首页|期刊导航|岩土工程学报|基于全国水库大坝病害数据库的大坝安全隐患特征统计分析

基于全国水库大坝病害数据库的大坝安全隐患特征统计分析OA

Statistical analysis of dam safety hazard characteristics based on national reservoir dam disease database

中文摘要英文摘要

受气候变化、强人类活动及工程老化等多种因素影响,病险问题一直是中国水库大坝安全管理重点.囿于大坝病险信息分散、非结构化存储难以利用,长期以来对大坝安全隐患特征的认识主要依赖专家经验和小范围工程统计,鲜见全国尺度统计分析.本文基于全国大坝基础信息库及近10 a内鉴定出的2万余座病险水库大坝安全鉴定报告书,采用人工智能技术对隐患信息进行提取与结构化处理,初步构建了全国水库大坝病害数据库,从工程规模、建成时间、坝型、坝高、区位等维度对大坝病害进行统计分析,初步分析了全国水库大坝安全隐患特征,并提出相应对策建议.结果表明,渗流和结构安全隐患占病险主导地位;防洪安全隐患在中小型水库,尤其是松辽河、黄河流域等北方区域的小型水库中较为显著;抗震安全隐患在海河、西南诸河等流域相对集中;金属结构安全隐患在大中型水库中更为突出.本研究可为中国水库大坝安全管理和病险水库除险加固决策及长效机制建设提供技术支撑.

Under the combined effects of climate change,intensified human activities,and structural aging,dam safety hazards have long been a major concern in reservoir safety management in China.The dispersed and unstructured nature of dam distress information limits its effective utilization.Existing understanding of dam safety hazards has mainly relied on expert experience and small-scale engineering statistics,while nationwide statistical analyses are rarely seen.In this study,based on the national dam basic information database and safety evaluation reports of more than 20,000 defective reservoir dams identified over the past 10 years,artificial intelligence techniques are used to extract and structurize hazard information,resulting in the preliminary construction of a nationwide reservoir dam distress database.Statistical analyses are conducted from the dimensions of engineering scale,completion time,dam type,dam height,and geographic location to analyze dam safety hazard characteristics at the national scale,and corresponding countermeasures and suggestions are proposed.The results show that seepage-related and structural safety issues are the two most prominent hazard types.Flood control safety hazards are most prominent in medium and small reservoirs,particularly for small reservoirs in northern regions such as the Songliao and Yellow River basins.Seismic safety hazards are relatively concentrated in the Haihe and Southwest Rivers region.Metal structure problems are more prominent in large and medium reservoirs.This study provides technical support for reservoir dam safety management in China,decision-making regarding hazard elimination and reinforcement of defective reservoirs,and the establishment of a long-term effective mechanism.

尹江珊;侯文昂;黄健峰;张士辰;蔡荨

南京水利科学研究院,江苏 南京 210029||水利部大坝安全管理中心,江苏 南京 210029南京水利科学研究院,江苏 南京 210029||水利部大坝安全管理中心,江苏 南京 210029||水利部水库大坝安全重点实验室,江苏 南京 210029||河海大学土木与交通学院,江苏 南京 210024南京水利科学研究院,江苏 南京 210029南京水利科学研究院,江苏 南京 210029||水利部大坝安全管理中心,江苏 南京 210029||水利部水库大坝安全重点实验室,江苏 南京 210029南京水利科学研究院,江苏 南京 210029||水利部大坝安全管理中心,江苏 南京 210029||水利部水库大坝安全重点实验室,江苏 南京 210029

建筑与水利

大坝安全人工智能病险水库病害数据库安全隐患对策建议

dam safetyartificial intelligencedefective reservoirsdistress databasesafety hazardscountermeasures and suggestions

《岩土工程学报》 2026 (9)

1827-1836,10

国家重点研发计划项目(2024YFC3210700)国家自然科学基金项目(52309159,52409166)中央级公益性科研院所基本科研业务费专项资金(Y724007,Y724010)This work was supported by the National Key Research and Development Program of China(Grant No.2024YFC3210700)National Natural Science Foundation of China(Grant Nos.52309159,52409166),and Central Public-interest Scientific Institution Basal Research Fund(Grant Nos.Y724007,Y724010).

10.11779/CJGE20260029

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