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Integrated geophysical, geospatial and multiple-criteria decision analysis techniques for delineation of groundwater potential zones in a semi-arid hard-rock aquifer in Maharashtra, India

Analyses d’aide à la décision multi-critères basées sur des données géophysiques spatialisées pour la délimitation de zones à potentialité en eaux souterraines dans un aquifère fissuré en climat semi-aride dans le Maharashtra, Inde

Técnicas integradas de análisis de decisiones geofísicas, geoespaciales y de criterios múltiples para la delineación de zonas potenciales de aguas subterráneas en un acuífero semiárido de roca dura en Maharashtra, India

描述印度马哈拉托特拉邦半干旱硬岩含水层地下水潜力带的地球物理、地理空间及多标准综合决策分析

Técnicas integradas geofísicas, geoespaciais e de análise de decisão multicritérios para o delineamento de zonas potenciais de águas subterrâneas em aquífero de rocha cristalina em uma região semiárida em Maharashtra, India

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Abstract

A novel framework has been developed for delineating groundwater potential zones (GWPZ) using fuzzy datasets and the analytical hierarchical process (AHP) integrated with hydrogeological, geophysical and geospatial data for a hard-rock trap-covered terrain in Maharashtra, India. This approach is based on the consideration of ten factors that influence groundwater potential: aquifer resistivity, aquifer thickness, transverse resistance, electrical anisotropy, drainage density, lineament density, rainfall, slope, geology and land use/land cover. The ranks and weights were obtained by fuzzy and AHP techniques and assigned to these layers and their feature class. The reclassified layers were integrated in a geographical information system environment to delineate the GWPZ of the study basin. The findings reveal that the areas of very high groundwater potential are located in the plateau region and plains of the basin that occupy about 11.5% of the total study area. These results are further validated using the relative operating characteristics technique, wherein area under the curve is 0.83, indicating good accuracy. The study highlights that such an integrated approach is reliable and can be applied in other semi-arid regions of the world to help hydrogeologists manage groundwater resources.

Résumé

Un nouveau cadre a été développé pour délimiter des zones à potentialité en eaux souterraines (ZPES) en utilisant la méthode d’ensembles flous et le processus analytique hiérarchisé (PAH) appliqués à des données spatialisées hydrogéologiques et géophysiques pour un milieu fissuré de socle sous couverture dans le Maharashtra en Inde. Cette approche est basée sur la prise en compte de dix facteurs qui influencent la présence potentielle en eaux souterraines: résistivité de l’aquifère, épaisseur de l’aquifère, résistance transversale, anisotropie électrique, densité de drainage, densité de linéaments, précipitations, pente, géologie et occupation et utilisation des terres. Les rangs et pondérations ont été obtenus par des techniques de logique floue et de PHA et attribués à ces couches et à leur classe de caractéristiques. Après une reclassification, les couches ont été intégrées dans un système d’information géographique afin de délimiter les ZPES du bassin étudié. Les résultats mettent en évidence que les zones à très forte potentialité en eaux souterraines sont situées dans les régions de plateau et de plaines du bassin, qui occupent environ 11.5% de la superficie totale de la zone étudiée. Ces résultats sont ensuite validés à l’aide de la technique des caractéristiques de fonctionnement relatives, dans laquelle l’aire sous la courbe est de 0.83, indiquant une bonne précision. L’étude souligne qu’une telle approche intégrée est fiable et peut être appliquée dans d’autres régions semi-arides du monde pour aider les hydrogéologiques à gérer les ressources en eaux souterraines.

