Use of GIS, Remote Sensing and Analytical Hierarchy Process for Groundwater Potential Assessment in an Arid Region – A Case Study

• Autorzy: Jari Abdessamad , Bachaoui El Mostafa , Jellouli Amine , El Harti Abderrazak , Khaddari Achraf , El Jazouli Aafaf

Identyfikatory

DOI

10.12912/27197050/152141

• Języki publikacji: EN

Abstrakty

EN

This research aims to evaluate the groundwater potentiality in the arid region “Telmzoun” located in the south of Morocco using the analytical hierarchy process (AHP) model of multi-criteria analysis in conjunction with geographic information system (GIS) and remote sensing techniques. The used methodology to generate the groundwater potential map starts with the preparation of thematic layers of different factors influencing the existence of groundwater, such as precipitation, lithology, geomorphology, lineament density, drainage density, slope, in addition to the proximity of the hydrographic network. Groundwater potential map was prepared using relative weights derived from the AHP. The results were mapped on ArcGIS 10.2 and validated using the existing borehole data and the ROC curve. The accuracy of the generated map reached over 70%. It represents five classes of groundwater potential that are as follows: very high potential areas consisting of 10.5% (2.14 km²), high potential representing a rate of 27.2% (5.53 km²), moderate potential areas consisting of 30% (6.06 km²), low potential 20.5% (4.17 km²) and very low potential areas showing a rate of 11.8% (2.40 km²) of the total study area. The results obtained are satisfactory and consist of a guide map to be used effectively in direct future groundwater exploration campaigns and to minimize various field costs.

Słowa kluczowe

EN

geographic information system; remote sensing; analytical hierarchy process; groundwater; Anti-Atlas belt

• Wydawca: Lubelski Oddział Polskiego Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology ; WNGB Wydawnictwo Naukowe
• Czasopismo: Ecological Engineering & Environmental Technology
• Rocznik: 2022
• Tom: Vol. 23, iss. 5
• Strony: 234--255
• Opis fizyczny: Bibliogr. 54 poz., rys., tab.

Twórcy

autor

Jari Abdessamad

• Laboratory of Geomatic, Georesources and Environment, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Mghilla Campus, PB 523, 23000 Beni Mellal, Marocco

• https://orcid.org/0000-0001-9091-1817

autor

Bachaoui El Mostafa

• Laboratory of Geomatic, Georesources and Environment, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Mghilla Campus, PB 523, 23000 Beni Mellal, Marocco

• https://orcid.org/0000-0003-4163-6307

autor

Jellouli Amine

• Laboratory of Geomatic, Georesources and Environment, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Mghilla Campus, PB 523, 23000 Beni Mellal, Marocco

• https://orcid.org/0000-0002-3094-020X

autor

El Harti Abderrazak

• Laboratory of Geomatic, Georesources and Environment, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Mghilla Campus, PB 523, 23000 Beni Mellal, Marocco

• https://orcid.org/0000-0003-3976-4588

autor

Khaddari Achraf

• Laboratory of Geosciences, Faculty of Sciences, Ibn Tofail University, Morocco University Campus, PB 133, Kenitra, Morocco

• https://orcid.org/0000-0002-3585-9806

autor

El Jazouli Aafaf

• Laboratory of Geomatic, Georesources and Environment, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Mghilla Campus, PB 523, 23000 Beni Mellal, Marocco

