Skip to main content
Log in

Spatiotemporal Analysis and Trend Detection of Groundwater Levels Using Gis Techniques in Nadia District of West Bengal, India

  • Original Article
  • Published:
Journal of the Geological Society of India

Abstract

Groundwater (GW) resources are influenced by several factors like over exploitation, geological formation, climate etc. A long-term GW level trend detection is necessary for sustainable groundwater usage planning in future. In the present study, long-term (1990–2013) spatio-temporal analysis of GW levels during pre-monsoon and post-monsoon was done to elucidate the GW level variation trends in Nadia. Results show that the groundwater levels dropped more than 2.5 m below ground level (bgl) in the central part of the district, however, this drop was less than 2.5 m (bgl) in the northern and southern part of the district. According to pre- and post-monsoon data, the average annual water level decreased beyond 3 m (bgl) in blocks of Tehatta II, Chapra and Chakdah. Average GW level at Krishnaganj and Chakdah, in pre-monsoon were 6.84 m (bgl) and 7.55 m (bgl) respectively, which was higher than the post-monsoon (4.20 m (bgl) and 4.43 m (bgl)). During post-monsoon except Karimpur-I, Krisnaganj (both negative trend) and Hashkali (no trend) and in pre-monsoon except Krisnaganj (negative trend) and Hashkali (no trend), all the other blocks had positive trend. The study reveals that the groundwater levels in the southeastern and northeastern regions of the district drops by more than 5 m bgl in pre-monsoon and more than 4 m bgl in post-monsoon. Such fluctuations of groundwater levels may have serious bearing on agricultural operations in this intensively cultivated and irrigated area.

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

Access this article

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Similar content being viewed by others

References

  • Anand, B., Karunanidhi, D., Subramani, T., Srinivasamoorthy, K., and Suresh, M. (2020) Long-term trend detection and spatiotemporal analysis of groundwater levels using GIS techniques in Lower Bhavani River basin, Tamil Nadu, India. Environ., Develop. Sustain., 22(4), 2779–2800. doi:https://doi.org/10.1007/s10668-019-00318-3

    Article  Google Scholar 

  • Arya, S., Vennila, G. and Subramani, T. (2018) Spatial and seasonal variation of groundwater levels in Vat- tamalaikarai River basin, Tamil Nadu, India—A study using GIS and GPS. Indian Jour. Geo- Marine Sci., v.47(9), pp.1749–1753.

    Google Scholar 

  • Bhattacharyya, K., Sengupta, S., Pari, A., Halder, S., Bhattacharya, P., Pandian, B.J. and Chinchmalatpure, A.R. (2021). Characterization and risk assessment of arsenic contamination in soil-plant (vegetable) system and its mitigation through water harvesting and organic amendment. Environ. Geochem. Health, v.43(8), pp.2819–2834.

    Article  Google Scholar 

  • Burrough, P.A. (1986) Principles of geographical information systems for land resources assessment. New York: Oxford University Press.

    Book  Google Scholar 

  • CGWB (2016) Central Ground Water Board report on aquifer mapping and management plan. Ministry of Water Resources, River Development and Ganga Rejuvenation Government of India. Eastern Region, Kolkata. http://cgwb.gov.in/AQM/NAQUIM_REPORT/WEST-BENGAL/Bardhman_nadia.pdf

    Google Scholar 

  • Duhan, D. and Pandey, A. (2013) Statistical analysis of long term spatial and temporal trends of precipita- tion during 1901–2002 at Madhya Pradesh, India. Atmosph. Res., v.122, 136–149. doi:https://doi.org/10.1016/j.atmosres.2012.10.010.

    Article  Google Scholar 

  • Goyal, S. K., Chaudhary, B. S., Singh, O., Sethi, G. K. and Thakur, P. K. (2010) Variability analysis of groundwater levels—A GIS based case study. Jour. Indian Soc. Rem. Sens., v.38(2), pp.355–364. doi:https://doi.org/10.1007/s12524-010-0024-8.

    Article  Google Scholar 

  • Grzywna, A., Kaminska, A. and Bochniak, A. (2016) Analysis of spatial variability in the depth of water table in grassland areas. Annual Set The Environment Protection, v.18, pp.291–302.

    Google Scholar 

  • Heine, G.W. (1986) A controlled study of some two-dimensional interpolation methods. COGS Computer Contrib., v.3(2), pp.60–72.

    Google Scholar 

  • Helsel, D.R. (1987) Advantages of nonparametric procedures for analysis of water quality data. Hydrol. Sci. Jour., v.32(2), pp.179–190. doi:https://doi.org/10.1080/02626668709491176

    Article  Google Scholar 

  • Jie, C., Hanting, Z., Hui, Q., Jianhua, W. and Xuedi, Z. (2013) Selecting proper method for groundwater interpolation based on spatial correlation. In 2013 Fourth International Conference on Digital Manufacturing & Automation (pp. 1192–1195). IEEE. https://doi.org/10.1109/ICDMA.2013.282

  • Karunanidhi, D., Vennila, G. and Suresh, M. (2012) GIS approach for rainfall fluctuation study in Omalur Taluk, Salem District, Tamil Nadu, India. Pollution Res., v.31(3), pp.493–497.