Resumen

Se ha desarrollado un enfoque novedoso para delinear zonas potenciales de agua subterránea (GWPZ) utilizando conjuntos de datos difusos y el proceso jerárquico analítico (AHP) integrado con datos hidrogeológicos, geofísicos y geoespaciales en un terreno cubierto por roca dura en Maharashtra, India. Este enfoque se basa en la consideración de diez factores que influyen en el potencial del agua subterránea: resistividad del acuífero, espesor del acuífero, resistencia transversal, anisotropía eléctrica, densidad de drenaje, densidad de lineamientos, precipitación pluvial, pendiente, geología y uso/cobertura del suelo. Los rangos y pesos se obtuvieron mediante técnicas difusas y de AHP y se asignaron a estas capas y su clase característica. Las capas reclasificadas se integraron en un entorno de sistema de información geográfica para delinear las GWPZ de la cuenca de estudio. Los hallazgos revelan que las áreas con un potencial de agua subterránea muy alto están ubicadas en la región de la meseta y las llanuras de la cuenca que ocupan alrededor del 11.5% del área total del estudio. Estos resultados se validan aún más utilizando la técnica de características operativas relativas, en donde el área bajo la curva es 0.83, lo que indica una buena precisión. El estudio destaca que este enfoque integrado es confiable y se puede aplicar en otras regiones semiáridas del mundo para ayudar a los hidrogeólogos a gestionar los recursos de aguas subterráneas.

摘要

开发了利用模糊数据集及综合水文地质、地球物理和地理空间数据的层次分析法描述印度马哈拉托特拉邦硬岩覆盖地区地下水潜力带的新的框架。该方法基于考虑十个影响地下水潜力的因子:含水层电阻率、含水层厚度、横断面电阻率、电各向异性、排水行密度、线性构造密度、降雨、坡度、地质条件和土地利用/土地覆盖类型。通过模糊和层次分析法技术获取了因子的级别和权重,级别和因子被分配到这些层中及其特色类中。重新分类的层结合到地理信息系统环境中,以描述研究流域的地下水潜力带。研究结果揭示,具有非常高地下水潜力的地区位于流域的高原区和平原,该流域面积为整个研究区的11.5%。采用相关的操作特征技术进一步验证了这些结果,其中曲线之下地区为0.83,表明准确性很高。研究强调了该综合方法是可靠的,可用于世界上其它半干旱地区,以帮助水文地质工作者管理地下水资源。

Resumo

Um novo arcabouço foi desenvolvido para o delineamento de zonas potenciais de águas subterrâneas (ZPAS) utilizando conjuntos de dados fuzzy e o processo hierárquico analítico (AHP) integrados com dados geoespaciais, geofísicos e hidrogeológicos para terreno de rochas cristalinas com coberturas armadilha em Maharashtra, Índia. Essa abordagem é baseada na consideração de dez fatores que influenciam o potencial de águas subterrâneas: a resistividade do aquífero, a espessura do aquífero, resistência transversa, anisotropia elétrica, densidade de drenagem, densidade de lineamento, precipitação, declividade, geologia e uso/cobertura da terra. As classificações e pesos foram obtidos por técnicas fuzzy e AHP e atribuídas para essas camadas com a classe de caraterística delas. As camadas reclassificadas foram integradas em ambiente de sistema de informação geográfica para delinear as ZPAS da bacia no estudo. As descobertas revelam que as áreas com potencial de águas subterrâneas muito alto estão localizadas na região de planalto e nas planícies da bacia que ocupam por volta de 11.5% da área de estudo total. Esses resultados foram posteriormente validados utilizando-se a técnica de características de operação relativa, onde a abaixo da curva é de 0.83, indicando boa precisão. O estudo destaca que tal abordagem integrada é confiável e pode ser aplicada em outras regiões semiáridas do mundo para ajudar hidrogeólogos a gerenciarem recursos hídricos subterrâneos.