• https://orcid.org/0000-0001-6838-0271

Bibliografia

• 1. Abijith D., Saravanan S., Singh L., Jennifer J.J., Saranya T., Parthasarathy K.S.S. 2020. GIS-based multi-criteria analysis for identification of potential groundwater recharge zones - a case study from Ponnaniyaru watershed, Tamil Nadu, India. Hydro-Research, 3, 1–14.
• 2. Adiat K.A.N., Nawawi M., Abdullah K. 2012. Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial prediction tool - A case of predicting potential zones of sustainable groundwater resources. J Hydrol., 440, 75–89.
• 3. Adiri Z., El Harti A., Jellouli A., Lhissou R., Maacha L., Azmi M., Zouhair M., Bachaoui E.M. 2017. Comparison of Landsat-8, ASTER and Sentinel 1 satellite remote sensing data in automatic lineaments extraction: A case study of Sidi Flah-Bouskour inlier, Moroccan Anti Atlas. Adv Sp Res, 60(11), 2355–2367. http://dx.doi.org/10.1016/j.asr.2017.09.006
• 4. Adiri Z., Harti A.E., Jellouli A., Maacha L., Bachaoui E.M. 2016. Lithological mapping using Landsat 8 OLI and Terra ASTER multispectral data in the Bas Drâa inlier, Moroccan Anti Atlas. J Appl Remote Sens.. 10(1), 016005.
• 5. Aggarwal M., Saravanan S., Jennifer J.J., Abijith D. 2019. Delineation of groundwater potential zones for hard rock region in Karnataka using AHP and GIS. In: Adv Sci Technol Innov. Springer Nature, 315–317.
• 6. Ajay Kumar V,, 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(3), 497–511.
• 7. Al-Abadi A.M., Al-Temmeme A.A., Al-Ghanimy M.A. 2016. A GIS-based combining of frequency ratio and index of entropy approaches for mapping groundwater availability zones at Badra–Al. Al-Gharbi–Teeb areas, Iraq. Sustain Water Resour Manag., 2(3), 265–283.
• 8. Al-Djazouli M.O., Elmorabiti K., Rahimi A., Amellah O., Fadil O.A.M. 2021. Delineating of groundwater potential zones based on remote sensing, GIS and analytical hierarchical process: a case of Waddai, eastern Chad. GeoJournal, 86(4), 1881–1894.
• 9. Al-Ruzouq R., Shanableh A., Merabtene T., Siddique M., Khalil M.A., Idris A.E., Almulla E. 2019. Potential groundwater zone mapping based on geo-hydrological considerations and multi-criteria spatial analysis: North UAE. Catena, 173, 511–524.
• 10.Arumugam J. 2016. Modeling groundwater probability index in Ponnaiyar River basin of South India using analytic hierarchy process. Model earth Syst Environ., 2.
• 11. Arunbose S., Srinivas Y., Rajkumar S., Nair N.C., Kaliraj S. 2021. Remote sensing, GIS and AHP techniques based investigation of groundwater potential zones in the Karumeniyar river basin, Tamil Nadu, southern India. Groundw Sustain Dev., 14, 100586.
• 12. Benjmel K., Amraoui F., Boutaleb S., Ouchchen M., Tahiri A., Touab A. 2020. Mapping of groundwater potential zones in crystalline terrain using remote sensing, GIS techniques, and multicriteria data analysis (Case of the ighrem region, Western Anti-Atlas, Morocco). Water (Switzerland), 12(2).
• 13. Brauner J., Arndt M., Yajioui Z., Karaoui B., Breitkreuz C., Mahmoudi A. 2020. Cambrian shallow-marine to emergent alkaline volcanism near Ouinguigui (Ougnat inlier, eastern Anti-Atlas, Morocco): Volcanic facies, geochemistry and geodynamic setting. J African Earth Sci., 161, 103581.
• 14. Chen W., Li H., Hou E., Wang S., Wang G., Panahi M., Li T., Peng T., Guo C., Niu C., et al. 2018. GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models. Sci Total Environ., 634, 853–867.
• 15. Dar T., Rai N., Bhat A. 2021. Delineation of potential groundwater recharge zones using analytical hierarchy process (AHP). Geol Ecol Landscapes, 5(4), 292–307.
• 16. Das B., Pal S.C. 2019. Combination of GIS and fuzzy-AHP for delineating groundwater recharge potential zones in the critical Goghat-II block of West Bengal, India. HydroResearch, 2, 21–30.
• 17. Das N., Mukhopadhyay S. 2020. Application of multi-criteria decision making technique for the assessment of groundwater potential zones: a study on Birbhum district, West Bengal, India. Environ Dev Sustain., 22(2), 931–955.
