Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

SpringerLink
Log in

Modeling and mapping of groundwater potentiality zones using AHP and GIS technique: a case study of Raniganj Block, Paschim Bardhaman, West Bengal

  • Original Article
  • Published:
Modeling Earth Systems and Environment Aims and scope Submit manuscript

Abstract

Water is the most significant natural resources stirring both surface water and groundwater for human civilization. This precious resource is occasionally scarce, sometimes plentiful but not uniformly concentrated, both in space and time. Groundwater is most valuable and dynamic resource that is not equally distributed. The dimensions of groundwater in an area are determined by numerous factors such as topography, lithology, geological structure, depth of weathering, slope, drainage pattern, land use and land cover (LULC), rainfall pattern. Delineation of groundwater potentiality zone is an indispensable part for the management of water resources numerous themes are included according to their relative magnitude for the potentiality mapping, these are—geology, slope gradient, LULC, soil texture, rainfall, lineament density, drainage density and groundwater fluctuation etc. The analytical hierarchical process (AHP) method has been used to find out the weights of different themes and their associated sub-themes and finally overlay analysis has been done in the geospatial environment. Groundwater potential zone is categorized as ‘very poor’ (18.22%), ‘poor’ (28.39%), ‘moderate’ (31.98%), ‘good’ (13.24%) and ‘excellent’ (8.17%). The groundwater potential map has been validated with Dug well data for accounting the implication of this model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28
Fig. 29
Fig. 30
Fig. 31

Similar content being viewed by others

References

  • Acharya T, Nag SK (2013) Study of groundwater prospects of the crystalline rocks in Purulia District, West Bengal, India using remote sensing data. Earth Resour 1(2):54–59

    Article  Google Scholar 

  • Aladejana OO, Anifowose AYB, Fagbohun BJ (2016) Testing the ability of an empirical hydrological model to verify a knowledge-based groundwater potential zone mapping methodology. Modeling Earth Syst Environ 2(4):174

    Google Scholar 

  • Anbazhagan S (1993) Integrated groundwater study in drought prone Pennagaram, Dharampuri district, Tamilnadu. Bull Indian Geol Assoc 26(2):117–123

    Google Scholar 

  • Anbazhagan S, Nair AM (2004) Geographic information system and groundwater quality mapping in Panvel Basin, Maharashtra, India. Environ Geol 45(6):753–761

    Article  Google Scholar 

  • Anbazhagan S, Ramasamy SM, Moses Edwin J (2000) Remote sensing and geophysical resistivity survey for groundwater exploration—a comparative analysis. In conference on groundwater exploration techniques. Tiruchirappallipp, pp 177–181

  • Anbazhagan S, Aschenbrenner F, Knoblich K (2001) Comparison of aquifer parameters with lineaments derived from remotely sensed data in Kinzig basin, Germany. Aa Balkema Publishers. http://dspace.library.iitb.ac.in/xmlui/handle/10054/16176

  • Avinash K, Deepika B, Jayappa KS (2014) Basin geomorphology and drainage morphometry parameters used as indicators for groundwater prospect: insight from geographical information system (GIS) technique. J Earth Sci 25(6):1018

    Article  Google Scholar 

  • Ayalew L, Yamagishi H, Ugawa N (2004) Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan. Landslides 1(1):73–81

    Article  Google Scholar 

  • Bisdorff R, Meyer P, Veneziano T (2009) XMCDA: a standard XML encoding of MCDA data. In EURO XXIII: European conference on operational research. pp 53–53

  • Bradley C (1996) Transient modelling of water-table variation in a floodplain wetland, Narborough Bog, Leicestershire. J Hydrol 185(1–4):87–114

    Article  Google Scholar 

  • Ceballos-Silva A, Lopez-Blanco J (2003) Delineation of suitable areas for crops using a multi-criteria evaluation approach and land use/cover mapping: a case study in Central Mexico. Agric Syst 77(2):117–136

    Article  Google Scholar 

  • Central Ground Water Board of India (CGWB) (2016) Report of the ground water resource estimation committee, Ministry of Water Resources, Govt. of India. http://cgwb.gov.in/Documents/GEC2016_Report_Final%2030.10.2017.pdf

