Assessment of groundwater potential zones in data-scarce regions using GIS-based multicriteria decision making approach

References

• Achu AL, Anjali N, Gopinath G. 2022. Delineation of groundwater potential zones in a tropical river basin using geospatial techniques and analytical hierarchy process. In: Singh VP, Yadav S, Yadav KK, Corzo Perez GA, Muñoz-Arriola F, Yadava RN, editors. Application of remote sensing and GIS in natural resources and built infrastructure management. Cham: springer International Publishing. p. 259–278. doi:10.1007/978-3-031-14096-9_13.
   Google Scholar
• Agarwal R, Garg PK. 2015. Remote sensing and GIS based groundwater potential & recharge zones mapping using multi-criteria decision making technique. Water Resour Manage. 30(1):243–260. doi:10.1007/s11269-015-1159-8.
   Web of Science ®Google Scholar
• Akinlalu AA, Adegbuyiro A, Adiat KAN, Akeredolu BE, Lateef WY. 2017. Application of multi-criteria decision analysis in prediction of groundwater resources potential: a case of Oke-Ana, Ilesa Area Southwestern, Nigeria. NRIAG J Astron Geophys. 6(1):184–200. doi:10.1016/j.nrjag.2017.03.001.
   Google Scholar
• Al-Abadi AM, Shahid S. 2015. A comparison between index of entropy and catastrophe theory methods for mapping groundwater potential in an arid region. Environ Monit Assess. 187(9):576. doi:10.1007/s10661-015-4801-2.
   PubMed Web of Science ®Google Scholar
• Anbarasu S, Brindha K, Elango L. 2020. Multi-influencing factor method for delineation of groundwater potential zones using remote sensing and GIS techniques in the western part of Perambalur district, southern India. Earth Sci Inform. 13(2):317–332. doi:10.1007/s12145-019-00426-8.
   Web of Science ®Google Scholar
• Arnous MO. 2016. Groundwater potentiality mapping of hard-rock terrain in arid regions using geospatial modelling: example from Wadi Feiran basin, South Sinai, Egypt. Hydrogeol J. 24(6):1375–1392. doi:10.1007/s10040-016-1417-8.
   Web of Science ®Google Scholar
• Balamurugan P, Kumar PS, Shankar K. 2020. Dataset on the suitability of groundwater for drinking and irrigation purposes in the Sarabanga River region, Tamil Nadu, India. Data Brief. 29:105255. doi:10.1016/j.dib.2020.105255.
   PubMed Web of Science ®Google Scholar
• Bello-Dambatta A, Farmani R, Javadi AA, Evans BM. 2009. The Analytical Hierarchy Process for contaminated land management. Adv Eng Inf. 23(4):433–441. doi:10.1016/j.aei.2009.06.006.
   Web of Science ®Google Scholar
• Bera A, Mukhopadhyay BP, Das D. 2019. Landslide hazard zonation mapping using multi-criteria analysis with the help of GIS techniques: a case study from Eastern Himalayas, Namchi, South Sikkim. Nat Hazards. 96(2):935–959. doi:10.1007/s11069-019-03580-w.
   Web of Science ®Google Scholar
• Bera B, Shit PK, Sengupta N, Saha S, Bhattacharjee S. 2021. Trends and variability of drought in the extended part of Chhota Nagpur plateau (Singbhum Protocontinent), India applying SPI and SPEI indices. Environ Challeng. 5:100310. doi:10.1016/j.envc.2021.100310.
   Google Scholar
• Bhadran A, Girishbai D, Jesiya NP, Gopinath G, Krishnan RG, Vijesh VK. 2022. A GIS based Fuzzy-AHP for delineating groundwater potential zones in tropical river basin, southern part of India. Geosyst Geoenviron. 1(4):100093. doi:10.1016/j.geogeo.2022.100093.
