Skip to main content

Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing, GIS and MCDM Techniques

Abstract

Remote sensing (RS) and geographic information system (GIS) are promising tools for efficient planning and management of vital groundwater resources, especially in data-scarce developing nations. In this study, a standard methodology is proposed to delineate groundwater potential zones using integrated RS, GIS and multi-criteria decision making (MCDM) techniques. The developed methodology is demonstrated by a case study in Udaipur district of Rajasthan, western India. Initially, ten thematic layers, viz., topographic elevation, land slope, geomorphology, geology, soil, pre- and post-monsoon groundwater depths, annual net recharge, annual rainfall, and proximity to surface water bodies were considered in this study. These thematic layers were scrutinized by principal component analysis technique to select influential layers for groundwater prospecting. Selected seven thematic layers and their features were assigned suitable weights on the Saaty’s scale according to their relative importance in groundwater occurrence. The assigned weights of the thematic layers and their features were then normalized by using AHP (analytic hierarchy process) MCDM technique and eigenvector method. Finally, the selected thematic maps were integrated by weighted linear combination method in a GIS environment to generate a groundwater potential map. Thus, four groundwater potential zones were identified and demarcated in the study area, viz., ‘good’, ‘moderate’, ‘poor’ and ‘very poor’ based on groundwater potential index values. The area falling in the ‘good’ zone is about 2,113 km2 (17% of the total study area), which encompasses major portions of Sarada, Salumber, Girwa, Dhariawad, and Mavli blocks of the study area. The northeast and southwest portions along with some scattered patches fall in the ‘moderate’ zone, which encompasses an area of 3,710 km2 (about 29%). The ‘poor’ zone is dominant in the study area which covers an area of 4,599 km2 (36% of the total area). The western portion and parts of eastern and southeast portions of the study area are characterized as having ‘very poor’ groundwater potential, and this zone covers an area of 2,273 km2 (18%). Moreover, in the ‘good’ zone, the mean annually exploitable groundwater reserve is estimated at 0.026 million cubic metres per km2 (MCM/km2), whereas it is 0.024 MCM/km2 in the ‘moderate’ zone, 0.018 MCM/km2 in the ‘poor’ zone, and 0.013 MCM/km2 in the ‘very poor’ zone. The groundwater potential map was finally verified using the well yield data of 39 pumping wells, and the result was found satisfactory.

This is a preview of subscription content, access via your institution.

References

  • Andreo B, Vías J, Durán JJ, Jiménez P, López-Geta JA, Carrasco F (2008) Methodology for groundwater recharge assessment in carbonate aquifers: application to pilot sites in southern Spain. Hydrogeol J 16(5):911–925

    Article  Google Scholar 

  • Bhuiyan C, Singh RP, Kogan FN (2006) Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data. Int J Appl Earth Observ Geoinform 8(4):289–302

    Article  Google Scholar 

  • CGWB (1997) Ground water resource estimation methodology - 1997. Report of the Ground Water Resource Estimation Committee, Central Ground Water Board (CGWB), Ministry of Water Resources, Government of India, New Delhi, India, 107 pp

  • Chen K, Blong R, Jacobson C (2001) MCE-RISK: integrating multicriteria evaluation and GIS for risk decision-making in natural hazards. Environ Model Softw 16:387–397

    Article  Google Scholar 

  • Chenini I, Mammou AB, May ME (2010) Groundwater recharge zone mapping using GIS-based multi-criteria analysis: a case study in central Tunisia (Maknassy basin). Water Resour Manag 24:921–939

    Article  Google Scholar 

  • Chi K-H, Lee B-J (1994) Extracting potential groundwater area using remotely sensed data and GIS techniques. In: Proceedings of the regional seminar on integrated application of remote sensing and GIS for land and water resource management. Bangkok, pp 64–69

  • 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):231–250

    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):1209–1222

    Article  Google Scholar 

  • Dillon R, Goldstein M (1984) Multivariate analyses: methods and applications. Wiley, New York

    Google Scholar 

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

    Article  Google Scholar 

  • Eastman JR (2003) IDRISI Kilimanjaro: guide to GIS and image processing. Clark Labs, Clark University, Worcester, 328 pp

    Google Scholar 

  • Edet AE, Okereke CS, Teme SC, Esu EO (1998) Application of remote-sensing data to groundwater exploration: a case study of the Cross River State, southeastern Nigeria. Hydrogeol J 6(3):394–404

    Article  Google Scholar 

  • Engman ET, Gurney RJ (1991) Remote sensing in hydrology. Chapman and Hall, London, 225 pp

    Google Scholar 

  • Ettazarini S (2007) Groundwater potentiality index: a strategically conceived tool for water research in fractured aquifers. Environ Geol 52:477–487

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Ganapuram S, Vijaya Kumar GT, Murali Krishna IV, Kahya E, Cüneyd Demirel M (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 

  • GOR (1999) Groundwater atlas of Rajasthan. World Bank (IDA) Aided project, state remote sensing application centre, Jodhpur, Rajasthan, Acc. No 13466, D24, STA, N9, 545 pp

  • GWD (2008) Reappraisal of ground water resources of Udaipur District on 31.03.2007. Ground Water Department (GWD), Government of Rajasthan, Jodhpur, Rajasthan, India

    Google Scholar 

  • Hajkowicz S, Higgins A (2008) A comparison of multiple criteria analysis techniques for water resource management. Eur J Oper Res 184:255–265