  • Chatterjee RS, Bhattacharya AK (1995) Delineation of the drainage pattern of a coal basin related inference using satellite remote sensing techniques. Asia Pacif Remote Sens 1:107–114

    Google Scholar 

  • Chen Y, Khan S, Paydar Z (2010) To retire or expand? A fuzzy GIS-based spatial multi-criteria evaluation framework for irrigated agriculture. Irrig Drain 59(2):174–188

    Google Scholar 

  • Chen Y, Li KW, Liu SF (2011) An OWA-TOPSIS method for multiple criteria decision analysis. Expert Syst Appl 38(5):5205–5211

    Article  Google Scholar 

  • Chowdhury A, Jha MK, Chowdary VM (2010) Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Environ Earth Sci 59(6):1209

    Article  Google Scholar 

  • Cisneros JM, Grau JB, Antón JM, De Prada JD, Cantero A, Degioanni AJ (2011) Assessing multi-criteria approaches with environmental, economic and social attributes, weights and procedures: a case study in the Pampas, Argentina. Agric Water Manag 98(10):1545–1556

    Article  Google Scholar 

  • Das S (2017) Delineation of groundwater potential zone in hard rock terrain in Gangajalghati block, Bankura district, India using remote sensing and GIS techniques. Modeling Earth Syst Environ 3(4):1589–1599. https://doi.org/10.1007/s40808-017-0396-7

    Article  Google Scholar 

  • Das S, Behera SC, Kar A, Narendra P, Guha S (1997) Hydrogeomorphological mapping in ground water exploration using remotely sensed data—a case study in keonjhar district, orissa. J Indian Soc Remote Sens 25(4):247–259

    Article  Google Scholar 

  • Dasho OA, Ariyibi EA, Akinluyi FO, Awoyemi MO, Adebayo AS (2017) Application of satellite remote sensing to groundwater potential modeling in Ejigbo area, Southwestern Nigeria. Modeling Earth Syst Environ 3(2):615–633

    Article  Google Scholar 

  • De Jong P (1984) A statistical approach to Saaty’s scaling method for priorities. J Math Psychol 28(4):467–478

    Article  Google Scholar 

  • Deepa S, Venkateswaran S, Ayyandurai R, Kannan R, Prabhu MV (2016) Groundwater recharge potential zones mapping in upper Manimuktha Sub basin Vellar river Tamil Nadu India using GIS and remote sensing techniques. Modeling Earth Syst Environ 2(3):137

    Article  Google Scholar 

  • Devi P, Sree S, Srinivasulu K, Kesava Raju (2001) Hydrogeomorphological and groundwater prospects of the Pageru river basin by using remote sensing data. Environ Geol 40(9):1088–1094

    Article  Google Scholar 

  • Dunning DJ, Ross QE, Merkhofer MW (2000) Multiattribute utility analysis for addressing Sect. 316 (b) of the Clean Water Act. Environ Sci Policy 3:7–14

    Article  Google Scholar 

  • Dutta RK, Dutta AB (2003) Coal resource of West Bengal. Bull Geol Survey India Ser A 7(45):109

    Google Scholar 

  • Ferdowsian R, Pannell DJ, McCarron C, Ryder A, Crossing L (2001) Explaining groundwater hydrographs: separating atypical rainfall events from time trends. Soil Res 39(4):861–876

    Article  Google Scholar 

  • Flug M, Seitz HL, Scott JF (2000) Multicriteria decision analysis applied to Glen Canyon Dam. J Water Res Plan Manag 126(5):270–276

    Article  Google Scholar 

  • Ganapuram S, Kumar GV, Krishna IM, Kahya E, Demirel MC (2009) Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS. Adv Eng Softw 40(7):506–518

    Article  Google Scholar 

  • Ghosh A, Tiwari AK, Das S (2015) A GIS based DRASTIC model for assessing groundwater vulnerability of Katri Watershed, Dhanbad, India. Modeling Earth Syst Environ 1(3):11

    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 western part of West Bengal. Modeling Earth Syst Environ 2(1):1

