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基于"数据-机理"驱动的土石坝渗流性态分析与分级预警研究

王铭铭

江淮水利科技2026,Vol.21Issue(2):9-13,5.
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江淮水利科技2026,Vol.21Issue(2):9-13,5.DOI:10.20011/j.cnki.JHWR.202602002

基于"数据-机理"驱动的土石坝渗流性态分析与分级预警研究

Seepage behavior analysis and hierarchical warning study of earth rock dam based on"data-mechanism"driving

王铭铭1

作者信息

  • 1. 安徽省·水利部淮河水利委员会水利科学研究院,安徽 合肥 230088||安徽省水科学与智慧水利重点实验室,安徽 合肥 230088
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摘要

Abstract

Seepage pressure monitoring data are an important indicator for conducting safety prediction and early warning of reservoir dams.However,the internal structure of earth-rock dams,soil conditions,and other operational factors are complex and easily affected by external factors such as rainfall and reservoir water levels,making it difficult to obtain accurate data.This paper aimed to analyze the influencing factors and correlation relationships of seepage behavior in reservoir dams,constructed an analytical warning model,and enhanced the ability to analyze,diagnose,and provide safety warnings for dam operation forms.The paper was based on long-term monitoring data of correlation factors such as seepage pressure and reservoir water level.Following the idea of"data governance,regression analysis,and interval extraction",multiple methods such as box plot,K-means clustering,and polynomial regression were used to integrate data governance and analysis,extract confidence intervals and prediction intervals.By constructing a"data-mechanism"driven dam seepage pressure grading warning model,an earth rock dam safety grading warning system was established,and the effectiveness of the research method and model was verified using the Qianshanmen Reservoir as an example.The research results indicated that this method had high accuracy and reliability in fitting the upstream water level seepage pressure curve,which was of great significance for the safe operation of reservoir dams.

关键词

渗流压力/渗流性态分析/分级预警/"数据-机理"驱动

Key words

seepage pressure/seepage behavior analysis/hierarchical warning/"data-mechanism"driving

分类

建筑与水利

引用本文复制引用

王铭铭..基于"数据-机理"驱动的土石坝渗流性态分析与分级预警研究[J].江淮水利科技,2026,21(2):9-13,5.

基金项目

水利技术示范项目(SF-202414) (SF-202414)

安徽省水利厅科研及技术咨询项目(SLKJ202501-07) (SLKJ202501-07)

江淮水利科技

1673-4688

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