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An integrated multi-criteria decision analysis and geographic information system-based assessment of groundwater potentiality and stress zones for sustainable agricultural practices: a case study of agriculture-dominating Koch Bihar District, West Bengal

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Abstract

Groundwater is considered an essential natural resource due to its greater resilience to natural catastrophes than surface water. A systematic strategy for groundwater exploration using modern technologies is necessary for the long-term sustainability of this vital resource. Overexploitation of groundwater for paddy cultivation has had a long-term, detrimental impact on groundwater levels in the Koch Bihar district. Previously, the scope of groundwater potential zones was not extensively evaluated, specifically focusing on groundwater stress zones. The primary objective of this present work is to assess the groundwater potential zones and groundwater stress zones of the Koch Bihar district. For this, 18 parameters for groundwater potential and 12 for groundwater stress zones were chosen after a multicollinearity analysis with a tolerance value of more than 0.1 and a variance inflation factor value of less than 10 for each parameter at p < 0.05. Three systematic and comprehensive Multi-Criteria Decision Analysis methods (Vise Kriterijumska Optimizacijaik Ompromisno Resenje, Technique for Order Preference by Similarity to Ideal Solution and Evaluation Based on Distance from Average Solution) have been used in the present study to evaluate the groundwater condition. The Receiver-Operating Characteristic curve has been used to validate the groundwater potential zone maps produced by the three models. The result shows that all three models have considerable discrimination ability. Among the three models, Vise Kriterijumska Optimizacijaik Ompromisno Resenje has manifested an excellent outcome with an acceptable level of discrimination determined by the area under curve value of 0.844. The study area’s riverine regions have been found to have greater groundwater potentiality, while urbanised areas have lower potentiality. Furthermore, the results indicate that increased agricultural and irrigation intensities have put Sitai, Haldibari, Mekhliganj, Dinhata-II, Sitalkuchi, Mathabhanga-I, and Tufanganj-II blocks under significant stress. The findings are significant, and decision-makers and local authorities might utilise the resulting maps to develop a proper groundwater extraction and management plan.

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References

  • Adham, M., Jahan, C., Mazumder, Q., Hossain, M., & Haque, A. (2010). Study on groundwater recharge potentiality of Barind tract, Rajshahi district, Bangladesh using GIS and remote sensing technique. Geological Society of India, 75, 432–438.

    Article  Google Scholar 

  • Ahmadi, H., Kaya, O. A., Babadagi, E., Savas, T., & Pekkan, E. (2021). Gis-based groundwater potentiality mapping using AHP and FR models in Central Antalya Turkey. Environmental Sciences Proceedings, 5, 11. https://doi.org/10.3390/iecg2020-08741

    Article  Google Scholar 

  • Al-Abadi, A. M. (2015). Groundwater potential mapping at northeastern Wasit and Missan governorates, Iraq using a data-driven weights of evidence technique in framework of GIS. Environmental Earth Sciences, 74, 1109–1124. https://doi.org/10.1007/s12665-015-4097-0

    Article  Google Scholar 

  • Arabameri, A., Roy, J., Saha, S., Blaschke, T., Ghorbanzadeh, O., & Bui, D. T. (2019). Application of probabilistic and machine learning models for groundwater potentiality mapping in Damghan sedimentary plain Iran. Remote Sensing, 11, 3015. https://doi.org/10.3390/rs11243015

    Article  Google Scholar 

  • Arnell, N. W. (1999). Climate change and global water. Global Environmental Change, 9, 43. https://doi.org/10.1038/s41598-018-35067-2

    Article  CAS  Google Scholar 

  • Awawdeh, M., Obeidat, M., Al-Mohammad, M., Al-Qudah, K., & Jaradat, R. (2014). Integrated GIS and remote sensing for mapping groundwater potentiality in the Tulul al Ashaqif, Northeast Jordan. Arabian Journal of Geosciences, 7, 2377–2392. https://doi.org/10.1007/s12517-013-0964-8

    Article  CAS  Google Scholar 

  • Chakrabortty, R., Pal, S. C., Malik, S., & Das, B. (2018). Modeling and mapping of groundwater potentiality zones using AHP and GIS technique: A case study of Raniganj Block, Paschim Bardhaman, West Bengal. Modeling Earth Systems and Environment, 4, 1085–1110. https://doi.org/10.1007/s40808-018-0471-8

    Article  Google Scholar 

  • Chen, W., Li, H., Hou, E., Wang, S., Wang, G., Panahi, M., Li, T., Peng, T., Guo, C., Niu, C., Xiao, L., Wang, J., Xie, X., & Ahmad, B. B. (2018). GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models. Science of the Total Environment, 634, 853–867. https://doi.org/10.1016/j.scitotenv.2018.04.055

