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Groundwater Potential Zone Delineation in Hard Rock Terrain for Sustainable Groundwater Development and Management in South Madhya Pradesh, India

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In view of the vital significance of water resources and issues emerging from their temporal and spatial distribution and utilization posing serious problems to the land resources and to the society United Nations has identified sustainable management of water resources (SDG 6) as one of the seventeen major Sustainable Development Goals (SDGs). In this perspective, the purpose of the study is to identify the groundwater potential zones in the hard rock terrain of Betul-Chhindwara Region, Madhya Pradesh, India, using AHP technique. The study area comprises the sub-watersheds of Tawa river (Narmada basin), Tapi river (Tapi basin), Kanhan and Pench rivers (Godavari basin). Various thematic layers such as geomorphology, geology, physiography, rainfall, soil, slope, lineament, drainage density, groundwater depth, and land use/ land cover were developed. The analytical hierarchy process helps to delineate groundwater prospect zones, which are categorized into five classes, i.e. very poor, poor, moderate, good, and very good based on objective, criteria, and preference. The good, moderate, and poor groundwater potential zones cover 4815 sq. km., 6423 sq. km, and 4857 sq. km, respectively, comprising 22.46%, 29.96%, and 22.65% of the entire region under study. The result indicates that 15.22% of the area comprising 3262.10 sq. km have very good groundwater potential whereas 9.71% (2080 sq. km) has very poor groundwater potential. The obtained result has been verified through field check based on the yield data collected from 16 bore wells in the study area. The accuracy of the results was 75% that proves the efficiency of the adopted techniques. Thus, this study will be efficient for the sustainable development and management of groundwater in the study area.

About the Authors

C. S. Dwivedi
Central University of Jharkhand

Department of Geoinformatics


Raghib Raza
Central University of Jharkhand

Department of Geoinformatics


D. Mitra
ISRO Department of Space, Govt. of India

Marine and Atmospheric Sciences Department, Indian Institute of Remote Sensing


A. C. Pandey
Central University of Jharkhand

Department of Geoinformatics


D. C. Jhariya
National Institute of Technology

Department of Applied Geology

Raipur, GE Road, Raipur-492010, Chhattisgarh


1. Aduah M.S. (2015). Analysis of Land Cover Change in Bonsa Catchment, Ankobra, Ghana. Appl. Ecol. Environ. Res.13:935-955

2. Banai R. (2010). Evaluation of land use – transportation systems with the analytic network process. Journal of Transport and Land Use, 3(1), 85–112.

3. CGWB (2009). A Report of Groundwater Resource Estimation Committee, Central Groundwater Board, Ministry of water resource, Government of India, 1–113

4. CGWB (2013). A Report of Groundwater Resource Estimation Committee, Central Groundwater Board, Ministry of water resource, Government of India, 1–135

5. Cheng E.W.L and Li H. (2004). Contractor selection using the analytic network process. Construction Management and Economics, 22, 1021–1032.

6. Chowdhury A., Jha M. K., Chowdhary V. M. and Mal B. C. (2009). Integrated remote sensing and GIS-based approach for accessing groundwater potential in west Medinipur district, West Bengal, India. Int. J. Remote Sens, 30(1), 231–250.

7. Cook P.G., Walker G.R., Jolly I.D. (1989). Spatial variability of groundwater recharge in a semiarid region. Journal of Hydrology, 111, 195–212

8. Dagdeviren M. and Ihsan Y. (2007). Personnel selection using analytic network process. Istanbul Ticaret Universitesi Fen BilimleriDergisiYil, 6(11), 99–118.

9. 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 Systems and Environ, 3(4), 1589–159.

10. Dehriya S. (2014). Development of Tribal Agriculture in Chhindwara-Seoni Region. Unpublished Ph.D. Thesis University of Sagar. 47–48.

11. District Groundwater Information Booklet (2013). Ministry of water resource, North Central Region, Bhopal India, 1–13.

12. Dunning D. J., Ross Q. E. and Merkhofer M. W. (2000). Multi attribute utility analysis for addressing Section 316(b) of the Clean Water Act. Environ Sci Policy, 3, 7–14.

13. Dwivedi C.S. (2007). Hydro-geomorphic study of sagar lake catchment area using remote sensing technique, Unpublished M.Phil. Dissertation University of Sagar. 28–32.

