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一种评估地表水水质的综合方法:贝尼·哈伦大坝(阿尔及利亚东北部)案例

An integrated approach for assessing surface water quality: Case of Beni Haroun dam (Northeast Algeria).

作者信息

Soltani Ahmed Amin, Bermad Abdelmalek, Boutaghane Hamouda, Oukil Amar, Abdalla Osman, Hasbaia Mahmoud, Oulebsir Rafik, Zeroual Sara, Lefkir Abdelouahab

机构信息

VESDD Laboratory, Hydraulic Department, University of M'sila, P.O. Box 166, 28000, Ichebilia, M'sila, Algeria.

Hydraulics Department, Ecole Nationale Polytechnique d'Alger, Algiers, Algeria.

出版信息

Environ Monit Assess. 2020 Sep 9;192(10):630. doi: 10.1007/s10661-020-08572-z.

Abstract

In this paper, we use an integrated approach to carry out a comprehensive evaluation of water quality in the Beni Haroun (BH) dam, the largest surface water resource in Algeria. Several techniques have been employed under the same framework, including the Canadian Council Ministers Environment Water Quality Index (CCME-WQI), principal component analysis and factor analysis (PCA/FA), the K-means clustering, and the ordinary least square (OLS) analysis. A data set of 22 physicochemical parameters has been collected, over a period of 11 years, from three sampling stations: Ain Smara (ST1) and Menia (ST2), both located upstream of "Wadi Rhumel," and BH dam station (ST3), located at the dam site. The PCA/FA enables the identification of seven key factors that influence significantly BH dam water quality. The average values of CCME indices at the BH dam were 17, 40, 42, and 32 for drinking, irrigation, industry, and aquatic life purposes, respectively, which indicate poor water quality, according to the CCME categorization scheme. Besides, the K-means algorithm has been proven to be a very useful machine learning tool to detect that the major source of BH dam pollution is "Wadi Rhumel." Finally, OLS analysis, along with the Mann-Kendall test, highlighted the positive trend of BH dam's water quality.

摘要

在本文中,我们采用综合方法对阿尔及利亚最大的地表水资源贝尼·哈伦(BH)大坝的水质进行全面评估。在同一框架下采用了多种技术,包括加拿大环境部长理事会水质指数(CCME-WQI)、主成分分析和因子分析(PCA/FA)、K均值聚类以及普通最小二乘法(OLS)分析。在11年的时间里,从三个采样站收集了包含22个理化参数的数据集:位于“瓦迪鲁梅尔”上游的艾因·斯马拉(ST1)和梅尼亚(ST2),以及位于大坝 site 的BH大坝站(ST3)。PCA/FA能够识别出对BH大坝水质有显著影响的七个关键因素。根据CCME分类方案,BH大坝用于饮用、灌溉、工业和水生生物的CCME指数平均值分别为17、40、42和32,这表明水质较差。此外,K均值算法已被证明是一种非常有用的机器学习工具,可检测出BH大坝污染的主要来源是“瓦迪鲁梅尔”。最后,OLS分析与曼-肯德尔检验一起突出了BH大坝水质的积极趋势。

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