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1 2024

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Spatiotemporal Interpolation of Water Quality Index and Nitrates Using ArcGIS Pro for Surface Water Quality Modeling in the Oum Er-Rabia Watershed

Ouhakki Hicham, El Fallah Kamal, El Mejdoub Nouredine

Ecological Engineering & Environmental Technology

2024

Vol. 25, iss. 5

312--323

This study aims to create complete surface water quality maps for the Oum Er Rabia watershed by predicting nitrate (NO3 - ) and water quality index (WQI) values at unsampled locations. Utilizing a combination of NO3 - , IQE data, and ArcGIS Pro software. Water samples were collected from 40 stations across the basin during twelve campaigns conducted in the winter and summer of 2021 and 2022. The database contains the analysis results of 12 parameters measured in 480 samples. The method used to model water quality is interpolation with ArcGIS Pro. The distribution map of nitrate values for all samples shows concentrations ranging from 0.26 to 38.89 mg/L. These values are lower than the admissible level recommended by the Moroccan standard for drinking water (50 mg/L). The resulting map of the modeling shows higher NO3 - concentrations in summur than in winter. The resulting map of the WQI modeling shows that water quality is excellent in most of the Oum Er-Rbia watershed, with the majority of the area falling into the “good” and “excellent” categories. The water quality deterio-rates in certain parts, especially at stations SS3, SS4, SS5, SS8, and PS9, where the water is of poor quality. In the central and eastern parts, the presence of excessively high ammonium concentrations has significantly compromised the water quality, leading to heavy pollution. Exceeding Moroccan drinking water standards, these observed levels likely stem from human activities. Accurate water quality predictions with ArcGIS Pro require considering data quality, historical trends, and spatiotemporal variations. Understanding these limitations ensures responsible and effective tool use. The study concluded that water pollution could be due to proximity to industrial and urban areas. This study’s uniqueness lies in integrating the WQI, NO3 -, and ArcGIS-Pro into maps. This approach makes information accessible to the public and useful for decision-makers to take action at all watershed points.