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Delineation of groundwater potential zones using the AHP technique: a case study of Alipurduar district, West Bengal

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Abstract

Increasing population with increasing demand of groundwater affects the level of groundwater. In the context of considerable change in the use of groundwater pattern, particularly with continuous increase in demand for groundwater due to many reasons, the present paper attempts to delineate groundwater potential zones (GWPZ) using integrated remote sensing, geographic information systems (GIS) and analytic hierarchy process (AHP) methods. To transform and harmonize geographic data and weightage ranking to get reliable information, geographic information systems are combined with analytical hierarchical processes. The current study has been done in the district where many areas are under tea garden and cultivated land. The use of excess of groundwater results in a drop in the water level. The mapping and the identification of groundwater potential zones were done for the Ganga alluvial plain of Alipurduar District of India. The groundwater potential index (GPI) was computed based on several factors (e.g., land use–land cover, soil type, geology, elevation, slope, rainfall, normalized difference vegetation index, drainage density, pre- and post-monsoon groundwater depth, etc.). To generate the groundwater potential zone map of the study area, an overlay weighted sum method was applied to integrate all thematic criteria. Groundwater potential index maps have been classified into five zones. The excellent potential zone comprise 50.5% (1583.68 km2), good 27.4% (859.26 km2), moderate11.3% (354.37 km2), poor 7.1% (222.66 km2) and very poor 3.7% (116.03 km2), respectively. After that, the maps were verified with groundwater-level fluctuation data of 30 observed wells through the ROC (receivers operating characteristic) curve. This paper has important implications for planning the sustainable groundwater plan and also different purposes, such as natural and artificial recharge, watershed delineation and proper water usage, can be effectively implemented in this agriculture-dominated areas in the district.

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References

  • Abijith D, Saravanan S, Singh L, Jennifer JJ, Saranya T, Parthasarathy KSS (2020) GIS-based multi-criteria analysis for identifcation of potential groundwater recharge zones—a case study from Ponnaniyaru watershed, Tamil Nadu, India. HydroResearch 3:1–14

    Article  Google Scholar 

  • Agarwal R, Garg PK (2016) Remote sensing and GIS based groundwater potential & recharge zones mapping using multi-criteria decision making technique. Water Resour Manag 30(1):243–260. https://doi.org/10.1007/s11269-015-1159-8

    Article  Google Scholar 

  • Agarwal E, Agarwal R, Garg RD, Garg PK (2013) Delineation of groundwater potential zone: an AHP/ANP approach. J Earth Syst Sci 122(3):887–898. https://doi.org/10.1007/s12040-013-0309-8

    Article  Google Scholar 

  • Aggarwal M, Saravanan S, Jacinth JJ, Abijith D (2019) Delineation of groundwater potential zones for hard rock region in Karnataka using AHP and GIS. Springer, Cham 2:265–283

    Google Scholar 

  • Agricultural contingency report. 2016, (annual report 2016–17), Department of Agriculture, Cooperation Farmers Welfare Ministry of Agriculture Farmers Welfare Government of India Krishi Bhawan, New Delhi. Retrieved from: https://agricoop.nic.in/sites/default/files/Annual_rpt_201617_E.pdf. Accessed 28 June 2022.

  • Al-Abadi AM, Al-Temmeme AA, Al-Ghanimy MA (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 2:265–283

    Article  Google Scholar 

  • Albhaisi M, Brendonck L, Batelaan O (2013) Predicted impacts of land use change on groundwater recharge of the upper Berg catchment. South Africa Water SA 39:2

    Google Scholar 

  • Al-Djazouli M, Elmorabiti K, Rahimi A, Amellah O, Fadil O (2020) Delineating of groundwater potential zones based on remote sensing, GIS and analytical hierarchical process: A case of Waddai, eastern Chad. GeoJournal 66:876