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References

  • Abuzied SM, Alrefaee HA (2017) Mapping of groundwater prospective zones integrating remote sensing, geographic information systems and geophysical techniques in El-Qaà Plain area, Egypt. Hydrogeol J 25:2067–2088

    Article  Google Scholar 

  • Adeoti L, Alile OM, Uchegbulam O (2010) Geophysical investigation of saline water intrusion into freshwater aquifers: a case study of Oniru, Lagos State. Sci Res Essays 5(3):248–259

    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 30:243–260

    Article  Google Scholar 

  • Ahmed K, Shahid S, Bin Harun S, Ismail T, Nawaz N, Shamsudin S (2015) Assessment of groundwater potential zones in an arid region based on catastrophe theory. Earth Sci Inf 8(3):539–549

    Article  Google Scholar 

  • Ammar A, Riksen M, Ouessar M, Ritsema C (2016) Identification of suitable sites for rainwater harvesting structures in arid and semi-arid regions: a review. Intern Soil Water Conservation Res 4(2):108–120. https://doi.org/10.1016/j.iswcr.2016.03.001

    Article  Google Scholar 

  • Aouragh MH, Essahlaoui A, El Ouali A, El Hmaidi A (2016) Groundwater potential of Middle Atlas plateaus, Morocco, using fuzzy logic approach, GIS and remote sensing. Geomat Natural Haz Risk. https://doi.org/10.1080/19475705.2016.1181676

  • Ayuk MA, Adelusi AO, Adiat KAN (2013) Evaluation of groundwater potential and aquifer protective capacity assaament at Tutugbua-Olugboyega area, off Ondo Road, Akure, southwestern Nigeria. Int J Phys Sci 8(1):37–50

    Article  Google Scholar 

  • Bernardinis LA (1993) A clear thinking on fuzzy logic. Mach Des 64:46–52

    Google Scholar 

  • Bobachev A (2003) Resistivity sounding interpretation. IPI2WIN: version 3.0.1, a 7.01.03; Moscow State University, Moscow

  • Bonham-Carter G (2014) Geographic information systems for geoscientists: modelling with GIS (no. 13). Elsevier, Oxford

    Google Scholar 

  • CGWB (2013) Groundwater information, Sindhudurg district, Maharashtra. Technical report, 1798, 1803, 1805, DBR/2013, Central Ground Water Board, Ministry of Water Resources, New Delhi

  • Dahlin T (2000) Electrode charge-up effects in DC resistivity data acquisition using multi electrode arrays. Geophys Prospect 48(1):181–187

    Article  Google Scholar 

  • Dahlin T, Zhou B (2004) A numerical comparison of 2D resistivity imaging with ten electrode arrays. Geophys Prospect 52:379–398

    Article  Google Scholar 

  • Deolankar SB (1980) The Deccan basalt of Maharashtra, India: their potential as aquifers. Groundwater 18(5):434–437

    Article  Google Scholar 

  • Edet AE, Okereke CS (1996) Assessment of hydrogeological conditions in basement aquifers of the Precambrian Oban Massif, southwestern Nigeria. J Appl Geophys 36:195–204

    Article  Google Scholar 

  • Elmahdy S, Mohamed M (2014) Groundwater potential modelling using remote sensing and GIS: a case study of the Al Dhaid area, United Arab Emirates. Geocarto Int 29(4):433–450

    Article  Google Scholar 

  • Elmahdy S, Mohamed M (2015) Automatic detection of near surface geological and hydrological features and investigating their influence on groundwater accumulation and salinity using remote sensing and GIS. Geocarto Int 30(2):132–144

    Google Scholar 

  • El-Qady G, Ushijima K, El-Sayed A (2000) Delineation of a geothermal reservoir by 2D inversion of resistivity data at Hammam Faraun area, Sinai, Egypt. In: Proc. of the World Geothermal Congress, Kyushu-Tohoku, Japan, May 28–June 10, 2000, pp 1103–1108

  • European Commission (1995) Soil terrain database. Land Management and Natural Hazards Unit. IES and JRC, European Commission, Brussels. Available at http://eusoils.jrc.ec.europa.eu/projects/SOTER/Soter_Model.html. Accessed December 2016

  • Fawcett T (2006) An introduction to ROC analysis. Pattern Recogn Lett 27:861–874. https://doi.org/10.1016/j.patrec.2005.10.010,2006

  • Fenta AA, Kifle A, Gebreyohannes T, Hailu G (2015) Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria evaluation in Raya Valley, northern Ethiopia. Hydrogeol J 23:195–206

