摘要
洪水概率预报通过提供具有一定置信度的预报区间,评估预报结果的可靠度,为防洪调度提供重要依据。以淮河关键防洪断面王家坝为研究对象,分别采用API和新安江(XAJ)确定性模型进行初始的确定性预报,在此基础上,再采用模型条件处理器(MCP)推求不同量级洪水预报流量的条件概率分布函数,实现洪水概率预报。分别从中位数的确定性精度评价和概率预报的可靠度评价两方面对预报结果进行分析,结果表明:MCP洪水概率预报结果不仅具有较高的可靠度,而且其中位数预报与确定性模型结果相比,预报精度整体有所提高,说明MCP具备一定的校正预报能力。
The probabilistic flood forecasting can provide a prediction interval with a certain reliability,and can be used to evaluate the reliability of forecasting results.It can provide an important basis for flood control scheduling.We took Wangjiaba cross-section,a key flood control section of Huaihe River,as the research object.Based on the prediction results of API and XAJ models,using the Model conditional processor(MCP)to deduce the conditional probability distribution function of the forecasting runoff of floods of different magnitudes,we realized probabilistic flood forecasting.The prediction results were analyzed in terms of the deterministic precision evaluation of median number and the reliability evaluation of probabilistic forecasting.The results showed that the MCP probabilistic flood forecasting has a high reliability,and its median number prediction has a higher prediction accuracy than the deterministic model,indicating that MCP has a certain ability of correction and prediction.
作者
王艳兰
梁忠民
王凯
罗俐雅
WANG Yanlan;LIANG Zhongmin;WANG Kai;LUO Liya(College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China;Bureau of Hydrology,Huaihe Water Conservancy Committee,Bengbu 233001,China;Jiangsu Province Hydrology and Water Resources Investigation Bureau,Nanjing 210098,China)
出处
《南水北调与水利科技》
CSCD
北大核心
2018年第6期39-45,共7页
South-to-North Water Transfers and Water Science & Technology
基金
国家重点研发计划(2016YFC0402709)
江苏省水利科技重点技术攻关项目(2017008)
水利部公益性行业专项经费项目(201301066)~~
关键词
洪水概率预报
模型条件处理器
API模型
新安江模型
probabilistic flood forecasting
model conditional processor
API model
Xin′anjiang model
