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This study focuses on mapping the groundwater’s vulnerability to pollution in the region of Ouargla, located in the North-East of the northern Sahara, exposed to potential risks of alteration. By applying the methods (GOD, DRASTIC, and SINTACS), coupled with a Geographic Information System (GIS), we were able to identify a medium to high vulnerability trend. In light of the results recorded, the DRASTIC and SINTACS methods prove to be more suitable for our study region. This makes it possible to highlight the recharge zones and land use as being the most vulnerable in the territory studied. The GOD method presents a strong vulnerability trend over 77.02% of the study area. Such a result is directly related to the depth of the water table. It can therefore be argued that this method is far from being representative of the reality on the ground because of these very heterogeneous characteristics.
Czasopismo
Rocznik
Tom
Strony
50--58
Opis fizyczny
Bibliogr. 26 poz., rys., tab., wykr.
Twórcy
autor
- Laboratory of Biogeochemistry of desert environments, Faculty of Natural and Life Sciences, Kasdi Marbah University, Ouargla, Algeria
autor
- Laboratory of Biogeochemistry of desert environments, Faculty of Natural and Life Sciences, Kasdi Marbah University, Ouargla, Algeria
- Ouargla Higher Normal School, Algeria
autor
- School of Health and Environmental Studies, Hamdan Bin Mohammed Smart University, Dubai, UAE
Bibliografia
- 1. Abunada, Z., Kishawi, Y., Alslaibi, T. M., Kaheil, N. & Mittelstet, A. (2021). The application of SWAT-GIS tool to improve the recharge factor in the DRASTIC framework: Case study. Journal of Hydrology, 592, [125613]. DOI:10.1016/j.jhydrol.2020.125613
- 2. ANRH. (2018). Données des fiches techniques des forages de la Wilaya de Ouargla.
- 3. ANRH. (2022). Inventaire des forages de la Wilaya de Ouargla.
- 4. Awawdeh, M., Al-Kharabsheh, N., Obeidat M. & Awawdeh, M. (2020) Groundwater vulnerability assessment using modified SINTACS model in Wadi Shueib, Jordan, Annals of GIS, 26:4, 377-394. DOI:10.1080/19475683.2020.1773535
- 5. Bera, A., Mukhopadhyay, B. P., Chowdhury, P., Ghosh, A. & Biswas, S. (2021). Groundwater vulnerability assessment using GIS-based DRASTIC model in Nangasai River Basin, India with special emphasis on agricultural contamination. Ecotoxicology and Environmental Safety, 214, 112085. DOI:10.1016/j.ecoenv.2021.112085
- 6. Chakraborty, B., Roy, S., Bera, A., Adhikary, P. P., Bera, B., Sengupta, D., Bhunia, G. S. & Shit, P. K. (2022). Groundwater vulnerability assessment using GIS-based DRASTIC model in the upper catchment of Dwarakeshwar river basin, West Bengal, India. Environmental Earth Sciences, 81,1, pp.1–15. DOI:10.1007/s12665-021-10002-3
- 7. Charikh, M., Slimani, R., Hamdi-aïssa, B., Bouadjila, O. & Hassaine, A. (2022). Evaluation of Arid Soil Landscapes Permeability in Algerian Sahara. Al-Qadisiyah Journal for Agricul-ture Sciences (QJAS), 12,2, pp. 12–18. DOI:10.33794/qjas.2022.134247.1050
- 8. El Baba, M. & Kayastha, P. (2022). Groundwater vulnerability, water quality, and risk assessment in a semi-arid region: a case study from the Dier al-Balah Governorate, Gaza Strip. Modeling Earth Systems and Environment, pp.1–16. DOI:10.3390/w12010262
- 9. Elzain, H. E., Chung, S. Y., Senapathi, V., Sekar, S., Lee, S. Y., Roy, P. D., Hassan, A. & Sabarathinam, C. (2022). Comparative study of machine learning models for evaluating groundwater vulnerability to nitrate contamination. Ecotoxicology and Environmental Safety, 229, 113061. DOI:10.1016/j.ecoenv.2021.113061
- 10. Fannakh, A. & Farsang, A. (2022). DRASTIC, GOD, and SI approaches for assessing groundwater vulnerability to pollution: a review. Environ Sci Eur 34, 77. DOI:10.1186/s12302-022-00646-8
- 11. Gao, Y.Y., Qian, H., Zhou, Y.H., Chen, J. Wang, H.K., Ren, W.H. & Qu, W.G. (2022). Cumulative health risk assessment of multiple chemicals in groundwater based on determinis-tic and Monte Carlo models in a large semiarid basin. J. Clean. Prod., 352. DOI:10.1016/j.jclepro.2022.131567.