    Article  Google Scholar 

  • ILWIS (2001) Integrated land and water information system, 3.2 academic, user’s guide. International Institute for Aerospace Survey and Earth Sciences (ITC), The Netherlands, pp 428–456

    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 

  • Jha MK, Peiffer S (2006) Applications of remote sensing and GIS technologies in groundwater hydrology: past, present and future. BayCEER, Bayreuth, Germany, 201 pp

    Google Scholar 

  • Jha MK, Chowdhury A, Chowdary VM, Peiffer S (2007) Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resour Manag 21(2):427–467

    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

    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 

  • Kamaraju MVV, Bhattacharya A, Reddy GS, Rao GC, Murthy GS, Rao TCM (1995) Groundwater potential evaluation of West Godavari District, Andhra Pradesh State, India—a GIS approach. Ground Water 34(2):318–325

    Article  Google Scholar 

  • Karanth KR (1989) Hydrogeology. McGraw-Hill, New Delhi, 720 pp

    Google Scholar 

  • Kolat C, Doyuran V, Ayday C, Süzen M (2006) Preparation of a geotechnical microzonation model using geographical information systems based on multicriteria decision analysis. Environ Geol 87:241–255

    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(4):2595–2618

    Article  Google Scholar 

  • Krishnamurthy J, Venkatesa Kumar N, Jayaraman V, Manuvel M (1996) An approach to demarcate groundwater potential zones through remote sensing and a geographical information system. Int J Remote Sens 17(10):1867–1884

    Article  Google Scholar 

  • Krishnamurthy J, Mani AN, Jayaram V, Manivel M (2000) Groundwater resources development in hard rock terrain: an approach using remote sensing and GIS techniques. Int J Appl Earth Observ Geoinform 2(3/4):204–215

    Article  Google Scholar 

  • Madrucci V, Taioli F, de Araújo CC (2008) Groundwater favorability map using GIS multicriteria data analysis on crystalline terrain, São Paulo State, Brazil. J Hydrol 357:153–173

    Article  Google Scholar 

  • Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, New York, 392 pp

    Google Scholar 

  • Meijerink AMJ (1996) Remote sensing applications to hydrology: groundwater. Hydrol Sci J 41(4):549–561

    Article  Google Scholar 

  • Mendoza GA, Martins H (2006) Multi-criteria decision analysis in natural resource management: a critical review of methods and new modelling paradigms. For Ecol Manag 230(1–3):1–22

    Article  Google Scholar 

  • Nour S (1996) Groundwater potential for irrigation in the East Oweinat area, Western Desert, Egypt. Environ Geol 27(3):143–154

    Google Scholar 

  • Oberlander TM (1989) Slope and pediment systems. In: Thomas DSG (ed) Arid zone geomorphology. Belhaven, London, pp 58–59

    Google Scholar 

  • Pereira JM, Duckstein L (1993) A multiple criteria decision-making approach to GIS-based land suitability evaluation. Int J Geogr Inf Syst 7(5):407–424

    Article  Google Scholar 

  • Rao YS, Jugran DK (2003) Delineation of groundwater potential zones and zones of groundwater quality suitable for domestic purposes using remote sensing and GIS. Hydrol Sci J 48(5):821–833

    Article  Google Scholar 

  • Ravi Shankar MN, Mohan G (2006) Assessment of the groundwater potential and quality in Bhatsa and Kalu river basins of Thane district, western Deccan Volcanic Province of India. Environ Geol 49:990–998

    Article  Google Scholar 

  • Roy AB (1988) Stratigraphic and tectonic framework of the Aravalli mountain range. In: Roy AB (ed) Precambrian of the Aravalli Mountain, Rajasthan, India. Geological Society of India, Mem. 7, Bangalore, India, pp 3–31

    Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resource allocation. McGraw-Hill, New York, 287 pp

    Google Scholar 

  • Sander P, Chesley MM, Minor TB (1996) Groundwater assessment using remote sensing and GIS in a rural groundwater project in Ghana: lessons learned. Hydrogeol J 4(3):40–49

    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 

  • 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

    Article  Google Scholar 

  • Shahid S, Nath SK (2002) GIS Integration of remote sensing and electrical sounding data for hydrogeological exploration. J Spat Hydro 2(1):1–12

    Google Scholar 

  • Shahid S, Nath SK, Roy J (2000) Groundwater potential modeling in a softrock area using a GIS. Int J Remote Sens 21(9):1919–1924

    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 Spat Hydro 4(2):1–24

    Google Scholar 

  • Solomon S, Quiel F (2006) Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea. Hydrogeol J 14:729–741

    Article  Google Scholar 

  • Thirumalaivasan D, Karmegam M, Venugopal K (2003) AHP-DRASTIC: software for specific aquifer vulnerability assessment using DRASTIC model and GIS. Environ Model Softw 18:645–656

    Article  Google Scholar 

  • USGS (2004) Shuttle radar topography mission, 1 arc second scene SRTM_u03_n008e004, unfilled unfinished 2.0, global land cover facility, University of Maryland, College Park, Maryland, February 2000

  • Waters P, Greenbaum P, Smart L, Osmaston H (1990) Applications of remote sensing to groundwater hydrology. Remote Sens Rev 4:223–264

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Deepesh Machiwal.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Machiwal, D., Jha, M.K. & Mal, B.C. Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing, GIS and MCDM Techniques. Water Resour Manage 25, 1359–1386 (2011). https://doi.org/10.1007/s11269-010-9749-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-010-9749-y

Keywords

  • Groundwater potential
  • Remote sensing
  • GIS
  • MCDM
  • Hard-rock aquifer system
  • Semi-arid region