延安市枯水期地表水污染源识别及贡献率研究

Identification and Contribution Analysis of Surface Water Pollution During Withered Water Period in Yan′an City

定量解析污染源是有效控制水污染的基础,研究综合利用数理统计、GIS空间分析和主成分分析-绝对主成分得分-多元线性回归模型(PCA-APCS-MLR)等方法,提出了一种数据预处理方式,对2018-2020年延安市地表水系内49个采样点的23项水质关键指标进行污染源及其贡献率定量分析。结果表明:污染源以营养物污染(54.02%)及重金属污染(17.97%)为主,营养物污染对各水质指标的平均贡献率(52.70%)大于重金属污染(47.30%),营养物污染主要对延安市东北部影响较大,重金属污染对延河、秀延河上游地区影响较大。相比原始数据预处理方法的分析结果,该结果更具有地区代表性,可对延安市地表水污染治理提供数据支持,为地表水水质保护政策的制定提供科学参考。

Clarifying the pollution status and quantitatively identifying the pollution sources are an important foundation for effective control of surface water pollution.This paper proposes a data preprocessing method by comprehensively uses mathematical statistics,GIS spatial analysis,and principal component analysis-absolute principal component score-multiple linear regression(PCA-APCS-MLR)model and other methods.Using this data preprocessing method,a quantitative analysis of pollution sources and their contribution rates was conducted on 23 key water quality indicators at 49 sampling points in the surface water system of Yan'an City from 2018 to 2020.The results indicate:①The main sources of surface water pollution are nutrient pollution(54.02%)and heavy metal pollution(17.97%).②The average contribution rate of nutrient pollution to various water quality indicators(52.70%)is greater than that of heavy metal pollution(47.30%).③Nutrient pollution has a greater impact on the northeastern part of Yan'an City,and heavy metal pollution has a greater impact on the upper reaches of Yan River and Xiuyan River.Compared with the traditional data preprocessing method,the analysis results of the data preprocessing method proposed in this paper are more regionally representative which can provide a data support for the treatment of surface water pollution in Yan'an City and a scientific reference for the designation of surface water quality protection policies.