Research article Special Issues

Numerical groundwater modelling for studying surface water-groundwater interaction and impact of reduced draft on groundwater resources in central Ganga basin


  • Received: 01 June 2022 Revised: 16 July 2022 Accepted: 26 July 2022 Published: 03 August 2022
  • Water resources in India's Indo-Gangetic plains are over-exploited and vulnerable to impacts of climate change. The unequal spatial and temporal variation of meteorological, hydrological and hydrogeological parameters has created additional challenges for field engineers and policy planners. The groundwater and surface water are extensively utilized in the middle Gangetic plain for agriculture. The primary purpose of this study is to understand the discharge and recharge processes of groundwater system using trend analysis, and surface water and groundwater interaction using groundwater modelling. A comprehensive hydrological, and hydrogeological data analysis was carried out and a numerical groundwater model was developed for Bhojpur district, Bihar, India covering 2395 km2 geographical area, located in central Ganga basin. The groundwater level data analyses for the year 2018 revealed that depth to water level varies from 3.0 to 9.0 meter below ground level (m bgl) in the study area. The M-K test showed no significant declining trend in the groundwater level in the study area. The groundwater modelling results revealed that groundwater head is higher in the southern part of the district and the groundwater flow direction is from south-west to north-east. The groundwater head fluctuation between the monsoon and the summer seasons was observed to be 2 m, it is also witnessed that groundwater is contributing more to rivers in the monsoon season in comparison with other seasons. Impact of reduction in pumping on groundwater heads was also investigated, considering a 10% reduction in groundwater withdrawal. The results indicated an overall head rise of 2 m in the southern part and 0.2–0.5 m in the middle and northern part of the district.

    Citation: Sumant Kumar, Anuj Kumar Dwivedi, Chandra Shekhar Prasad Ojha, Vinod Kumar, Apourv Pant, P. K. Mishra, Nitesh Patidar, Surjeet Singh, Archana Sarkar, Sreekanth Janardhanan, C. P. Kumar, Mohammed Mainuddin. Numerical groundwater modelling for studying surface water-groundwater interaction and impact of reduced draft on groundwater resources in central Ganga basin[J]. Mathematical Biosciences and Engineering, 2022, 19(11): 11114-11136. doi: 10.3934/mbe.2022518

    Related Papers:

  • Water resources in India's Indo-Gangetic plains are over-exploited and vulnerable to impacts of climate change. The unequal spatial and temporal variation of meteorological, hydrological and hydrogeological parameters has created additional challenges for field engineers and policy planners. The groundwater and surface water are extensively utilized in the middle Gangetic plain for agriculture. The primary purpose of this study is to understand the discharge and recharge processes of groundwater system using trend analysis, and surface water and groundwater interaction using groundwater modelling. A comprehensive hydrological, and hydrogeological data analysis was carried out and a numerical groundwater model was developed for Bhojpur district, Bihar, India covering 2395 km2 geographical area, located in central Ganga basin. The groundwater level data analyses for the year 2018 revealed that depth to water level varies from 3.0 to 9.0 meter below ground level (m bgl) in the study area. The M-K test showed no significant declining trend in the groundwater level in the study area. The groundwater modelling results revealed that groundwater head is higher in the southern part of the district and the groundwater flow direction is from south-west to north-east. The groundwater head fluctuation between the monsoon and the summer seasons was observed to be 2 m, it is also witnessed that groundwater is contributing more to rivers in the monsoon season in comparison with other seasons. Impact of reduction in pumping on groundwater heads was also investigated, considering a 10% reduction in groundwater withdrawal. The results indicated an overall head rise of 2 m in the southern part and 0.2–0.5 m in the middle and northern part of the district.