    Article  CAS  Google Scholar 

  • Chen, W., Panahi, M., Khosravi, K., Pourghasemi, H. R., Rezaie, F., & Parvinnezhad, D. (2019). Spatial prediction of groundwater potentiality using ANFIS ensembled with teaching-learning-based and biogeography-based optimisation. Journal of Hydrology, 572, 435–448. https://doi.org/10.1016/j.jhydrol.2019.03.013

    Article  Google Scholar 

  • Das, B., & Pal, S. C. (2019). Combination of GIS and fuzzy-AHP for delineating groundwater recharge potential zones in the critical Goghat-II block of West Bengal, India. HydroResearch, 2, 21–30. https://doi.org/10.1016/j.hydres.2019.10.001

    Article  Google Scholar 

  • District Census Handbook (2011). Koch Bihar, Census of India 2011.WEST BENGAL. Retrieved from: https://censusindia.gov.in/nada/index.php/catalog/1332

  • District Survey Report (2020). Cooch Behar District. Retrieved from: https://coochbehar.gov.in/document/district-survey-report-of-cooch-behar-district/

  • Döll, 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 

  • Elbeih, S. F. (2015). An overview of integrated remote sensing and GIS for groundwater mapping in Egypt. Ain Shams Engineering Journal, 6, 1–15. https://doi.org/10.1016/j.asej.2014.08.008

    Article  Google Scholar 

  • Elewa, H. H., & Qaddah, A. A. (2011). Groundwater potentiality mapping in the Sinai Peninsula, Egypt, using remote sensing and GIS-watershed-based modeling. Hydrogeology Journal, 19, 613–628. https://doi.org/10.1007/s10040-011-0703-8

    Article  Google Scholar 

  • Elmahdy, S. I., & Mohamed, M. M. (2015). Probabilistic frequency ratio model for groundwater potential mapping in Al Jaww plain, UAE. Arabian Journal of Geosciences, 8, 2405–2416. https://doi.org/10.1007/s12517-014-1327-9

    Article  Google Scholar 

  • Ferozur, R. M., Jahan, C. S., Arefin, R., & Mazumder, Q. H. (2019). Groundwater potentiality study in drought prone barind tract, NW Bangladesh using remote sensing and GIS. Groundwater for Sustainable Development, 8, 205–215. https://doi.org/10.1016/j.gsd.2018.11.006

    Article  Google Scholar 

  • Gaber, A., Mohamed, A. K., Elgalladi, A., Abdelkareem, M., Beshr, A. M., & Koch, M. (2020). Mapping the groundwater potentiality of West Qena area, Egypt, using integrated remote sensing and hydro-geophysical techniques. Remote Sensing, 12, 1559. https://doi.org/10.3390/rs12101559

    Article  Google Scholar 

  • Guru, B., Seshan, K., & Bera, S. (2017). Frequency ratio model for groundwater potential mapping and its sustainable management in cold desert, India. Journal of King Saud University Science, 29, 333–347. https://doi.org/10.1016/j.jksus.2016.08.003

    Article  Google Scholar 

  • Hwang, C. L., Yoon, K., Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making: Methods and applications a state-of-the-art survey (pp. 58–191).

  • Ifediegwu, S. I. (2022). Assessment of groundwater potential zones using GIS and AHP techniques: A case study of the Lafia district, Nasarawa State Nigeria. Applied Water Science, 12, 10. https://doi.org/10.1007/s13201-021-01556-5

    Article  Google Scholar 

  • Jamrah, A., Al-futaisi, A., Rajmohan, N., & Al-yaroubi, S. (2008). Assessment of groundwater vulnerability in the coastal region of Oman using DRASTIC index method in GIS environment. Environmental Monitoring and Assessment, 147, 125–138. https://doi.org/10.1007/s10661-007-0104-6

    Article  CAS  Google Scholar 

  • Kamruzzaman, M., Mandal, T., Rahman, A. T. M. S., Abdul Khalek, M., Alam, G. M. M., & Rahman, M. S. (2021). Climate modeling, drought risk assessment and adaptation strategies in the western part of Bangladesh. Climate Change Management, 21–54. https://doi.org/10.1007/978-3-030-77259-8_2

  • 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 Resources Management, 28, 4449–4466. https://doi.org/10.1007/s11269-014-0663-6

    Article  Google Scholar 

  • Machiwal, D., Gupta, A., Jha, M. K., & Kamble, T. (2019). Analysis of trend in temperature and rainfall time series of an Indian arid region: Comparative evaluation of salient techniques. Theoretical and Applied Climatology, 136, 301–320. https://doi.org/10.1007/s00704-018-2487-4

