Mapping Favorable Groundwater Potential Recharge Areas Using a GIS-Based Analytical Hierarchical Process – A Case Study of Ferkla Oasis, Morocco

• Autorzy: Ismail Ait Lahssaine , Lahcen Kabiri , Badre Messaoudi , Badre Essafraoui , Mohamed El Ouali , Lamya Ouali , Jean Albergel , Meryem El Amraoui , Amina Kassou , Essahlaoui Ali

Identyfikatory

DOI

10.12912/27197050/182842

• Języki publikacji: EN

Abstrakty

EN

In the Ferkla Oasis, much like in numerous other oases across the southeastern region of Morocco, a range of socioeconomic and environmental challenges are intricately linked to the inadequate management of water resources. One proposed remedy to address these concerns is the implementation of artificial aquifer recharge, which stands as an alternative strategy to safeguard the crucial oasis ecosystems. Thus, to evaluate the viability of this method in promoting sustainable water resource usage, it becomes imperative to delineate groundwater recharge potential zones (GRPZs). This study aims to achieve this objective by mapping GRPZs within the Ferkla Oasis, employing a fusion of the analytical hierarchy process (AHP), geospatial information derived from remote sensing (RS), and geographic information system (GIS) technologies. In pursuit of this goal, an array of geological, topographical, pedological, hydrological, and climatic criteria have been meticulously selected, classified, and assigned weights following their relevance to water infiltration suitability. This comprehensive approach culminates in the generation of seven thematic maps: slope, lineament density, lithology, soil type, drainage density, land use/land cover, and rainfall distribution. Through the integration of these aforementioned maps, a tripartite classification of potential GRPZs emerges, comprising low, medium, and high categories. The findings underscore the distribution: 30% of the total study area exhibits a low potential for GRPZs, 50% of the total land area is characterized as having medium potential GRPZs, while the remaining 20% is designated as high potential GRPZs. These outcomes have been substantiated through validation against piezometric levels, which have been ascertained through recent field surveys. Consequently, these results stand as a testament to the efficacy of the presented approach as a robust decision-making tool. The approach effectively facilitates the establishment of conditions conducive to viable artificial recharge, thereby offering a means to safeguard the groundwater reservoirs that sustain the fragile oasis environments.

Słowa kluczowe

EN

groundwater reservoirs; safeguard; artificial recharge; remote sensing; Ferkla oasis; Morocco

• Wydawca: Lubelski Oddział Polskiego Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology ; WNGB Wydawnictwo Naukowe
• Czasopismo: Ecological Engineering & Environmental Technology
• Rocznik: 2024
• Tom: Vol. 25, iss. 3
• Strony: 311--325
• Opis fizyczny: Bibliogr. 52 poz., rys., tab.

Twórcy

autor

Ismail Ait Lahssaine

• Geo-Resource Geo-Environment Geological and Oasis Heritage Research Team, Department of Geosciences, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia, Morocco
• Center of Applied Research, Karlsruhe University of Applied Sciences, 76133 Karlsruhe, Germany

• https://orcid.org/0000-0002-8002-7881

autor

Lahcen Kabiri

• Geo-Resource Geo-Environment Geological and Oasis Heritage Research Team, Department of Geosciences, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia, Morocco

• https://orcid.org/0000-0001-9101-4579

autor

Badre Messaoudi

• Geo-Resource Geo-Environment Geological and Oasis Heritage Research Team, Department of Geosciences, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia, Morocco

• https://orcid.org/0009-0009-0575-2248

autor

Badre Essafraoui

• Geo-Resource Geo-Environment Geological and Oasis Heritage Research Team, Department of Geosciences, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia, Morocco

• https://orcid.org/0000-0002-5445-5719

autor

Mohamed El Ouali

• Geo-Resource Geo-Environment Geological and Oasis Heritage Research Team, Department of Geosciences, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia, Morocco

• https://orcid.org/0000-0002-4849-106X

autor

Lamya Ouali

• Geo-Resource Geo-Environment Geological and Oasis Heritage Research Team, Department of Geosciences, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia, Morocco

