historical baseline (1981-2010): two RCP 8.5-based climate change scenarios (near-future: 2040-2069; far-future: 2070-2099) derived from a GCM, a reforestation LULC scenario, and their combined interactions. The calibrated model met satisfactory performance thresholds across calibration and validation periods (NSE: 0.70-0.75; RSR: 0.50-0.54; PBIAS: 2.47-4.29%). The calibration results yielded four behavioral parameter sets, whereas the uncalibrated model failed to meet performance standards. The climate change scenarios substantial increases in runoff (∼62.8%) and extreme flow indices (∼70.8%) relative to the baseline, due to changes in precipitation. In contrast, reforestation mitigated these increases through enhanced water uptake by vegetation. The combined scenarios showed relatively moderate changes due to interaction effects between climate and LULC change. These findings demonstrate that RS-ET-based ensemble calibration can serve as a robust framework for scenario-based hydrological assessments in ungauged watersheds, while accounting for uncertainty, and highlight the role of forestation in mitigating climate-driven hydrological changes.