Assessment of potential contamination of groundwater in abandoned mining region of Ben Taieb, Northeastern Morocco using statistical studies

Gueddari, Hicham; Akodad, Mustapha; Baghour, Mourad; Moumen, Abdelmajid; Skalli, Alí; Chahban, Mohamed; Azizi, Ghizlane; Hmeid, Hanane Ait; Maach, Mustapha; Riouchi, Riouchi; Yousfi, Yassine El

doi:10.53730/ijhs.v6ns3.6694

Cited by 4 publications

(6 citation statements)

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“…Their results showed that the pollution of the wells studied were characterized by salinization phenomena and very mineralized. The results of a study conducted by [77] in regions of the Rif found that the water from the wells in the Ben Taib region did not significantly exceed Moroccan or world standards.…”

Section: Analysis Of Artificial Neural Networkmentioning

confidence: 96%

Assessment and Prediction of the Water Quality Index for the Groundwater of the Ghiss-Nekkor (Al Hoceima, Northeastern Morocco)

et al. 2022

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Water quality index (WQI) is the primary method applied to characterize water quality in the world. The current study employed the statistical analysis and multilayer perceptron (MLP) approaches for predicting groundwater quality in the Ghiss-Nekkor aquifer, northeast of Al Hoceima, Morocco. Fifty sampled groundwater were identified and analyzed for major anions and cations throughout May 2019. Several physicochemical parameters of all the samples were identified in this investigation, such as TDS, pH, EC, Na, K, Ca, Mg, HCO3, NO3, Br, SO4, and Cl. The entropy-weighted groundwater quality index (EWQI) was calculated from these parameters. The WQI procedure determined the suitability of groundwater for consumption. The WQI value varied from 90.98 to 337.28. The EC, TDS, WQI, and Cl- spatial distribution showed that EC and Cl- are associated with poor groundwater quality. A single sample (W16) represented unsuitable water for drinking purposes and offered a WQI value of 337.28, indicating poor drinking quality due to seawater intrusion, overexploitation, and harsh weather conditions. The majority of the values obtained for the parameters exceeded the recommended limit of the World Health Organization (WHO)’s guidelines for consumption. The findings show that using parameters is a straightforward method for predicting water quality indexes with sufficient and suitable precision. The MLP model shows good predictive performances in terms of the coefficient of determination R2, mean absolute error (MAE), and root-mean-square error (RMSE) with values of 0.9885, 5.8031, and 4.7211, respectively. The ANN approach was applied to develop a model that can accurately predict WQI utilizing mineralization, TH, NO3, and NO2 as inputs. The MAE for the model’s performance was calculated to be 4.72. A Bland–Altman test was used to validate that the model is suitable. Following the test, it was determined that the model is appropriate for predicting WQI, with an error of just 0.1%.

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Section: Analysis Of Artificial Neural Networkmentioning

confidence: 96%

Assessment and Prediction of the Water Quality Index for the Groundwater of the Ghiss-Nekkor (Al Hoceima, Northeastern Morocco)

et al. 2022

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“…In addition, it is because ions that are free to move about in an electric current are present in the medium. [3,5,6,28]. The readings vary from 880 to 13760 s.cm-2, which is 30 percent higher than the threshold established by the WHO (Fig.…”

Section: Conductivitymentioning

confidence: 73%

“…The chemistry analysis for the significant ions was carried out by the protocols outlined below: -As specified by the international standard ISO 17294-2:2016, nitrate measurement is used to determine the water quality of the sampling water. The analysis of certain chemical parameters as Nitrites, nitrates, phosphates on of the sampled waters were carried out using the spectrophotometer [20][21][22][23].…”

