Skip to main content

Advertisement

Log in

Application of multi-criteria decision making technique for the assessment of groundwater potential zones: a study on Birbhum district, West Bengal, India

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

Thriving depletion of groundwater resource in the present era of green revolution and industrialization requires sustainable development and management through precise quantitative assessment-based scientific principles and modern techniques. The analytical hierarchy process (AHP) model as a popular method of multi-criteria decision-making technique is applied to determine the importance of groundwater influencing factors. Geographic information system (GIS) as a part of geospatial technology has also been used to integrate the groundwater influencing spatial dataset. In this study nine groundwater influencing thematic layers, viz. geology, drainage density, aquifer thickness, pond frequency, soil texture, lineament density, land use/land cover and rainfall, have been selected to assess groundwater potential. In this article, Birbhum district of West Bengal has been chosen as the area of case study. On the basis of AHP model and GIS technology, five groundwater potential zones have been extracted in the study area comprising very low, low, moderate, high and very high groundwater potential zones. It has been estimated that an area of 212.27 km2 has very high potential, which is only 4.77% of the total study area. However, the areas having high, moderate, low and very low groundwater potential are about 23.33, 47.84, 25.16, and 3.65%, respectively. Finally, the validation of the groundwater potential map has been done with the data of 41 drilled boreholes which are present in a scattered manner throughout the district. The results depict that the prediction of groundwater potential zone of the area has 76.1% accuracy.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Adiat, K. A. N., Nawawi, M. N. M., & Abdullah, K. (2012). Assessing the accuracy of GIS-based elementary Multi-criteria decision analysis as a spatial prediction tool—A case of predicting potential zones of sustainable groundwater resources. Journal of Hydrology,440, 79–89. https://doi.org/10.1016/j.jhydrol.2012.03.028.

    Article  Google Scholar 

  • Agarwal, E., Agarwal, R., Garg, R. D., & Garg, P. K. (2013). Delineation of groundwater potential zone: An AHP/ANP approach. Journal of Earth System Science,122(3), 887–898.

    Article  Google Scholar 

  • Al Saud, M. (2010). Mapping potential areas for groundwater storage in Wadi Aurnah basin, western Arabian Peninsula, using remote sensing and geographic information system techniques. Hydrogeology Journal,18, 1481–1495. https://doi.org/10.1007/s10040-010-0598-9.

    Article  Google Scholar 

  • Ali, Q. S. W., Lal, D., & Ahsan, J. (2015). Assessment of groundwater potential zones in Allahabad district by using remote sensing & GIS techniques. International Journal of Applied Research,1(13), 586–591.

    Google Scholar 

  • Ayazi, M. H., Pirasteh, S., Arvin, A. K. P., Pradhan, B., Nikouravan, B., & Mansor, S. (2010). Disasters and risk reduction in groundwater: Zagros Mountain Southwest Iran using geo-informatics techniques. Disaster Advances,3(1), 1–8.

    Google Scholar 

  • Bardy, N. C. (1984). Soils (pp. 35–45). New York: Macmillan Publishing Co. Inc.

    Google Scholar 

  • Bhunia, G. S., Samanta, S., Pal, B., Memorial, R., & Agamkuan, S. (2012). Deciphering prospective groundwater zones of Morobe province, Papua New Guinea. International Journal on Engineering Applications,2(3), 752–766.

    Google Scholar 

  • Biswas, A., Jana, A., & Sharma, S. P. (2012). Delineation of Groundwater potential zones using satellite remote sensing and geographic information techniques: A case study from Gunjam district, Orissa, India. Research Journal of Recent Sciences,1(9), 59–66.

    Google Scholar 

  • Biswas, T. D., & Mukherjee, S. K. (1994). Textbook of soil science (pp. 153–163). New Delhi: Tata Mcgraw Hill Education Private Limited.

    Google Scholar 

  • Bureau of Applied Economics & Statistics. (1997). District statistical handbook, Government of West Bengal (pp. 1–5).

  • Bureau of Applied Economics & Statistics. (2014). District statistical handbook, Government of West Bengal.

  • CGWB. (2009). Report of the groundwater resource estimation committee (pp. 8–12). New Delhi: Ministry of Water Resources, Government of India.

    Google Scholar 

  • CGWB. (2014).Groundwater Year Book of West Bengal and Andaman and Nicobar Island 2014-15. Ministry of Water Resources, Government of India. http://www.cgwb.gov.in. Accessed January 20, 2017.

  • Chowdhury, V. M., Chakraborty, D., Jeyaram, A., Krishna Murty, Y. V. N., Sharma, J. R., & Dadhwal, V. K. (2013). Multi-criteria decision making approach for watershed prioritization using analytic hierarchy process technique and GIS. Water Resource Management,27, 3555–35571. https://doi.org/10.1007/s11269-013-0364-6.

