贝叶斯概率水文预报系统在中长期径流预报中的应用  

Application of the Bayesian statistic hydrological forecast system to middle-and long-term runoff forecast

作　　者：张铭[1] 李承军[1] 张勇传[1] 

机构地区：[1]华中科技大学数字流域科学与技术湖北省重点实验室,湖北武汉430074

出　　处：《水科学进展》2009年第1期40-44,共5页Advances in Water Science

基　　金：国家自然科学基金资助项目(50579022);国家"十一五"科技支撑计划项目(2006BAC05B03)~~

摘　　要：采用贝叶斯概率水文预报理论制订水电站水库中长期径流预报模型,以概率分布的形式定量地描述水文预报的不确定度,探索概率水文预报理论及其应用价值。采用气象因子灰关联预报模型处理输入因子的不确定度,将实时气象信息和历史水文资料有效结合,突破传统确定性预报方法在信息利用和样本学习方面的局限性,以提高水文预报的精确度。以丰满水电厂水库为例对所建模型进行检验,模拟计算结果表明,该模型与确定性径流预报方法相比,不仅有利于决策人员定量考虑不确定性,而且在期望意义上提高了径流预报精度,具有较高的应用价值。To study the probability hydrological forecast and its application value, the Bayesian statistic forecast theory is adopted to formulate the reservoir middle-and long-term runoff forecast model, which describes the uncertainty of hydrological forecast by the distribution function. The gray correlation prediction model for the meteorological factors is presented to count the uncertainty of the input factor. The real-time meteorological information and history hydrological data are coupled effectively, which breakthrough the limitations on the information utilization and samples concerning the determined forecast method and improve the accuracy of hydrological forecast. The established model is tested on the runoff forecast of the Feng-man reservoir. The application results fully show that the superiority is apparent compared with the conventional forecast method. Not only does the model benefits the user to consider the uncertainty quantitatively in decision-making, but ulso improves the forecast accuracy expectatively.

关 键 词：概率水文预报 不确定度 贝叶斯方法 气象因子 中长期径流预报 

分 类 号：P338.2[天文地球—水文科学]