湖泊科学2017，Vol.29Issue(6)：1491-1501,11.DOI:10.18307/2017.0621
半湿润流域水文模型比较与集合预报
Hydrological models comparison and ensemble forecasting in semi-humid watersheds
摘要
Abstract
Watershed hydrological simulation is a measure to simulate the real world hydrological processes based on hydrological models.A large number of conceptual hydrological models have been invented driven by different generalizations of the identical hydrological process.The advantages of different models can be investigated by comparison of different hydrological models.Ensemble forecasting is a means that integrates several model results to obtain more reliable and stable predictions.Arithmetic Mean,Weighted Averaging and Bayesian Model Averaging are three common ensemble forecasting methods.In this study,seven hydrological models were applied and compared in three semi-humid watersheds in the northem China to explore the applicability of different models in each watershed.Bayesian Model Averaging scheme were used to integrate these models to compare the advantages of different combinations,and the application effect of Bayesian Model Averaging scheme was studied.The results show that models withsaturation-excess mechanisms have a good simulation effect in semi-humid watersheds.Traditional models are improved based on the characteristics of different watersheds,and the accuracy of simulation is higher after improvement.The certainty forecasting results and probabilistic forecasting results are provided by Bayesian Model Averaging scheme.The integrated result of few good-simulated models shows poor stability.Bayesian Model Averaging scheme can take advantages of each model efficiently and provide high-precision forecasting results by increasing the number of integrated models properly.关键词
半湿润流域/水文模拟/模型对比/贝叶斯模型平均法Key words
Semi-humid watershed/hydrological simulation/models comparison/Bayesian Model Averaging引用本文复制引用
霍文博,李致家,李巧玲..半湿润流域水文模型比较与集合预报[J].湖泊科学,2017,29(6):1491-1501,11.基金项目
国家自然科学基金项目(41130639,51179045)和水利部公益项目(201501022)联合资助. （41130639,51179045）