    Article  Google Scholar 

  • Machiwal, D., Jha, M. K., & Mal, B. C. (2011). Assessment of groundwater potential in a semi-arid region of India using remote sensing, GIS and MCDM techniques. Water Resources Management, 25, 1359–1386. https://doi.org/10.1007/s11269-010-9749-y

    Article  Google Scholar 

  • Mahato, S., & Pal, S. (2019). Groundwater potential mapping in a rural river basin by union (OR) and intersection (AND) of four multi-criteria decision-making models. Natural Resources Research, 28, 523–545. https://doi.org/10.1007/s11053-018-9404-5

    Article  Google Scholar 

  • Maity, B., Mallick, S. K., Das, P., & Rudra, S. (2022). Comparative analysis of groundwater potentiality zone using fuzzy AHP, frequency ratio and Bayesian weights of evidence methods. Applied Water Science, 12, 63. https://doi.org/10.1007/s13201-022-01591-w

    Article  Google Scholar 

  • Mallick, J., Talukdar, S., Kahla, N. B., Ahmed, M., Alsubih, M., Almesfer, M. K., Reza, A., & Islam, T. (2021). A novel hybrid model for developing groundwater potentiality model using high resolution digital elevation model (DEM) derived factors. Water, 13, 2632. https://doi.org/10.3390/w13192632

    Article  Google Scholar 

  • Mitra, R., & Das, J. (2023). A comparative assessment of flood susceptibility modelling of GIS-based TOPSIS, VIKOR, and EDAS techniques in the Sub-Himalayan foothills region of Eastern India. Environmental Science and Pollution Research, 30, 16036–16067. https://doi.org/10.1007/s11356-022-23168-5

    Article  Google Scholar 

  • Mohamed, M. M., & Elmahdy, S. I. (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 International, 32, 1120–1138. https://doi.org/10.1080/10106049.2016.1195884

    Article  Google Scholar 

  • Mukherjee, I., & Singh, U. K. (2020). Delineation of groundwater potential zones in a drought-prone semi-arid region of east India using GIS and analytical hierarchical process techniques. CATENA, 194, 104681. https://doi.org/10.1016/j.catena.2020.104681

    Article  Google Scholar 

  • Myers, J.,L., Well, A.,D., Lorch, Jr. R.,F. (2010). Introduction to multiple regression. In: Myers JL, Well AD, Lorch Jr. RF (Eds.) Research Design and Statistical Analysis. Routledge, New York, pp. 528–547. https://doi.org/10.4324/9780203726631.

  • Naghibi, S. A., Pourghasemi, H. R., Pourtaghi, Z. S., & Rezaei, A. (2015). Groundwater qanat potential mapping using frequency ratio and Shannon’s entropy models in the Moghan watershed Iran. Earth Science Informatics, 8, 171–186. https://doi.org/10.1007/s12145-014-0145-7

    Article  Google Scholar 

  • Nithya, C. N., Srinivas, Y., Magesh, N. S., & Kaliraj, S. (2019). Assessment of groundwater potential zones in Chittar basin, Southern India using GIS based AHP technique. Remote Sensing Applications: Society and Environment, 15, 100248. https://doi.org/10.1016/j.rsase.2019.100248

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156, 445–455.

    Article  Google Scholar 

  • Pal, S. C., Ghosh, C., & Chowdhuri, I. (2020a). Assessment of groundwater potentiality using geospatial techniques in Purba Bardhaman district, West Bengal. Applied Water Science, 10, 1–13. https://doi.org/10.1007/s13201-020-01302-3

    Article  Google Scholar 

  • Pal, S., Kundu, S., & Mahato, S. (2020b). Groundwater potential zones for sustainable management plans in a river basin of India and Bangladesh. Journal of Cleaner Production, 257, 120311. https://doi.org/10.1016/j.jclepro.2020.120311

    Article  Google Scholar 

  • Pal, S., Saha, A., & Das, T. (2019). Analysis of flow modifications and stress in the Tangon river basin of the Barind tract. International Journal of River Basin Management, 17, 301–321. https://doi.org/10.1080/15715124.2018.1546714

    Article  Google Scholar 

  • Pettorelli, N., Vik, J. O., Mysterud, A., Gaillard, J. M., Tucker, C. J., & Stenseth, N. C. (2005). Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology & Evolution, 20, 503–510.

    Article  Google Scholar 

  • Prasad, Y. S., & Rao, B. V. (2018). Groundwater depletion and groundwater balance studies of Kandivalasa River Sub Basin, Vizianagaram District, Andhra Pradesh, India. Groundwater for Sustainable Development, 6, 71–78. https://doi.org/10.1016/j.gsd.2017.11.003.