    Article  Google Scholar 

  • Gilliams S, Raymaekers D, Muys B, Van Orshoven J (2005) Comparing multiple criteria decision methods to extend a geographical information system on afforestation. Comput Electron Agric 49(1):142–158

    Article  Google Scholar 

  • Gintamo TT (2010) School Of Graduate Studies Department Of Earth Sciences (Doctoral dissertation, Addis Ababa University). http://deepholedriller.com/wp-content/uploads/2013/01/Thesis-Final1.pdf

  • Gintamo TT (2015) Ground water potential evaluation based on integrated GIS and remote sensing techniques. In Bilate River Catchment: South Rift Valley of Ethiopia. Am Sci Res J Eng Technol Sci (ASRJETS) 10(1):85–120

    Google Scholar 

  • Giupponi C, Eiselt B, Ghetti PF (1999) A multicriteria approach for mapping risks of agricultural pollution for water resources: the Venice Lagoon watershed case study. J Environ Manag 56(4):259–269

    Article  Google Scholar 

  • Gorsevski PV, Jankowski P, Gessler PE (2006) An heuristic approach for mapping landslide hazard by integrating fuzzy logic with analytic hierarchy process. Control Cybern 35:121–146

    Google Scholar 

  • Goyal S, Bharawadaj RS, Jugran DK (1999) Multicriteria analysis using GIS for groundwater resource evaluation in Rawasen and Pilli watershed. UP Proc. Map India, pp 99

  • Greppi M (2004) Infiltration process and groundwater table raising in a paddy field area. Paddy Water Environ 2(3):171–179

    Article  Google Scholar 

  • Harinarayana P, Gopalakrishna GS, Balasubramanaian A (2000) Remote sensing data for groundwater development and management in Keralapura watersheds of Cauvery basin, Karnataka, India. Indian Mineral 34(2):11–17

    Google Scholar 

  • Horton RE (1932) Drainage-basin characteristics. Eos Trans Am Geophys Union 13(1):350–361

    Article  Google Scholar 

  • Hussein AA, Govindu V, Nigusse AGM (2017) Evaluation of groundwater potential using geospatial techniques. Appl Water Sci 7(5):2447–2461

    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 development—an approach. Int J Remote Sens 24(5):993–1008

    Article  Google Scholar 

  • Jan CD, Chen TH, Lo WC (2007) Effect of rainfall intensity and distribution on groundwater level fluctuations. J Hydrol 332(3):348–360

    Article  Google Scholar 

  • Jothibasu A, Anbazhagan S (2016) Modeling groundwater probability index in Ponnaiyar River basin of South India using analytic hierarchy process. Modeling Earth Syst Environ 2(3):109

    Article  Google Scholar 

  • Joubert A, Stewart TJ, Eberhard R (2003) Evaluation of water supply augmentation and water demand management options for the City of Cape Town. J Multi Criteria Decis Anal 12(1):17–25

    Article  Google Scholar 

  • Kächele H, Dabbert S (2002) An economic approach for a better understanding of conflicts between farmers and nature conservationists—an application of the decision support system MODAM to the Lower Odra Valley National Park. Agric Syst 74(2):241–255

    Article  Google Scholar 

  • Kangas J, Kangas A, Leskinen P, Pykäläinen J (2001) MCDM methods in strategic planning of forestry on state-owned lands in Finland: applications and experiences. J Multi Criteria Decis Anal 10(5):257–271

    Article  Google Scholar 

  • Karanth KR, Seshu Babu K (1978) Identification of major lineaments on satellite imagery and on aerial photographs for delineation for possible potential groundwater zones in Penukonda and Dharmavaram taluks of Anantapur district. In Proc. of Joint Indo US Workshop on Remote Sensing of Water Resources NRSA Hyderabad, pp 188–197

  • Konkul J, Rojborwornwittaya W, Chotpantarat S (2014) Hydrogeologic characteristics and groundwater potentiality mapping using potential surface analysis in the Huay Sai area, Phetchaburi province, Thailand. Geosci J 18(1):89–103

