基于数值天气预报产品的气象水文耦合径流预报

以福建金溪池潭水库流域为例,采用TIGGE数据中心的ECMWF、UKMO、NCEP等7种模式控制预报产品驱动新安江模型,开展径流集合预报。通过集合挑选、多模式集成前处理以及基于BMA模型的后处理等过程,探讨不同处理方案和初始集合质量对气象水文耦合径流预报精度及不确定性的影响。结果表明,不同的处理方案均能有效提高径流预报的精度和稳定性,同时进行前处理和后处理能从降低误差输入和控制误差输出两方面减小预报误差,相对于其他方案表现更好。初始集合质量对气象水文耦合径流集合预报有一定影响,但前处理或后处理对预报误差的有效控制使得该影响并不显著。总体而言,前处理和后处理过程是提高气象水文耦合径流预报准确性和可靠性必不可少的环节,应予以重视。

Meteo-hydrological coupled runoff forecasting based on numerical weather prediction products

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.