Assessing Groundwater Resource Vulnerability by Coupling GIS-Based DRASTIC and Solute Transport Model in Ajmer District, Rajasthan

Authors

  • G.B. Pant University of Agriculture and Technology, Pantnagar – 263 145
  • Department of Hydrology, Indian Institute of Technology Roorkee, Roorkee – 247 667

DOI:

https://doi.org/10.1007//s12594-018-0958-y

Abstract

Groundwater aquifer vulnerability has been assessed by incorporating the major geological and hydrogeological factors that affect and control the groundwater contamination using GIS-based DRASTIC model along with solute transport modeling. This work demonstrates the potential of GIS to derive a vulnerability map by overlying various spatially referenced digital data layers (i.e., depth to water, net recharge, aquifer media, soil media, topography, the impact of vadose zone and hydraulic conductivity) that portrays cumulative aquifer sensitivity ratings in Kishangarh, Rajasthan. It provides a relative indication of groundwater aquifer vulnerability to contamination. The soil moisture flow and solute transport regimes of the vadose zone associated with specific hydrogeological conditions play a crucial role in pollution risk assessment of the underlying groundwater resources. An effort has been made to map the vulnerability of shallow groundwater to surface pollutants of thestudy area, using soil moisture flow and contaminant transport modeling. The classical advection-dispersion equation coupled with Richard's equation is numerically simulated at different point locations for assessing the intrinsic vulnerability of the valley. The role of soil type, slope, and the land-use cover is considered for estimating the transient flux at the top boundary from daily precipitation and evapotranspiration data of the study area. The time required by the solute peak to travel from the surface to the groundwater table at the bottom of the soil profile is considered as an indicator of avulnerability index. Results show a high vulnerability in the southern region, whereas low vulnerability is observed in the northeast and northern parts. The results have recognized four aquifer vulnerability zones based on DRASTIC vulnerability index (DVI), which ranged from 45 to 178. It has been deduced that approximately 18, 25, 34, and 23% of the area lies in negligible, low, medium and high vulnerability zones, respectively. The study may assist in decision making related to theplanning of industrial locations and the sustainable water resources development of the selected semi-arid area.

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Section

Research Articles

Published

2018-07-09

How to Cite

Joshi, P., & Gupta, P. K. (2018). Assessing Groundwater Resource Vulnerability by Coupling GIS-Based DRASTIC and Solute Transport Model in Ajmer District, Rajasthan. Journal of Geological Society of India, 92(1), 101–106. https://doi.org/10.1007//s12594-018-0958-y

References

Akhtar, M. M. and Tang, Z. (2014) Evaluation of local groundwater vulnerability based on DRASTIC index method in Lahore, Pakistan. Geofisica Internat., v. 54(1), pp. 67-81.

Albinet, M. and Margat, J. (1970) Cartographie de la vulnérabilité í la pollution des nappes d'eau souterraines. (Mapping aquifer vulnerability to pollution) in French. Bull. BRGM, v. 2(3-4), pp. 13-22.

Aller, L., Bennet, T., Leher, J.H., Petty, R.J. and Hackett, G. (1987) DRASTIC: A standardized system for evaluating groundwater pollution potential using hydro geologicalsetting. EPA, v. 600/2-87-035:622.

American Public Health Association (APHA) (1985) Standard methods for the examination of water and waste. 16th ed. Amer. Public Health Assoc., Washington.

Bai, L., Wang, Y. and Meng, F. (2012) Application of DRASTIC and extension theory in the groundwater vulnerability evaluation. Water and Environ. Jour., v. 26(3), pp. 381-391.

Browen, E., Skougstad and Fishman, M.J. (1974) Method for Collection and Analysis of Water Samples for Dissolved Mineral and Gasses. US Govt. Printing Office, Washington.

Datta, K.K. and Jong, C de. (2002) Adverse effect of waterlogging and soil salinity on crop and land productivity in the North-west region of Haryana, India. Agri. Water Managmt., v. 57, pp. 223-38.

Insaf, S.B., Mohamed, A.A. M., Tetsuya, H. and Kikuo, K. (2005) A GISbased DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan. Sci. Total Environ., v. 345(1-3), pp. 127-140.