    Article  Google Scholar 

  • Krishnamurthy J, Srinivas G (1995) Role of geological and geomorphological factors in ground water exploration: a study using IRS LISS data. Int J Remote Sens 16(14):2595–2618

    Article  Google Scholar 

  • Krishnamurthy JN, Venkatesa K, Jayaraman V, Manivel M (1996) An approach to demarcate ground water potential zones through remote sensing and geographical information system. Int J Remote Sens 17:1867–1884

    Article  Google Scholar 

  • Kumar A, Srivastava SK (1991) Geomorphological units, their geohydrological characteristic and vertical electrical sounding response near Munger, Bihar. J Indian Soc Remote Sens 19(3):205–215

    Article  Google Scholar 

  • Lee YW, Bogardi I, Kim JH (2000) Decision of water supply line under uncertainty. Water Res 34(13):3371–3379

    Article  Google Scholar 

  • Makropoulos CK, Butler D, Maksimovic C (2003) Fuzzy logic spatial decision support system for urban water management. J Water Res Plan Manag 129(1):69–77

    Article  Google Scholar 

  • Malczewski J (2004) GIS-based land-use suitability analysis: a critical overview. Prog Plan 62(1):3–65

    Article  Google Scholar 

  • Malczewski J, Rinner C (2016) Multicriteria decision analysis in geographic information science. Springer, New York

    Google Scholar 

  • Martin NJ, Onge BS, Waaub JP (1999) An integrated decision aid system for the development of Saint Charles River alluvial plain, Quebec, Canada. Int J Environ Pollut 12(2–3):264–279

    Article  Google Scholar 

  • Martz LW, Garbrecht J (1999) An outlet breaching algorithm for the treatment of closed depressions in a raster DEM. Comput Geosci 25(7):835–844

    Article  Google Scholar 

  • Matsumoto N (1992) Regression analysis for anomalous changes of ground water level due to earthquakes. Geophys Res Lett 19(12):1193–1196

    Article  Google Scholar 

  • Matsumoto N, Kitagawa G, Roeloffs EA (2003) Hydrological response to earthquakes in the Haibara well, central Japan–I. Groundwater level changes revealed using state space decomposition of atmospheric pressure, rainfall and tidal responses. Geophys J Int 155(3):885–898

    Article  Google Scholar 

  • Matthews KB, Sibbald AR, Craw S (1999) Implementation of a spatial decision support system for rural land use planning: integrating geographic information system and environmental models with search and optimisation algorithms. Comput Electron Agric 23(1):9–26

    Article  Google Scholar 

  • Mondal S (2012) Remote sensing and GIS based ground water potential mapping of Kangshabati irrigation command area, West Bengal. J Geogr Nat Disast 1(1):1–8

    Article  Google Scholar 

  • Mondal MS, Pandey AC, Garg RD (2008) Groundwater prospects evaluation based on hydrogeomorphological mapping using high resolution satellite images: a case study in Uttarakhand. J Indian Soc Remote Sens 36(1):69

    Article  Google Scholar 

  • Moore GK (1978) The role of remote sensing in groundwater exploration. Proc. of Joint Indo-US Workshop on Remote Sensing of Water Resources, NRSA, Hyderabad, pp 22–40

  • Muralidhar M, Raju KRK, Raju KSVP., Prasad JR (2000) Remote sensing applications for the evaluation of water resources in rainfed area, Warangal district, Andhra Pradesh. Indian Mineral 34(2):33–40

    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

    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

    Article  Google Scholar 

  • Narayanpethkar AB, Vasanthi A, Mallick K (2006) Electrical resistivity technique for exploration and studies on flow pattern of groundwater in multi-aquifer system in the basaltic terrain of the Adila basin, Maharashtra. Geol Soc India 67(1):69–82

    Google Scholar 

  • Oseji JO (2010) Geoelectric investigation of groundwater resources and aquifer characteristics in Utagba-Ogbe kingdom Ndokwa land area of Delta State, Nigeria. J Environ Chem Ecotoxicol 2(3):38–46

