Integrated GIS-MCDA (AHP) Framework for Groundwater Potential Mapping in Humid, Structurally Complex Watersheds

Abstract

Mapping the potential of groundwater is important for managing water resources in a way that will last, especially when the climate changes, land use changes, and water demand rise. This study examines the integration of Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) methodologies, focusing on the Analytical Hierarchy Process (AHP), and illustrates their implementation in the Fork Fish Creek watershed, a humid Appalachian headwater basin in West Virginia, USA. Although GIS-AHP methodologies are extensively utilized in semi-arid areas, their efficacy in humid, structurally intricate mountainous environments is still inadequately investigated. Using expert-based AHP weighting and GIS-based weighted overlay analysis, six thematic parameters were combined: rainfall, geology and soil characteristics, slope, drainage density, land use and land cover (LULC), and lineament density. The appropriate AHP consistency ratio (<0.1) showed that the weights were reliable. The resulting groundwater potential map divided the watershed into three zones: Good (6.7%), Moderate (76.5%), and Low (16.8%). The prevalence of Moderate potential indicates the impact of fragmented topography and drainage configuration, which limit groundwater storage despite sufficient precipitation. Validation encompassed an evaluation of hydrogeomorphic consistency and an additional comparison with USGS monitoring-well depth data, so offering empirical corroboration for the Moderate-dominated distribution. The results show that groundwater potential patterns vary greatly from one place to the next. They also show how useful GIS-MCDA frameworks may be for assessing groundwater in humid, data-poor mountainous areas.

Keywords

Groundwater potential mapping / GIS / MCDA / AHP / Watershed-scale assessment / Appalachian plateau / Remote sensing

Statement of the Use of Generative AI and AI-Assisted Technologies in the Writing Process

During the preparation of this manuscript, the authors used OpenAI to improve readability and grammatical clarity. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

Author Contributions

Conceptualization, A.S. and D.D.; Methodology, A.S. and A.K.; Software, D.D. and A.K.; Validation, B.P. (Bibas Pokhrel), S.S. and B.P. (Bishal Poudel); Formal Analysis, D.D. and S.S.; Investigation, S.S.; Resources, B.P. (Bishal Poudel); Data Curation, A.S.; Writing—Original Draft Preparation, B.P. (Bibas Pokhrel) and B.P. (Bishal Poudel); Writing—Review & Editing, A.S., B.P. (Bibas Pokhrel) and A.K.; Visualization, A.S. and S.S.; Supervision, A.K.

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data used in the study are available on public websites, and the links are provided in the data section of the manuscripts.

Funding

This research received no external funding.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

[1] Famiglietti JS. The Global Groundwater Crisis. Nat. Clim. Change 2014, 4, 945-948, DOI:10.1038/nclimate2425

[2] Taylor RG, Scanlon B, Döll P, Rodell M, van Beek R, Wada Y, et al. Ground Water and Climate Change. Nat. Clim. Change 2013, 3, 322-329. DOI:10.1038/nclimate1744

[3] Dahal D, Bhattarai N, Silwal A, Shrestha S, Shrestha B, Poudel B, et al. A Review on Climate Change Impacts on Freshwater Systems and Ecosystem Resilience. Water 2025, 17, 3052. DOI:10.3390/W17213052

[4] Zacharia F, Nobert J, Liwenga E. Geospatial Mapping of Groundwater Potential for Irrigated Agriculture in Semi-Arid Kongwa District, Central Tanzania. Front. Water 2025, 7, 1679500. DOI:10.3389/FRWA.2025.1679500

[5] Famiglietti JS, Lo M, Ho SL, Bethune J, Anderson KJ, Syed TH, et al. Satellites Measure Recent Rates of Groundwater Depletion in California’s Central Valley. Geophys. Res. Lett. 2011, 38, L03403. DOI:10.1029/2010GL046442

[6] Wada Y, van Beek LPH, Sperna Weiland FC, Chao BF, Wu Y, Bierkens MFP. Past and Future Contribution of Global Groundwater Depletion to Sea-Level Rise. Geophys. Res. Lett. 2012, 39, L09402. DOI:10.1029/2012GL051230

[7] Israil M, Al-hadithi M, Singhal DC, Kumar B. Groundwater-Recharge Estimation Using a Surface Electrical Resistivity Method in the Himalayan Foothill Region, India. Hydrogeol. J. 2006, 14, 44-50. DOI:10.1007/S10040-004-0391-8

[8] Machiwal D, Jha MK, Mal BC. GIS-Based Assessment and Characterization of Groundwater Quality in a Hard-Rock Hilly Terrain of Western India. Environ. Monitor. Assess. 2011, 174, 645-663. DOI:10.1007/S10661-010-1485-5

