摘要
为进一步探索提高模型精度的方法,比较不同集合预报方法的优劣,选择了4种水文模型(新安江模型、Simhyd模型、GR4J模型和人工神经网络模型)分别在浙江省西部山区的4个典型流域做模拟对比,分析这4个模型在流域上的适用性,并将模型的模拟结果作为集合成员,使用黑箱集合预报法和诱导有序二项式系数集合预报法对成员进行集合预报,研究模型的应用效果,并进行4种模型和2种集成方法的优势对比。研究结果表明,新安江模型和GR4J模型在研究区域的适用性方面较好。黑箱集合预报法和诱导有序二项式系数集合预报法分别代表固定权重和变动权重的两种集合预报方法,模拟结果显示,后者对集合成员的改进程度更高,说明其在动态权重方法下更能充分发挥各模型的优势之处,达到择优互补的模拟效果,从而提高预报精度。
In order to further explore the methods to improve the accuracy of the model and compare the the advantages and disadvantages of different ensemble forecasting methods,taking four catchments located in the west mountain areas of Zhejiang province as a study case,four hydrological models(Xin′anjiang model,Simhyd model,GR4J model and artificial neural network model)were used to simulate hydrologic process and compare the applicability in this paper.Choosing the simulation results as ensemble members,ensemble forcasting method based the black-box and the induction of binomial coefficient were used to study the application effect and advantages in comparison.The results indicated that Xin′anjiang model and GR4J model have better applicability in the research area.Ensemble forecasting method based the black-box and the induction of binomial coefficient respectively static weight and dynamic weight ensemble forecast method,the latter to a greater degree of improvement.In other words,under the dynamic weight method,the advantages of each model can be fully utilized to achieve the effect of matching and complementing,thereby improving the forecasting accuracy.
作者
王婕
刘翠善
刘艳丽
鲍振鑫
宋明明
刘悦
王国庆
WANG Jie;LIU Cuishan;LIU Yanli;BAO Zhenxin;SONG Mingming;LIU Yue;WANG Guoqing(State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Nanjing Hydraulic Research Institute,Nanjing 210029,China;Research Center for Climate Change of Ministry of Water Resources,Nanjing 210029,China;College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China)
出处
《华北水利水电大学学报（自然科学版）》
2019年第6期32-38,共7页
Journal of North China University of Water Resources and Electric Power：Natural Science Edition
基金
国家“十三五”重点研发计划项目(2017YFA0605002,2016YFA0601501)
国家自然科学基金项目(41830863,51879162,51779145)
江苏省“六大人才高峰”资助项目(RJFW-031)
关键词
集合预报
水文模型
诱导二项式系数法
浙江省西部山区
ensemble forecasting
hydrological model
induction of binomial coefficient method
western mountains of Zhejiang province