    Google Scholar 

  • Owusu S, Mul ML, Ghansah B, Osei-Owusu PK, Awotwe-Pratt V, Kadyampakeni D (2017) Assessing land suitability for aquifer storage and recharge in northern Ghana using remote sensing and GIS multi-criteria decision analysis technique. Modeling Earth Syst Environ 3(4):1383–1393. https://doi.org/10.1007/s40808-017-0360-6

  • Ozturk D, Batuk F (2011) Implementation of GIS-based multicriteria decision analysis with VB in ArcGIS. Int J Inf Technol Decis Making 10(06):1023–1042

    Article  Google Scholar 

  • Palanivel S, Ganesh A, Vasantha Kumaran T (1996) Geohydrological evaluation of Upper Agniar and Vellar Basins, Tamil Nadu: an integrated approach using Remote Sensing, Geophysical and well inventory data. J Indian Soc Remote Sens 24(3):153–168

    Article  Google Scholar 

  • Pani S, Chakrabarty A, Bhadury S (2016) Groundwater potential zone identification by analytical hierarchy process (AHP) weighted overlay in gis environment a case study of Jhargram Block, Paschim Medinipur. Int JRemote Sens Geosci 5(3):1–10. http://www.ijrsg.com/Files/IJATER_25_01.pdf

    Google Scholar 

  • Pareta K, Pareta U (2011) Quantitative morphometric analysis of a watershed of Yamuna basin, India using ASTER (DEM) data and GIS. Int J Geom Geosci 2:248

    Article  Google Scholar 

  • Pratap K, Ravindran KV, Prabakaran B (2000) Groundwater prospect zoning using remote sensing and geographical information system: a case study in Dala-Renukoot area, Sonbhadra District, Uttar Pradesh. J Indian Soc Remote Sens 28(4):249–263

    Article  Google Scholar 

  • Raju KCB, Rao GVK, Kumar BJ (1985) Analytical aspects of remote sensing techniques for groundwater prospecting in hard rocks. Proc. of the Sixth Asian Conference on Remote Sensing, pp 127132

  • Rashed T, Weeks J (2003) Assessing vulnerability to earthquake hazards through spatial multicriteria analysis of urban areas. Int J Geogr Inf Sci 17(6):547–576

    Article  Google Scholar 

  • Reddy GO, Mouli KC, Srivastav SK, Srinivas CV, Maji AK (2000) Evaluation of ground water potential zones using remote sensing data-A case study of Gaimukh watershed, Bhandara District, Maharashtra. J Indian Soc Remote Sens 28(1):19

    Article  Google Scholar 

  • Reghu S, Gopinath G, Srinivas R, Regunath R, Sajan K (2013) Demarcation of groundwater prospective zones in humid tropical river basin: a geospatial approach. Iran J Earth Sci 5:13–20

    Google Scholar 

  • Reitsma RF, Carron JC (1997) Object-oriented simulation and evaluation of river basin operations. J Geogr Inf Decis Anal 1(1):9–24

    Google Scholar 

  • Riedl L, Vacik H, Kalasek R (2000) MapModels: a new approach for spatial decision support in silvicultural decision making. Comput Electron Agric 27(1):407–412

    Article  Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resources allocation. New York, McGraw, 281

  • Sankar K (2002) Evaluation of groundwater potential zones using remote sensing data in Upper Vaigai river basin, Tamil Nadu, India. J Indian Soc Remote Sens 30(3):119–129

    Article  Google Scholar 

  • Sar N, Khan A, Chatterjee S, Das A (2015) Hydrologic delineation of ground water potential zones using geospatial technique for Keleghai river basin, India. Modeling Earth Syst Environ 1(3):25

    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

    Article  Google Scholar 

  • Satyanarayana R (1991) Remote sensing studies on the land and water resources of Hyderabad city and Environs. Ph. D thesis, Sri Venkateswara University, Tirupati, India

  • Schlaepfer R, Iorgulescu I, Glenz C (2002) Management of forested landscapes in mountain areas: an ecosystem-based approach. For Pol Econ 4(2):89–99