    Article  Google Scholar 

  • Forkuor G, Pavelic P, Asare E, Obuobie E (2013) Modelling potential areas of groundwater development for agriculture in northern Ghana using GIS/RS. Hydrol Sci J 58(2):437–451. https://doi.org/10.1080/02626667.2012.754101

    Article  Google Scholar 

  • Gupta RP (2003) Remote sensing geology, 2nd edn. Springer, Heidelberg, Germany, pp 1–11

  • Gupta G, Patil SN, Padmane ST, Erram VC, Mahajan SH (2015) Geoelectric investigation to delineate groundwater potential and recharge zones in Suki River basin, north Maharashtra. J Earth Syst Sci 124(7):1487–1501

    Article  Google Scholar 

  • Hamzah U, Samudin AR, Malim EP (2007) Groundwater investigation in Kuala Selangor using vertical electric sounding (VES) surveys. Environ Geol 51:1349–1359

    Article  Google Scholar 

  • Jaiswal RK, Ghosh NC, Galkate RV, Thomas T (2015) Multi criteria decision analysis (MCDA) for watershed prioritization. Aquat Proced 4:1553–1560. https://doi.org/10.1016/j.aqpro.2015.02.201

    Article  Google Scholar 

  • Jenifer MA, Jha MK (2017) Comparison of analytic hierarchy process: catastrophe and entropy techniques for evaluating groundwater prospect of hard-rock aquifer systems. J Hydrol 548:605–624. https://doi.org/10.1016/j.jhydrol.2017.03.023

    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 18:1713–1728

    Article  Google Scholar 

  • Kadam AK, Kale SS, Pande NN, Pawar NJ, Sankhua RN (2012) Identifying potential rainwater harvesting sites of a semi-arid, basaltic region of western India, using SCS-CN method. Water Resour Manag 26(9):2537–2554. https://doi.org/10.1007/s11269-012-0031-3

    Article  Google Scholar 

  • Kaliraj S, Chandrasekar N, Magesh NS (2013) Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique. Arab J Geosci 7:1385–1401. https://doi.org/10.1007/s12517-013-0849-x

    Article  Google Scholar 

  • Keller GV, Frischknecht FC (1966) Electrical methods in geophysical prospecting. International Series in Electromagnetic Waves, 10, Pergamon, Oxford, 526 pp

  • Krishna Brahmam N, Negi JG (1973) Rift valleys beneath Deccan Trap, India. Geophys Res Bull 11:207–237

    Google Scholar 

  • Kumar D, Thiagarajan S, Rai SN (2011) Deciphering geothermal resources in Deccan Trap region using electrical resistivity tomography technique. J Geol Soc India 78:541–548

    Article  Google Scholar 

  • Kumar D, Rai SN, Thiagarajan S, Ratnakumari Y (2014) Evaluation of heterogeneous aquifers in hardrocks from resistivity sounding data in parts of Kalmeshwar Taluk of Nagpur district, India. Curr Sci 107(7):1137–1145

    Google Scholar 

  • Kumar T, Gautam AK, Jhariya DC (2016) Multi-criteria decision analysis for planning and management of groundwater resources in Balod District, India. Environ Earth Sci. https://doi.org/10.1007/s12665-016-5462-3

  • Langemeyer J, Gómez-Baggethun E, Haase D, Scheuer S, Elmqvist T (2016) Bridging the gap between ecosystem service assessments and land-use planning through multi-criteria decision analysis (MCDA). Environ Sci Pol 62:45–56. https://doi.org/10.1016/j.envsci.2016.02.013

    Article  Google Scholar 

  • Lewis Brent R (2001) Applications of electrical resistivity: a surface geophysical method. Resource Notes no. 62. Soils/Geology 62:1–2

  • Licker MD (2003) Dictionary of geology and mineralogy. McGraw-Hill, New York

    Google Scholar 

  • Loke MH (2011) Electrical imaging surveys for environmental and engineering studies: a practical guide to 2-D and 3-D surveys, Penang. http://www.geoelectrical.com/coursenotes.zip.. Accessed December 2016

