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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.
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Tom
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312--323
Opis fizyczny
Bibliogr. 36 poz., rys., tab.
Twórcy
autor
- Laboratory of Organic Chemistry, Catalysis and Environment, Department of Chemistry, Faculty of Science, University Ibn Toufail BP 133-14000 Kenitra, Morocco
autor
- Laboratory of Natural Resources and Sustainable Development, Department of Biology, Faculty of Science, University Ibn Toufail, BP 133-14000, Kenitra, Morocco
autor
- Laboratory of Organic Chemistry, Catalysis and Environment, Department of Chemistry, Faculty of Science, University Ibn Toufail BP 133-14000 Kenitra, Morocco
Bibliografia
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- 10. Das, A., Joardar, M., De, A., Mridha D., Chowdhury, N. R., Khan, M.T.B.K., Chakrabartty P., Roychowdhury T. 2021. Pollution index and health risk assessment of arsenic through different groundwater sources and its load on soil-paddy-rice system in a part of Murshidabad district of West Bengal, India. Groundwater for Sustainable Development, 15, 100652. doi:10.1016/j.gsd.2021.100652
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- 12. Emenike, P.G.C., Tenebe I.T., Neris J.B., Omole, D.O., Afolayan, O., Okeke C.U., Emenike I.K. 2020. An integrated assessment of land-use change impact, seasonal variation of pollution indices and human health risk of selected toxic elements in sediments of River Atuwara, Nigeria. Environmental Pollution, 265, 114795. doi:10.1016/j.envpol.2020.114795
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- 17. Islam, A.R.M.T., Talukdar S., Mahato S., Ziaul S., Eibek K.U., Akhter S., Pham Q.B., Mohammadi B., Karimi F., Linh N.T.T. 2021. Machine learning algorithm-based risk assessment of riparian wetlands in Padma River Basin of Northwest Bangladesh. Environmental Science and Pollution Research, 28(26), 34450–71. doi:10.1007/s11356-021-12806-z
- 18. Kaliraj, S., Adhikari K., Dharumarajan S., Lalitha M., Kumar N. 2024.Chapter 3 - Remote sensing and geographic information system applications in mapping and assessment of soil resources. 25–41, in Remote Sensing of Soils, édité par S. Dharumarajan, S. Kaliraj, K. Adhikari, M. Lalitha, N. Kumar. Elsevier.
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- 23. Markad, A.T., Landge, A.T., Nayak, B.B., Inamdar, A.B., Mishra, A.K. 2021. A multivariate statistical approach for the evaluation of spatial and temporal dynamics of surface water quality from the small reservoir located in the drought-prone area of South-West India: a case study of Tiru reservoir (India). Environmental Science and Pollution Research, 28(24), 31013–31. doi:10.1007/s11356-020-12001-6
- 24. Mishra V., Shah H.L. 2018. Hydroclimatological perspective of the kerala flood of 2018. Journal of the Geological Society of India, 92(5), 645–50. doi:10.1007/s12594-018-1079-3
- 25. Mukherjee, S., Paramanik M. 2022. Water quality and pollution status of River Nunia, at Asansol, West Bengal.
- 26. Ouhamdouch, S., Bahir M., Carreira P.M. 2018. Impact du changement climatique sur la ressource en eau en milieu semi-aride : exemple du bassin d’Essaouira (Maroc). Revue des sciences de l’eau, 31(1), 13–27. doi:10.7202/1047050ar
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- 28. Pervez, S., Dugga, P., Siddiqui, M.N., Bano, S., Verma, M., Candeias, C., Mishra, A., Verma, S. R., Tamrakar, A., Karbhal, I., Deb, M.K., Shrivas, K., Pervez, Y., Jha, R.K. 2021. Sources and health risk assessment of potentially toxic elements in groundwater in the mineral-rich tribal belt of Bastar, Central India. Groundwater for Sustainable Development, 14, 100628. doi:10.1016/j.gsd.2021.100628
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- 30. Ruhela, M., Paritosh, K., Varun, T., Ahamad F., Ram K. 2018. Assessment of water quality of River Ganga at Haridwar with reference to Water Quality Index. Environment Conservation Journal, 19. doi:10.36953/ECJ.2018.19306
- 31. Şener, Ş., Şener, E., Davraz, A. 2017. Evaluation of water quality using water quality index (WQI) method and GIS in Aksu River (SW-Turkey). Science of The Total Environment, 584–585, 131-44. doi:10.1016/j.scitotenv.2017.01.102
- 32. Strohmeier, S., López, P., Haddad, M., Nangia, V., Karrou, M., Montanaro, G., Boudhar, A., Linés, C., Veldkamp, T., Sterk G. 2020. Surface Runoff and Drought Assessment Using Global Water Resources Datasets - from Oum Er Rbia Basin to the Moroccan Country Scale. Water Resources Management, 34(7), 2117–33. doi:10.1007/s11269-019-02251-6
- 33. Supardi, I., Abdullah, N.M., Ismail, B., Tugi, A., Opaluwa, Y. 2023. Generating water quality maps of Klang River based on Geographic Information System (GIS) and Water Quality Index (WQI). International Journal of Sustainable Construction Engineering and Technology, 14. doi:10.30880/ijscet.2023.14.03.034
- 34. Wu, Z., Wang, X., Chen, Y., Cai, Y., Deng, J. 2018. Assessing river water quality using water quality index in Lake Taihu Basin, China. Science of The Total Environment, 612, 914–22. doi:10.1016/j.scitotenv.2017.08.293
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- 36. Zheng, W., Wang, S., Kangda, T., Lei, Y. 2020. Nitrate accumulation and leaching potential is controlled by land-use and extreme precipitation in a headwater catchment in the North China Plain. Science of The Total Environment 707, 136168. doi:10.1016/j.scitotenv.2019.136168
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cf6aab53-8c01-408b-af34-8158321a677c