14. Dwivedi C.S., Husain J. and Shukla S. (2017). Change Detection Analysis Using Multi-Temporal Satellite Data: A Case study from Seoul and Gyeonggi-Do, South Korea. Forging a Multidimensional Partnership in the 21st Century, Manak Publication Pvt. Ltd. New Delhi. ISBN 978–93–7831–443–8

15. Fashae O. A., Tijani M. N., Talabi A. O. and Adedeji O. I. (2014). Delineation of groundwater potential zones in the crystalline basement terrain of SW-Nigeria: An integrated GIS and remote sensing approach. Applied Water Science ,4 (1), 19–38.

16. Flug M., Seitz H. L. H. and Scott J. F. (2000). Multi criteria decision analysis applied to Glen Canyon Dam. J. Water Resour Plan Manage, ASCE 126, 270–276.

17. Galkate R., Thomas T., Pandey R.P., Singh S. and Jaiswal R.K. (2008). Assessment of rainwater availability and planning for water resources development in Chhindwara districtof MP, India. Journal of Indian Water Resources Society, 28(2), 6–14.

18. Ghosh P. K. Jana, N., C., (2017). Groundwater potentiality of the Kumari River Basin in drought prone Purulia upland, Eastern India: a combined approach using quantitative geomorphology and GIS. Sustainable Water Resources Management, 1–17.

19. Groundwater Year Book Madhya Pradesh (2016-17) CGWB, North Central Region, Ministry of Water Resource, River Development and Ganga Rejuvenation, Government of India, 1–142

20. Gupta M. and Srivastava P. K. (2010). Integrating GIS and remote sensing for identification of groundwater potential zones in the hilly terrain of Pavagarh, Gujarat, India. Water International, 35(2), 233–245.

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

22. Jaiswal R., Mukherjee S., Krishnamurthy J. and Saxena R. (2003). Role of remote sensing and GIS techniques for generation of groundwater prospect zone towards rural development – an approach. Int. J. Remote Sens., 24(5), 993–108.

23. Jha M. K., Chowdary V. M. and Chowdhury A. (2010). Groundwater assessment in Salboni Block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques. Hydrogeology J, 18(7), 1713–1728.

24. Jhariya D. C., Kumar T., Gobinath M., Diwan P. and 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.

25. Joubert A., Stewart T. J. and 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, 17–25.

26. King L. C. (1962). The Morphology of the Earth, Edinburgh and London, Oliver and Boyd, (2),699.

27. Krishnamurthy J., Kumar N. V., Jayaraman V. and Manivel M. (1996). An approach to demarcate groundwater potential zone through remote sensing and a geographic information system. Int. J. Remote Sens., 17(10), 1867– 1884.

28. Leduc C., Favreau G., Schroeter P. (2001). Long-term rise in a Sahelian water-table: the continental terminal in south-west Niger. Journal of Hydrology, 243, 43–54.

29. Machiwal D., Jha M. K. and Mal B. C. (2011). Assessment of groundwater potential in a semi-arid region of India using remote sensing, GIS and MCDM techniques. J. Water Resourc. Manag, 25(5), 1359–1386.

30. Machiwal D., Rangi N. and Sharma A. (2015). Integrated knowledge- and data-driven approaches for groundwater potential zoning using GIS and multi-criteria decision-making techniques on hard-rock terrain of Ahar catchment, Rajasthan, India. Environ. Earth Sc., 73(4), 1871–1892.

31. Malczewski J. (1999) GIS and multi criteria decision analysis. New York: John Wiley and Sons, 392.

32. Malczewski J. (2006). GIS–based multi criteria decision analysis: A survey of the literature. Int. J. Geog. Info. Sc., 20(7), 703–726. Monitoring and Assessment, Kluwer Academic Publishers 94 263–277.

33. Malczewski J. and Rinner C. (2015). Multi criteria decision analysis in geographic information science. New York: Springer.

34. MOWR (2009). Report of the Groundwater Resource Estimation Committee. Ministry of Water Resources, Government of India, New Delhi,

35. Mukherjee P., Singh C. K. and Mukherjee S. (2012). Delineation of groundwater potential zones in arid region of India— A remote sensing and GIS approach. Water Resources Manag, 26(9), 2643–2672.