• https://orcid.org/0000-0002-0463-7143

autor

Jean Albergel

• Montpellier SupAgro, IRD, University of Montpellier, Montpellier, France

• https://orcid.org/0000-0003-2809-5278

autor

Meryem El Amraoui

• Geo-Resource Geo-Environment Geological and Oasis Heritage Research Team, Department of Geosciences, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia, Morocco

• https://orcid.org/0000-0002-4448-0427

autor

Amina Kassou

• Geo-Resource Geo-Environment Geological and Oasis Heritage Research Team, Department of Geosciences, Faculty of Sciences and Techniques, Moulay Ismail University, Errachidia, Morocco

• https://orcid.org/0000-0003-2722-666X

autor

Essahlaoui Ali

• Geoengineering and Environment Laboratory, Research Group “Water Sciences and Environment Engineering”, Sciences Faculty of Meknes, Moulay Ismail University, Morocco

• https://orcid.org/0000-0002-2439-1769

Bibliografia

• 1. ABH-GZR. 2021. Étude d’actualisation du plan directeur d’aménagement intégré des ressources en eau des bassins hydrauliques du Guir-Ziz-Rheris et Maider. Errachidia.
• 2. Abijith, D., Saravanan, S., Singh, L., Jennifer, J., Saranya, T., Parthasarathy, K. 2020. GIS-based multi-criteria analysis for identification of potential groundwater recharge zones A case study from Ponnaniyaru watershed, Tamil Nadu, India. HydroResearch, 3, 1–14. https://doi.org/10.1016/j.hydres.2020.02.002
• 3. Abimbola, H., Bolanle, A., Ojokoh Adebayo, O. 2020. Performance analysis of fuzzy analytic hierarchy process multi-criteria decision support models for contractor selection, Scientific African, 9, e00471, https://doi.org/10.1016/j.sciaf.2020.e00471.
• 4. Ahmed, J.B., Mansor, S. 2018. Overview of the application of geospatial technology to groundwater potential mapping in Nigeria. Arab J Geosci 11, 504. https://doi.org/10.1007/s12517-018-3852-4
• 5. Ait Said, B., Mili, E.M., El Faleh, E.M., Mehdaoui, R., Mahboub, A., Hamid, F.E., El Fakir, R. 2023. Hydrochemical evolution and groundwater quality assessment of the Tinejdad-Touroug quaternary aquifer, South-East Morocco. Front. Ecol. Evol, 11, 1201748. https://doi.org/10.3389/fevo.2023.1201748
• 6. Al-Ruzouq, R., Shanableh, A., Yilmaz, A.G., Idris, A., Mukherjee, S., Khalil, M.A., Gibril, M.B.A. 2019. Dam site suitability mapping and analysis using an integrated GIS and machine learning approach. Water, 11(9), 1880
• 7. Aouragh, M.H., Essahlaoui, A., El ouali, A., El hmaidi, A., Kamel, S. 2017. Groundwater potential of Middle Atlas plateaus, Morocco, using fuzzy logic approach, GIS and remote sensing, Geomatics, Natural Hazards and Risk, 8(2), 194 206, DOI: 10.1080/19475705.2016.1181676
• 8. Arshad, A., Zhang, Z., Zhang, W., Dilawar, A. 2020. Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model: A case study from an agro-urban region of Pakistan. Geosci. Front. https://doi.org/10.1016/j.gsf.2019.12.013.
• 9. Badi, I., Pamučar, D., Stević, Ž., Muhammad, L.J. 2023. Wind farm site selection using BWM-AHPMARCOS method: A case study of Libya. Scientific African, 19, e01511.
• 10. Boudad, L., Kabiri, L., Weisrock, A., Wengler, L., Fontugne, M., El Maatoui, M., Makayssi, A., Vernet, J.L. 2003. Les formations fluviatiles du Pléistocène supérieur et de l’Holocène dans la «plaine» de Tazoughmit (Oued Rhéris, piémont sud-atlasique de Goulmina, Maroc), Quaternaire, 14(3), 139-154. https://hal.archives-ouvertes.fr/hal-02504318