    Google Scholar 

  • Aluko OE, Igwe O (2017) An integrated geomatics approach to groundwater potential delineation in the Akoko-Edo Area. Nigeria Environ Earth Sci 76(6):240. https://doi.org/10.1007/s12665-017-6557-1

    Article  Google Scholar 

  • Aneesh R, Deka PC (2015) Groundwater potential recharge zonation of bengaluru urban district—a GIS based analytic hierarchy process (AHP) technique approach. Int Adv Res J Sci Eng Technol. 2:129–136

    Google Scholar 

  • Ansari S, Sheereen Z (2016) Socio-economic condition of tea garden worker in Alipurduar district, West Bengal. IJRSS. 6:6654

    Google Scholar 

  • Arabameri A, Pradhan B, Pourghasemi HR, Rezaei K (2018) Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS. Geomatics 9(1):1129–1155. https://doi.org/10.1080/19475705.2018.1513084

    Article  Google Scholar 

  • Arulbalaji P, Padmalal D, Sreelash K (2019) GIS and AHP techniques based delineation of groundwater potential zones: a case study from Southern Western Ghats. India Sci Rep. https://doi.org/10.1038/s41598-019-38567-x

    Article  Google Scholar 

  • Bagyaraj M, Ramkumar T, Venkatramanan S, Gurugnanam B (2013) Application of remote sensing and GIS analysis for identifying groundwater potential zone in parts of Kodaikanal Taluk, South India. Front Earth Sci 7(1):65–75. https://doi.org/10.1007/s11707-012-0347-6

    Article  Google Scholar 

  • Barua S, Mukhopadhyay BP, Bera A (2021) Integrated assessment of groundwater potential zone under agricultural dominated areas in the western part of Dakshin Dinajpur district, West Bengal. India Arab J Geosci 14:1042. https://doi.org/10.1007/s12517-021-07312-y

    Article  Google Scholar 

  • Bates BC, Kundzewicz ZW, Wu S, Palutikof JP (eds) (2008) Climate change and water. Technical paper of the intergovernmental panel on climate change, IPCC Secretariat, Geneva

    Google Scholar 

  • Bhunia GS (2020) An approach to demarcate groundwater recharge potential zone using geospatial technology. Appl Water Sci 10:138. https://doi.org/10.1007/s13201-020-01231-1

    Article  Google Scholar 

  • Biswas S, Mukhopadhyay BP, Bera A (2020) Delineating groundwater potential zones of agriculture dominated landscapes using GIS based AHP techniques: a case study from Uttar Dinajpur district. West Bengal Environ Earth Sci 79(12):1–25. https://doi.org/10.1007/s12665-020-09053-9

    Article  Google Scholar 

  • Bonilla Valverde JP, Blank C, Roidt M, Schneider L, Stefan C (2016) Application of a gis multi-criteria decision analysis for the identification of intrinsic suitable sites in costa rica for the application of managed aquifer recharge (mar) through spreading methods. Water 8(9):391. https://doi.org/10.3390/w8090391

    Article  Google Scholar 

  • CGWB (2019) National compilation on dynamic ground water resources of India, 2017,Central Ground Water Board, Department of Water Resources, RD & GR. Ministry of Jal Shakti, Government of India, Faridabad. Retrieved from: http://cgwb.gov.in/GW-Assessment/GWRA-2017-National-Compilation.pdf. Accessed 1 May 2022.

  • Chenini I, Mammou AB, El May M (2010) Groundwater recharge zone mapping using GIS-based multi-criteria analysis: a case study in Central Tunisia (Maknassy Basin). Water Resource Manag 24(5):921–939. https://doi.org/10.1007/s11269-009-9479-1

    Article  Google Scholar 

  • Chowdhury A, Jha MK, Chowdary VM, Mal BC (2009) Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Medinipur district, West Bengal. India. Int J Remote Sens 30(1):231e250

    Google Scholar 

  • Council D, Program DS (2010) Measuring the depletion of groundwater resources worldwide. In: Walker L (ed) Science News. Sacramento, CA

    Google Scholar 

  • CWC and CGWB (2016) A 21st Century Institutional Architecture for India's Water Reforms. Retrieved from: http://cgwb.gov.in/INTRA-CGWB/Circulars/Report_on_Restructuring_CWC_CGWB.pdf. Accessed 11 June 2022.

