Demonstrates improved runoff simulations in a data-sparse region, suggesting benefits of using merged precipitation products.
The validity of hydrological modelling relies on high-quality precipitation data. Satellite precipitation products (SPPs) provide an alternative to precipitation in data-sparse regions, but they suffer from rough spatial resolution and poor accuracy, making it difficult to meet the demand for refined hydrological modelling. To that end, a novel geographically weighted regression kriging (GWRK) method was developed to correct precipitation in the upper Hanjiang River basin, and the reliability of multiple precipitation datasets, encompassing SPPs and merged precipitation products (MPPs), was assessed. Results indicated that MPPs offered superior accuracy with higher R (>0.96) and lower RMSE and BIAS. Compared with SPPs and gauge observations, the daily and monthly runoff forced by MPPs were in better agreement with observed runoff. Additionally, all precipitation datasets exhibited a slight underestimation of peak runoff simulations. The work in this study is expected to confirm the potential of MPPs generated by the GWRK method for hydrometeorological applications.
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Xu et al. (2025) studied this question.
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