• 11. Chaaou, I., Kabiri, L., Essafraoui, B., Charroud, A., Si Mhamdi, H., Abioui, M., Abdelrahman, K., Neto, C., Fnais, S. 2022. Lithostratigraphic, paleoenvironmental characterization and correlations of the Albian–Turonian deposits of the Errachidia–Boudnib–Erfoud basin (southeast Morocco). Applied Sciences, 12(21), 11048. https://doi.org/10.3390/app122111048
• 12. Destombes, J., Hollard, H. 1986. Carte géologique du Maroc au 1/200 000, feuille Tafilalt-Taouz. Notes Mém. Serv. Géo. du Maroc, 244.
• 13. Díaz-Alcaide, S., Martínez-Santos, P. 2019. Advances in groundwater potential mapping. Hydrogeology Journal, 27(7), 2307-2324.
• 14. DRPE. 2007. Direction de la Recherche et de la Planification de l’Eau : état de la qualité des ressources en eau au Maroc année 2007-2008, 110.
• 15. El Amraoui, M., Kabiri, L., Kassou, A., Ouali, L., Nutz, A. 2022. Diachronic Study of the Vegetation Covers Spatiotemporal Change Using GIS and Remote Sensing in the Ferkla Oasis: Case Study, Bour El Khourbat, Tinjdad, Morocco. Journal of Geoscience and Environment Protection, 10, 173-188. 10.4236/gep.2022.101012
• 16. El Ouali, M., Kabiri, L., Essafraoui, B., Kabiri, L., Charroud, A., Krencker, F.N., Bodin, S. 2021. Stratigraphic and geodynamic characterization of Jurassic-Cretaceous “red beds” on the Errachidia-Msemrir transect (Central High Atlas, Morocco). Journal of African Earth Sciences, 183. https://doi.org/10.1016/j.jafrearsci.2021.104330
• 17. Essafraoui, B. 2014. Enregistrement séquentiel du Cénomano-Turonien des bassins sudatlasiques sur la transversale Agadir-Goulmima (Maroc). Thesis. Ibn Zohr University of Agadir, p. 178.
• 18. Hadri, M. 1997. Carte Géologique du Maroc 1: 100.000. TINEJDAD. Notes et Mémoires du Service Geologique du Maroc.
• 19. Harini, P., Sahadevan, D.K., Das, I.C., Manikyamba, C., Durgaprasad, M., Nandan, M.J. 2018. Regional groundwater assessment of Krishna River Basin using integrated GIS approach. Journal of the Indian Society of Remote Sensing, 46(9), 1365–1377. https://doi.org/10.1007/s12524-018-0780-4
• 20. Hsin-Fu, Y., Lee, C., Hsu, K., Po-Sun, C. 2009. GIS for assessment of groundwater recharge potential zone. Environ Geol. 58, 185–195. https://doi.org/10.1007/s00254-008-1504-9
• 21.Jaafari, A., Zenner, E.K., Panahi, M., Shahabi, H. 2019. Hybrid artificial intelligence models based on a neuro-fuzzy system and metaheuristic optimization algorithms for spatial prediction of wildfire probability. Agricultural and forest meteorology, 266, 198-207.
• 22.Janizadeh, S., Avand, M., Jaafari, A., Phong, T.V., Bayat, M., Ahmadisharaf, E., Lee, S. 2019. Prediction success of machine learning methods for flash flood susceptibility mapping in the Tafresh watershed, Iran. Sustainability, 11(19), 5426. https://doi.org/10.3390/su11195426
• 23.Jothibasu, A., Anbazhagan, S. 2016. Modeling groundwater probability index in Ponnaiyar River basin of South India using analytic hierarchy process. Model. Earth Syst. Environ. 2, 109. https://doi.org/10.1007/s40808-016-0174-y
• 24.Jothiprakash, V., Marimuthu, G., Muralidharan, R., Senthilkumar, N. 2003. Delineation of potential zones for artificial recharge using GIS. Journal of the Indian Society of Remote Sensing, 31, 37-47. https://doi.org/10.1007/BF03030750
• 25. Kabiri, L. 2003. Impact des changements climatiques et anthropiques sur les ressources en eau dans l’Oasis de Ferkla. MAB, UNESCO, p. 52.