  • Das M, Ashok N, Bishnupriya D, Om V (2018) Groundwater quality assessment and mapping using multivariate statistics and analytic hierarchy process in Bhubaneswar city, Odisha. India Inter J Water 12:195–207. https://doi.org/10.1504/IJW.2018.093668

    Article  Google Scholar 

  • Dey S, Shukla UK, Mehrishi P, Mall RK (2021) Appraisal of groundwater potentiality of multilayer alluvial aquifers of the Varuna river basin, India, using two concurrent methods of MCDM. Environ Dev Sustain. https://doi.org/10.1007/s10668-021-01400-5

    Article  Google Scholar 

  • Do P, Florke M (2005) Global-scale estimation of diffuse groundwater recharge. In: Din M (ed) Frankfurt hydrology paper 03. Institute of Physical Geography, Frankfurt University, Germany

    Google Scholar 

  • Ebrahimi H, Ghazavi R, Karimi H (2016) Estimation of groundwater recharge from the rainfall and irrigation in an arid environment using inverse modelling approach and RS. Water Resour Manag 30(6):1939–1951. https://doi.org/10.1007/s11269-016-1261-6

    Article  Google Scholar 

  • GhorbaniNejad S, Falah F, Daneshfar M, Haghizadeh A, Rahmati O (2017) Delineation of groundwater potential zones using remote sensing and GIS based data-driven models. Geocarto Int 32(2):167–187. https://doi.org/10.1080/10106049.2015.1132481

    Article  Google Scholar 

  • Ghosh PK, Bandyopadhyay S, Jana NC (2016) Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in gal. Model Earth Sys Environ 2(1):1. https://doi.org/10.1007/s40808-015-0044-z

    Article  Google Scholar 

  • Godebo TR (2005) Application of remote sensing and GIS for geological investigation and groundwater potential zone identification, southeastern Ethiopian plateau, Bale Mountains and the surrounding areas. Addis Ababa University. Retrieved from: http://etd.aau.edu.et/handle/123456789/7948. Accessed 13 May 2022.

  • Greenbaum D (1992) Structural influences on the occurrence of groundwater in SE Zimbabwe. Geol Soc Lond Spec Publ 66(1):77–85. https://doi.org/10.1144/GSL.SP.1992.066.01.04

    Article  Google Scholar 

  • Gumma MK, Pavelic P (2013) Mapping of groundwater potential zones across Ghana using remote sensing, geographic information systems, and spatial modeling. Environ Monit Assess 185(4):3561–3579. https://doi.org/10.1007/s10661-012-2810-y

    Article  Google Scholar 

  • Gupta SK, Deshpande RD (2004) Water for India in 2050: first-order assessment of available options. Curr Sci 86(9):1216–1224

    Google Scholar 

  • Gupta D, Yadav S, Tyagi D (2018a) Tomar L Multi-Criteria Decision Analysis for Identifying of Groundwater Potential Sites. Haridwar 3:9–15

    Google Scholar 

  • Guru B, Seshan K, Bera S (2017) Frequency ratio model for groundwater potential mapping and its sustainable management in cold desert. India J King Saud Univ Sci 29(3):333–347. https://doi.org/10.1016/j.jksus.2016.08.003

    Article  Google Scholar 

  • Hossein A, Ardakani H, Ekhtesasi MR (2016) Groundwater potentiality through analytic hierarchy process (AHP) using remote sensing and geographic information system (GIS). Jgeope 6:75–88

    Google Scholar 

  • IPCC (2018) Global Warming of 1.5°C.An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press.

