Optimizing WRF-Hydro Calibration in the Himalayan Basin: Precipitation Influence and Parameter Sensitivity Analysis

Lack of in-situ observations and reliable climate information in large part of the Himalayas poses a significant challenges for assessing water resources vulnerability accurately. Further, the reliance on only a few coarse resolution gridded datasets with considerable uncertainty complicates this problem. However, 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 PEST framework, using eight simulations with two meteorological forcings from two WRF realisations. Model calibration improves the accuracy of the basin discharge simulation, however the choice of precipitation forcing is also critically important. We propose an ensemble weighting scheme to optimize an intra-annual tradeoff between streamflow under- and overestimation in different WRF-Hydro configurations. This study demonstrate the efficacy of using coupled (offline) WRF and WRF-Hydro for providing climate change impact-relevant information in data-sparse basins.