Abstract
Groundwater is one of the important necessary renewable resources of the world. Without water, no life can be possible on this earth. It is not only sustaining all biotic elements of the earth but also it helps to fulfill the requirement of various sectors like agriculture, industries, and other domestic purposes. Not all types of water but the mineral added purified water is safe for the human being. Unfortunately, in this age of development, it's very difficult to get naturally purified water because of the application of chemical fertilizer to get more production from agriculture, extensive industrialization pollutes groundwater resources badly. So, it’s high time to think about this most valuable resource. In this context, current research aims to identify the most polluted or vulnerable zones of groundwater in the Birbhum district. From several studies, it has been found that Birbhum district is one of the fluoride contaminated districts. Except, fluoride, another chemical component i.e. iron is also another harmful component in this district. Therefore, to assess the most vulnerable groundwater zones DRASTIC model has been applied here. DRASTIC is a widely used model for this purpose. This study deals with how the application of the DRASTIC model can help to extract the vulnerable zones of groundwater. To run the DRASTIC model various parameters viz. Depth to water level, Net recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, and Hydraulic conductivity have been used here. The final vulnerable map shows that the western part is more vulnerable than the eastern part because the western part consists of the plateau fringe area with basalt and granite and more weathering prone that’s why contamination of harmful minerals dissolve with groundwater most quickly. Moreover, the groundwater level is near to surface in the western part due to the presence of hard rocks near the surface than the eastern part. The applied DRASTIC model has been validated using the receiver operating characteristic curve (ROC) and this curve has been prepared based on some random points composed of various harmful chemical components. The result of the receiver operating characteristic curve depicts that this model is 73% valid in this concerned region.
Similar content being viewed by others
References
Adnan S, Iqbal J, Maltamo M, Valbuena R (2018) GIS-based DRASTIC model for groundwater vulnerability and pollution risk assessment in the Peshawar District, Pakistan. Arab J Geosci 11:. https://doi.org/https://doi.org/10.1007/s12517-018-3795-9
Agarwal E, Agarwal R, Garg RD, Garg PK (2013) Delineation of groundwater potential zone: an AHP/ANP approach. J Earth Syst Sci 122:887–898. https://doi.org/10.1007/s12040-013-0309-8
Agyare A, Kwame G, Amos A, Kabo T (2017) Assessing the vulnerability of aquifer systems in the Volta river basin : a case-study on Afram Plains, Ghana. Model Earth Syst Environ 3:1141–1159. https://doi.org/10.1007/s40808-017-0363-3
Ahada CPS, Suthar S (2018) A GIS based DRASTIC model for assessing aquifer vulnerability in Southern Punjab, India. Model Earth Syst Environ 4:635–645. https://doi.org/10.1007/s40808-018-0449-6
Al-Abadi AM, Al-Shammaa AM, Aljabbari MH (2017) A GIS-based DRASTIC model for assessing intrinsic groundwater vulnerability in northeastern Missan governorate, southern Iraq. Appl Water Sci 7:89–101. https://doi.org/10.1007/s13201-014-0221-7
Al-Adamat RAN, Foster IDL, Baban SMJ (2003) Groundwater vulnerability and risk mapping for the Basaltic aquifer of the Azraq basin of Jordan using GIS. Remote Sens DRASTIC 23:303–324. https://doi.org/10.1016/j.apgeog.2003.08.007
Al Farajat M, Al Ansari N, Mashagbeh A, Abou Salah R (2005) Hydrogeophysical and environmental investigation of groundwater potentials in Al Sokhna Alluvium Aquifer in Zarqa - Jordan. J Hydrogeologie und Umwelt 33(7):1–14
Alam F, Umar R, Ahmed S, Dar FA (2012) A new model (DRASTIC-LU) for evaluating groundwater vulnerability in parts of central Ganga Plain, India. Arabian J Geosci. https://doi.org/10.1007/s12517-012-0796-y
Aller L, Bennett T, Lehr JH, Petty R (1986) Potential of hydrogeologic settings by pesticides