  • IPCC (2001) Climate Change 2001. Synthesis Report. IPCC Third Assessment Report (TAR):A Contribution of Working Groups I, II, and III to the Third Assessment Report of the Integovernmental Panel on Climate Change. Ipcc, 409.

  • Ibrahim-Bathis K, Ahmed SA (2016) Geospatial technology for delineating groundwater potential zones in Doddahalla watershed of Chitradurga district, India. Egypt J Remote Sens Sp Sci 19:223–234. https://doi.org/10.1016/j.ejrs.2016.06.002

    Article  Google Scholar 

  • Ishizaka A, Labib A (2011) Review of the main developments in the analytic hierarchy process. Expert Syst Appl 38(11):14336–14345. https://doi.org/10.1016/j.eswa.2011.04.143

    Article  Google Scholar 

  • Jaiswal RK, Mukherjee S, Krishnamurthy J, Saxena R (2003) Role of remote sensing and GIS techniques for generation of groundwater prospect zones towards rural developmentean approach. Int J Remote Sens 24(5):993e1008

    Article  Google Scholar 

  • Jasrotia AS, Kumar A, Singh R (2016) Integrated remote sensing and GIS approach for delineation of groundwater potential zones using aquifer parameters in Devak and Rui watershed of Jammu and Kashmir. India Arabian J Geosci 9(4):1–15. https://doi.org/10.1007/s12517-016-2326-9

    Article  Google Scholar 

  • Jat M, Khare D, Garg P (2009) Urbanization and its impact on groundwater: a remote sensing and GIS-based assessment approach. Environmentalist 29:17–32. https://doi.org/10.1007/s10669-008-9176-2

    Article  Google Scholar 

  • Jha MK, Chowdary VM, Chowdhury A (2010) Groundwater assessment in Salboni Block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques. Hydrogeol J 18(7):1713–1728. https://doi.org/10.1007/s10040-010-0631-z

    Article  Google Scholar 

  • Kochhar A, Singh H, Sahoo S et al (2022) Prediction and forecast of pre-monsoon and post-monsoon groundwater level: using deep learning and statistical modelling. Model Earth Syst Environ 8:2317–2329. https://doi.org/10.1007/s40808-021-01235-z

    Article  Google Scholar 

  • Krishnamurthy J, Srinivas G (1995) Role of geological and geomorphological factors in groundwater exploration: a study using IRS LISS data. Int J Remote Sens 16(14):2595–2618. https://doi.org/10.1080/01431169508954579

    Article  Google Scholar 

  • Krishnamurthy J, Venkatesa Kumar N, Jayaraman V, Manivel M (1996) An approach to demarcate ground water potential zones through remote sensing and a geographical information system. Int J Remote Sens 17(10):1867–1884. https://doi.org/10.1080/01431169608948744

    Article  Google Scholar 

  • Kumar SS, Shruti K, Kant MS (2017) Delineation of groundwater potential zone using geospatial techniques for shimla city, himachal pradesh (India). IJSRD Inter J Sci Res. 50:665

    Google Scholar 

  • Kundzewicz ZW et al (2007) Freshwater resources and their management. In Parry ML, (eds) Climate change 2007: impacts, adaptation and vulnerability. Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press Cambridge, UK

  • Lee S, Lee CW (2015) Application of decision-tree model to groundwater productivity-potential mapping. Sustainability 7(10):13416–13432. https://doi.org/10.3390/su71013416

    Article  Google Scholar 

  • Lee S, Hong SM, Jung HS (2017) GIS-based groundwater potential mapping using artificial neural network and support vector machine models: the case of Boryeong city in Korea. Geocarto Int. https://doi.org/10.1080/10106049.2017.1303091

    Article  Google Scholar 

  • Machiwal D, Jha MK, Mal BC (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. https://doi.org/10.1007/s11269-010-9749-y

    Article  Google Scholar 

  • Madani A, Niyazi B (2015) Groundwater potential mapping using remote sensing techniques and weights of evidence GIS model: a case study from Wadi Yalamlam basin, Makkah Province. Western Saudi Arabia Environ Earth Sci 74(6):5129–5142. https://doi.org/10.1007/s12665-015-4524-2

    Article  Google Scholar 

  • Madrucci V, Taioli F, de Araújo CC (2008) Groundwater favorability map using GIS multicriteria data analysis on crystalline terrain, Sao Paulo. J Hydrol 357(3):153–173. https://doi.org/10.1016/j.jhydrol.2008.03.0260

    Article  Google Scholar 

  • Magesh NS, Chandrasekar N, JP (2012) Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geosci Front 3(2):189–196. https://doi.org/10.1016/j.gsf.2011.10.007

    Article  Google Scholar 

  • Mahmoud SH, Alazba AA, Amin MT (2014) Identification of Potential Sites for Groundwater Recharge Using a GIS-Based Decision Support System in Jazan Region-Saudi Arabia. Water Resour Manag 28(10):3319–3340. https://doi.org/10.1007/s11269-014-0681-4

    Article  Google Scholar 

  • Malczewski J (2006) GIS-based multicriteria decision analysis: a survey of the literature. Int J Geogr Inf Sci 20(7):703–726. https://doi.org/10.1080/13658810600661508

    Article  Google Scholar 

  • Mallick J, Singh CK, Al-Wadi H, Ahmed M, Rahman A, Shashtri S, Mukherjee S (2015) Geospatial and geostatistical approach for groundwater potential zone delineation. Hydrol Process 29(3):395–418. https://doi.org/10.1002/hyp.10153

    Article  Google Scholar 

  • McFEETERS SK (1996) The use of the normalized difference water index (ndwi) in the delineation of open water features. Int J Remote Sens 17(7):1425–1432. https://doi.org/10.1080/01431169608948714

    Article  Google Scholar 

  • McGarry D (2006) A Methodology of Visual-soil Field Assessment Tool to Support, Enhance, and Contribute to the LADA Program. Food and Agriculture Organization, Rome, Italy. Retrieved from: https://www.fao.org/3/i6362e/i6362e.pdf. Accessed 27 May 2022.

  • Mogaji K, Omosuyi G, Adelusi A, Lim H (2016) Application of GIS-based evidential belief function model to regional groundwater recharge potential zones mapping in hardrock geologic terrain. Environ Process 3:93–123

    Article  Google Scholar 

  • Moges DM, Bhat H, Thrivikramji KP (2019) Investigation of groundwater resources in highland Ethiopia using a geospatial technology. Model Earth Syst Environ. https://doi.org/10.1007/s40808-019-00603-0

    Article  Google Scholar 

  • Mukherjee P, Singh CK, Mukherjee S (2012) Delineation of groundwater potential zones in arid region of India-a remote sensing and gis approach. Water Resour Manag 26(9):2643–2672. https://doi.org/10.1007/s11269-012-0038-9

    Article  Google Scholar 

  • Murmu P, Kumar M, Lal D, Sonkerb I, Singh SK (2019) Delineation of groundwater potential zones using geospatial techniques and analytical hierarchy process in Dumka district. Groundwater Sustain Dev, Jharkhand, India. https://doi.org/10.1016/j.gsd.2019

    Book  Google Scholar 

  • Murthy KSR (2000) Ground water potential in a semi-arid region of Andhra Pradesh - a geographical information system approach. Int J Remote Sens 21(9):1867–1884. https://doi.org/10.1080/014311600209788

    Article  Google Scholar 

  • Nag SK, Ghosh P (2013) Delineation of groundwater potential zone in Chhatna Block, Bankura District, West Bengal, India using remote sensing and GIS techniques. Environ Earth Sci 70(5):2115–2127. https://doi.org/10.1007/s12665-012-1713-0