• 18. Doke A.B., Zolekar R.B., Patel H., Das S. 2021. Geospatial mapping of groundwater potential zones using multi-criteria decision-making AHP approach in a hardrock basaltic terrain in India. Ecol Indic., 127, 107685.
• 19. Erinjery J.J., Singh M., Kent R. 2018. Mapping and assessment of vegetation types in the tropical rainforests of the Western Ghats using multispectral Sentinel-2 and SAR Sentinel-1 satellite imagery. Remote Sens Environ., 216, 345–354.
• 20. Ettazarini S., El Jakani M. 2020. Mapping of groundwater potentiality in fractured aquifers using remote sensing and GIS techniques: the case of Tafraoute region, Morocco. Environ Earth Sci, 79(5). https://doi.org/10.1007/s12665-020-8848-1
• 21. Ferozur R.M., Jahan C.S., Arefin R., Mazumder Q.H. 2019. Groundwater potentiality study in drought prone barind tract, NW Bangladesh using remote sensing and GIS. Groundw Sustain Dev., 8, 205–215.
• 22. El Hasnaoui A., Soulaimani A., Maacha L., Michard A., Saddiqi O., El Maidani A. 2011. Azougar n’Tilili, nouveau gîte polymétallique aurifère dans le Cambrien du Bas-Draa (Anti-Atlas occidental). Nouv Guid gé ologiques miniers du Maroc, 9, 564.
• 23. Ifediegwu S.I. 2022. Assessment of groundwater potential zones using GIS and AHP techniques: a case study of the Lafia district, Nasarawa State, Nigeria. Appl Water Sci, 12(1).
• 24. El Jazouli A., Barakat A., Khellouk R. 2019. GIS-multicriteria evaluation using AHP for landslide susceptibility mapping in Oum Er Rbia high basin (Morocco). Geoenvironmental Disasters, 6(1).
• 25. Jellouli A., El Harti A., Adiri Z., Chakouri M., El Hachimi J., Bachaoui E.M. 2021. Application of optical and radar satellite images for mapping tectonic lineaments in kerdous inlier of the Anti-Atlas belt, Morocco. Remote Sens Appl Soc Environ., 22, 100509.
• 26. Lee S., Kim Y.S., Oh H.J. 2012. Application of a weights-of-evidence method and GIS to regional groundwater productivity potential mapping. J Environ Manage., 96(1), 91–105.
• 27. Lentswe G.B., Molwalefhe L. 2020. Delineation of potential groundwater recharge zones using analytic hierarchy process-guided GIS in the semi-arid Motloutse watershed, eastern Botswana. J Hydrol Reg Stud., 28.
• 28.Machiwal D,, Jha M.K., Mal B.C. 2011. Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing, GIS and MCDM Techniques. Water Resour Manag., 25(5), 1359–1386.
• 29.Magesh N.S., Chandrasekar N., Soundranayagam J.P. 2012. Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geosci Front., 3(2), 189–196.
• 30. Maity D.K., Mandal S. 2019. Identification of groundwater potential zones of the Kumari river basin, India: an RS & GIS based semi-quantitative approach. Environ Dev Sustain., 21(2), 1013–1034.
• 31. Maloof A.C., Schrag D.P., Crowley J.L., Bowring S.A. 2005. An expanded record of Early Cambrian carbon cycling from the Anti-Atlas Margin, Morocco. Can J Earth Sci., 42(12), 2195–2216.
• 32. Martín-Loeches M., Reyes-López J., Ramírez-Hernández J., Temiño-Vela J., Martínez-Santos P. 2018. Comparison of RS/GIS analysis with classic mapping approaches for siting low-yield boreholes for hand pumps in crystalline terrains. An application to rural communities of the Caimbambo province, Angola. J African Earth Sci., 138, 22–31.
• 33. Mogaji K.A., Omobude O.B. 2017. Modeling of geoelectric parameters for assessing groundwater potentiality in a multifaceted geologic terrain, Ipinsa Southwest, Nigeria – A GIS-based GODT approach. NRIAG J Astron Geophys., 6(2), 434–451.
• 34. Morjani E., Abidine Z.E. 2002. Conception d’un système d’information à référence spatiale pour la gestion environnementale: application à la sélection de sites potentiels de stockage de déchets ménagers et industriels en région semi-aride (Souss, Maroc). In: [place unknown].