   Google Scholar
• Biswas T, Pal SC, Ruidas D, Islam ARMT, Saha A, Costache R, Shit M. 2023a. Modelling of groundwater potential zone in hard rock-dominated drought-prone region of eastern India using integrated geospatial approach. Environ Earth Sci. 82(3):81. doi:10.1007/s12665-023-10768-8.
   Web of Science ®Google Scholar
• Biswas T, Pal SC, Saha A. 2023b. Hydro-chemical assessment of coastal groundwater aquifers for human health risk from elevated arsenic and fluoride in West Bengal, India. Mar Pollut Bull. 186:114440. doi:10.1016/j.marpolbul.2022.114440.
   PubMed Web of Science ®Google Scholar
• Daliakopoulos IΝ, Coulibaly P, Tsanis IK. 2005. Groundwater level forecasting using artificial neural networks. J Hydrol. 309(1-4):229–240. doi:10.1016/j.jhydrol.2004.12.001.
   Web of Science ®Google Scholar
• Dar IA, Sankar K, Dar MA. 2010. Remote sensing technology and geographic information system modeling: an integrated approach towards the mapping of groundwater potential zones in Hardrock terrain, Mamundiyar basin. J Hydrol. 394(3-4):285–295. doi:10.1016/j.jhydrol.2010.08.022.
   Web of Science ®Google Scholar
• Das B, Pal SC, Malik S, Chakrabortty R. 2019. Modeling groundwater potential zones of Puruliya district, West Bengal, India using remote sensing and GIS techniques. Geol Ecol Landscapes. 3(3):223–237. doi:10.1080/24749508.2018.1555740.
   Google Scholar
• Das S. 2019. Comparison among influencing factor, frequency ratio, and analytical hierarchy process techniques for groundwater potential zonation in Vaitarna basin, Maharashtra, India. Groundwater Sustain Dev. 8:617–629. doi:10.1016/j.gsd.2019.03.003.
   Google Scholar
• Deng F, Deng Z, Lv D, Wang D, Duan H, Xing Z. 2016. Application of remote sensing and GIS analysis in groundwater potential estimation in west Liaoning Province, China. J Engineer Res. 4(3):1–17. https://kuwaitjournals.org/jer/index.php/JER/article/view/976
   Web of Science ®Google Scholar
• Dinesan VP, Gopinath G, Ashitha MK. 2015. Application of geoinformatics for the delineation of groundwater prospects zones- a case study for Melattur Grama Panchayat in Kerala, India. Aquat Procedia. 4:1389–1396. doi:10.1016/j.aqpro.2015.02.180.
   Google Scholar
• Donahue RL, Miller RW, Shickluna JC. 1978. Soils – An introduction to soils and plant growth. Soil Sci. 125(4):271. doi:10.1097/00010694-197804000-00019.
   Google Scholar
• Ejepu JS, Jimoh MO, Abdullahi S, Mba MA. 2022. Groundwater Exploration using multi criteria decision analysis and analytic hierarchy process in federal capital territory, Abuja, Central Nigeria. IJG. 13(01):33–53. doi:10.4236/ijg.2022.131003.
   Google Scholar
• Foster SSD. 2001. The interdependence of groundwater and urbanisation in rapidly developing cities. Urban Water. 3(3):185–192. doi:10.1016/S1462-0758(01)00043-7.
   Google Scholar
• Ghosh PK, Bandyopadhyay S, Jana NC. 2015. Mapping of groundwater potential zones in hard rock terrain using geoinformatics: a case of Kumari watershed in western part of West Bengal. Model Earth Syst Environ. 2(1):1. doi:10.1007/s40808-015-0044-z.
   Google Scholar
• Godfray G, Tembo MM. 2022. Assessment of ground water potentiality in semi-arid area of central Tanzania. implication from geology and geomorphology of the dodoman supergroup. Geol Ecol Landscapes. 1–20. doi:10.1080/24749508.2022.2109833.
   Google Scholar
• Gopinath G, Seralathan P. 2004. Identification of groundwater prospective zones using irs-id liss iii and pump test methods. J Indian Soc Remote Sens. 32(4):329–342. doi:10.1007/BF03030858.