    加载中


    [1] R. Kumar, R. D. Singh, K. D. Sharma, Water resources of India, Curr. Sci., 89 (2005), 794–811. https://www.jstor.org/stable/24111024
    [2] M. K. Goyal, R. Y. Surampalli, Impact of climate change on water resources in India, J. Environ. Eng., 144 (2018), 04018054. https://doi.org/10.1061/(ASCE)EE.1943-7870.0001394 doi: 10.1061/(ASCE)EE.1943-7870.0001394
    [3] K. Rudra, Combating flood and erosion in the lower ganga plain in India: some unexplored issues, in Disaster Studies, (2020), 173–186. https://doi.org/10.1007/978-981-32-9339-7_9
    [4] T. Oki, S. Kanae, Global hydrological cycles and world water resources, Science, 313 (2006), 1068–1072. https://doi.org/10.1126/science.1128845 doi: 10.1126/science.1128845
    [5] C. K. Pawe, A. Saikia, Unplanned urban growth: land use/land cover change in the Guwahati Metropolitan Area, India, Geografisk Tidsskrift-Danish J. Geogr., 118 (2018), 88–100. https://doi.org/10.1080/00167223.2017.1405357 doi: 10.1080/00167223.2017.1405357
    [6] S. Chaudhuri, D. Parakh, M. Roy, H. Kaur, Groundwater-sourced irrigation and agro-power subsidies: Boon or bane for small/marginal farmers in India? Groundwater Sustainable Dev., 15 (2021), 100690. https://doi.org/10.1016/j.gsd.2021.100690 doi: 10.1016/j.gsd.2021.100690
    [7] J. Timsina, D. J. Connor, Productivity and management of rice–wheat cropping systems: issues and challenges, Field crops Res., 69 (2001), 93–132. https://doi.org/10.1016/S0378-4290(00)00143-X doi: 10.1016/S0378-4290(00)00143-X
    [8] N. Subash, M. Shamim, V. K. Singh, B. Gangwar, B. Singh, D. S. Gaydon, et al., Applicability of APSIM to capture the effectiveness of irrigation management decisions in rice-based cropping sequence in the Upper-Gangetic Plains of India, Paddy Water Environ., 13 (2015), 325–335. https://doi.org/10.1007/s10333-014-0443-1 doi: 10.1007/s10333-014-0443-1
    [9] J. R. Stevenson, N. Villoria, D. Byerlee, T. Kelley, M. Maredia, Green Revolution research saved an estimated 18 to 27 million hectares from being brought into agricultural production, Proc. Natl. Acad. Sci., 110 (2013), 8363–8368. https://doi.org/10.1073/pnas.1208065110 doi: 10.1073/pnas.1208065110
    [10] M. Kabir, M. Salam, A. Chowdhury, N. Rahman, K. Iftekharuddaula, M. Rahman, et al., Rice vision for Bangladesh: 2050 and beyond, Bangladesh Rice J., 19 (2015), 1–18. https://doi.org/10.3329/brj.v19i1.25213 doi: 10.3329/brj.v19i1.25213
    [11] M. Bazilian, H. Rogner, M. Howells, S. Hermann, D. Arent, D. Gielen, et al., Considering the energy, water and food nexus: Towards an integrated modelling approach, Energy policy, 39 (2011), 7896–7906. https://doi.org/10.1016/j.enpol.2011.09.039 doi: 10.1016/j.enpol.2011.09.039
    [12] S. Valley, Groundwater Availability of the Central Valley Aquifer, California, 2009. Available from: https://www.researchgate.net/profile/Claudia-Faunt/publication/255565139_Groundwater_Availability_of_the_Central_Valley_Aquifer/links/549197390cf269b0486165f4/Groundwater-Availability-of-the-Central-Valley-Aquifer.pdf.
    [13] Z. Sheng, Impacts of groundwater pumping and climate variability on groundwater availability in the Rio Grande Basin, Ecosphere, 4 (2013), 1–25. https://doi.org/10.1890/ES12-00270.1 doi: 10.1890/ES12-00270.1
    [14] T. Jafari, S. Javadi, A. S. Kiem, Integrated simulation of surfacewater-groundwater (SW-GW) interactions using SWAT-MODFLOW (Case study: Shiraz Basin, Iran), in Riverine Systems, (2022), 113–131. https://doi.org/10.1007/978-3-030-87067-6_7
    [15] S. Kumar, S. Singh, Forecasting groundwater level using hybrid modelling technique, in Management of Natural Resources in a Changing Environment, (2015), 93–98. https://doi.org/10.1007/978-3-319-12559-6_6
    [16] S. Kumar, V. Kumar, R. Saini, N. Pant, R. Singh, A. Singh, et al., Floodplains landforms, clay deposition and irrigation return flow govern arsenic occurrence, prevalence and mobilization: A geochemical and isotopic study of the mid-Gangetic floodplains, Environ. Res., 201 (2021), 111516. https://doi.org/10.1016/j.envres.2021.111516 doi: 10.1016/j.envres.2021.111516
