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【目的】为推进三峡库区农村饮水安全巩固提升，提出三峡库区农村饮水安全云评价模型，以评估三峡库区农村饮水安全水平。【方法】针对三峡库区农村饮水的现状与特点，构建了三峡库区农村饮水安全评价指标体系。采用云模型算法生成农村饮水安全评价标准云，并结合不确定层次分析法确定各评价指标的权重，建立了农村饮水安全云评价模型。最后，以三峡库区移民安置村兰草村饮水工程为例进行农村饮水安全评价。【结果】结果显示：兰草村饮水安全等级为Ⅲ级，处于基本安全状态。评价结果与实际情况相符，验证了方法的正确性和可靠性。后续巩固提升工作需在水量、水质和供水保证率方面重点展开。【结论】结果表明：三峡库区农村饮水安全云评价模型能有效评定研究区域整体和各单项指标饮水安全等级，研究成果为三峡库区农村饮水安全巩固提升工作提供了参考依据，完善了农村饮水安全评价体系。
Abstract：[Objective]In order to promote the consolidation and improvement of rural drinking water safety in the Three Gorges Reservoir Area by proposing a cloud evaluation model. The model is designed to assess the level of rural drinking water safety in the area.[Methods]The study constructed an evaluation index system for rural drinking water safety in the Three Gorges Reservoir Area based on the current situation and characteristics of rural drinking water. The cloud model algorithm was then employed to generate the evaluation standard cloud for rural drinking water safety. The weight of each evaluation index was determined using the uncertain hierarchical analysis method, which led to the establishment of the cloud evaluation model for rural drinking water safety.[Results]The results show that Lancao Village has a drinking water safety level of Ⅲ, which corresponds to the basic safety state. The evaluation result align with the actual situation, validating the method′s correctness and reliability. The subsequent consolidation and improvement efforts should prioritize water quantity, water quality, and water supply guarantee rate.[Conclusion]In conclusion, the cloud evaluation model for rural drinking water safety in the Three Gorges reservoir area demonstrates its effectiveness in assessing the overall drinking water safety level and individual indices. The research findings offer a reference for consolidating rural drinking water safety in the region and enhancing the evaluation system.
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基本信息:
DOI：10.13928/j.cnki.wrahe.2023.11.018
中图分类号:S277.7
引用信息:
[1]邵波,王硕,赵金山,等.三峡库区农村饮水安全云评价模型研究[J].水利水电技术(中英文),2023,54(11):205-213.DOI:10.13928/j.cnki.wrahe.2023.11.018.
基金信息:
国家自然科学基金项目(72204141)