   Google Scholar
• Guchhait S, Dolui G, Das S, Das N. 2023. Chapter 15 - Groundwater fluctuation and agricultural insecurity: a geospatial analysis of West Bengal in India. In: Shit P, Bhunia G, Adhikary P, editors. Case studies in geospatial applications to groundwater resources. Elsevier. p. 275–288. doi:10.1016/B978-0-323-99963-2.00002-X.
   Google Scholar
• Hasanuzzaman M, Mandal MH, Hasnine M, Shit PK. 2022. Groundwater potential mapping using multi-criteria decision, bivariate statistic and machine learning algorithms: evidence from Chota Nagpur Plateau, India. Appl Water Sci. 12(4):58. doi:10.1007/s13201-022-01584-9.
   Web of Science ®Google Scholar
• Holt CLR. 1965. Geology and water resources of Portage County, Wisconsin. U.S. Geological Survey. doi:10.3133/wsp1796.
   Google Scholar
• Jesiya NP, Gopinath G. 2019. A Customized FuzzyAHP - GIS based DRASTIC-L model for intrinsic groundwater vulnerability assessment of urban and peri urban phreatic aquifer clusters. Groundwater Sustain Dev. 8:654–666. doi:10.1016/j.gsd.2019.03.005.
   Google Scholar
• Jesiya NP, Gopinath G. 2020. A fuzzy based MCDM–GIS framework to evaluate groundwater potential index for sustainable groundwater management - A case study in an urban-periurban ensemble, southern India. Groundwater Sustain Dev. 11:100466. doi:10.1016/j.gsd.2020.100466.
   Google Scholar
• Jhariya DC, Kumar T, Gobinath M, Diwan P, Kishore N. 2016. Assessment of groundwater potential zone using remote sensing, GIS and multi criteria decision analysis techniques. J Geol Soc India. 88(4):481–492. doi:10.1007/s12594-016-0511-9.
   Web of Science ®Google Scholar
• Krakauer NY, Li H, Fan Y. 2014. Groundwater flow across spatial scales: importance for climate modeling. Environ Res Lett. 9(3):034003. doi:10.1088/1748-9326/9/3/034003.
   Web of Science ®Google Scholar
• Kumar KK, Patwardhan SK, Kulkarni A, Kamala K, Rao KK, Jones R. 2011. Simulated projections for summer monsoon climate over India by a high-resolution regional climate model (PRECIS). Current Science. 101(3):312–326.
   Web of Science ®Google Scholar
• Kumari A, Singh A. 2021. Delineation of Groundwater Potential Zone using Analytical Hierarchy Process. J Geol Soc India. 97(8):935–942. doi:10.1007/s12594-021-1794-z.
   Web of Science ®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. doi:10.1007/s12665-015-4524-2.
   Web of Science ®Google Scholar
• Magesh NS, Chandrasekar N, Soundranayagam 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. doi:10.1016/j.gsf.2011.10.007.
   Web of Science ®Google Scholar
• Mahmoud SH, Alazba AA. 2016. Integrated remote sensing and GIS‐based approach for deciphering groundwater potential zones in the central region of Saudi Arabia. Environ Earth Sci. 75(4):344. doi:10.1007/s12665-015-5156-2.
   Web of Science ®Google Scholar
• Maity DK, Mandal S. 2017. 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. Mismatch] doi:10.1007/s10668-017-0072-0.
   Web of Science ®Google Scholar
• Mall RK, Gupta A, Singh R, Singh RS, Rathore LS. 2006. Water resources and climate change: an Indian perspective. Current Sci. 90(12):1610–1626.
   Web of Science ®Google Scholar
• Manap MA, Sulaiman WNA, Ramli MF, Pradhan B, Surip N. 2013. A knowledge-driven GIS modeling technique for groundwater potential mapping at the Upper Langat Basin, Malaysia. Arab J Geosci. 6(5):1621–1637. doi:10.1007/s12517-011-0469-2.
