Assessing the role of gridded evapotranspiration products in improving streamflow simulation and reducing hydrological modeling uncertainty

Streamflow simulation is crucial for ecological conservation and water resource planning. Hydrological models are the main tools for streamflow simulation, typically calibrated using streamflow measurements. However, this approach cannot guarantee accurate estimates of other hydrological variables, leading to large uncertainty in hydrological simulation. The inclusion of other variables, such as evapotranspiration (ET), offers a potential approach to overcoming this limitation. This study systematically evaluated the incorporation of gridded ET products to constrain hydrological models and reduce prediction uncertainty. To this end, three calibration experiments, established based on streamflow observations (benchmark), ET products, and their combination, were applied to constrain a process-based hydrological model in the Baihe River basin. Results indicated that single-variable calibration with ET products provided acceptable monthly streamflow estimates, with average Nash–Sutcliffe Efficiency (NSE) values of 0.75 and 0.67 during the calibration and validation periods, respectively. Multi-variable calibration using additional ET data achieved streamflow simulation results comparable to the benchmark, with average NSE values of 0.84 and 0.87, respectively. Model calibration using a single variable could lead to large uncertainty in parameters and simulated results. In contrast, multi-variable calibration improved the reliability of model outputs and reduced overall parameter uncertainty, providing better constraints for representing hydrologic processes. Compared to the original ET data, the bias-corrected ET data performed better in reducing prediction uncertainty and improved the estimation of median and low flows. These findings provide valuable insights for applying ET products in hydrological simulation, and contribute scientific support for sustainable water resources management and ecological protection decision-making.