• 26. Kabiri, L. 2004. Contribution à la connaissance, la préservation et la valorisation des Oasis du Sud marocain : cas de Tafilalt. Thèse d’habilitation universitaire, Facultés des Sciences et Techniques, Errachidia, Université My Ismaïl, Maroc, p. 280.
• 27. Krishnamurthy, J., Srinivas, G. 1995. Role of geological and geomorphological features in groundwater exploration: A study using IRS LISS data. International Journal of Remote Sensing, 16(14), 2595–2618. https://doi.org/10.1080/01431169508954579
• 28. Krishnamurthy, J., Venkatesa Kumar, N., Jayaraman, V., Manivel, M. 1996. An approach to demarcate groundwater potential zones through remote sensing and a geographical information system. Int J Remote Sensing, 7, 1867–1884.
• 29. Kumar, T., Gautam, A.K., Kumar, T. 2014. Appraising the accuracy of GIS-based multi-criteria decision-making technique for delineation of groundwater potential zones. Water Resources Management, 28(13), 4449–4466. https://doi.org/10.1007/s11269-014-0663-6
• 30. Kumar, V.A., Mondal, N.C., Ahmed, S. 2020. Identification of Groundwater Potential Zones Using RS, GIS and AHP Techniques: A Case Study in a Part of Deccan Volcanic Province (DVP), Maharashtra, India. J. Indian Soc. Remote Sens. 48, 497–511. https://doi.org/10.1007/s12524-019-01086-3
• 31. Lightfoot, D.R. 1996. Moroccan khettara: traditional irrigation and progressive desiccation. Geoforum, 27(2), 261-273. https://doi.org/10.1016/0016-7185(96)00008-5
• 32. Madani, K., Guégan, M., Uvo, C.B. 2014. Climate change impacts on high-elevation hydroelectricity in California. J. Hydrol. 510, 153–163. https://doi.org/10.1016/j.jhydrol.2013.12.001
• 33. Mageshkumar, P., Subbaiyan, A., Lakshmanan, E., Thirumoorthy, P. 2019. Application of geospatial techniques in delineating groundwater potential zones: a case study from South India. Arabian Journal of Geosciences, 12, 1-15. https://doi.org/10.1007/s12517-019-4289-0
• 34. Mallick, J., Khan, R.A., Ahmed, M., Alqadhi, S.D., Alsubih, M., Falqi, I., Hasan, M.A. 2019. Modeling Groundwater Potential Zone in a Semi-Arid Region of Aseer Using Fuzzy-AHP and Geoinformation Techniques. Water, 11, 2656. https://doi.org/10.3390/w11122656
• 35. Margat, J., Destombes, J., Hollard, H. 1962. Mémoire explicatif de la carte hydrogéologique au 1/50000 de la plaine du Tafilalt. Notes Mém. Serv. Géo. du Maroc, n°150 bis.
• 36. Meena, S.R., Mishra, B., Piralilou, S.T. 2019. Hybrid Spatial Multi-Criteria Evaluation Method for Mapping Landslide Susceptible Areas in Kullu Valley, Himalayas. Geosciences, 9, 156. https://doi.org/10.3390/geosciences9040156
• 37. Messaoudi, B., Kabiri, L., Ait Lahssaine, I., et al. 2023. Groundwater resources management using Hydrodynamic modelling in southeastern Moroccan oases: case of Ferkla Oasis. https://doi.org/10.21203/rs.3.rs-3044585/v1
• 38. Moody, P., Brown, C. 2013. Robustness indicators for evaluation under climate change: Application to the upper Great Lakes: Robustness Indicators for Climate Change on Lakes. Water Resour. Res., 49, 3576–3588. https://doi.org/10.1002/wrcr.20228
• 39. Murmu, P., Kumar, M., Lal, D., Sonker, I., Singh, S.K. 2019. Delineation of groundwater potential zones using geospatial techniques and analytical hierarchy process in Dumka district, Jharkhand, India. Groundw. Sustain. Dev., 9, 100239. https://doi.org/10.1016/j.gsd.2019.100239