   Web of Science ®Google Scholar
• Miraki S, Zanganeh SH, Chapi K, Singh VP, Shirzadi A, Shahabi H, Pham BT. 2018. Mapping groundwater potential using a novel hybrid intelligence approach. Water Resour Manage. 33(1):281–302. doi:10.1007/s11269-018-2102-6.
   Web of Science ®Google Scholar
• Mishra RK. 2023. Fresh Water availability and Its Global challenge. BJMAS. 4(3):1–78. doi:10.37745/bjmas.2022.0208.
   Google Scholar
• Mogaji KA. 2016. Combining geophysical techniques and multi-criteria GIS-based application modeling approach for groundwater potential assessment in southwestern Nigeria. Environ Earth Sci. 75(16):1181. doi:10.1007/s12665-016-5897-6.
   Web of Science ®Google Scholar
• Mohammady M, Pourghasemi HR, Pradhan B. 2012. Landslide susceptibility mapping at Golestan Province, Iran: a comparison between frequency ratio, Dempster–Shafer, and weights-of-evidence models. J Asian Earth Sci. 61:221–236. doi:10.1016/j.jseaes.2012.10.005.
   Web of Science ®Google Scholar
• Moharir KN, Pande CB, Gautam VK, Singh SK, Rane NL. 2023. Integration of hydrogeological data, GIS and AHP techniques applied to delineate groundwater potential zones in sandstone, limestone and shales rocks of the Damoh district, (MP) central India. Environ Res. 228:115832. doi:10.1016/j.envres.2023.115832.
   PubMed Web of Science ®Google Scholar
• Moiwo JP, Yang Y, Li H, Han S, Yang Y. 2010. Impact of water resource exploitation on the hydrology and water storage in Baiyangdian Lake. Hydrol Processes. 24(21):3026–3039. doi:10.1002/hyp.7716.
   Web of Science ®Google Scholar
• Mukherjee I, Singh UK. 2018. Groundwater fluoride contamination, probable release, and containment mechanisms: a review on Indian context. Environ Geochem Health. 40(6):2259–2301. doi:10.1007/s10653-018-0096-x.
   PubMed Web of Science ®Google Scholar
• Murmu P, Kumar M, Lal D, Sonker I, Singh SK. 2019. Delineation of groundwater potential zones using geospatial techniques and analytical hierarchy process in Dumka district, Jharkhand, India. Groundwater Sustain Dev. 9:100239. doi:10.1016/j.gsd.2019.100239.
   Google Scholar
• Naghibi SA, Pourghasemi HR, Dixon BM. 2015. 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. doi:10.1007/s10661-015-5049-6.
   PubMed Web of Science ®Google Scholar
• Naghibi SA, Vafakhah M, Hashemi H, Pradhan B, Alavi SJ. 2018. Groundwater augmentation through the site selection of floodwater spreading using a data mining approach (case study: mashhad Plain, Iran). Water. 10(10):1405. doi:10.3390/w10101405.
   Web of Science ®Google Scholar
• Naidoo S, Olaniran AO. 2014. Treated Wastewater Effluent as a Source of Microbial Pollution of Surface Water Resources. Int J Environ Res Public Health. 11(1):249–270. doi:10.3390/ijerph110100249.
   Web of Science ®Google Scholar
• 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):1–20. doi:10.1007/s13201-021-01522-1.
   Web of Science ®Google Scholar
• Pandey HK, Singh VK, Singh SK. 2022. Multi-criteria decision making and Dempster-Shafer model–based delineation of groundwater prospect zones from a semi-arid environment. Environ Sci Pollut Res. :1–19.
   Web of Science ®Google Scholar
• Paneerselvam B, Ravichandran N, Li P, Thomas M, Charoenlerkthawin W, Bidorn B. 2023. Machine learning approach to evaluate the groundwater quality and human health risk for sustainable drinking and irrigation purposes in South India. Chemosphere. 336:139228. doi:10.1016/j.chemosphere.2023.139228.
