水利学报2026，Vol.57Issue(6)：861-876,889,17.DOI:10.3724/j.slxb.20250511
多源降水数据的不确定性解析与融合算法研究
Uncertainty analysis and algorithms for multi-source precipitation data merging:a review
摘要
Abstract
High-precision,high-resolution precipitation data are critical for simulating river basin hydrological pro-cesses,managing water resources management,and monitoring floods and droughts.Satellite remote sensing and reanalysis systems can provide valuable spatiotemporal coverage;however,their raw estimates often exhibit large uncertainties,making it difficult to meet the application requirements of sectors like water resources.Data quality must be improved through bias correction and data merging,while traditional multi-source precipitation merging approaches,which rely heavily on dense gauge networks,are unsuitable for sparsely observed regions.Statistical uncertainty analysis offers an alternative by jointly evaluating multiple datasets with no much dependence on ground observations,quantifying their error characteristics,and minimizing overall errors to produce optimal merged esti-mates.This review summarizes major statistical uncertainty analysis methods,outlines common error sources and cor-responding correction strategies,and highlights emerging challenges and future directions in multi-source precipita-tion merging.This study aims to provide more reliable precipitation estimates and holds significant importance for improving the quality of precipitation products to support water management and agricultural risk reduction.关键词
卫星遥感/不确定性分析/偏差校正/数据融合Key words
satellite remote sensing/uncertainty analysis/bias correction/data merging分类
天文与地球科学引用本文复制引用
亢晓琪,张慧文,魏玲娜,董建志,单顾天,齐丹..多源降水数据的不确定性解析与融合算法研究[J].水利学报,2026,57(6):861-876,889,17.基金项目
国家重点研发计划项目(2024YFF0810600) （2024YFF0810600）
国家自然科学基金项目(42450248,52179021) （42450248,52179021）
江苏省水利科技项目(2025025) （2025025）
