Skip to main content

Advertisement

SpringerLink
Log in

Can Groundwater Scenarios Be Predicted from Future Regional Climatic Input Variables?

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

Conjunctive use of water is an integral part of water resources management. Future groundwater scenarios will dictate the water management policies. The present research focuses on future groundwater scenario generation based on regional scale CMIP5 data. The future scenarios for the years 2030, 2050 and 2080 were generated in terms of the groundwater potential zones (GWPZs) with seven futuristic parameters [land use and land cover, maximum temperature, minimum temperature, rainfall, groundwater recharge, groundwater table and evapotranspiration (ET)]. The Dyna-CLUE and MIROC5 were used for generation of the future change in climate and land use/land cover scenarios. The Soil and Water Assessment Tool (SWAT) was utilized for the recharge and ET estimation. Future groundwater heads were calculated by using the Modular Three-Dimensional Finite-Difference Groundwater Flow (MODFLOW). Bias corrected rainfall and temperature data of Representative Concentration Pathways (RCP 4.5) were utilized. Total twelve water quality parameters (pH, Cl−, Mg2+, F−, Na+, EC, TH, HCO3−, K+, Ca2+, SO42− and PO42−) were used for groundwater quality zone (GWQZ) mapping. These GWPZ and GWQZ were divided into three (poor potential, moderate potential, and good potential) and four zones (good quality, moderate quality, poor quality and above permissible limit) respectively. The lower part of the basin was identified as poor GWPZ (35.76% for 2030) and GWQZ due to an increase in urban areas. However, the middle and upstream portion covers good, moderate zones. Field-based soil moisture and groundwater level monitoring data were utilized for validation purposes. It was observed that groundwater level < 5 m bgl corresponds to good GWPZ. It was also observed that recharge and pH were the crucial parameters for good GWPZ (+11.83%) and GWQZ (−21.31%) according to sensitivity analysis.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Achu AL, Thomas J, Reghunath R (2020) Multi-criteria decision analysis for delineation of groundwater potential zones in a tropical river basin using remote sensing, GIS and analytical hierarchy process (AHP). Groundw Sustain Dev, 100365

  • Alonso J, Lamata T (2006) Consistency in the analytic hierarchy process: a new approach. Int J Uncertainty Fuzziness Knowledge Based Syst 14(4):445–459

    Article  Google Scholar 

  • Amineh ZBA, Hashemian SJAD, Magholi A (2017) Integrating Spatial Multi Criteria Decision Making (SMCDM) with Geographic Information Systems (GIS) for delineation of the most suitable areas for aquifer storage and recovery (ASR). J of hydro 551:577–595.

  • Bathrellos GD, Gaki-Papanastassiou K, Skilodimou HD, Papanastassiou D, Chousianitis KG (2012) Potential suitability for urban planning and industry development using natural hazard maps and geological–geomorphological parameters. Environ Earth Sci 66(2):537–548

    Article  Google Scholar 

  • Bathrellos GD, Skilodimou HD, Chousianitis K, Youssef AM, Pradhan B (2017) Suitability estimation for urban development using multi-hazard assessment map. Sci Total Environ 575:119–134

    Article  Google Scholar 

  • Chen W, Li H, Hou E, Wang S, Wang G, Panahi M, Xiao L (2018) GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models. Sci Total Environ 634:853–867

    Article  Google Scholar 

  • Das B, Pal SC (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

    Article  Google Scholar 

  • De Andreis S, Ricci PE (2005) Modelling population growth vialaguerre-type exponentials. Math Comput Model 42(13):1421–1428

    Article  Google Scholar 

  • Dhanasekarapandian M, Chandran S, Devi DS, Kumar V (2016) Spatial and temporal variation of groundwater quality and its suitability for irrigation and drinking purpose using GIS and WQI in an urban fringe. J Afr Earth Sci 124:270–288

    Article  Google Scholar 

  • Dhar A, Sahoo S, Sahoo M (2015) Identification of groundwater potential zones considering water quality aspect. Environ Earth Sci 74(7):5663–5675

    Article  Google Scholar 

  • Fang GH, Yang J, Chen YN, Zammit C (2015) Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China. Hydrol Earth Syst Sci 19(6):2547–2559

    Article  Google Scholar 

  • Freeze RA, Cherry JA (1979) Groundwater, 604 pp.

  • Fukunaga DC, Cecilio RA, Zanetti SS, Oliveira LT, Caiado MAC (2015) Application of the SWAT hydrologic model to a tropical watershed at Brazil. Catena 125:206–213

    Article  Google Scholar 

  • Guzman JA, Moriasi DN, Gowda PH, Steiner JL, Starks PJ, Arnold JG, Srinivasan R (2015) A model integration framework for linking SWAT and MODFLOW. Environ Modelling & Software, 73:103–116.

  • Harbaugh A W (2005) MODFLOW-2005, the US geological survey modular ground-water model: the ground-water flow process (p. 253). Reston, VA: US Department of the Interior, US Geol Surv

  • Jasrotia AS, Ajay KT, Upasna A, Baghwan DB (2018) Geoinformatics based groundwater quality assessment for domestic and irrigation uses of the Western Doon valley, Uttarakhand, India. Groundw for Sustain Dev 6:200–212

  • Kim KH, Cho J, Lee YH, Lee WS (2015) Predicting potential epidemics of rice leaf blast and sheath blight in South Korea under the RCP 4.5 and RCP 8.5 climate change scenarios using a rice disease epidemiology model, EPIRICE. Agric For Meteorol 203:191–207

    Article  Google Scholar 

  • Kumar A, Pandey AC (2016) Geoinformatics based groundwater potential assessment in hard rock terrain of Ranchi urban environment, Jharkhand state (India) using MCDM–AHP techniques. Groundw Sustain Dev 2:27–41