   PubMedGoogle Scholar
• Panneerselvam B, Karuppannan S, Muniraj K. 2020. Evaluation of drinking and irrigation suitability of groundwater with special emphasizing the health risk posed by nitrate contamination using nitrate pollution index (NPI) and human health risk assessment (HHRA). Hum Ecolog Risk Assess International J. 27(5):1324–1348. doi:10.1080/10807039.2020.1833300.
   Web of Science ®Google Scholar
• Panneerselvam B, Muniraj K, Duraisamy K, Pande C, Karuppannan S, Thomas M. 2023. An integrated approach to explore the suitability of nitrate-contaminated groundwater for drinking purposes in a semiarid region of India. Environ Geochem Health. 45(3):647–663. doi:10.1007/s10653-022-01237-5.
   PubMed Web of Science ®Google Scholar
• Panneerselvam B, Muniraj K, Pande C, Ravichandran N. 2023. Prediction and evaluation of groundwater characteristics using the radial basic model in Semi-arid region, India. Inter J Environ Analyt Chem. 103(6):1377–1393. doi:10.1080/03067319.2021.1873316.
   Web of Science ®Google Scholar
• 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. Sustainability. 9(7):1157. doi:10.3390/su9071157.
   Web of Science ®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. doi:10.1007/s10040-013-1089-6.
   Web of Science ®Google Scholar
• Roy P, Pal SC, Chakrabortty R, Chowdhuri I, Saha A, Shit M. 2022. Climate change and groundwater overdraft impacts on agricultural drought in India: vulnerability assessment, food security measures and policy recommendation. Sci Total Environ. 849:157850. doi:10.1016/j.scitotenv.2022.157850.
   PubMed Web of Science ®Google Scholar
• Ruidas D, Pal SC, Islam T, Md AR, Saha A. 2022. Hydrogeochemical evaluation of groundwater aquifers and associated health hazard risk mapping using ensemble data driven model in a water scares plateau region of Eastern India. Expo Health. 15(1):113–131. doi:10.1007/s12403-022-00480-6.
   Web of Science ®Google Scholar
• Saha S. 2017. Groundwater potential mapping using analytical hierarchical process: a study on Md. Bazar Block of Birbhum District, West Bengal. Spat Inf Res. 25(4):615–626. doi:10.1007/s41324-017-0127-1.
   Web of Science ®Google Scholar
• Sankar K, Karunanidhi D, Kalaivanan K, Subramani T, Shanthi D, Balamurugan P. 2023. Integrated hydrogeophysical and GIS based demarcation of groundwater potential and vulnerability zones in a hard rock and sedimentary terrain of Southern India. Chemosphere. 316:137305. doi:10.1016/j.chemosphere.2022.137305.
   PubMed Web of Science ®Google Scholar
• Saaty TL. 1980. The analytical hierarchy process, planning, priority. Pittsburgh: RWS publications. New York, NY: McGraw-Hill.
   Google Scholar
• Saaty TL. 1990a. Eigenvector and logarithmic least squares. Eur J Oper Res. 48(1):156–160. doi:10.1016/0377-2217(90)90073-K.
   Web of Science ®Google Scholar
• Saaty TL. 1990b. How to make a decision: the analytic hierarchy process. Eur J Oper Res. 48(1):9–26. doi:10.1016/0377-2217(90)90057-I.
   Web of Science ®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):960. doi:10.1007/s12517-021-07316-8.
   Web of Science ®Google Scholar
• Shaji E, Santosh M, Sarath KV, Prakash P, Deepchand V, Divya BV. 2021. Arsenic contamination of groundwater: a global synopsis with focus on the Indian Peninsula. Geosci Front. 12(3):101079. doi:10.1016/j.gsf.2020.08.015.
   Web of Science ®Google Scholar
• Shao Z, Huq M, Cai B, Altan O, Li Y. 2020. Integrated remote sensing and GIS approach using Fuzzy-AHP to delineate and identify groundwater potential zones in semi-arid Shanxi Province, China. Environ Modell Softw. 134:104868. doi:10.1016/j.envsoft.2020.104868.