    Google Scholar 

  • Kendall, M.G. (1975) Rank correlation methods. Griffin, London. http://www.sciencedirect.com/science/refhub/S0895-9811(15)00014-0/sref18.

    Google Scholar 

  • Kshetrimayum, K.S. and Bajpai, V.N. (2012) Assessment of groundwater quality for irrigation use and evolution of hydrochemical facies in Markanda river basin, North western India. Jour. Geol. Soc. India, v.79, pp.189–198. doi:https://doi.org/10.1007/s12594-012-0024-0.

    Article  Google Scholar 

  • Luo, Y., Liu, S., Fu, S., Liu, J., Wang, G. and Zhou, G. (2008) Trends of precipitation in Beijiang River basin, Guangdong province, China. Hydrol. Process. An Internat. Jour., v.22(13), pp.2377–2386. doi:https://doi.org/10.1002/hyp.6801

    Article  Google Scholar 

  • Mann, H.B. (1945) Non-parametric tests against trend. Econometrica, v.13, pp.245–259. doi:https://doi.org/10.2307/1907187.

    Article  Google Scholar 

  • Nayak, T. R., Gupta, S. K., & Galkate, R. (2015). GIS based mapping of groundwater fluctuations in Bina Basin. Aquatic Procedia, v.4, pp.1469–1476. doi:https://doi.org/10.1016/j.aqpro.2015.02.190.

    Article  Google Scholar 

  • Panda, D.K., Mishra, A., Jena, S.K., James, B.K. and Kumar, A. (2007) The influence of drought and anthropogenic effects on groundwater levels in Orissa, India. Jour. Hydrol., v.343(3), pp.140–153. doi:https://doi.org/10.1016/j.jhydrol.2007.06.007.

    Article  Google Scholar 

  • Roy, M., Nilson, L. and Pal, P. (2008) Development of groundwater resources in a region with high population density: a study of environmental sustainability. Environ. Sci., v.5(4), pp.251–267. doi:https://doi.org/10.1080/15693430802358605

    Article  Google Scholar 

  • Salmi, T. (2002). Detecting trends of annual values of atmospheric pollutants by the Mann-Kendall test and Sen’s slope estimates-the Excel template application MAKESENS. Ilmatieteen laitos.

  • Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s tau. Jour. Amer. Statist. Assoc., v.63(324), pp.1379–1389.

    Article  Google Scholar 

  • Sengupta, S., Bhattacharyya, K., Mandal, J., Bhattacharya, P., Halder, S. and Pari, A. (2021) Deficit irrigation and organic amendments can reduce dietary arsenic risk from rice: Introducing machine learning-based prediction models from field data. Agriculture, Ecosystems & Environment, v.319, 107516.

    Article  Google Scholar 

  • Singh, R., Sah, S., Chaturvedi, G., Das, B. and Pathak, H. (2021) Innovative trend analysis of rainfall in relation to soybean productivity over western Maharashtra. Jour. Agrometeorol., v.23(2), pp.228–235.

    Article  Google Scholar 

  • Sivapragasam, C., Kannabiran, K., Karthik, G., & Raja, S. (2015) Assessing suitability of GP modeling for groundwater level. Aquatic Procedia, v.4, pp.693–699. doi:https://doi.org/10.1016/j.aqpro.2015.02.089.

    Article  Google Scholar 

  • Subramani, T., Babu, Savithri, & Elango, L. (2013) Computation of groundwater resources and recharge in Chithar River Basin, South India. Environ. Monit. Assess., v.185, pp.983–994. doi:https://doi.org/10.1007/s10661-012-2608-y.

    Article  Google Scholar 

  • Subramani, T., Prabaharan, S. and Karunanidhi, D. (2015) Groundwater prospecting in a part of Tami- rabarani River basin, South India using Remote Sensing and GIS. Indian Jour. Geo-Marine Sci., v.44(9), pp.1401–1408.

    Google Scholar 

  • Tabari, H., Nikbakht, J. and Some’e, B. S. (2012) Investigation of groundwater level fluctuations in the north of Iran. Environ. Earth Sci., v.66, pp.231–243. doi:https://doi.org/10.1007/s12665-011-1229-z.

    Article  Google Scholar 

  • Tiwari, A.K., Singh, P.K., Chandra, S. and Ghosh, A. (2015) Assessment of groundwater level fluc- tuation by using remote sensing and GIS in West Bokaro coal field, Jharkhand, India. Jour. Hydraulic Eng., v.22(1), pp.59–67.

    Article  Google Scholar 

  • Xiao, Y., Gu, X., Yin, S., Shao, J., Cui, Y., Zhang, Q., et al. (2016). Geostatistical interpolation model selec- tion based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China. SpringerPlus, v.5(425), pp.1–15. doi:https://doi.org/10.1186/s40064-016-2073-0.

    Google Scholar 

Download references

Acknowledgement

Authors are grateful to State Water Investigation Directorate (SWID)-Kolkata, Govt of West Bengal for providing block wise GW level data of Nadia district.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Aniket Baishya.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baishya, A., Chowdhury, A., Chakrabarty, R. et al. Spatiotemporal Analysis and Trend Detection of Groundwater Levels Using Gis Techniques in Nadia District of West Bengal, India. J Geol Soc India 99, 868–874 (2023). https://doi.org/10.1007/s12594-023-2394-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12594-023-2394-x

Navigation