Section: Methodsmentioning

confidence: 99%

“…This resource is finds in several phases in the hydrologic cycle, the water cycle comprises water in the atmosphere, the oceans, the landscape and the subsurface [1] and can be affect by many contamination due to the various human activities including industrialization and agricultural practices [2]. However, it may also be a source of illness since it is a transporter of potentially hazardous substances [3][4][5], such as pathogenic microorganisms and chemical compounds. It can make it a possible vector for disease transmission [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Study of groundwater pollution of irrigated Ain Zohra commune (North-eastern Morocco) by nitrates using GIS. Understanding the Climate–Water–Energy–Food Nexus and the Transition Towards a Circular Economy: The Case of Morocco

et al. 2023

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The contamination of Morocco’s water resources comes from three sources as like agriculture, industry, and urbanization. Within this project’s scope, we investigated groundwater contamination in the suburban community of Ain Zohra (located in the Mediterranean zone, Driouch province, eastern part of Morocco). The Zohra area is limited in east part by the rural municipality of Ain Zohra, in the north part by Driouch city and in the southern and western parts is bounded by the Boubker rural municipality. In July 2021, 21 samples were taken from the field (20 wells and 1 spring). In general, the results of this study showed that some water wells are highly mineralized as the conductivity is far above the drinking water standard. Every well’s pH is basic. Nitrate contamination in two places shows that the permeability of city soil affects the groundwater. The nitrate content might be higher than groundwater, which has 200 mg/l. In certain wells, groundwater contamination has raised organic matter levels above drinking water regulations. The water quality maps of some parameters were obtained based on application of Geographic Information System (GIS) for the study area.

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“…As compared to surface water, groundwater is currently the purest drinking water source [ 19 ]. Groundwater’s chemical quality has been altered due to the extensive usage of aquifers.…”

Section: Introductionmentioning

confidence: 99%

Pollution Vulnerability of the Ghiss Nekkor Alluvial Aquifer in Al-Hoceima (Morocco), Using GIS-Based DRASTIC Model

Yousfi

Himi

Aqnouy

et al. 2023

IJERPH

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Groundwater resources of the alluvial aquifer Ghiss Nekkor, which covers an area of 100 km2, are the main source of domestic and agricultural freshwater supply in the region of Al Hoceima in Morocco. Due to human activities (overexploitation, increase in agricultural activity), this alluvial aquifer has become very sensitive to chemical pollution. The principal objective of this current study is to develop and implement a calibration method to assess, map, and estimate the vulnerability of the Ghiss Nekkor alluvial aquifer to pollution risk. In this work, the GIS-based DRASTIC model was used to estimate the inherent vulnerability to contamination of the Ghiss Nekkor alluvial aquifer with seven standard hydrogeological parameters. Nitrate (NO3) and electrical conductivity (EC) data were used to validate the DRASTIC map. The results of the vulnerability map analysis show that the vulnerability to contaminants varies from non-existent in the southwestern part of the plain (7.3% of the total area), to very high (14.5%). The vulnerability is moderate in the central and northeastern areas (26.9%), while it is high in the other areas (17.5%). Furthermore, the most sensitive areas are mainly concentrated near the coastal strip and the central plain on both sides of the Nekkor River. In these areas, the NO3 and EC values are above the maximum allowable limit of the World Health Organization. The results suggest that the DRASTIC model can be an effective tool for decision-makers concerned about managing groundwater sustainability.

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Assessment of potential contamination of groundwater in abandoned mining region of Ben Taieb, Northeastern Morocco using statistical studies

Cited by 4 publications

References 0 publications

Assessment and Prediction of the Water Quality Index for the Groundwater of the Ghiss-Nekkor (Al Hoceima, Northeastern Morocco)

Assessment and Prediction of the Water Quality Index for the Groundwater of the Ghiss-Nekkor (Al Hoceima, Northeastern Morocco)

Study of groundwater pollution of irrigated Ain Zohra commune (North-eastern Morocco) by nitrates using GIS. Understanding the Climate–Water–Energy–Food Nexus and the Transition Towards a Circular Economy: The Case of Morocco

Pollution Vulnerability of the Ghiss Nekkor Alluvial Aquifer in Al-Hoceima (Morocco), Using GIS-Based DRASTIC Model

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