- 12. Gharekhani, M., Nadiri, A. A., Khatibi, R., Sadeghfam, S. & Moghaddam, A. A. (2022). A study of uncertainties in groundwater vulnerability modelling using Bayesian model averaging (BMA). Journal of Environmental Management, 303, 114168. DOI:10.1016/j.jenvman.2021.114168
- 13. Goyal, D., Haritash, A. K. & Singh, S. K. (2021). A comprehensive review of groundwater vulnerability assessment using index-based, modelling, and coupling methods. Journal of Environmental Management, 296, 113161. DOI:10.1016/j.jenvman.2021.113161
- 14. Griffel, L. M., Toba, A-L., Paudel, R., Lin, Y., Hartley D. S. & Langholtz, M. (2022). A multi-criteria land suitability assessment of field allocation decisions for switchgrass, I, 136, 108617. DOI:10.1016/j.ecolind.2022.108617.
- 15. Hamdi-Aïssa, B., & Girard, M.-C. (2000). Utilisation de la télédétection en régions sahariennes, pour l’analyse et l’extrapolation spatiale des pédopaysages. Science et Changements Planétaires/Sécheresse, 11,3, pp. 179–188.
- 16. Hamza, M.H. & Chmit, M. (2022). "GIS-Based Planning and Web/3D Web GIS Applications for the Analysis and Management of MV/LV Electrical Networks (A Case Study in Tuni-sia)" Applied Sciences 12, no. 5: 2554. DOI:10.3390/app12052554
- 17. Kirlas, M.C., Karpouzos, D.Κ., Georgiou, P.E. & Katsifarakis, K. L. (2022). A comparative study of groundwater vulnerability methods in a porous aquifer in Greece. Appl Water Sci 12, 123.DOI:10.1007/s13201-022-01651-1.
- 18. Qian, H. Chen, J. & Howard, K. W.F. (2020). Assessing groundwater pollution and potential remediation processes in a multi-layer aquifer system. Environ. Pollut., 263. DOI:10.1016/j.envpol.2020.114669.
- 19. Saranya, T. & Saravanan, S. (2022). Assessment of groundwater vulnerability using analytical hierarchy process and evidential belief function with DRASTIC parameters, Cuddalore, India. Int. J. Environ. Sci. Technol. DOI:10.1007/s13762-022-03944-z
- 20. Sarkar, M. & Pal, S.C. (2021). Application of DRASTIC and Modified DRASTIC Models for Model-ing Groundwater Vulnerability of Malda District in West Bengal. J Indian Soc Remote Sens, 49, pp. 1201–1219. DOI:10.1007/s12524-020-01176-7
- 21. Slimani, R, & Guendouz, A. (2015). Groundwater vulnerability and risk mapping for the Phreatic aquifer in the Ouargla Oasis of Algerian Sahara using GIS and GOD method. Inter-national Journal of AgriculturalScience and Research (IJASR). ISSN(P): 2250-0057; ISSN(E): 2321-0087. Vol. 5, Issue 3, Jun 2015, pp. 149-158 © TJPRC Pvt. Ltd.
- 22. Slimani, Rabia, Guendouz, A., Trolard, F., Moulla, A. S., Hamdi-Aïssa, B. & Bourrié, G. (2017). Identification of dominant hydrogeochemical processes for groundwaters in the Alge-rian Sahara supported by inverse modeling of chemical and isotopic data. Hydrology and Earth System Sciences, 21, 3, pp.1669–1691. DOI:10.5194/hess-21-1669-2017, 2017.
- 23. Stigter, T. Y., Ribeiro, L., & Dill, A. M. M. C. (2006). Application of a groundwater quality index as an assessment and communication tool in agro-environmental policies–Two Portuguese case studies. Journal of Hydrology, 327, 3–4, pp. 578–591. DOI:10.1016/j.jhydrol.2005.12.001
- 24. UNESCO. (2020). Rapport mondial des Nations Unies sur la mise en valeur des ressources en eau 2020: l’eau et les changements climatiques. UNESCO. https://unesdoc.unesco.org/notice?id=p::usmarcdef_0000372941
- 25. United Nations. (2022). The United Nations World Water Development Report 2022: groundwater: making the invisible visible. UNESCO. https://unesdoc.unesco.org/notice?id=p::usmarcdef_0000380721.
- 26. Zhang, Q., Qian, H., Xu, P., Li, W., Feng, W., & Liu, R. (2021). Effect of hydrogeological conditions on groundwater nitrate pollution and human health risk assessment of nitrate in Jiaokou Irrigation District. Journal of Cleaner Production, 298, 126783. DOI:10.1016/j.jclepro.2021.126783.
Uwagi
PL
Opracowane ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3e1a82e3-3b3a-4c0d-92d0-8b89448413bd