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作 者:徐炳生 王伟[2] 徐颖 杨哲 XU Bing-sheng;WANG Wei;XU Ying;YANG Zhe(PowerChina Hydropower Development Group CO.,LTD.,Chengdu 610096,China;Sichuan Water Conservancy Vocational College,Chengdu,611231,China;College of Water Resource&Hydropower,Sichuan University,Chengdu 610065,China)
机构地区:[1]中国电建水电开发集团有限公司,四川成都610096 [2]四川水利职业技术学院,四川成都611231 [3]四川大学水利水电学院,四川成都610065
出 处:《水电能源科学》2022年第7期98-101,共4页Water Resources and Power
摘 要:心墙渗流监控模型构建是保障高土石坝安全运行的关键技术问题。针对单测点模型难以有效反映心墙渗流空间分布、传统空间模型方法无法考虑环境量影响等问题,引入协同克里金法,构建了以关键环境因子作为协变量的大坝心墙渗流协同克里金空间模型,并将该模型应用于某土石坝心墙渗流中。工程应用结果表明,基于水位协变量的大坝心墙渗流协同克里金空间模型精度较高,能有效反映心墙渗流整体空间分布规律,其中测点位置、协变量因子的选取及建模测点数量是影响模型精度的主要因素,具有一定工程应用价值。The construction of core wall seepage monitoring model is the key technical issue for the safe operation of high earth-rockfill dam. It was difficult to effectively reflect the spatial distribution of the core wall seepage through existing single-point model, and the traditional spatial model can not consider the environmental influence. In this paper, the cooperative Kriging was introduced, which took key environmental factors as covariates, and a collaborative Kriging spatial model of core wall seepage was constructed. The model was applied to the seepage of a certain core-wall earth-rockfill dam. The project application shows that the cooperative Kriging model of core wall seepage based on water level covariate has high accuracy, and it can effectively reflect the spatial distribution of core wall seepage and has certain application value to projects. The location of measuring points, the selection of covariates and the number of modeling measuring points are the main factors affecting the accuracy of the model.
分 类 号:TV642.2[水利工程—水利水电工程]
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