    Article  Google Scholar 

  • Kwon TS, Lee CM (2015) Prediction of abundance of ants according to climate change scenarios RCP 4.5 and 8.5 in South Korea. J Asia Pac Biodiv 8(1):49–65

    Article  Google Scholar 

  • Maheswaran R, Khosa R, Gosain AK, LahariS SSK, Chahar BR, Dhanya CT (2016) Regional scale groundwater modelling study for Ganga River basin. J Hydrol 541:727–741

    Article  Google Scholar 

  • Mahmoud HH, Kotb ADM (2017) Impact of the geological structures on the groundwater potential using geophysical techniques in west BaniMazar area, El Minia–Western Desert, Egypt. J Afr Earth Sci 130:161–173

    Article  Google Scholar 

  • Mechal A, Wagner T, Birk S (2015) Recharge variability and sensitivity to climate: the example of GidaboRiver Basin, Main Ethiopian rift. J Hydrol Reg Stud 4:644–660

    Article  Google Scholar 

  • Mogaji KA, San Lim H (2018) Application of Dempster-Shafer theory of evidence model to geoelectric and hydraulic parameters for groundwater potential zonation. NRIAG J Astron Geophys,

  • Naghibi SA, Moghaddam DD, Kalantar B, Pradhan B, Kisi O (2017) A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping. J Hydrol 548:471–483

    Article  Google Scholar 

  • Nampak H, Pradhan B, Manap MA (2014) Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. J Hydrol 513:283–300

    Article  Google Scholar 

  • Panagopoulos GP, Bathrellos GD, Skilodimou HD, Martsouka FA (2012) Mapping urban water demands using multi-criteria analysis and GIS. Water Resour Manag 26(5):1347–1363

    Article  Google Scholar 

  • Prasad YS, Rao BV (2018) Groundwater depletion and groundwater balance studies of KandivalasaRiverSubBasin, Vizianagaram District, Andhra Pradesh, India. Groundw Sustain Dev 6:71–78

    Article  Google Scholar 

  • Rahmati O, Pourghasemi HR, Melesse AM (2016) Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: a case study at Mehran region, Iran. Catena 137:360–372

    Article  Google Scholar 

  • Raju KS, Sonali P, Kumar DN (2017) Ranking of CMIP5-based global climate models for India using compromise programming. Theor Appl Climatol 128(3–4):563–574

    Article  Google Scholar 

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

    Google Scholar 

  • Sahoo S, Sil I, Dhar A, Debsarkar A (2018) Das P Kar a (2018) future scenarios of land-use suitability modeling for agricultural sustainability in a river basin. J Clean Prod 205:313–328

    Article  Google Scholar 

  • Sahoo S, Dey S, Dhar A, Debsarkar A, Pradhan B (2019a) On projected hydrological scenarios under the influence of bias-corrected climatic variables and LULC. Ecol Indic 106:105440

    Article  Google Scholar 

  • Sahoo S, Dhar A, Debsarkar A, Kar A (2019b) Future scenarios of environmental vulnerability mapping using grey analytic hierarchy process. Nat Resour Res 28(4):1461–1483

    Article  Google Scholar 

  • Sakai N, Mohamad ZF, Nasaruddin A, Kadir SNA, Salleh MSAM, Sulaiman AH (2018) Eco-heart index as a tool for community-based water quality monitoring and assessment. Ecol Indic 91:38–46

    Article  Google Scholar 

  • Velasco V, Tubau I, Vázquez-Suñè E, Gogu R, Gaitanaru D, Alcaraz M, Sanchez-Vila X (2014) GIS-based hydrogeochemical analysis tools (QUIMET). Comput Geosci 70:164–180

    Article  Google Scholar 

  • Verburg PH, Soepboer W, Veldkamp A, Limpiada R, Espaldon V, Mastura SS (2002) Modeling the spatial dynamics of regional land use: the CLUE-S model. Environ Manag 30(3):391–405

    Article  Google Scholar 

  • Wei X, Bailey RT, Records RM, Wible TC, Arabi M (2018) Comprehensive simulation of nitrate transport in coupled surface-subsurface hydrologic systems using the linked SWAT-MODFLOW-RT3D model. Environ Model Softw

  • Zahedi S (2017) Modification of expected conflicts between drinking water quality index and irrigation water quality index in water quality ranking of shared extraction wells using multi criteria decision making techniques. Ecol Indic 83:368–379

    Article  Google Scholar 

  • Zaidi FK, Nazzal Y, Ahmed I, Naeem M, Jafri MK (2015) Identification of potential artificial groundwater recharge zones in northwestern Saudi Arabia using GIS and Boolean logic. J Afr Earth Sci 111:156–169

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Ecology & Environment Studies, Nalanda University, Bihar, Rajgir, 803116, India

    Satiprasad Sahoo

  2. Department of Civil Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India

    Anirban Dhar

  3. Department of Civil Engineering, Jadavpur University, Kolkata, India

    Anupam Debsarkar

  4. Superintending Hydrogeologist, Central Ground Water Board, Kolkata, India

    Amlanjyoti Kar

Authors
  1. Satiprasad Sahoo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anirban Dhar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Anupam Debsarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amlanjyoti Kar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Satiprasad Sahoo.

Ethics declarations

Conflict of Interest

No conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sahoo, S., Dhar, A., Debsarkar, A. et al. Can Groundwater Scenarios Be Predicted from Future Regional Climatic Input Variables?. Water Resour Manage 34, 4815–4830 (2020). https://doi.org/10.1007/s11269-020-02692-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-020-02692-4

Keywords

Search

Navigation