水科学进展2025，Vol.36Issue(4)：621-633,13.DOI:10.14042/j.cnki.32.1309.2025.04.007
基于多模式降水与水文模型的径流预报不确定性分析
Uncertainty analysis of streamflow forecast based on multi-model precipitation and hydrological models
摘要
Abstract
To improve the accuracy and reliability of streamflow forecasting,nine ensemble runoff prediction schemes were developed for the Qingjiang River basin by combining two precipitation forecasts(ECMWF and NCEP)with two hydrological models(GR4J and XAJ).A generator-based post-processing method(GPP)was applied to correct systematic biases in model precipitation.The performance of each scheme was comprehensively evaluated from deterministic,probabilistic,and uncertainty perspectives.Results indicate that the GPP method significantly enhanced precipitation quality,thereby improving streamflow forecasting accuracy—particularly for the NCEP product,which exhibited larger initial errors.Integrating high-accuracy precipitation forecasts with multiple hydrological models further improved the robustness and reliability of ensemble runoff predictions.During validation against a typical flood event in 2020,all schemes accurately captured the flood peak timing at 1-and 3-day lead time.Notably,the ensemble-mean peak flows from the multi hydrological model integration schemes closely matched the observed peak.关键词
集合径流预报/数值预报模式/水文模型/后处理/不确定性Key words
ensemble streamflow forecasting/numerical weather prediction/hydrological model/post-processing/uncertainty分类
天文与地球科学引用本文复制引用
向怡衡,彭涛,殷志远,祁海霞,沈铁元..基于多模式降水与水文模型的径流预报不确定性分析[J].水科学进展,2025,36(4):621-633,13.基金项目
国家自然科学基金项目(U2340201) （U2340201）
灾害天气国家重点实验室开放基金项目(2024LASW-B04)The study is financially supported by the National Natural Science Foundation of China(No.U2340201)and the Open Grants of the State Key Laboratory of Severe Weather of China(No.2024LASW-B04). （2024LASW-B04）
