Assessment of the physicochemical water quality of the Moulouya River, Morocco, using the SEQ-Eau index

Hmaidi, Abdellah El; Talhaoui, Abdelghani; Manssouri, Imad; Jaddi, Hajar; Ben-Daoud, Mohamed; Kasse, Zahra; Ouali, Abdelhadi El; Essahlaoui, Ali

doi:10.1007/s10661-021-09636-4

Cited by 11 publications

(4 citation statements)

References 13 publications

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“…The data used are represented in Table 1 according to 10 criteria, 9 independent variable inputs (pH, T°C, EC, O2-diss, NH4 + , NO3 -, SO4 2-, PO4 3and BOD5) and a single output, the system surface water quality assessment (QES-Water) [5] or the water quality index (WQI) [6].…”

Section: Fig 5 Synthesis Of the Used Methodology 3 Results And Discus...mentioning

confidence: 99%

“…Fig. 1 Moulouya watershed in northern Morocco [5,6] Because of the vastness and complexity of the Moulouya watershed's reliefs, the climate varies greatly from one region to another. The climate shifts from a Mediterranean type in the lower Moulouya valley to a rather cold continental climate in the Upper Moulouya and subarid with a Saharan propensity in the Middle Moulouya's high plateaus [7].…”

Section: Introductionmentioning

confidence: 99%

“…Fig. 2 Extract from the geological map of the Moulouya basin [5] The physico-chemical quality of the surface waters of Moulouya River has been already assessed by means of the global pollution index PI and by monitoring several parameters. The results showed that 86.4% of the stations do not exhibit any pollution [11].…”

Section: Introductionmentioning

confidence: 99%

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Unsupervised Classification of Water Quality Using Artificial Intelligence: The Case of the Moulouya Wadi's Surface Waters (NE, Morocco)

Manssouri¹,

Manssouri

Hmaidi

et al. 2023

JERA

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Due to its cruciality, water requires a high care to its physicochemical and microbiological properties to ensure the quality of several utilizations. The particles it carries are likely to be ingested, breathed, or come into contact with the skin. For the classification of the quality of surface water in the Moulouya River (NE, Morocco), this study presents many unsupervised classification methods. The overall quality of surface water in the Moulouya River in northeast Morocco was assessed using nine physicochemical parameters (pH, T°C, EC, O2-diss, NH4+, NO3-, SO42-, PO43-, and biological oxygen demand after 5 days (BOD5)) from March to August 2014. Over a 600-kilometer stretch, twenty-two sites were examined, from the river's source in the High Atlas to its mouth in the Mediterranean. During the first stage, three quality classes (excellent, good and poor) were defined by the calculation of the water quality index (WQI) and water quality evaluation system (QES-Water). In the second stage, the K-means algorithm, the fuzzy C-means algorithm and the self-organizing maps (SOM) of Kohonen were applied to the nine physicochemical parameters used as input variables for the model. The classification method used is capable of projecting high-dimensional data into a lower dimension, typically 2D. This nonlinear projection can be useful in classes’ analysis and their discovery. In terms of performance, the SOM classification showed very close results compared to the K-means and the fuzzy C-means algorithms, with only an insignificant difference across the three models, with SOM maps having a slight advantage.

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Section: Fig 5 Synthesis Of the Used Methodology 3 Results And Discus...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Unsupervised Classification of Water Quality Using Artificial Intelligence: The Case of the Moulouya Wadi's Surface Waters (NE, Morocco)

Manssouri¹,

Manssouri

Hmaidi

et al. 2023

JERA

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“…The new vulnerability index (Vi) is calculated according to Equation ( 2) and Table 1: The resulting intrinsic vulnerability map from the study area is developed according to the following sequential methodology (Figure 4) and characteristic vulnerability index classification (Table 2). Groundwater vulnerability refers to the potential of a groundwater system to be affected by contamination from the soil surface [26]. The choice of the more appropriate method to assess vulnerability is highly dependent on the objective and scope of a particular study, data availability, and especially, the user's cost and time [27,28].…”

