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基于系统聚类的分水江站水位分类预报和区间预报

Classification Forecast and Interval Forecast for Water Level of Fenshuijiang Station Based on Systematic Clustering

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【作者】 姬战生刘小勇王军张振林

【Author】 JI Zhan-sheng;LIU Xiao-yong;WANG Jun;ZHANG Zhen-lin;Hangzhou Hydrology and Water Resources Monitoring Center;Hydraulic Engineering Science and Technology Consultation Limited Company of Jiangsu Province;College of Hydrology and Water Resources, Hohai University;

【通讯作者】 王军;

【机构】 杭州市水文水资源监测中心江苏省水利工程科技咨询股份有限公司河海大学水文水资源学院

【摘要】 研究分水江流域控制站——分水江站的水位预报方法,提高预报精度,对支撑区域防洪决策具有重要意义。利用分水江站2012~2020年典型历史洪水,基于系统聚类分析方法,以最大1 d洪量、洪峰流量、洪峰水位、洪水起涨历时占比作为聚类指标,将洪水分为Ⅰ、Ⅱ类两类洪水,采用流量演算—水位流量关系转换法对分水江站进行水位分类预报,并构建不同类型洪水水位流量关系的上下边界,提出一种分类洪水水位区间预报方法。结果表明,两类洪水的洪峰水位预报精度有所提高,预报区间宽度明显减小,提高了区间预报结果的可利用性。

【Abstract】 The research on water level prediction method of Fenshui River control station in Fenshui River basin that improves the prediction accuracy is of great significance to support regional flood control decision-making. The typical historical floods of Fenshuijiang hydrology station from 2012 to 2020 were selected and classified into category Ⅰ and Ⅱ flood based on systematic cluster analysis method, with the maximum 1-day flood volume, peak discharge, peak water level and the proportion of flood initiation duration as cluster indexes. The water level classification and prediction of water level stations were carried out by flow routing and water level and flow relation conversion method. The upper and lower boundaries of the water level and flow relationship of different flood types were constructed, and a classified interval prediction method of flood level was proposed. The results show that the accuracy of flood peak water level prediction for the two types of floods is improved effectively, the width of forecast interval is obviously reduced, and the availability of forecast results is improved.

【基金】 国家自然科学基金重点项目(41730750);浙江省水利科技计划项目(RC1901,RB2102,RC2153);杭州市科技计划引导项目(20211231Y086)
  • 【文献出处】 水电能源科学 ,Water Resources and Power , 编辑部邮箱 ,2023年02期
  • 【分类号】P338
  • 【下载频次】83
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