[9] Kumar A, Krishna AP. Assessment of Groundwater Potential Zones in Coal Mining Impacted Hard-Rock Terrain of India by Integrating Geospatial and Analytic Hierarchy Process (AHP) Approach. Geocarto Int. 2018, 33, 105-129. DOI:10.1080/10106049.2016.1232314

[10] Saaty TL. What Is the Analytic Hierarchy Process? In Mathematical Models for Decision Support; Springer: Berlin/Heidelberg, Germany, 1988; pp. 109-121. DOI:10.1007/978-3-642-83555-1_5

[11] Ghosh A, Adhikary PP, Bera B, Bhunia GS, Shit PK. Assessment of Groundwater Potential Zone Using MCDA and AHP Techniques: Case Study from a Tropical River Basin of India. Appl. Water Sci. 2022, 12, 37. DOI:10.1007/s13201-021-01548-5

[12] Benjmel K, Amraoui F, Boutaleb S, Ouchchen M, Tahiri A, Touab A. 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 2020, 12, 471. DOI:10.3390/W12020471

[13] Machiwal D, Jha MK, Mal BC. Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing, GIS and MCDM Techniques. Water Resour. Manag. 2011, 25, 1359-1386. DOI:10.1007/s11269-010-9749-y

[14] Ajayi OG, Nwadialor IJ, Odumosu JO, Adetunji OO, Abdulwasiu IO. Assessment and Delineation of Groundwater Potential Zones Using Integrated Geospatial Techniques and Analytic Hierarchy Process. Appl. Water Sci. 2022, 12, 276. DOI:10.1007/S13201-022-01802-4

[15] Sander P. Lineaments in Groundwater Exploration: A Review of Applications and Limitations. Hydrogeol. J. 2006, 15, 71-74. DOI:10.1007/S10040-006-0138-9

[16] Elshalkany M, Ahmed M, Sauck W, Abouelmagd A, Mansour S, El-Nekhiely IN, et al. Geophysical and Remote-Sensing Constraints on the Fault Controls on Groundwater Accumulation in Basement Rock Aquifers in Sinai, Egypt. Surv. Geophys. 2025, 46, 627-664. DOI:10.1007/S10712-025-09883-X

[17] Embaby A, Youssef YM,Abu El-Magd SA. Delineation of lineaments for groundwater prospecting in hard rocks: inferences from remote sensing and geophysical data. Environ Earth Sci 2024, 83(2), 62. https://doi.org/10.1007/s12665-023-11389-x.

[18] Pappaka RK, Nakkala AB, Badapalli PK, Gugulothu S, Anguluri R, Hasher FFB, et al. Machine Learning-Driven Groundwater Potential Zoning Using Geospatial Analytics and Random Forest in the Pandameru River Basin, South India. Sustainability 2025, 17, 3851. DOI:10.3390/SU17093851

[19] Naghibi SA, Pourghasemi HR, Dixon B. GIS-Based Groundwater Potential Mapping Using Boosted Regression Tree, Classification and Regression Tree, and Random Forest Machine Learning Models in Iran. Environ. Monit. Assess. 2016, 188, 44, DOI:10.1007/S10661-015-5049-6

[20] Ayadi Y, Gentilucci M, Ncibi K, Hadji R, Hamed Y. Assessment of a Groundwater Potential Zone Using Geospatial Artificial Intelligence (Geo-AI), Remote Sensing (RS), and GIS Tools in Majerda Transboundary Basin (North Africa). Water 2025, 17, 331. DOI:10.3390/W17030331

[21] Maurya S, Pradhan RM, Singh A. Characterization of Structurally Complex Granitic Basement Rocks Using Multi-Geophysical Data: Insights into Subsurface Weathered Bedrock Zones and Groundwater Exploration. Near Surf. Geophys. 2025, 23, 324-342. DOI:10.1002/nsg.70007

[22] Rukundo E, Doğan A. Dominant Influencing Factors of Groundwater Recharge Spatial Patterns in Ergene River Catchment, Turkey. Water 2019, 11, 653. DOI:10.3390/W11040653

[23] Saha P, Gayen SK. Identification of Suitable Land for Sustainable Agricultural Practices in Koch Bihar District, West Bengal: A RS-GIS Based MCDA Approach. Environ. Dev. Sustain. 2025, 27, 1-42. DOI:10.1007/S10668-025-06262-9

[24] Tabassum F, Krishna AP. Groundwater Potential Mapping Using AHP and Machine Learning in the Upper Subarnarekha River Basin, India. In Proceedings of the 2024 IEEE India Geoscience and Remote Sensing Symposium (InGARSS), Goa, India, 2-5 December 2024. DOI:10.1109/INGARSS61818.2024.10983912

