Quantifying the Reliability and Uncertainty of Satellite, Reanalysis, and Merged Precipitation Products in Hydrological Simulations over the Topographically Diverse Basin in Southwest China

With the continuous emergence of remote sensing technologies and atmospheric models, multi-source precipitation products (MSPs) are increasingly applied in hydrometeorological research, especially ungauged or data-scarce regions. This study comprehensively evaluates reliability MSPs quantifies uncertainty sources streamflow simulation. Firstly, performance seven state-of-the-art is assessed using rain gauges Block-wise use TOPMODEL (BTOP) hydrological model under two calibration schemes over Jialing River Basin, China. Then, a variance decomposition approach (Analysis variance, ANOVA) employed to quantify contribution products, parameters, their interaction The include five satellite-based (GSMaP, IMERG, PERCDR, CHIRPS, CMORPH), one reanalysis (ERA5L), ensembled product (PXGB2). results evaluation show that have temporal spatial variability PXGB2 has best performance. hydrologic utility different methods. When gauge-based PXGB2-based simulation performs best, whereas ERA5L relatively poor In comparison, recalibrated by individual significantly improves accuracy most MSPs, with GSMaP having ANOVA reveal larger than parameters interaction. impact suggests better attributes an optimal combination rather solely relying on MSPs. These new findings valuable for improving suitability applications.