    [17] H. Tabari, J. Nikbakht, B. S. Somee, Investigation of groundwater level fluctuations in the north of Iran, Environ. Earth Sci., 66 (2012), 231–243. https://doi.org/10.1007/s12665-011-1229-z doi: 10.1007/s12665-011-1229-z
    [18] F. D. Vousoughi, Y. Dinpashoh, M. T. Aalami, D. Jhajharia, Trend analysis of groundwater using non-parametric methods (Case study: Ardabil plain), Stochastic Environ. Res. Risk Assess., 27 (2013), 547–559. https://doi.org/10.1007/s00477-012-0599-4 doi: 10.1007/s00477-012-0599-4
    [19] D. Machiwal, M. K. Jha, Characterizing rainfall–groundwater dynamics in a hard-rock aquifer system using time series, geographic information system and geostatistical modelling, Hydrol. Processes, 28 (2014), 2824–2843. https://doi.org/10.1002/hyp.9816 doi: 10.1002/hyp.9816
    [20] L. Ribeiro, N. Kretschmer, J. Nascimento, A. Buxo, T. Rotting, G. Soto, et al., Evaluating piezometric trends using the Mann-Kendall test on the alluvial aquifers of the Elqui River basin, Chile, Hydrol. Sci. J., 60 (2015), 1840–1852. https://doi.org/10.1080/02626667.2014.945936 doi: 10.1080/02626667.2014.945936
    [21] D. R. Helsel, R. M. Hirsch, Statistical Methods in Water Resources, 1992.
    [22] S. Yue, P. Pilon, G. Cavadias, Power of the Mann–Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series, J. Hydrol., 259 (2002), 254–271. https://doi.org/10.1016/S0022-1694(01)00594-7 doi: 10.1016/S0022-1694(01)00594-7
    [23] S. Yue, C. Y. Wang, Applicability of pre whitening to eliminate the influence of serial correlation on the Mann-Kendall test, Water Resour. Res., 38 (2002). https://doi.org/10.1029/2001WR000861 doi: 10.1029/2001WR000861
    [24] S. Yue, P. Pilon, Interaction between deterministic trend and autoregressive process, Water Resour. Res., 39 (2003). https://doi.org/10.1029/2001WR001210 doi: 10.1029/2001WR001210
    [25] K. Adamowski, J. Bougadis, Detection of trends in annual extreme rainfall, Hydrol. Processes, 17 (2003), 3547–3560. https://doi.org/10.1002/hyp.1353 doi: 10.1002/hyp.1353
    [26] M. G. Kendall, J. Gibbons, Rank Correlation Methods, 1970.
    [27] K. H. Hamed, A. R. Rao, A modified Mann-Kendall trend test for autocorrelated data, J. Hydrol., 204 (1998), 182–196. https://doi.org/10.1016/S0022-1694(97)00125-X doi: 10.1016/S0022-1694(97)00125-X
    [28] C. R. Fitts, Groundwater Science, Elsevier, 2002.
    [29] M.G. McDonald, A. W. Harbaugh, A Modular Three-Dimensional Finite-Difference Ground-Water Flow Model, US Geological Survey, 1988.
    [30] M. P. Anderson, W. W. Woessner, R. J. Hunt, Applied groundwater modeling: simulation of flow and advective transport, Academic press, 2015.
    [31] CGWB, Groundwater Information Booklet: Bhojpur District, Bihar, Central Ground Water Board, Ministry of Water Resources, RD & GR. Government of India: New Delhi, India, 2013. Available from: http://cgwb.gov.in/District_Profile/Bihar/Bhojpur.pdf.
    [32] S. Kumar, M. Kumar, V. K. Chandola, V. Kumar, R. K. Saini, N. Pant, et al., Groundwater quality issues and challenges for drinking and irrigation uses in central Ganga Basin Dominated with rice-wheat cropping system, Water, 13 (2021), 2344. https://doi.org/10.3390/w13172344 doi: 10.3390/w13172344
    [33] CGWB, National Aquifer Mapping, parts of Bhojpur and Buxar districts, Bihar, Central Ground Water Board, Ministry of Water Resources, RD & GR. Government of India: New Delhi, India, 2016. Available from: http://cgwb.gov.in/AQM/NAQUIM_REPORT/Bihar/Parts%20of%20Bhojpur%20and%20Buxar%20Districts.pdf.
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(2466) PDF downloads(183) Cited by(2)

Article outline

Figures and Tables

Figures(15)  /  Tables(6)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog