• 关键词：地表水质  地理探测器  影响因素  水质评价

• 基金项目：国家水体污染控制与治理科技重大专项（No.2017ZX07402-003）；中国博士后科学基金资助项目（No.2019M650798）

• 王研
• 中国环境科学研究院环境基准与风险评估国家重点实验室，北京 100012;中国环境科学研究院水生态环境研究所，北京 100012

• 马瑞瑞
• 中国环境科学研究院环境基准与风险评估国家重点实验室，北京 100012;中国环境科学研究院水生态环境研究所，北京 100012

• 李娟
• 中国环境科学研究院环境基准与风险评估国家重点实验室，北京 100012;中国环境科学研究院水生态环境研究所，北京 100012

• 秦延文
• 中国环境科学研究院国家环境保护河口与海岸带环境重点实验室，北京 100012

• 迟明慧
• 中国环境科学研究院国家环境保护河口与海岸带环境重点实验室，北京 100012

• 曾萍
• 中国环境科学研究院环境基准与风险评估国家重点实验室，北京 100012;中国环境科学研究院水生态环境研究所，北京 100012;中国环境科学研究院，北京 100012

• 王辉锋
• 中国环境科学研究院，北京 100012

• 潘小云
• 吕梁市生态环境局，吕梁 033000

• 高艳梅
• 吕梁市生态环境局，吕梁 033000

• 摘要：水质变化的影响因素是地表水研究的重要内容.为揭示市域尺度规模的地表水质污染特点及其影响因素，本文以山西省吕梁市为例，通过断面水质评价法对研究区内24个监测断面的地表水质污染状况进行评价.在此基础上，利用地理探测器分析自然因素（包括年均气温、年均降水量、高程）与社会经济因素（包括土地利用类型、人口密度、人均GDP）对2020年吕梁市地表水质的影响与交互作用.结果表明：研究区域地表水质整体状况为轻度污染，部分断面存在中度污染，且在空间上分布不均匀，主要污染指标为COD_Cr、NH₃-N和TP.地表水质是多种因素共同作用的结果，与自然因素相比，社会经济因素对地表水质的影响更加明显.人口密度、年平均降水量和土地利用类型是吕梁市地表水质的主要影响因素，各因素的影响程度在交互作用后均有所增强.人均GDP和高程在与其他因素交互后为非线性增强，可作为地表水质空间预测模型的辅助因素.

• Abstract：The analysis of influential factors on the variation of water quality is an important portion of surface water science. To identify and characterize influential factors of surface water pollution on a city scale， Lvliang City in Shanxi Province was selected as the model venue. The section water quality evaluation method was used to assess the surface water pollution status and key pollution indicators in the research zone based on the results of 24 monitoring cross-sections. By use of the geological detector， the effects and interactions of socioeconomic factors （i.e.， land use type， population density， and per capita GDP） and natural factors （i.e.， annual average temperature， annual average precipitation） on the surface water quality was evaluated in 2020’s Lvliang City. The results demonstrated that the overall water status was light pollution， and some sections were moderately polluted. The polluted sites were distributed unevenly in space， with COD_Cr， NH₃-N， and TP serving as the primary pollution index. the quality of the surface water is the comprehensive outcome of a variety of influential factors， in which socioeconomic factors have a more pronounced impact on surface water quality than natural factors. The primary influential factors on surface water quality in Lvliang City were population density， annual average precipitation， and land use type. The combined impact would be enhanced when these factors interacted with one another. As the per capita GDP and elevation increased nonlinearly when interacting with other variables， they can be used as auxiliary parameters in the surface water quality spatial prediction model.

• Key words：surface water quality  geodetector  influential factors  water quality assessment

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