    Article  Google Scholar 

  • Chowdhury, A., Jha, M. K., & Chowdhury, V. M. (2010). Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Environmental Earth Sciences,59, 1209–1222. https://doi.org/10.1007/s12665-009-0110-9.

    Article  Google Scholar 

  • Chowdhury, A., Jha, M. K., Chowdhury, V. M., & Mal, B. C. (2009). Integrated remote sensing and GIS based approach for accessing groundwater potential in west Medinipur district, West Bengal, India. International Journal of Remote Sensing,30(1), 231–250. https://doi.org/10.1080/01431160802270131.

    Article  Google Scholar 

  • Doll, P., & Fiedler, K. (2008). Global-scale modeling of groundwater recharge. Hydrology and Earth System Sciences,12, 863–885. https://doi.org/10.5194/hess-12-863-2008.

    Article  Google Scholar 

  • Edet, A. E., & Okereke, C. S. (1996). Assessment of hydrogeological conditions in basement aquifers of the Precambrian Oban massif, southeastern Nigeria. Journal of Applied Geophysics,36, 195–204. https://doi.org/10.1016/S0926-9851(96)00049-3.

    Article  Google Scholar 

  • Ettazarini, S. (2007). Groundwater potential index: A strategically conceived tool for water research in fractured aquifers. Environmental Geology,52, 477–487.

    Article  CAS  Google Scholar 

  • Hachem, A. M., Ali, E., Abdelhadi, E. O., AbdellahK, E. H., & Said, K. (2015). Using remote sensing and GIS–multicriteria decision analysis for groundwater potential mapping in the Middle Atlas Plateau, Morocco. Research Journal of Recent Sciences,4(7), 33–41.

    Google Scholar 

  • Hajkowicz, S., & Higgins, A. (2008). A comparison of multiple criteria analysis techniques for water resource management. European Journal of Operational Research,184, 255–265. https://doi.org/10.1016/j.ejor.2006.10.045.

    Article  Google Scholar 

  • Haridas, V. R., Aravindan, S., & Girish, G. (1998). Remote sensing and its applications for groundwater favorable area identification. Quarterly Journal of Geological Association and Research Centre,6, 18–22.

    Google Scholar 

  • Hofkes, E. H., & Visscher, J. T. (1986). Artificial groundwater recharge for water supply of medium size communities in developing countries. In International reference centre for community water supply and sanitation, The Hague, The Netherlands. www.samsamwater.com. Accessed June 25, 2017.

  • Horton, R. E. (1932). Drainage basin characteristics. Transactions of the American Geophysical Union,14, 350–361.

    Article  Google Scholar 

  • Jaiswal, R. K., 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. International Journal of Remote Sensing,24(5), 993–1008. https://doi.org/10.1080/01431160210144543.

    Article  Google Scholar 

  • Jha, M. K., Chowdary, V. M., & Chowdhury, A. (2010). Groundwater assessment in Salboni Block, West Bengal (India)using remote sensing, geographical information system and multi-criteria decision analysis techniques. Hydrogeology Journal,18(7), 1713–1728. https://doi.org/10.1007/s10040-010-0631-z.

    Article  Google Scholar 

  • Jha, M. K., Chowdhury, A., Chowdhury, V. M., & Peiffer, S. (2007). Groundwater management and development by integrated remote sensing and geographic information systems: Prospect and constraints. Water Resource Management,21(2), 427–467. https://doi.org/10.1007/s11269-006-9024-4.

    Article  Google Scholar 

  • Jhariya, D. C., Kumar, T., Gobinath, M., Diwan, P., & Kishore, N. (2016). Assessment of groundwater potential zone using remote sensing, GIS and multi-criteria decision analysis techniques. Journal of the Geological Society of India,88, 481–492.

    Article  Google Scholar 

  • Kaliraj, S., Chandrasekar, N., & Magesh, N. S. (2014). Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique. Arabian Journal of Geosciences,7(4), 1385–1401. https://doi.org/10.1007/s12517-013-0849-x.

    Article  Google Scholar 

  • Krishhamurthy, J., Kumar, N. V., Jayaraman, V., & Manivel, M. (1996). An approach to demarcate groundwater potential zone through remote sensing and a geographic information system. International Journal of Remote Sensing,17(10), 1867–1884. https://doi.org/10.1080/01431169608948744.

    Article  Google Scholar 

  • Kumar, T., Gautam, A. K., & Kumar, T. (2014). Appraising the accuracy of GIS based multi-criteria decision making technique for delineation of groundwater potential zones. Water Resource Management,28, 4449–4466. https://doi.org/10.1007/s11269-014-0663-6.

    Article  Google Scholar 

  • Kumar, T., & Jhariya, D. C. (2015). Land quality index assessment for agricultural purpose using multi-criteria decision analysis (MCDA). Geocarto International,30(7), 822–841. https://doi.org/10.1080/10106049.2014.997304.

