CAJ | 학술논문

传统水文预报都是确定性的预报，没有充分利用气象预报信息，并且未给出预报的不确定性信息。分析了美国国家环境预报中心（National Centers for Environmental Prediction，NCEP）提供的全球预报（Global Forecast System，GFS）降水数据；然后通过集合预报前处理，将预报降水输入到分布式水文模型；最终给出水文集合预报。通过对比分析，表明采用了降水预报数据的水文集合预报要比传统水文预报准确率高。采用全球天气预报信息进行水文集合预报是发展水文预报的有效途径。
전통수문예보도시학정성적예보，몰유충분이용기상예보신식，병차미급출예보적불학정성신식。분석료미국국가배경예보중심（National Centers for Environmental Prediction，NCEP）제공적전구예보（Global Forecast System，GFS）강수수거；연후통과집합예보전처리，장예보강수수입도분포식수문모형；최종급출수문집합예보。통과대비분석，표명채용료강수예보수거적수문집합예보요비전통수문예보준학솔고。채용전구천기예보신식진행수문집합예보시발전수문예보적유효도경。
Traditional hydrological prediction is a type of deterministic prediction, which does not make full use of the weather forecast information, or give forecast uncertainty. This paper analyzed the precipitation hindcast data provided by the Global Forecast System (GFS) in National Centers for Environmental Prediction (NCEP); and then the hindcast data was processed by the ensemble pre-processor in order to drive the hydrological model. Finally, we got the hydrological ensemble prediction. The results show that the hydrological ensemble prediction is better than the traditional ensemble streamlfow prediction (ESP). The hydrological ensemble prediction on GFS is an effective way of developing hydrological prediction.