   Web of Science ®Google Scholar
• Shelar RS, Shinde SP, Pande CB, Moharir KN, Orimoloye IR, Mishra AP, Varade AM. 2022. Sub-watershed prioritization of Koyna river basin in India using multi criteria analytical hierarchical process, remote sensing and GIS techniques. Phys Chem Earth Parts A/B/C. 128:103219. doi:10.1016/j.pce.2022.103219.
   Web of Science ®Google Scholar
• Shiferaw B, Reddy VR, Wani SP. 2008. Watershed externalities, shifting cropping patterns and groundwater depletion in Indian semi-arid villages: the effect of alternative water pricing policies. Ecol Econ. 67(2):327–340. doi:10.1016/j.ecolecon.2008.05.011.
   Web of Science ®Google Scholar
• Sikakwe GU. 2023. Mineral exploration employing drones, contemporary geological satellite remote sensing and geographical information system (GIS) procedures: a review. Remote Sens Appl: soc Environ. 31:100988. doi:10.1016/j.rsase.2023.100988.
   Google Scholar
• Strahler AN. 1952. Hypsometric (area-altitude) analysis of erosional topography. Geol Soc America Bull. 63(11):1117. doi:10.1130/0016-7606(1952)63[1117:HAAOET]2.0.CO;2.
   Web of Science ®Google Scholar
• Suryanarayana C, Sudheer C, Mahammood V, Panigrahi BK. 2014. An integrated wavelet-support vector machine for groundwater level prediction in Visakhapatnam India. Neurocomputing. 145:324–335. doi:10.1016/j.neucom.2014.05.026.
   Web of Science ®Google Scholar
• Swetha TV, Gopinath G, Thrivikramji KP, Jesiya NP. 2017. Geospatial and MCDM tool mix for identification of potential groundwater prospects in a tropical river basin, Kerala. Environ Earth Sci. 76(12):428. doi:10.1007/s12665-017-6749-8.
   Web of Science ®Google Scholar
• Tahmassebipoor N, Rahmati O, Noormohamadi F, Lee S. 2015. Spatial analysis of groundwater potential using weights-of-evidence and evidential belief function models and remote sensing. Arab J Geosci. 9(1):79. doi:10.1007/s12517-015-2166-z.
   Web of Science ®Google Scholar
• Thakur JK, Singh SK, Ekanthalu VS. 2017. Integrating remote sensing, geographic information systems and global positioning system techniques with hydrological modeling. Appl Water Sci. 7(4):1595–1608. doi:10.1007/s13201-016-0384-5.
   Web of Science ®Google Scholar
• Torabi Haghighi A, Abou Zaki N, Rossi PM, Noori R, Hekmatzadeh AA, Saremi H, Kløve B. 2020. Unsustainability syndrome—from meteorological to agricultural drought in arid and semi-arid regions. Water. 12(3):838. doi:10.3390/w12030838.
   Web of Science ®Google Scholar
• Tucker GE, Catani F, Rinaldo A, Bras RL. 2001. Statistical analysis of drainage density from digital terrain data. Geomorphology. 36(3-4):187–202. doi:10.1016/S0169-555X(00)00056-8.
   Web of Science ®Google Scholar
• Wang Y, Li R, Wu X, Yan Y, Wei C, Luo M, Xiao Y, Zhang Y. 2023. Evaluation of groundwater quality for drinking and irrigation purposes using GIS-Based IWQI, EWQI and HHR model. Water. 15(12):2233. doi:10.3390/w15122233.
   Web of Science ®Google Scholar
• Yesilnacar MI, Gulluoglu MS. 2008. Hydrochemical characteristics and the effects of irrigation on groundwater quality in Harran Plain, GAP Project, Turkey. Environ Geol. 54(1):183–196. doi:10.1007/s00254-007-0804-9.
   Google Scholar