    Article  Google Scholar 

  • Kumar, R., Thaman, S., Agarwal, G., & Poonam, S. (2011). Rain water harvesting and groundwater recharging in North Western Himalayan Region for sustainable agricultural productivity. Universal Journal of Environmental Research and Technology,1(4), 539–544.

    Google Scholar 

  • Madrucci, V., Taioli, F., & Cesar de Araujo, C. (2008). Groundwater favorability map using GIS multicriteria data analysis on Crystalline terrain, Sao Paulo State, Brazil. Journal of Hydrology,357, 153–173. https://doi.org/10.1016/j.jhydrol.2008.03.026.

    Article  Google Scholar 

  • Magesh, N. S., Chandrasekar, N., & Soundranayagam, J. P. (2012). Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geoscience Frontiers,3(2), 189–196. https://doi.org/10.1016/j.gsf.2011.10.007.

    Article  Google Scholar 

  • Majumdar, D. (1975). West Bengal District Gazetteer, Birbhum. State editor, Government of West Bengal, Kolkata (pp. 1–79).

  • Malczewski, J. (1999). GIS and multicriteria decision analysis (pp. 177–192). New York: Wiley.

    Google Scholar 

  • Manap, M. A., Nampak, H., Pradhan, B., Lee, S., Sulaiman, W. N. A., & Ramli, M. F. (2012). Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing and GIS. Arabian Journal of Geosciences,7(2), 711–724. https://doi.org/10.1007/s12517-012-0795-z.

    Article  Google Scholar 

  • Manap, M. A., Sulaiman, W. N. A., Ramli, M. F., Pradhan, B., & Surip, N. (2013). A knowledge-driven GIS modeling technique for groundwater potential mapping at the Upper Langat Basin, Malaysia. Arabian Journal of Geosciences,6, 1621–1637. https://doi.org/10.1007/s12517-011-0469-2.

    Article  Google Scholar 

  • Mohammady, M., Pourghasemi, H. R., & Pradhan, B. (2012). Landslide susceptibility mapping at Golestan Province, Iran: A comparison between frequency ratio, Dempster-Shafer, and weights-of-evidence models. Journal of Asian Earth Sciences,61, 221–236.

    Article  Google Scholar 

  • Mukherjee, D. (2016). A review on artificial groundwater recharge in India. International Journal of Civil Engineering,3(1), 60–65.

    Article  Google Scholar 

  • Mukherjee, P., Singh, C. K., & Mukherjee, S. (2012). Delineation of groundwater potential zone in arid region of India—A remote sensing and GIS approach. Water Resource Management,26, 2643–2672. https://doi.org/10.1007/s11269-012-0038-9.

    Article  Google Scholar 

  • Murthy, K. S. R., & Mamo, A. G. (2009). Multi-criteria decision making evaluation in groundwater zones identification in Moyale-Teltele subbasin, South Ethopia. International Journal of Remote Sensing,30, 2729–2740. https://doi.org/10.1080/01431160802468255.

    Article  Google Scholar 

  • Nolan, B. T., Baehr, A. L., & Kauffman, L. J. (2003). Spatial variability of groundwater recharge and its effect on shallow groundwater quality in Southern New Jersey. Vadose Zone Journal,2, 677–691.

    Article  CAS  Google Scholar 

  • Oh, H. J., Kim, Y. S., Choi, J. K., Park, E., & Lee, S. (2011). GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea. Journal of Hydrology,399, 158–172. https://doi.org/10.1016/j.jhydrol.2010.12.027.

    Article  Google Scholar 

  • Pande, C. B., Khadri, S. F. R., Moharir, K. N., et al. (2017). Assessment of groundwater potential zonation of Mahesh River basin Akola and Buldhana districts, Maharashtra, India using remote sensing and GIS techniques. Sustainable Water Resources Management, 4, 1–15. https://doi.org/10.1007/s40899-017-0193-5.

    Article  Google Scholar 

  • Panigrahi, B., Nayak, A. K., & Sharma, S. D. (1995). Application of remote sensing technology for groundwater potential evaluation. Water Resource Management,9(3), 161–173. https://doi.org/10.1007/BF00872127.

    Article  Google Scholar 

  • Pourtaghi, Z. S., & Pourghasemi, H. R. (2014). GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province, Iran. Hydrogeology Journal,22, 643–662. https://doi.org/10.1007/s10040-013-1089-6.

    Article  Google Scholar 

  • Pradhan, B. (2013). A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzymodels in landslide susceptibility mapping using GIS. Computers & Geosciences,51, 350–365.