    Article  Google Scholar 

  • Nagarajan M, Singh S (2009) Assessment of groundwater potential zones using GIS technique. J Indian Soc Remote Sens 37(1):69–77. https://doi.org/10.1007/s12524-009-0012-z

    Article  Google Scholar 

  • Naghibi SA, Pourghasemi HR, Dixon B (2016) GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran. Environ Monit Assess 188(1):44. https://doi.org/10.1007/s10661-015-5049-6

    Article  Google Scholar 

  • Nampak H, Pradhan B, Manap MA (2014) Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. J Hydrol 513:283–300. https://doi.org/10.1016/j.jhydrol.2014.02.053

    Article  Google Scholar 

  • Patra S, Mishra P, Mahapatra SC, Mithun SK (2016) Modelling impacts of chemical fertilizer on agricultural production: a case study on Hooghly district, West Bengal. India Model Earth Syst Environ 2(4):180. https://doi.org/10.1007/s40808-016-0223-6

    Article  Google Scholar 

  • Patra S, Mishra P, Mahapatra SC (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

    Article  Google Scholar 

  • Pourtaghi ZS, Pourghasemi HR (2014) GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province. Iran Hydrogeol J 22(3):643–662. https://doi.org/10.1007/s10040-013-1089-6

    Article  Google Scholar 

  • Prasad RK, Mondal NC, Banerjee P, Nandakumar MV, Singh VS (2008) Deciphering potential groundwater zone in hard rock through the application of GIS. Environ Geol 55(3):467–475. https://doi.org/10.1007/s00254-007-0992-3

    Article  Google Scholar 

  • Preeja KR, Joseph S, Thomas J, Vijith H (2011) Identification of groundwater potential zones of a tropical river basin (Kerala, India) using remote sensing and GIS techniques. J Indian Soc Remote Sens 39(1):83e94

    Article  Google Scholar 

  • Rahman MA, Rusteberg B, Gogu RC, Lobo Ferreira JP, Sauter M (2012) A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge. J Environ Manage 30(99):61–75. https://doi.org/10.1016/j.jenvman.2012.01.003

    Article  Google Scholar 

  • Rajasekhar M, Sudarsana Raju G, Sreenivasulu Y, Raju RS (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. Hydro Res. 10:554

    Google Scholar 

  • Rao S (2006) N (2006) Groundwater potential index in a crystalline terrain using remote sensing data. Environ Geol 50:1067–1076. https://doi.org/10.1007/s00254-006-0280-7

    Article  Google Scholar 

  • Razavi-Termeh S, Sadeghi-Niaraki A, Choi S (2019) Groundwater Potential Mapping Using an Integrated Ensemble of Three Bivariate Statistical Models with Random Forest and Logistic Model Tree Models. Water 11:1596

    Article  Google Scholar 

  • Report of the Ground Water Resource Estimation Committee (2009) Ministry of Water Resources Government of India, New Delhi. Retrieved from: http://cgwb.gov.in/documents/gec97.pdf. Accessed 22 June 2022.

  • Roark D, Healy D(1998) Quantification of Deep Percolation from Two Flood-Irrigated Alfalfa Fields, Roswell Basin, New Mexico; USGS Water Resources Investigation Report 98–4096; U.S. Department of the Interior, U.S. Geological Survey: Albuquerque, NM, USA, 32p. Available online: https://pubs.usgs.gov/wri/1998/4096/report.pd Accessed on 30 Dec 2022

  • Rodell M, Velicogna I, Famiglietti JS (2009) Satellite-based estimates of groundwater depletion in India. Nature 460(7258):999–1002

    Article  Google Scholar 

  • Rudra K, Mukherjee SS, Mukhopadhyay UK, Gupta D (2017) State of environment report, West Bengal, 2016. Saraswaty Press Ltd, West Bengal Pollution Control Board. Retrieved from: https://www.wbpcb.gov.in/writereaddata/files/SOE_Report_2016_1.pdf. Accessed 17 June 2022.