Aller L, Bennett T, Lehr JH, et al (1987) DRASTIC : a standardized method for evaluating ground water pollution potential using hydrogeologic settings. NWWA/Epa-600/2-87-035 455
Ar à (2008) A GIS based DRASTIC model for assessing groundwater vulnerability in shallow aquifer in Aligarh. India 28:32–53. https://doi.org/10.1016/j.apgeog.2007.07.008
Brindha K, Elango L (2015) Cross comparison of five popular groundwater pollution vulnerability index approaches. J Hydrol. https://doi.org/10.1016/j.jhydrol.2015.03.003
Chandoul IR, Bouaziz S, Ben DH (2015) Groundwater vulnerability assessment using GIS-based DRASTIC models in shallow aquifer of Gabes North (South East Tunisia). Arab J Geosci 8:7619–7629. https://doi.org/10.1007/s12517-014-1702-6
Das N, Mukhopadhyay S (2020) 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. https://doi.org/10.1007/s10668-018-0227-7
Das N, Mondal P, Ghosh R, Sutradhar S (2019) Groundwater quality assessment using multivariate statistical technique and hydro-chemical facies in Birbhum District, West Bengal. SN Appl Sci. https://doi.org/10.1007/s42452-019-0841-5
de Barros Santiago D, Correia Filho WLF, de Oliveira-Júnior JF, da Silva Junior CA (2019) Mathematical modeling and use of orbital products in the environmental degradation of the Araripe Forest in the Brazilian Northeast. Model Earth Syst Environ 5:1429–1441. https://doi.org/10.1007/s40808-019-00614-x
Delhi NEW (2017) GEC (2015) Ground Water Resource Estimation Committee
District M, Bengal W (2007) Journal of Spatial Hydrology Journal of Spatial Hydrology 7
Dixon B (2005) Groundwater vulnerability mapping: A GIS and fuzzy rule based integrated tool. Appl Geogr 25:327–347. https://doi.org/10.1016/j.apgeog.2005.07.002
Flaxman EW (1988) National water policies. J Prof Issues Eng Educ Pract 114:408–412. https://doi.org/10.1061/(ASCE)1052-3928(1988)114:4(408)
Farajat M Al, Hamdan I, Mohammad AH (2005) GIS mapping of ground water vulnerability against pollution in Amman using GIS mapping of ground water vulnerability against pollution in Amman using DRASTIC index
Foster SRDMM (2002) Groundwater quality protection : a guide for water utilities, municipal authorities, and environment agencies
GEC (2015) Report of the ground water resource estimation committee, ministry of water resources. New Delhi, Government of India
Ghamghami M, Ghahreman N, Olya H, Ghasdi T (2019) Comparison of three multi-site models in stochastic reconstruction of winter daily rainfall over Iran. Model Earth Syst Environ 5:1319–1332. https://doi.org/10.1007/s40808-019-00599-7
Ghosh T, Kanchan R (2016) Aquifer vulnerability assessment in the Bengal alluvial tract, India, using GIS based DRASTIC model. Model Earth Syst Environ 2:1–13. https://doi.org/10.1007/s40808-016-0208-5
Ghosh A, Tiwari AK, Das S (2015) A GIS based DRASTIC model for assessing groundwater vulnerability of Katri Watershed, Dhanbad, India. Model Earth Syst Environ 1:1–14. https://doi.org/10.1007/s40808-015-0009-2
Goldscheider N (2000) The PI method—a GIS-based approach to mapping groundwater vulnerability with special consideration of karst aquifers The PI method—a GIS-based approach to mapping groundwater vulnerability with special consideration of karst aquifers
Hamza MH (2007) A GIS-based DRASTIC vulnerability and net recharge reassessment in an aquifer of a semi-arid region (Metline-Ras Jebel-Raf Raf aquifer, Northern Tunisia). J Environ Mange 84:12–19. https://doi.org/10.1016/j.jenvman.2006.04.004
Herlinger R, Antonio JE, Viero P (2008) Groundwater vulnerability assessment in coastal plain of Rio Grande do Sul State, Brazil, using drastic and adsorption capacity of soils. Environ Geol 54:1799. https://doi.org/10.1007/s00254-008-1334-9
Iqbal J, Pathak G, Gorai AK (2014) Development of hierarchical fuzzy model for groundwater vulnerability to pollution assessment. Arab J Geosci. https://doi.org/10.1007/s12517-014-1417-8
Jasrotia AS, Kumar A, Singh R (2016) Integrated remote sensing and GIS approach for delineation of groundwater potential zones using aquifer parameters in Devak and Rui watershed of Jammu and Kashmir, India. Arab J Geosci 9:1–15. https://doi.org/10.1007/s12517-016-2326-9
