Optimizing wrf-hydroWRF-Hydro calibration in the Himalayan Basin: Precipitation influence and parameter sensitivity analysis

The lack of in situ observations and reliable climate information in large parts of the Himalayas poses significant challenges for assessing water resources vulnerability. Integrated hydrometeorological modeling systems, like WRF-Hydro, have the potential to provide information in such ungauged or poorly observed regions, yet they require careful calibration. Here, we calibrate and assess the fidelity of WRF-Hydro in simulating the hydrological regime of the Beas basin. Selected WRF-Hydro model parameters are calibrated using the parameter estimation (PEST) framework, leveraging eight WRF-Hydro simulations with two meteorological forcings from two WRF realizations. Model calibration improves the accuracy of the basin discharge simulation; however, the choice of precipitation forcing is also found to be critically important. The performance of a given WRF-Hydro configuration varies with seasons. We thus propose an ensemble-weighting scheme to optimize an intra-annual trade-off between streamflow under- and overestimation in different WRF-Hydro configurations. This study demonstrates the efficacy of using WRF and WRF-Hydro for providing climate change impact–relevant information in data-sparse basins.