36. Murkute Y.A. and Joshi S.P. (2015). Environment of geological setting for uranium mineralization and geochemical exploration with review from central India. International Journal of Geology, Earth and Environmental Sciences, ISSN: 2277–2081, Vol. 5 (3) SeptemberDecember, 108–117

37. Guhathakurta P. and Rajeevan M. (2007). Trends in the rainfall pattern over Indi. International Journal of Climatology Int. J. Climatol. 28, 1453–1469, (2008) Published online 6 November 2007 in Wiley Inter Science ( DOI: 10.1002/joc.1640

38. Pandey. A. and Dwivedi. C.S. (2014). Changing Land use Pattern in Ambedkarnagar District: A Block wise Analysis. National Geographer, Vol. XLIX, No.1+2, 97–108

39. Phillips F.M. (1994). Environmental tracers for water movement in desert soils of the American Southwest. Soil Science Society of America Journal, 58, 14–24.

40. Rajeeva R., Rahul B., Shrivastava, V. K., Majumdar, A., Roy M. K. and Maithani P. B. (2012). Sedimentological and Geochemical Studies of Lower Gondwana Sediments in parts of Pench-Kanhan Sub-basin, Satpura Gondwana Basin, Chhindwara District, Madhya Pradesh: Implication for Uranium Mineralisation. Gond. Geol. Mag., 27(1), 1–16

41. Roark D.M., Healy D.F. (1998). Quantification of deep percolation from two flood-irrigated alfalfa fields, Roswell Basin, New Mexico. USGS Water Resources Investigation Report, 98–4096, 32.

42. Saaty T. L. (1980). The Analytic Hierarchy Process. McGraw- Hill, New York, NY.

43. Saaty T. L. (1996). Decision making with dependence and feedback, The Analytic Network Process. RWS Publications, Pittsburgh.

44. Saaty T. L. (1999). Fundamentals of the analytic network process. International Symposium of the Analytic Hierarchy Process (ISAHP), Kobe, Japan.

45. Saaty T. L. (2004). Fundamentals of the analytic network process – multiple networks with benefits, costs, opportunitie,s and risks. J. Systems Science and Systems Engineering, 13(3), 348–379.

46. Shankar M.N.R. and Mohan G. (2005). GIS based hydro-geomorphic approach foridentificationofsite-specificartificialrechargetechniquesinthe Deccan Volcanic Province. J Earth Sys Sci., 134(4), 505–514.

47. Shekhar S. and Pandey A. C. (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.

48. Shekhar S., Pandey A. C. and Tirkey A. S. (2014). A GIS-based DRASTIC model for assessing groundwater vulnerability in hard rock granitic aquifer. Arab J. Geosci, 8, 1385–1401.

49. Strahler, A.N. (1952). Hypsometric Analysis of Erosional Topography. Bull. Geol. Soc. Amer., 63, 1117–1142.

50. Sun H., Xu G. and Tian P. (2007). Design alternatives evaluation of emergency bridge by applying analytic network process (ANP). System Engineering Theory and Practice, 27(3), 63–70.

51. Tirkey A. S., Ghosh M. and Pandey A. C. (2016). Soil erosion assessment for developing suitable sites for artificial recharge of groundwater in drought prone region of Jharkhand state using geospatial techniques. Arab J Geosci,. 9, 362.

52. Tran L. T., Knight C. G., O’Neill R. V. and Smith E. R. (2004). Integrated environmental assessment of the Mid-Atlantic Region with Analytical Network Process. Environmental.

53. Tyler S.W., Chapman J.B., Conrad S.H. (1996). Soil-water flux in the southern Great Basin, United States: temporal and spatial variations over the last 120,000 years. Water Resources Research, 32, 1481–1499

54. United Nations (2020). A Report “Sustainable Development Goals Report” Department of Economic and Social Affairs, 1–68, DOI: file:///E:/GES/The-Sustainable-Development-Goals-Report-2020.pdf

55. Wang Ru-Hang, Huang Jian-Guo and Zhang Qun-Fei (2009)“Underwater multiple target tracking decision making based on an analytic network process” Journal of Marine Science Application 8(4) 305–310.

56. Yang C. L., Chuang S. P., Huang R. H. and Tai C. C. (2008). Location selection based on AHP/ANP approach. IEEE, International Conference on Industrial Engineering and Engineering Management, Singapore, 1148–1153.

For citation:

Dwivedi C., Raza R., Mitra D., Pandey A., Jhariya D. Groundwater Potential Zone Delineation in Hard Rock Terrain for Sustainable Groundwater Development and Management in South Madhya Pradesh, India. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2021;14(1):106-121.

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