  • Maggirwar BC, Umrikar BN (2011) Influence of various factors on the fluctuation of groundwater level in hard rock terrain and its importance in the assessment of groundwater. J Geol Mining Res 3(11):305–317

    Google Scholar 

  • Maillet R (1947) The fundamental equation of electrical prospecting. Geophysics 12:529–556

    Article  Google Scholar 

  • Maiti S, Erram VC, Gupta G, Tiwari RK, Kulkarni UD, Sangpal RR (2013) Assessment of groundwater quality: a fusion of geochemical and geophysical information via Bayesian Neural Networks. Environ Monit Assess 185. https://doi.org/10.1007/s10661-012-2802-y3445-3465.

  • Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, New York

    Google Scholar 

  • Menke W (1984) Geophysical data analysis: discrete inverse theory. Academic, New York

    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 75:1–20. https://doi.org/10.1007/s12665-016-5897-6

    Article  Google Scholar 

  • Mohamed MM, Elmahdy SI (2017) Fuzzy logic and multi-criteria methods for groundwater potentiality mapping at Al Fo’ah area , the United Arab Emirates (UAE): an integrated approach. Geocarto Int 32(10). https://doi.org/10.1080/10106049.2016.1195884

  • Mondal NC, Singh VP, Ahmed S (2013) Delineating shallow saline groundwater zones from southern India using geophysical indicators. Environ Monit Assess 185:4869–4886

    Article  Google Scholar 

  • Naik PK, Awasthi AK (2003) Groundwater resources assessment of the Koyna River basin, India. Hydrogeol J 11:582–594. https://doi.org/10.1007/s10040-003-0273-5

    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 

  • Nasiri H, Boloorani AD, Sabokbar HAF, Jafari HR, Hamzeh M, Rafii Y (2013) Determining the most suitable areas for artificial groundwater recharge via an integrated PROMETHEE II-AHP method in GIS environment: case study—Garabaygan Basin, Iran. Environ Monit Assess 185:707–718. https://doi.org/10.1007/s10661-012-2586-0

    Article  Google Scholar 

  • NRSC (2016) Search and order data. National Remote Sensing Centre, Indian Space Research Organisation. www.nrsc.gov.in. Accessed December 2016

  • Oikonomidis D, Dimogianni S, Kazakis N, Voudouris K (2015) A GIS/remote sensing-based methodology for groundwater potentiality assessment in Tirnavos area, Greece. J Hydrol 525:197–208. https://doi.org/10.1016/j.jhydrol.2015.03.056

    Article  Google Scholar 

  • Orellana E, Mooney HM (1966) Master tables and curves for vertical electrical sounding over layered structures. Interciencia, Madrid, 159 pp

    Google Scholar 

  • Pandey OP, Chandrakala K, Parthasarathy G, Reddy PR (2009) Upwarped high velocity mafic crust, subsurface tectonics and causes of intraplate Latur-Killari (M 6.2) and Koyna (M 6.3) earthquakes, India: a comparative study. J Asian Earth Sci 34:781–795

    Article  Google Scholar 

  • Park YH, Doh SJ, Yun ST (2007) Geoelectric resistivity sounding of riverside alluvial aquifer in an agricultural area at Buyeo, Geum River watershed, Korea: an application to groundwater contamination study. Environ Geol 53:849–859

    Article  Google Scholar 

  • Phadtare PN (1986) Hydrogeology of the Deccan Basalts of the Sina-Man basins, Maharashtra. In: Powar KB, Thigale SS (eds) Hydrogeology of volcanic terrains. University of Pune, Pune, pp 121–135

  • Prakasam C (2010) Land use and land cover change detection through remote sensing approach: a case study of Kodaikanal Taluk, Tamil Nadu. Int J Geomatics Geosci 1(2):103–113

