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

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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.

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Abbreviations

AI:

artificial intelligence

ALWQI:

aquatic life WQI

ANOVA:

analysis of variance

ANRH:

Agence Nationale des Resources Hydrauliques

BCWQI:

British Columbia WQI

BH:

Beni Haroun

BOD:

biochemical oxygen demand

CA:

cluster analysis

CCME-WQI:

Canadian Council Ministers Environments WQI

CEC:

Commission of European Committees

COD:

chemical oxygen demand

CWQI:

Canadian WQI

DA:

discriminant analysis

DO:

dissolved oxygen

DWAF:

Department of Water Affairs and Forestry

DWQI:

drinking WQI

EC:

electrical conductivity

FA:

factor analysis

FAO:

Food and Agriculture Organization

InWQI:

industrial WQI

IWQI:

irrigation WQI

KMO:

Kaiser-Meyer-Olkin

NSF-WQI:

National Sanitation Foundation WQI

OLS:

ordinary least square

PCA:

principal component analysis

PCs:

principal components

pH:

power of hydrogen

ST1:

Ain Smara station

ST2:

Menia station

ST3:

Grarem station

T:

water temperature

TSS:

total suspended solid

VFs:

Varifactors

WE:

Wadi Endja

WHO:

World Health Organization

WQI:

Water Quality Index

WR:

Wadi Rhumel

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Acknowledgments

The authors would like to thank Agence Nationale des Resources Hydrauliques (ANRH) for their assistance in providing the necessary data. They also are grateful to Professor Abderrahmane BOUDOUKHA of the University of Batna, Algeria, for his pertinent information and valuable advice.

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Authors and Affiliations

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

    Ahmed Amin Soltani, Mahmoud Hasbaia & Sara Zeroual

  2. Hydraulics Department, Ecole Nationale Polytechnique d’Alger, Algiers, Algeria

    Abdelmalek Bermad

  3. Hydraulics Department, Engineering Faculty, Badji Mokhtar University, Annaba, Algeria

    Hamouda Boutaghane

  4. Department of Operations Management & Business Statistics, College of Economics & Political Science, Sultan Qaboos University, P.O. Box 20, PC 123, Muscat, Al Khoud, Oman

    Amar Oukil

  5. Water Research Center, Department of Earth Sciences, College of Science, Sultan Qaboos University, P.O. Box 36, PC 123, Muscat, Al Khoud, Oman

    Osman Abdalla

  6. Université des Sciences et de la Technologie Houari Boumediene, Algiers, Algeria

    Rafik Oulebsir

  7. Ecole National des Travaux Publics, Algiers, Algeria

    Abdelouahab Lefkir

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  1. Ahmed Amin Soltani
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Soltani, A.A., Bermad, A., Boutaghane, H. et al. An integrated approach for assessing surface water quality: Case of Beni Haroun dam (Northeast Algeria). Environ Monit Assess 192, 630 (2020). https://doi.org/10.1007/s10661-020-08572-z

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