• 35. Namous M., Hssaisoune M., Pradhan B., Lee C.W., Alamri A., Elaloui A., Edahbi M., Krimissa S., Eloudi H., Ouayah M., et al. 2021. Spatial prediction of groundwater potentiality in large semi‐arid and karstic mountainous region using machine learning models. Water (Switzerland), 13(16).
• 36. Nampak H., Pradhan B., Manap M.A. 2014. Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. J Hydrol., 513, 283–300.
• 37. Oh H.J., Kim Y.S., Choi J.K., Park E., Lee S. 2011. GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea. J Hydrol., 399(3–4), 158–172.
• 38. Ozdemir A. 2011. GIS-based groundwater spring potential mapping in the Sultan Mountains (Konya, Turkey) using frequency ratio, weights of evidence and logistic regression methods and their comparison. J Hydrol., 411(3–4), 290–308.
• 39. Pande CB, Moharir KN, Panneerselvam B, Singh SK, Elbeltagi A, Pham QB, Varade AM, Rajesh J. 2021. Delineation of groundwater potential zones for sustainable development and planning using analytical hierarchy process (AHP), and MIF techniques. Appl Water Sci. 11(12).
• 40. Park S., Hamm S.Y., Jeon H.T., Kim J. 2017. Evaluation of logistic regression and multivariate adaptive regression spline models for groundwater potential mapping using R and GIS. Sustain., 9(7).
• 41. Patra S., Mishra P., Mahapatra S.C. 2018. Delineation of groundwater potential zone for sustainable development: A case study from Ganga Alluvial Plain covering Hooghly district of India using remote sensing, geographic information system and analytic hierarchy process. J Clean Prod., 172, 2485–2502.
• 42. Pourtaghi Z.S., Pourghasemi H.R. 2014. GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province, Iran. Hydrogeol J., 22(3), 643–662.
• 43. Rahmati O., Nazari Samani A., Mahdavi M., Pourghasemi H.R., Zeinivand H. 2015. Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS. Arab J Geosci., 8(9), 7059–7071.
• 44. Rajan Girija R., Mayappan S. 2019. Mapping of mineral resources and lithological units: a review of remote sensing techniques. Int J Image Data Fusion., 10(2), 79–106.
• 45. Rajasekhar M., Sudarsana Raju G., Sreenivasulu Y., Siddi Raju R. 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.
• 46. Razandi Y., Pourghasemi H.R., Neisani N.S., Rahmati O. 2015. Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS. Earth Sci Informatics, 8(4), 867–883.
• 47. Saaty T.L. 1980. The analytic hierarchy process McGraw-Hill. New York, 324.
• 48. Sajil Kumar P.J., Elango L., Schneider M. 2022. GIS and AHP Based Groundwater Potential Zones Delineation in Chennai River Basin (CRB), India. Sustainability, 14(3), 1830. https://www.mdpi.com/2071-1050/14/3/1830
• 49. Sapkota S., Pandey V.P., Bhattarai U., Panday S., Shrestha S.R., Maharjan S.B. 2021. Groundwater potential assessment using an integrated AHP-driven geospatial and field exploration approach applied to a hard-rock aquifer Himalayan watershed. J Hydrol Reg Stud., 37.
• 50. Shekhar S., Pandey A.C. 2015. Delineation of groundwater potential zone in hard rock terrain of India using remote sensing, geographical information system (GIS) and analytic hierarchy process (AHP) techniques. Geocarto Int., 30(4), 402–421.
• 51. Soulaimani A., Le Corre C., Farazdaq R. 1997. Déformation hercynienne et relation socle/couverture dans le domaine du Bas-Drâa (Anti-Atlas occidental, Maroc). J African Earth Sci., 24(3), 271–284.
• 52. Soulaimani A., Lecorre C., Bouabdelli M. 1996. Influence du socle précambrien sur la tectonique hercynienne dans l’Anti-Atlas occidental: l’exemple du poinçonnement du Bas-Drâa (Maroc). Mines, géologie et énergie, 55, 73–78.
• 53.Venkateswaran S., Ayyandurai R. 2015. Groundwater Potential Zoning in Upper Gadilam River Basin Tamil Nadu. Aquat Procedia, 4, 1275–1282.
• 54.Yao A.B., Goula B.T.A., Kane A., Mangoua O.M.J., Kouassi K.A. 2016. Cartographie du potentiel en eau souterraine du bassin versant de la Lobo (Centre-Ouest, Côte d’Ivoire): approche par analyse multicritère. Hydrol Sci J., 61(5), 856–867.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).