    Google Scholar 

  • Rahmati O, Haghizadeh A, Stefanidis S (2016) Assessing the accuracy of GIS-based analytical hierarchy process for watershed prioritization: Gorganrood River Basin, Iran. Water Resour Manag 30(3):1131–1150. https://doi.org/10.1007/s11269-015-1215-4

    Article  Google Scholar 

  • Rajaveni SP, Brindha K, Elango L (2017) Geological and geomorphological controls on groundwater occurrence in a hard rock region. Appl Water Sci 7:1377. https://doi.org/10.1007/s13201-015-0327-6

    Article  Google Scholar 

  • Satty T (1980) The analytic hierarchy process. McGraw Hill, New York

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

    Google Scholar 

  • Shikalgar RS (2015) A study on population growth of man river basin in Maharashtra. Golden Res Thoughts 4(8)

  • Singh CL, Singh SN (1970) Some geoelectrical investigations for potential groundwater in part of Azamgrah area of UP. PAGEOPH 82:270–285

    Article  Google Scholar 

  • Singh LK, Jha MK, Chowdary VM (2017) Multi-criteria analysis and GIS modeling for identifying prospective water harvesting and artificial recharge sites for sustainable water supply. J Clean Prod 142(4):1436–1456. https://doi.org/10.1016/j.jclepro.2016.11.163

    Article  Google Scholar 

  • Survey of India (SOI) (2016) http://www.surveyofindia.gov.in. Accessed December 2016

  • Thapa R, Gupta S, Gupta A, Reddy DV, Kaur H (2018) Use of geospatial technology for delineating groundwater potential zones with an emphasis on water-table analysis in Dwarka River basin, Birbhum, India. Hydrogeol J 26:899–922

    Article  Google Scholar 

  • Tiwari VM, Vyaghreswara Rao MBS, Mishra DC (2001) Density in homogenities beneath Deccan Volcanic Province, India as derived from gravity data. J Geodyn 31:1–17

    Article  Google Scholar 

  • Tsepav MT, Ibrahim SI, Bayegun FA (2015) Geoelectrical characterization of aquifer precincts in parts of Lapai, north central Nigeria. J Appl Sci Environ Manag 19(2):295–301

    Google Scholar 

  • Vijith H, Madhu G (2007) Application of GIS and frequency ratio model in mapping the potential surface failure sites in the Poonjar sub-watershed of Meenachil River in Western Ghats of Kerala. Indian Soc Remote Sens 35(3):275–285

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy Sets. Inf Control 8:338–353

    Article  Google Scholar 

  • Zohdy AAR, Eaton GP, Mabey DR (1974) Application of surface geophysics to ground-water investigation, 2nd edn. US Geological Survey, Reston, VA

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Acknowledgements

The authors extend their sincere thanks to the director of the Indian Institute of Geomagnetism, Navi Mumbai, and the head of the Departments of Geology and Environmental Sciences, Savitribai Phune, Pune University, Pune, for providing all the facilities for analysis and for according permission to publish this work. Thanks are also due to Shri B.I. Panchal for drafting the figures.

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The first author (GS) is indebted to the Indian Institute of Geomagnetism for the financial support in the form of a fellowship.

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  1. Indian Institute of Geomagnetism, New Panvel (W), Navi Mumbai, Maharashtra, 410218, India

    G. Shailaja & G. Gupta

  2. Department of Environmental Sciences, Savitribai Phule Pune University, Pune, Maharashtra, 411007, India

    A. K. Kadam

  3. Department of Geology, Savitribai Phule Pune University, Pune, Maharashtra, 411007, India

    B. N. Umrikar & N. J. Pawar

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  1. G. Shailaja
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Shailaja, G., Kadam, A.K., Gupta, G. et al. Integrated geophysical, geospatial and multiple-criteria decision analysis techniques for delineation of groundwater potential zones in a semi-arid hard-rock aquifer in Maharashtra, India. Hydrogeol J 27, 639–654 (2019). https://doi.org/10.1007/s10040-018-1883-2

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