Meteo-hydrological coupled runoff forecasting based on numerical weather prediction products
JIN Junliang1,2, SHU Zhangkang1,2, CHEN Min3, WANG Guoqing1,2, SUN Zhouliang2,3, HE Ruimin1,2
1. Nanjing Hydraulic Research Institute, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing 210029, China; 2. Research Center for Climate Change of Ministry of Water Resources, Nanjing 210029, China; 3. College of Hydraulic and Environment, China Three Gorges University, Yichang 443000, China
Abstract：This study implements ensemble runoff forecasts using the Xin'anjiang model driven by ECMWF,UKMO,NCEP and other seven control forecast products of TIGGE data center in Chitan reservoir watershed in Jinxi,Fujian Province,China. By means of ensemble selection,pre-processing via multi-model integration,and post-processing based on the BMA model,the influences of data-processing scheme and initial set quality on the accuracy and uncertainty of the meteo-hydrological runoff predictions were investigated. The results show that different treatment schemes could effectively improve the accuracy and stability of runoff forecasts. Combination of pre-processing and post-processing led to better performances than other schemes due to its error reduction in two aspects,i.e. lowering the input errors and controlling the output errors. Although the initial set quality exerted a perceptible impact on the ensemble runoff forecasts,the effect was not significant since either pre-processing or post-processing procedure effectively controlled the forecasting errors. Overall,we conclude that the pre-processing and post-processing processes are indispensable to improve the accuracy and reliability of meteo-hydrological runoff forecasts,which should be paid attention to.
金君良, 舒章康, 陈敏, 王国庆, 孙周亮, 贺瑞敏. 基于数值天气预报产品的气象水文耦合径流预报[J]. 水科学进展, 2019, 30(3): 316-325.
JIN Junliang, SHU Zhangkang, CHEN Min, WANG Guoqing, SUN Zhouliang, HE Ruimin. Meteo-hydrological coupled runoff forecasting based on numerical weather prediction products. Advances in Water Science, 2019, 30(3): 316-325.
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2019, Vol. 30 