  • Saaty TL (1980) The Analytic Hierarchy Process: Planning, Priority Setting. Resource Allocation, McGraw-Hill, New York

    Google Scholar 

  • Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48(1):9–26. https://doi.org/10.1016/0377-2217(90)90057-I

    Article  Google Scholar 

  • Saaty TL (2008) Decision making with the analytic hierarchy process. Int J Serv Sci 1(1):83

    Google Scholar 

  • Saha D, Dhar YR, Vittala SS (2010) Delineation of groundwater development potential zones in parts of marginal Ganga Alluvial Plain in South Bihar. Eastern India Environ Monit Assess 165(1):179–191. https://doi.org/10.1007/s10661-009-0937-2

    Article  Google Scholar 

  • Sahoo S, Dhar A, Kar A, Ram P (2017) Grey analytic hierarchy process applied to effectiveness evaluation for groundwater potential zone delineation. Geocarto Int. 32(11):1188–1205. https://doi.org/10.1080/10106049.2016.1195888

    Article  Google Scholar 

  • Sajad M, Mohammad B, Rather Dr G, Durdanah M (2021) Groundwater potential zonation using integration of remote sensing and ahp/anp approach in north kashmir, western himalaya. India. Rem Sens Land. 5:41–58

    Article  Google Scholar 

  • Sar N, Khan A, Chatterjee S et al (2015) Hydrologic delineation of ground water potential zones using geospatial technique for Keleghai river basin. India Model Earth Syst Environ 1:25. https://doi.org/10.1007/s40808-015-0024-3

    Article  Google Scholar 

  • Saraf AK, Choudhury PR (1998) Integrated remote sensing and GIS for groundwater exploration and identification of artificial recharge sites. Int J Remote Sens 19(10):1825–1841. https://doi.org/10.1080/014311698215018

    Article  Google Scholar 

  • Saranya T, Saravanan S (2020) Groundwater potential zone mapping using analytical hierarchy process (AHP) and GIS for Kancheepuram District, Tamilnadu. India Model Earth Syst Environ 6:1105–1122. https://doi.org/10.1007/s40808-020-00744-7

    Article  Google Scholar 

  • Scanlon B, Reedy R, Stonestrom D, Prudic D, Dennehy K (2005) Impact of land use and land cover change on groundwater recharge and quality in the southwestern US. Glob Chang Biol 11:1577–1593

    Article  Google Scholar 

  • Schultz GA, Engman ET (2012) Remote sensing in hydrology and water management. Springer Sci. https://doi.org/10.1007/978-3-642-59583-7

    Article  Google Scholar 

  • Senanayake IP, Dissanayake DMDOK, Mayadunna BB, Weerasekera WL (2016) An approach to delineate groundwater recharge potential sites in Ambalantota, Sri Lanka using GIS techniques. Geosci Front 7(1):115–124. https://doi.org/10.1016/j.gsf.2015.03.002

    Article  Google Scholar 

  • Senapati U, Das TK (2020) Assessment of potential land degradation in Akarsha Watershed, using GIS and multi-infuencing factor technique. In: Shit P (ed) Gully erosion studies from India and surrounding regions. Advances in Science, Technology Innovation, Cham Newyork

    Google Scholar 

  • Senapati U, Das TK (2021) Assessment of basin-scale groundwater potentiality mapping in drought-prone upper Dwarakeshwar River basin, West Bengal, India, using GIS-based AHP techniques. Arab J Geosci 14(11):1–22. https://doi.org/10.1007/s12517-021-07316-8

    Article  Google Scholar 

  • Sener E, Davraz A, Ozcelik M (2005) An integration of GIS and remote sensing in groundwater investigations: A case study in Burdur Turkey. Hydrogeol J 13(5–6):826–834. https://doi.org/10.1007/s10040-004-0378-5