[25] Maghribi AA, Dimyati M, Supriatna S. Geographic Information System and Multi-Criteria Decision Analysis for the Determination of Groundwater Recharge Potential: Systematic Review. Water Suppl. 2022, 22, 7027-7039, DOI:10.2166/WS.2022.297

[26] Kodihal S, Akhtar MP. GIS Based Multi-Criteria Decision Making to Identify Regional Groundwater Potential Zones: A Critical Review. Sustain. Water Resour. Manag. 2024, 10, 61. DOI:10.1007/S40899-024-01080-9

[27] Lee S, Hyun Y, Lee S, Lee MJ. Groundwater Potential Mapping Using Remote Sensing and GIS-Based Machine Learning Techniques. Remote Sens. 2020, 12, 1200. DOI:10.3390/rs12071200

[28] Ramasubramanian S, Ravindran A, Abishek SR, Christinal J, Kingston JV, Promilton AA. An Application of Remote Sensing and GIS Used in Groundwater Potential Zones for Sustainable Urban Development in Coastal Areas between Chettikulam and Kolachal, Southern India. Appl. Geomat. 2025, 17, 83-102. DOI:10.1007/s12518-024-00604-4

[29] Jha MK, Chowdhury A, Chowdary VM, Peiffer S. Groundwater Management and Development by Integrated Remote Sensing and Geographic Information Systems: Prospects and Constraints. Water Resour. Manag. 2006, 21, 427-467. DOI:10.1007/S11269-006-9024-4

[30] Saraf AK, Choudhury PR. Integrated Remote Sensing and GIS for Groundwater Exploration and Identification of Artificial Recharge Sites. Int. J. Remote Sens. 1998, 19, 1825-1841. DOI:10.1080/014311698215018

[31] Melese T, Belay T. Groundwater Potential Zone Mapping Using Analytical Hierarchy Process and GIS in Muga Watershed, Abay Basin, Ethiopia. Glob. Chall. 2022, 6, 2100068. DOI:10.1002/GCH2.202100068

[32] Doke AB, Zolekar RB, Patel H, Geospatial Mapping of Groundwater Potential Zones Using Multi-Criteria Decision-Making AHP Approach in a Hardrock Basaltic Terrain in India. Ecol. Indic. 2021, 127, 107685. DOI:10.1016/J.ECOLIND.2021.107685

[33] Pinheiro G, Raj A, Rather IH. Role of Remote Sensing and GIS in Sustainable Computing Practices. In Green Computing for Sustainable Development; Taylor & Francis Group: Oxfordshire, UK, 2025; pp. 66-84. DOI:10.1201/9781003471356-4

[34] Moore ID, Grayson RB, Ladson AR. Digital Terrain Modelling: A Review of Hydrological, Geomorphological, and Biological Applications. Hydrol. Process. 1991, 5, 3-30. DOI:10.1002/HYP.3360050103

[35] Nag SK. Delineation of Groundwater Potential Zones in Hard Rock Terrain in Kashipur Block, Purulia District, West Bengal, Using Geospatial Techniques. Int. J. Waste Resour. 2016, 6, 1-13. DOI:10.4172/2252-5211.1000201

[36] Mabee SB, Hardcastle KC, Wise DU. A Method of Collecting and Analyzing Lineaments for Regional-Scale Fractured-Bedrock Aquifer Studies. Groundwater 1994, 32, 884-894. DOI:10.1111/J.1745-6584

[37] Singh LK, Jha MK, Chowdary VM. Assessing the Accuracy of GIS-Based Multi-Criteria Decision Analysis Approaches for Mapping Groundwater Potential. Ecol. Indic. 2018, 91, 24-37. DOI:10.1016/J.ECOLIND.2018.03.070

[38] Malczewski J. GIS and Multicriteria Decision Analysis; John Wiley & Sons: Hoboken, NJ, USA, 1999; p. 392.

[39] Forman EH. Multi Criteria Decision Making and the Analytic Hierarchy Process. In Readings in Multiple Criteria Decision Aid; Springer: Berlin/Heidelberg, Germany, 1990; pp. 295-318. DOI:10.1007/978-3-642-75935-2_13

[40] Patel DK, Thakur TK, Thakur A, Karuppannan S, Swamy SL, Pant RR. Groundwater Potential Zone Mapping Using AHP and Geospatial Techniques in the Upper Narmada Basin, Central India. Discov. Sustain. 2024, 5, 355. DOI:10.1007/S43621-024-00560-4

[41] Shinde SP, Barai VN, Gavit BK, Kadam SA, Atre AA, Pande CB, et al. Assessment of Groundwater Potential Zone Mapping for Semi-Arid Environment Areas Using AHP and MIF Techniques. Environ. Sci. Eur. 2024, 36, 87. DOI:10.1186/S12302-024-00906-9