  • Rajasekhar, M., Sudarsana Raju, G., Sreenivasulu, Y., & Siddi Raju, R. (2019). Delineation of groundwater potential zones in semi-arid region of Jilledubanderu river basin, Anantapur District, Andhra Pradesh, India using fuzzy logic, AHP and integrated fuzzy-AHP approaches. HydroResearch, 2, 97–108. https://doi.org/10.1016/j.hydres.2019.11.006

    Article  Google Scholar 

  • Rokni, K., Ahmad, A., Selamat, A., & Hazini, S. (2014). Water feature extraction and change detection using multitemporal Landsat imagery. Remote sensing, 6(5), 4173–4189.

    Article  Google Scholar 

  • Saha, P., Mitra, R., Chakraborty, K., & Roy, M. (2022). Application of multi layer perceptron neural network Markov Chain model for LULC change detection in the Sub-Himalayan North Bengal. Remote Sensing Applications: Society and Environment, 26, 100730.

    Article  Google Scholar 

  • Sahoo, S., Chakraborty, S., Pham, Q. B., Sharifi, E., Sammen, S. S., Vojtek, M., Vojteková, J., Elkhrachy, I., Costache, R., & Linh, N. T. T. (2021). Recognition of district-wise groundwater stress zones using the GLDAS-2 catchment land surface model during lean season in the Indian state of West Bengal. Acta Geophysica, 69, 175–198. https://doi.org/10.1007/S11600-020-00509-X/TABLES/4

    Article  Google Scholar 

  • Shao, Z., Huq, M. E., Cai, B., Altan, O., & Li, Y. (2020). Integrated remote sensing and GIS approach using Fuzzy-AHP to delineate and identify groundwater potential zones in semi-arid Shanxi Province China. Environmental Modelling and Software, 134, 104868. https://doi.org/10.1016/j.envsoft.2020.104868

    Article  Google Scholar 

  • Srinivasamoorthy, K., & Vijayaraghavan, K. (2011). Assessment of groundwater vulnerability in Mettur region, Tamilnadu, India using drastic and GIS techniques. Arabian Journal of Geosciences, 4, 1215–1228. https://doi.org/10.1007/s12517-010-0138-x

    Article  CAS  Google Scholar 

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

  • Talukdar, S., Mallick, J., Sarkar, S. K., Roy, S. K., Islam, A. R. M. T., Praveen, B., Rahman, A., & Sobnam, M. (2022). Novel hybrid models to enhance the efficiency of groundwater potentiality model. Applied Water Science, 12, 62.

    Article  Google Scholar 

  • Uc Castillo, J. L., Martínez Cruz, D. A., Ramos Leal, J. A., Tuxpan Vargas, J., Rodríguez Tapia, S. A., & Marín Celestino, A. E. (2022). Delineation of groundwater potential zones (GWPZs) in a semi-arid basin through remote sensing, GIS, and AHP approaches. Water, 14, 2138.

    Article  CAS  Google Scholar 

  • Van Rooy, M. P. (1965). A rainfall anomaly index independent of time and space, notos. Weather Bureau of South Africa, 14, 43–48.

  • Yazdani, M., Torkayesh, A. E., Santibanez-Gonzalez, E. D., & Otaghsara, S. K. (2020). Evaluation of renewable energy resources using integrated Shannon Entropy—EDAS model. Sustainable Operations and Computers, 1, 35–42.

    Article  Google Scholar 

  • Zomer, R. J., Xu, J., & Trabucco, A. (2022). Version 3 of the global aridity index and potential evapotranspiration database. Scientific Data, 9, 409.

    Article  Google Scholar 

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Acknowledgements

The authors want to express gratitude to their respective Departments and Universities for providing all essential support. They are thankful to the USGS, GSI, NBSS, IMD, CHRS, MOSDAC, CGWB, ISRIC, and OSMF officials for providing the data required for the study free of cost. Dr. A. H. Hassani deserves the most profound gratitude for his excellent editorial assistance on this manuscript. The authors would like to thank the anonymous reviewers for their insightful and constructive comments to improve the quality of this paper.

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  1. Department of Geography, Cooch Behar Panchanan Barma University, Cooch Behar, 736101, India

    P. Saha & S. K. Gayen

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Saha, P., Gayen, S.K. An integrated multi-criteria decision analysis and geographic information system-based assessment of groundwater potentiality and stress zones for sustainable agricultural practices: a case study of agriculture-dominating Koch Bihar District, West Bengal. Int J Energ Water Res (2024). https://doi.org/10.1007/s42108-024-00286-z

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