    Article  Google Scholar 

  • Pradhan, B., Singh, R. P., & Buchroithner, M. F. (2006). Estimation of stress and its in evaluation of landslide prone regions using remote sensing data. Advances in Space Research,37(4), 698–709. https://doi.org/10.1016/j.asr.2005.03.137.

    Article  Google Scholar 

  • Prasad, R. K., Mondal, N. C., Banerjee, P., Nandakumar, M. V., & Singh, V. S. (2008). Deciphering potential groundwater zone in hard rock through the application of GIS. Environmental Geology,55(3), 467–475. https://doi.org/10.1007/s00254-007-0992-3.

    Article  Google Scholar 

  • Rahmati, O., Nazari Samani, A., Mahdavi, M., Pourghasemi, H. R., & Zeinivand, H. (2015). Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS. Arabian Journal of Geosciences,8(9), 7059–7071. https://doi.org/10.1007/s12517-014-1668-4.

    Article  Google Scholar 

  • Ramu, M. B., & Vinay, M. (2014). Identification of ground water potential zones using GIS and remote sensing techniques: A case study of Mysore taluk—Karnataka. International Journal of Geomatics and Geosciences,5(3), 393–403.

    Google Scholar 

  • Rao, N. S., Chakradhar, G. K. J., & Srinivas, V. (2001). Identification of groundwater potential zones using remote sensing techniques in an around Gunur town, Andhra Pradesh, India. Journal of the Indian Society of Remote Sensing,29, 69–78. https://doi.org/10.1007/BF02989916.

    Article  Google Scholar 

  • Razandi, Y., Pourghasemi, H. R., & Neisani, N. S. (2015). Application of analytical hierarchy process, frequency ratio and certainty factor models for groundwater potential mapping using GIS. Earth Science Informatics,8(4), 883–886. https://doi.org/10.1007/s12145-015-0220-8.

    Article  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation. New York: McGraw Hill.

    Google Scholar 

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

  • Saaty, T. L. (2004). Fundamental of analytic network process-multiple network with benefits, costs, opportunities and risks. Journal of Systems Science and Systems Engineering,13(3), 348–379. https://doi.org/10.1007/s11518-006-0171-1.

    Article  Google Scholar 

  • Sahai, V. N. (1990). Fundamental of soil (pp. 5–25). New Delhi: Kalyani Publishers.

    Google Scholar 

  • Sajikumar, N., & Pulikkottil, G. (2013). Integrated remote sensing and GIS approach for groundwater exploration using analytic hierarchy process technique. International Journal of Innovative Research in Science, Engineering and Technology,2, 66–74.

    Google Scholar 

  • Sandar, P., Chesley, M. M., & Minor, T. B. (1996). Groundwater assessment using remote sensing and GIS in a rural groundwater project in Ghana: Lesson learned. Hydrogeology Journal,4(3), 40–49. https://doi.org/10.1007/s100400050086.

    Article  Google Scholar 

  • Shekhar, S., & Pandey, A. C. (2014). 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 International,30(4), 402–421. https://doi.org/10.1080/10106049.2014.894584.

    Article  Google Scholar 

  • Singh, P. K., Bhardwaj, O. A., & Kumar, A. (2011). Site selection for groundwater recharge zone in municipal wastewaters a case study of Varanasi (India). Recent Advance in Civil Engineering Conservation,10(2), 98–103.

    Google Scholar 

  • Strahler, A. N. (1952). Dynamics basin geomorphology. Geological Society of America Bulletin,63, 1117–1142.

    Article  Google Scholar 

  • Thomas, B. F., Ali, B., & Famiglietti, J. S. (2016). Precipitation intensity effects on groundwater recharge in the Southwestern United States. Water,8, 2–15.

    Article  Google Scholar 

  • Todd, D. K. (1980). Groundwater hydrology (pp. 37–45). New York: Wiley.

    Google Scholar 

  • Yahaya, S., Ahmed, M., & Abdalla, R. F. (2010). Multicriteria analysis for flood vulnerable areas in Hadejia-Jama’ river basin, Nigeria. European Journal of Scientific Research,42(1), 71–83. https://doi.org/10.3390/w8030090.

    Article  Google Scholar 

Download references

Acknowledgements

The authors are very grateful to Central Groundwater Board (CGWB) for providing necessary data. The authors also wish their thanks to Dr. Gautam Sen, Ranajit Ghosh and Subhasish Sutradhar for their extending help and assistance to complete this work successfully. Authors are also grateful to the editors and reviewers for their careful reading of our manuscript and their many insightful comments and suggestions.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Niladri Das.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Das, N., Mukhopadhyay, S. Application of multi-criteria decision making technique for the assessment of groundwater potential zones: a study on Birbhum district, West Bengal, India. Environ Dev Sustain 22, 931–955 (2020). https://doi.org/10.1007/s10668-018-0227-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-018-0227-7

Keywords

Navigation