Jeannin P-Y, Zwahlen F, Doerfliger N (1999) Water vulnerability assessment in karst environments: a new method of defining protection areas using a multi-attribute approach and GIS tools (EPIK method). Environ Geol 39:165–176
Kaliraj S, Chandrasekar N, Peter TS et al (2015) Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model. Environ Monit Assess. https://doi.org/10.1007/s10661-014-4073-2
Kazakis N, Voudouris KS (2015) Groundwater vulnerability and pollution risk assessment of porous aquifers to nitrate: modifying the DRASTIC method using quantitative parameters. J Hydrol 525:13–25. https://doi.org/10.1016/j.jhydrol.2015.03.035
Khan A, Khan HH, Umar R (2014) An integrated approach for aquifer vulnerability mapping using GIS and rough sets: study from an alluvial aquifer in North India. Hydrogeol J. https://doi.org/10.1007/s10040-014-1147-8
Kozłowski M, Sojka M (2019) Applying a modified DRASTIC model to assess groundwater vulnerability to pollution: a case study in central Poland. Polish J Environ Stud 28:1223–1231. https://doi.org/10.15244/pjoes/84772
Kumar P, Thakur PK, Bansod BKS (2016) Assessment of the effectiveness of DRASTIC in predicting the vulnerability of groundwater to contamination: a case study from Fatehgarh Sahib district in Punjab, India. Environ Earth Sci. https://doi.org/10.1007/s12665-016-5712-4
Lad S, Ayachit R, Kadam A, Umrikar B (2019) Groundwater vulnerability assessment using DRASTIC model: a comparative analysis of conventional, AHP, Fuzzy logic and Frequency ratio method. Model Earth Syst Environ 5:543–553. https://doi.org/10.1007/s40808-018-0545-7
Libanda B, Nkolola NB (2019) Skill of CMIP5 models in simulating rainfall over Malawi. Model Earth Syst Environ 5:1615–1626. https://doi.org/10.1007/s40808-019-00611-0
Mehra M, Oinam B, Singh CK (2016) Integrated assessment of groundwater for agricultural use in Mewat District of Haryana, India using geographical information system (GIS). J Indian Soc Remote Sens 44:747–758. https://doi.org/10.1007/s12524-015-0541-6
Mogaji KA, Lim HS, Abdullar K (2014) Modeling groundwater vulnerability to pollution using optimized DRASTIC model. IOP Conf Ser Earth Environ Sci 20. https://doi.org/10.1088/1755-1315/20/1/012002
Mohammady M, Pourghasemi HR, Pradhan B (2012) Landslide susceptibility mapping at Golestan Province, Iran: A comparison between frequency ratio, Dempster-Shafer, and weights-of-evidence models. J Asian Earth Sci 61:221–236. https://doi.org/10.1016/j.jseaes.2012.10.005
Mukherjee P, Singh CK, Mukherjee S (2012) Delineation of groundwater potential zones in Arid Region of India—a remote sensing and GIS approach. Water Resour Manag 26:2643–2672. https://doi.org/10.1007/s11269-012-0038-9
Murmu P, Kumar M, Lal D et al (2019) Groundwater for sustainable development delineation of groundwater potential zones using geospatial techniques and analytical hierarchy process in Dumka district, Jharkhand. India Groundw Sustain Dev 9:100239. https://doi.org/10.1016/j.gsd.2019.100239
Pathak DR, Hiratsuka A (2011) An integrated GIS based fuzzy pattern recognition model to compute groundwater vulnerability index for decision making. J Hydro-Environ Res 5:63–77. https://doi.org/10.1016/j.jher.2009.10.015
Pradhan B (2013) A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS. Comput Geosci 51:350–365. https://doi.org/10.1016/j.cageo.2012.08.023
Rahman A (2008) A GIS based DRASTIC model for assessing groundwater vulnerability in shallow aquifer in Aligarh, India. Appl Geogr 28(1):32–53. https://doi.org/10.1016/j.apgeog.2007.07.008
Rahmati O, Samani AN (2014) Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS. Arab J Geosci. https://doi.org/10.1007/s12517-014-1668-4
Rundquist DC, Peters AJ, Rodekohr DA et al (1991) Statewide groundwater-vulnerability assessment in nebraska using the drastic/GIS model. Geocarto Int 6:51–58. https://doi.org/10.1080/10106049109354307
Saha D, Alam F (2014) Groundwater vulnerability assessment using DRASTIC and pesticide DRASTIC models in intense agriculture area of the Gangetic plains, India. Environ Monit Assess 186:8741–8763. https://doi.org/10.1007/s10661-014-4041-x