Section: Groundwater Vulnerability Assessmentmentioning

confidence: 99%

Groundwater Vulnerability and Potentially Toxic Elements Associated with the Iron Mining District of Ouixane (Northeast of Morocco)

Khafouri

Talbi

Abdelouas

et al. 2022

Water

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This study aims to investigate the groundwater vulnerability concerning potentially toxic elements in the vicinity of the abandoned iron mine of Ouixane (Morocco). A modified DRASTIC method (DRSTI) is proposed with satisfactory results. High vulnerability zones represent 40% of the study area, while medium and low vulnerability represent, respectively, 42% and 18% of the study area. These results have been validated by groundwater geochemical analyses of potentially toxic elements carried out in the framework of previous studies in the same area. Thus, the superposition of the waste rock and tailings map with the vulnerability map showed that the latter is located in areas of high to medium vulnerability and therefore constitutes the main cause of the deterioration of the geochemical quality of groundwater. Otherwise, the vulnerability method showed that the main parameters that significantly affect the vulnerability are: the depth of water (D), net recharge (R), and the unsaturated zone (I), while the other parameters do not significantly affect the model used and do not have much influence on the results of the vulnerability assessment. The method used allowed us to locate the most vulnerable areas to potentially metallic toxic elements pollution resulting from the abandoned iron mine of Ouixane, and it constitutes a tool for decision support and for developing effective action plans to mitigate and monitor the effects of the transfer of potentially toxic elements pollution to groundwater.

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Comparative evaluation of spatiotemporal variations of surface water quality using water quality indices and GIS

Uslu,

Dugan,

El Hmaidi

et al. 2024

Earth Sci Inform

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There is a need for a comprehensive comparative analysis of spatiotemporal variations in surface water quality, particularly in regions facing multiple pollution sources. While previous research has explored the use of individual water quality indices (WQIs), there is limited understanding of how different WQIs perform in assessing water quality dynamics in complex environmental settings. The objective of this study is to evaluate the effectiveness of three WQIs (Canadian Council of Ministers of the Environment (CCME), National Sanitation Foundation (NSF) and System for Evaluation of the Quality of rivers (SEQ-Eau) and a national water quality regulation in assessing water quality dynamics. The pilot study area is the Acısu Creek in Antalya City of Turkey, where agricultural practices and discharge of treated wastewater effluents impair the water quality. A year-long intensive monitoring study was conducted includig on-site measurements, analysis of numerous physicochemical and bacteriological parameters. The CCME and SEQ-Eau indices classified water quality as excellent/good at the upstream, gradually deteriorating to very poor downstream, showing a strong correlation. However, the NSF index displayed less accuracy in evaluating water quality for certain monitoring stations/sessions due to eclipsing and rigidity problems. The regulatory approach, which categorized water quality as either moderate or good for different sampling sessions/stations, was also found less accurate. The novelty of this study lies in its holistic approach to identify methodological considerations that influence the performance of WQIs. Incorporating statistical analysis, artificial intelligence or multi-criteria decision-making methods into WQIs is recommended for enhanced surface water quality assessment and management strategies.

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Assessment of the physicochemical water quality of the Moulouya River, Morocco, using the SEQ-Eau index

Cited by 11 publications

References 13 publications

Unsupervised Classification of Water Quality Using Artificial Intelligence: The Case of the Moulouya Wadi's Surface Waters (NE, Morocco)

Unsupervised Classification of Water Quality Using Artificial Intelligence: The Case of the Moulouya Wadi's Surface Waters (NE, Morocco)

Groundwater Vulnerability and Potentially Toxic Elements Associated with the Iron Mining District of Ouixane (Northeast of Morocco)

Comparative evaluation of spatiotemporal variations of surface water quality using water quality indices and GIS

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