    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

    Article  Google Scholar 

  • Shahid S, Nath SK (2002) GIS integration of remote sensing and electrical sounding data for hydrogeological exploration. J Spatial Hydrol 2(1). http://www.spatialhydrology.net/index.php/JOSH/article/view/5/4

  • Shahzad F, Mahmmod SA, Gloaguen R (1999) Drainage network response to geological structures: a case study of Joya Mair oil field (Pakistan). In international petroleum technology conference

  • Sharma D, Jugran DK (1992) Hydromorphogeological studies around Pinjaur-Morni-Kala Amb area, Ambala district (Haryana), and Sirmur district (Himachal Pradesh). J Indian Soc Remote Sens 20(4):187–197

    Article  Google Scholar 

  • Technical guidelines of Integrated Mission for Sustainable Development (1995) National Remote Sensing Agency, Department of Space, Govt. of India, Balanagar, Hyderabad. https://nrsc.gov.in/Development_Planning

  • Teeuw RM (1995) Groundwater exploration using remote sensing and a low-cost geographical information system. Hydrogeol J 3(3):21–30

    Article  Google Scholar 

  • Tiwari A, Rai B (1996) Hydromorphogeological mapping for groundwater prospecting using landsat-MSS images—a case study of part of Dhanbad District, Bihar. J Indian Soc Remote Sens 24(4):281–285

    Article  Google Scholar 

  • Tkach RJ, Simonovic SP (1997) A new approach to multicriteria decision making in water resources. J Geogr Inf Decis Anal 1(1):25–44

    Google Scholar 

  • Varni M, Comas R, Weinzettel P, Dietrich S (2013) Application of the water table fluctuation method to characterize groundwater recharge in the Pampa plain, Argentina. Hydrol Sci J 58(7):1445–1455

    Article  Google Scholar 

  • Venetis C (1971) Estimating infiltration and/or the parameters of unconfined aquifers from ground water level observations. J Hydrol 12(2):161–169

    Article  Google Scholar 

  • Vertinsky I, Brown S, Schreier H, Thompson WA, Van Kooten GC (1994) A hierarchical-GIS-based decision model for forest management: the systems approach. Interfaces 24(4):38–53

    Article  Google Scholar 

  • Viswanathan MN (1984) Recharge characteristics of an unconfined aquifer from the rainfall-water table relationship. J Hydrol 70(1–4):233–250

    Article  Google Scholar 

  • Wu J, Zhang R, Yang J (1996) Analysis of rainfall-recharge relationships. J Hydrol 177(1–2):143–160

    Article  Google Scholar 

  • Zeng J, An M, Smith NJ (2007) Application of a fuzzy based decision making methodology to construction project risk assessment. Int J Project Manag 25(6):589–600

    Article  Google Scholar 

Download references

Acknowledgements

We are thankful to the Department of Geography, The University of Burdwan for providing necessary facilities regarding this work. We are thankful to Central Ground Water Board (CGWB) for providing the primary data of Groundwater. We are thankful to US Geological Survey and Department of Space Indian Space Research Organisation for providing the Remotely Sensed data-sets. We are also thankful to Mr. Manoj Kumar Mahato and Susanta Mandal, Dept. of Geography, The University of Burdwan during the field survey. The authors are very much thankful to Md. Nazrul Islam (Executive Editor-in-Chief of Modeling Earth Systems and Environment) and reviewers regarding the valuable positive suggestions for  the improvement of this paper.

Author information

Authors and Affiliations

  1. Department of Geography, The University of Burdwan, Bardhaman, India

    Rabin Chakrabortty, Subodh Chandra Pal, Sadhan Malik & Biswajit Das

Authors
  1. Rabin Chakrabortty
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Subodh Chandra Pal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sadhan Malik
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Biswajit Das
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rabin Chakrabortty.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 626 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chakrabortty, R., Pal, S.C., Malik, S. et al. Modeling and mapping of groundwater potentiality zones using AHP and GIS technique: a case study of Raniganj Block, Paschim Bardhaman, West Bengal. Model. Earth Syst. Environ. 4, 1085–1110 (2018). https://doi.org/10.1007/s40808-018-0471-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40808-018-0471-8

Keywords

Search

Navigation