[42] Pirasteh S, Samad A, Ahmad R, Thakural LN, Khan HH, Chauhan P, et al. Geospatial and AHP Based Identification of Potential Zones for Groundwater Recharge in Haridwar District of India. Front. Environ. Sci. 2025, 13, 1421918. DOI:10.3389/fenvs.2025.1421918

[43] Doke A. Delineation of the Groundwater Potential Using Remote Sensing and GIS: A Case Study of Ulhas Basin, Maharashtra, India. Arch. Photogram. Cartogr. Remote Sens. 2019, 31, 49-64. DOI:10.2478/apcrs-2019-0004

[44] Singh SK, Zeddies M, Shankar U, Griffiths GA. Potential Groundwater Recharge Zones within New Zealand. Geosci. Front. 2019, 10, 1065-1072. DOI:10.1016/J.GSF.2018.05.018

[45] Kamaraj P, Jothimani M, Panda B, Sabarathinam C. Mapping of Groundwater Potential Zones by Integrating Remote Sensing, Geophysics, GIS, and AHP in a Hard Rock Terrain. Urban Clim. 2023, 51, 101610. DOI:10.1016/J.UCLIM.2023.101610

[46] Kinzelbach W, Wang H, Li Y, Wang L, Li N. Groundwater Overexploitation in the North China Plain: A Path to Sustainability; Springer: Singapore, 2022; p. 157.

[47] Horton RE. Erosional Development of Streams and Their Drainage Basins Hydrophysical Approach to Quantitative Morphology. Geol. Soc. Am. Bull. 1945, 56, 275-370. DOI:10.1130/0016-7606(1945)56[275:EDOSAT]2.0.CO;2

[48] Achu AL, Reghunath R, Thomas J. Mapping of Groundwater Recharge Potential Zones and Identification of Suitable Site-Specific Recharge Mechanisms in a Tropical River Basin. Earth Syst. Environ. 2019, 4, 131-145. DOI:10.1007/S41748-019-00138-5

[49] Meng F, Khan MI, Naqvi SAA, Sarwar A, Islam F, Ali M, et al. Identification and Mapping of Groundwater Recharge Zones Using Multi Influencing Factor and Analytical Hierarchy Process. Sci. Rep. 2024, 14, 19240. DOI:10.1038/s41598-024-70324-7

[50] Ifediegwu SI. Assessment of Groundwater Potential Zones Using GIS and AHP Techniques: A Case Study of the Lafia District, Nasarawa State, Nigeria. Appl. Water Sci. 2021, 12, 10. DOI:10.1007/S13201-021-01556-5

[51] Balasubramaniyan G, Ganesan DA, Murugesan B, Swaminathan B, Karuppannan S, Duraisamy K. AHP and Geospatial Technology-Based Assessment of Groundwater Potential Zones in Natham Taluk, Tamil Nadu, India. Sci. Rep. 2025, 15, 28045. DOI:10.1038/s41598-025-13829-z

[52] Shekhar S, Pandey AC. 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. 2015, 30, 402-421. DOI:10.1080/10106049.2014.894584

[53] Al-Djazouli MO, Elmorabiti K, Rahimi A, Amellah O, Fadil OAM. Delineating of Groundwater Potential Zones Based on Remote Sensing, GIS and Analytical Hierarchical Process: A Case of Waddai, Eastern Chad. GeoJournal 2020, 86, 1881-1894. DOI:10.1007/S10708-020-10160-0

[54] Elmahdy S, Mohamed M, Ali T. Land Use/Land Cover Changes Impact on Groundwater Level and Quality in the Northern Part of the United Arab Emirates. Remote Sens. 2020, 12, 1715. DOI:10.3390/RS12111715

[55] Jasrotia AS, Singh R. Modeling Runoff and Soil Erosion in a Catchment Area, Using the GIS, in the Himalayan Region, India. Environ. Geol. 2006, 51, 29-37. DOI:10.1007/S00254-006-0301-6

[56] Dahal D, Ale Magar B, Aryal A, Poudel B, Banjara M, Kalra A. Analyzing Climate Dynamics and Developing Machine Learning Models for Flood Prediction in Sacramento, California. Hydroecol. Eng. 2024, 1, 10003. DOI:10.70322/HEE.2024.10003

[57] Silwal A, Subedi A, Tamrakar R, Dahal K, Dahal D, Ekpetere KO, et al. A Comprehensive Review of Machine Learning and Deep Learning Methods for Flood Inundation Mapping. Earth 2026, 7, 44. DOI:10.3390/earth7020044