Impacts of Precipitation Forcing on Hydrological Simulation over Monsoon Asia

Globally important hydroclimatic variations take place over monsoon Asia. However, sound understanding of hydrological processes is still challenging due to the unevenly distributed observation stations. This rising issue has been partially solved through land surface model (LSM) simulations, which is known as one of the most effective ways to predict hydrological states and fluxes in ungauged regions. Recent advances in remote sensing techniques produced several multi-source-based precipitation data, which serves as a major input forcing for modeling the land surface processes. In this context, this study aims to validate the precipitation estimates from Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), Global Data Assimilation System (GDAS), Integrated Multi-satellite Retrievals for GPM (IMERG), and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and also evaluate the LSM-simulated soil moisture (SM) and evapotranspiration (ET) through NASA Land Information System (LIS). Precipitation products are validated with ground measurements-based Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) gridded data. Spatiotemporal errors in SM and ET outputs originating from precipitation uncertainty are quantified at locations with dense ground precipitation observations. Overall, the outcomes could possibly reveal additional error sources such as land use land cover (LULC) surface dataset or model parameterizations, which is crucial for more sophisticated LSM simulations.