• 40. Ouali, L., kabiri, L., Essafraoui, B., et al. 2023. Spatial modeling of water erosion vulnerability and mapping potential sites of control measures using GIS and MCDM: A case study from the drylands of southeastern Morocco. Model. Earth Syst. Environ., 9, 3473–3482. https://doi.org/10.1007/s40808-023-01720-7
• 41. Patil, S.G, Lad, R.K. 2021. Evaluation of spatiotemporal dynamics of groundwater recharge and locating artificial recharge structures for watershed in Upper Bhima Basin, Pune, India. Journal of the Indian Society of Remote Sensing, 49, 2467-2488. https://doi.org/10.1007/s12524-021-01400-y
• 42. Rahmati, O, Samani, A.N., Mahdavi, M., Pourghasemi, H.R., Zeinivand, H. 2015. Groundwater potential mapping at Kurdistan region of Iran using the analytic hierarchy process and GIS. Arabian Journal of Geosciences, 8(9), 7059–7071. https://doi.org/10.1007/s12517-014-1668-4
• 43. Rajasekhar, M., Raju, G.S., Sreenivasulu, Y., Raju R.S. 2019. Delineation of groundwater potential zones in semi-arid region of Jilledubanderu river basin, Anantapur District, Andhra Pradesh, India using fuzzy logic, AHP and integrated fuzzy-AHP approaches. HydroResearch., 2, 97–108. https://doi.org/10.1016/j.hydres.2019.11.006
• 44. Saaty, T.L., Bennett, J.P. 1977. A theory of analytical hierarchies applied to political candidacy. Behavioral Science, 22(4), 237-245.
• 45. Saraf, A.K, Choudhury, P.R. 1998. Integrated remote sensing and GIS for groundwater exploration and identification of artificial recharge sites. International journal of Remote sensing, 19(10), 1825-1841.
• 46. Satapathy, I., Syed, T.H. 2015. Characterization of groundwater potential and artificial recharge sites in Bokaro District, Jharkhand (India), using remote sensing and GIS-based techniques. Environ Earth Sci, 74, 4215–4232. https://doi.org/10.1007/s12665-015-4474-8
• 47. Selvarani, A.G., Maheswaran, G., Elangovan, K. 2017. Identification of artificial recharge sites for Noyyal River Basin using GIS and remote sensing. Journal of the Indian Society of Remote Sensing, 45, 67-77. https://doi.org/10.1007/s12524-015-0542-5
• 48. Sener, E., Davraz, A., Ozcelik, M. 2005. An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. Southeastern Nigeria. Hydrogeology J., 6, 394–404. https://doi.org/10.1007/s10040-004-0378-5
• 49. Shaban, A., Khawlie, M., Abdallah, C. 2006. Use of remote sensing and GIS to determine recharge potential zones: the case of Occidental Lebanon. Hydrogeology Journal, 14, 433-443. https://doi.org/10.1007/s10040-005-0437-6
• 50. Souissi, D., Msaddek, M.H., Zouhri, L., Chenini, I., May, M., Dlala, M. 2018. Mapping groundwater recharge potential zones in arid region using GIS and Landsat approaches, southeast Tunisia. Hydrol. Sci. J., 63, 251–268. https://doi.org/10.1080/02626667.2017.1414383
• 51. Swetha, T.V., Gopinath, G., Thrivikramji, K.P., Jesiya, N.P. 2017. Geospatial and MCDM tool mix for identification of potential groundwater prospects in a tropical river basin, Kerala. Environ Earth Sci 76, 428. https://doi.org/10.1007/s12665-017-6749-8
• 52. Zghibi, A., Mirchi, A., Msaddek, M.H., et al. 2020. Using analytical hierarchy process and multi-influencing factors to map groundwater recharge zones in a semi-arid Mediterranean coastal aquifer. Water, 12(9), 2525. https://doi.org/10.3390/w12092525

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).