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Accurate high-resolution estimates of precipitation are vital to improvingthe understanding of basin-scale hydrology in mountainous areas. Thetraditional interpolation methods or satellite-based remote sensing productsare known to have limitations in capturing the spatial variability ofprecipitation in mountainous areas. In this study, we develop a fusionframework to improve the annual precipitation estimation in mountainous areasby jointly utilizing the satellite-based precipitation, gauge measuredprecipitation, and vegetation index. The development consists of vegetationdata merging, vegetation response establishment, and precipitation remapping.The framework is then applied to the mountainous areas of the Nu River basinfor precipitation estimation. The results demonstrate the reliability of theframework in reproducing the high-resolution precipitation regime andcapturing its high spatial variability in the Nu River basin. In addition,the framework can significantly reduce the errors in precipitation estimatesas compared with the inverse distance weighted (IDW) method and the TRMM(Tropical Rainfall Measuring Mission) precipitation product

Remapping annual precipitation in mountainous areas based on vegetation patterns: a case study in the Nu River basin