Saravanan S, Parthasarathy KSS, Sivaranjani S (2019) Assessing coastal aquifer to seawater intrusion: application of the GALDIT method to the Cuddalore aquifer. Elsevier Inc, India
Saud MA (2010) Mapping potential areas for groundwater storage in Wadi Aurnah Basin, western Arabian Peninsula, using remote sensing and geographic information system techniques. Hydrogeol J 18:1481–1495. https://doi.org/10.1007/s10040-010-0598-9
Shekhar S, Pandey AC (2015) 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 Int 30:402–421. https://doi.org/10.1080/10106049.2014.894584
Singh A, Sudhir SKS, Govind K (2015) A modified-DRASTIC model ( DRASTICA ) for assessment of groundwater vulnerability to pollution in an urbanized environment in Lucknow, India. Environ Earth Sci 74:5475–5490. https://doi.org/10.1007/s12665-015-4558-5
Sinha MK, Verma MK, Ahmad I et al (2016) Assessment of groundwater vulnerability using modified DRASTIC model in Kharun Basin, Chhattisgarh, India. Arab J Geosci 9:1–22. https://doi.org/10.1007/s12517-015-2180-1
Siva Prasad Y, Venkateswara Rao B (2018) Groundwater recharge estimation studies in a Khondalitic terrain of India. Appl Water Sci 8:1–9. https://doi.org/10.1007/s13201-018-0738-2
Srinivasamoorthy K, Vijayaraghavan K (2011) Assessment of groundwater vulnerability in Mettur region, Tamilnadu, India using drastic and GIS techniques. Arab J Geosci 4:1215–1228. https://doi.org/10.1007/s12517-010-0138-x
Thapa R, Gupta S (2017) Assessment of groundwater potential zones using multi-influencing factor (MIF ) and GIS: a case study from Birbhum district, West Bengal. Appl Water Sci 7:4117–4131. https://doi.org/10.1007/s13201-017-0571-z
Thapa R, Gupta S, Guin S, Kaur H (2018) Sensitivity analysis and mapping the potential groundwater vulnerability zones in Birbhum district, India: a comparative approach between vulnerability models. Water Sci 32:44–66. https://doi.org/10.1016/j.wsj.2018.02.003
Thirumalaivasan SKD (2014) GIS based assessment of groundwater vulnerability using drastic model. Arab J Sci Eng 39:207–216. https://doi.org/10.1007/s13369-013-0843-3
Thirumalaivasan D, Karmegam M, Venugopal K (2003) AHP-DRASTIC: software for specific aquifer vulnerability assessment using DRASTIC model and GIS. Environ Model Softw 18:645–656. https://doi.org/10.1016/S1364-8152(03)00051-3
Tiwari AK, Singh PK, De MM (2016) Evaluation of aquifer vulnerability in a coal mining of India by using GIS-based DRASTIC model. Arab J Geosci 9:1–15. https://doi.org/10.1007/s12517-016-2456-0
Tomer T, Katyal D, Joshi V (2019) Sensitivity analysis of groundwater vulnerability using DRASTIC method: a case study of National Capital Territory, Delhi, India. Groundw Sustain Dev 9:100271. https://doi.org/10.1016/j.gsd.2019.100271
Vadillo I (2004) COST Action 620 Vulnerability and risk mapping for the protection of carbonate (karst ) aquifers Final report Edited by
Van Stempvoort D, Ewert L, Wassenaar L (1993) Aquifer vulnerability index: a gis-compatible method for groundwater vulnerability mapping. Can Water Resour J 18:25–37. https://doi.org/10.4296/cwrj1801025
Wang J, He J, Chen H (2012) Science of the total environment assessment of groundwater contamination risk using hazard quantification, a modified DRASTIC model and groundwater value, Beijing Plain, China. Sci Total Environ 432:216–226. https://doi.org/10.1016/j.scitotenv.2012.06.005
Wu W, Yin S, Liu H, Chen H (2014) Groundwater vulnerability assessment and feasibility mapping under reclaimed water irrigation by a modified DRASTIC model. Water Resour Manag 28:1219–1234. https://doi.org/10.1007/s11269-014-0536-z
Zhao Y, Dong Z, Guo H (2011) Projection pursuit model based on shuffled frog leaping algorithm and its application. 1610–1614
Acknowledgements
The authors are very grateful to Snehasish Dutta for his 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
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ghosh, R., Sutradhar, S., Mondal, P. et al. Application of DRASTIC model for assessing groundwater vulnerability: a study on Birbhum district, West Bengal, India. Model. Earth Syst. Environ. 7, 1225–1239 (2021). https://doi.org/10.1007/s40808-020-01047-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40808-020-01047-7