    Article  Google Scholar 

  • Shekhar S, Jha M (2022) Groundwater level prediction of Varanasi wells during pre-monsoon and post-monsoon using intelligence approach. Arab J Geosci 15:88. https://doi.org/10.1007/s12517-021-08875-6

    Article  Google Scholar 

  • Shekhar S, Pandey AC (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. https://doi.org/10.1080/10106049.2014.894584

    Article  Google Scholar 

  • Sikdar PK, Chakraborty S, Adhya E, Paul PK (2004) Land use/Land cover changes and groundwater potential zoning in and around Raniganj coal mining area, Bardhaman District, West Bengal-A GIS and Remote Sensing Approach. J. Spatial Hydrol. 4:776

    Google Scholar 

  • Singh SK, Kanga S, Mishra S (2017) Delineation of Groundwater Potential Zone Using Geospatial Techniques for Shimla City, Himachal Pradesh (India). IJSRD - International Journal for Scientific Research & Development 5(0)

  • Srivastava PK, Bhattacharya AK (2006) Groundwater assessment through an integrated approach using remote sensing, GIS and resistivity techniques: a case study from a hard rock terrain. Int J Remote Sens 27(20):4599–4620. https://doi.org/10.1080/01431160600554983

    Article  Google Scholar 

  • Taylor RG, Todd MC, Kongola L, Maurice L, Nahozya E, Sanga H, MacDonald A (2013) Evidence of the dependence of groundwater resources on extreme rainfall in East Africa. Nat Clim Change 3(4):374–378. https://doi.org/10.1038/nclimate1731

    Article  Google Scholar 

  • Thapa R, Gupta S, Guin S, Kaur H (2017) Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS a case study from Birbhum district, West Bengal. Appl. Water Sci. 7:4117–4131. https://doi.org/10.1007/s13201-017-0571-z

    Article  Google Scholar 

  • Tucker CJ (1979) Red and photographic infrared linear combinations for monitoringvegetation. Remote Sens Environ 8:127–150. https://doi.org/10.1016/0034-4257(79)90013-0

    Article  Google Scholar 

  • Yeh H, Cheng Y, Lin H, Lee C (2016) Mapping groundwater recharge potential zone using a GIS approach in Hualian River, Taiwan. Sustain Environ Res. 6(1):33–43 https://doi.org/10.1016/j.serj.2015.09.005

    Article  Google Scholar 

  • Zaidi FK, Nazzal Y, Ahmed I, Naeem M, Jafri MK (2015) Identification of potential artificial groundwater recharge zones in Northwestern Saudi Arabia using GIS and Boolean logic. J African Earth Sci 111:156–169. https://doi.org/10.1016/j.jafrearsci.2015.07.008

    Article  Google Scholar 

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Acknowledgements

The authors are sincerely thankful to the editor and anonymous reviewers for their valuable comments and suggestions. Moreover, the authors are grateful to different agencies for providing the required data free of cost. Central Ground Water Board and India-WRIS provided necessary data free of charge to us. The USGS provided the required satellite data. The district groundwater related information was provided by the State Water Resources & Development Department and SWID (Jalpaiguri), Government of West Bengal.

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Authors and Affiliations

  1. Department of Geography, State Aided College Teacher, Cooch Behar College, Cooch Behar, India

    Saumyajit Ghosh

  2. Department of Geography, Cooch Behar Panchanan Barma University, Cooch Behar, India

    Dipankar Das & Shasanka Kumar Gayen

  3. Department of Geography, Government College Bahu, Jhajjar, Haryana, India

    Pankaj Bhardwaj

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  1. Saumyajit Ghosh
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  2. Dipankar Das
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Ghosh, S., Das, D., Gayen, S.K. et al. Delineation of groundwater potential zones using the AHP technique: a case study of Alipurduar district, West Bengal. Model. Earth Syst. Environ. 9, 4507–4537 (2023). https://doi.org/10.1007/s40808-023-01733-2

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