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湖南省地表水水质时空变化特征及驱动因子分析

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开展区域水质监测与成因分析是实施水污染治理的重要前提.基于2021-2022年湖南省的547个监测断面的地表水水质指标数据,依据GB 3838-2002《地表水环境质量标准》,分析湖南省地表水水质时间变化规律与区域性差异,采用主成分分析法识别主要污染指标,运用灰色关联度法探究驱动水质异质化的主要因子.主要研究结果表明:2021-2022年湖南省水质整体良好,每月Ⅰ-Ⅱ类水断面比例不低于70%.湖南省地表水水质的月际变化特征表现为夏季劣于其他季节.与2021年相比,2022年水质状况有所提升.高锰酸盐指数、氨氮、总磷和溶解氧为湖南省主要污染指标.各驱动因子中,工业取水总量、城镇污水排放量、地区生产总值和城镇人口与水质指标的灰色关联度均值>0.8,是驱动不同城市地表水水质异质化的关键性因子,且与工业型城市的水环境质量关联紧密.
TEMPORAL AND SPATIAL VARIATION CHARACTERISTICS AND DRIVING FACTORS OF SURFACE WATER QUALITY IN HUNAN PROVINCE,CHINA
Regional water quality monitoring and cause analysis are important prerequisites for controlling water pollution.Based on the surface water quality data of 547 monitoring sections in Hunan Province from 2021 to 2022,and the GB 3838-2002 Surface Water Environmental Quality Standard,the temporal variation patterns and regional differences in surface water quality in Hunan Province were analyzed.The principal component analysis method was used to identify the main pollution indicators,and the grey relational analysis method was applied to explore the main factors driving the heterogeneity of water quality.The results showed that from 2021 to 2022,the overall surface water quality in Hunan Province was good,with the proportion of Class I to Ⅱ sections not less than 70%each month.The monthly variation characteristics of surface water quality in Hunan Province showed that the quality in summer was inferior to other seasons.Compared with 2021,the water quality improved in 2022.The main pollution indicators in Hunan Province are the permanganate index,ammonia nitrogen,total phosphorus,and dissolved oxygen.Among the various driving factors,the total industrial water intake,urban sewage discharge,gross regional product,and urban population had an average grey relational grade greater than 0.8 with water quality indicators,which are key factors driving the heterogeneity of surface water quality in different cities and closely related to the water environmental quality of industrial cities.

Hunan Provincewater quality assessmentdriving factorsprincipal component analysisgrey correlation degree

高雯媛、邹霖、朱俊毅、肖童觉、于奕、沈健林

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湖南省生态环境监测中心,长沙 410014

中国科学院亚热带农业生态研究所,长沙 410125

中国科学院大学资源与环境学院,北京 100094

湖南省 水质评价 驱动因子 主成分分析法 灰色关联度

国家重点研发计划项目湖南省杰出青年基金项目

2022YFD17007002022JJ10056

2024

环境工程
中冶建筑研究总院有限公司,中国环境科学学会环境工程分会

环境工程

CSTPCD
影响因子:0.958
ISSN:1000-8942
年,卷(期):2024.42(8)