Javadi, K.N. (2011) Modification of DRASTIC model to map groundwater vulnerability to pollution using nitrate measurements in agricultural areas. Jour Agri. Sci. Tech., v. 13, pp. 239-249.

Kaliraj, S., Chandrasekar, N., Simon Peter, T., Selvakumar, S. and Magesh, N.S. (2015) Mapping of coastal aquifer vulnerable zone in the south west coast of Kanyakumari, South India, using GIS-based DRASTIC model. Environ. Monit. Assess., v. 187, pp. 4073.

Kim, Y.J. and Hamm, S. (1999) Assessment of the potential for groundwater contamination using DRASTIC/EGIS technique, Cheonghu area, South Korea. Hydrol. Jour., v. 7, pp. 227-235.

Mamadou, S. and Zhonghua, T. (2010) Assessment of groundwater pollution potential of the Datong Basin, Northern China. Jour. Sustainable Develop., v. 3(2), pp. 140-152.

Mondal N.C., Saxena v. K. and Singh v. S. (2005) Assessment of groundwater pollution due to tanneries in and around Dindigul, Tamil Nadu, India. Environ. Geol., v. 48(2), pp. 149-157.

Mondal, N.C. and Singh, v. P. (2011) Hydrochemical analysis of salinization for a tannery belt in Southern India. Jour. Hydrol., v. 405(2-3), pp. 235-247.

Mondal, N.C., Singh, v. P., Singh, S. and Singh, v. S. (2011) Hydrochemical characteristic of coastal aquifer from Tuticorin, Tamil Nadu, India. Environ. Monit. Assess., v. 175(1-4), pp. 531-550.

Moulton, D.L. (1992) DRASTIC analysis of the potential for groundwater pollution in Pinal County. Arizona. Arizona Geol. Surv. , 11 Sheets, 67p.

Prasad, K. and Shukla, J.P. (2014) Assessment of groundwater vulnerability using GIS- based DRASTIC technology for the basaltic aquifer of Burhner watershed, Mohgaon block, mandla (India). Curr. Sci., v. 107(10), pp. 1649-1656.

Prasad, R.K., Mondal, N.C., Banerjee, P., Nandakumar, M.v. and Singh, v. S. (2008) Deciphering potential groundwater zone in hard rock through the application of GIS. Environ. Geol., v. 55(3), pp. 467-475.

Prasad, R.K., Singh, v. S., Krishnamacharyulu, S.K. andBanerjee, P. (2011) Application of DRASTIC model and GIS: for assessing vulnerability in hard rock granitic aquifer. Environ. Monit. Assess., v. 176, pp. 143-155.

Public Works Department (PWD) (2000) Groundwater perspective-a profile of Dindigul District, Tamil Nadu. Chennai, India. p. 102.

Salwa, S., Salem, B. and Hamed, B.D. (2011) Sensitivity analysis in groundwater vulnerability assessment based on GIS in the mahdiaKsourEssaf aquifer, Tunisia: a validation study. Jour. Hydrol. Sci., v. 56(2), pp. 288-304.

Singh, v. S., Mondal, N.C., Ron Barker, Thangarajan, M., Rao, T.v. and Subramaniyam, K. (2003) Assessment of groundwater regime in Kodaganar river basin (Dindigul district), Tamil Nadu. Tech. Rept. No. NGRI-2003-GW-269, p. 104.

Stigter, T.Y., Ribeiro, L. and Dill, A.(2006) Evaluation of an intrinsic and a specific vulnerability assessment method in comparison with ground-water stalinization and nitrate contamination levels in two agricultural regions in the South of Portugal. Hydrol. Jour., v. 14(1–2), pp. 79–99.

Tirkey, K., Gorai, A.K. and Iqbal, K. (2013) AHP- GIS based DRASTIC model for groundwater vulnerability to pollution assessment: A case study of Hazaribag district, Jharkhand, India. Internat. Jour. Environ. Protec., v. 2(3), pp. 20-31.

Wolters, T., Koch, M. andRahimian, M. (2014) Groundwater vulnerability assessment of a metropolitan area using an adapted approach of the DRASTIC- and SINTACS-index model. In: Proc. 11th Internat. Conf. Hydroscience & Engineering, ICHE Hamburg 2014, R. Lehfeldt and R. Kopmann (Eds.), Hamburg, Germany, pp. 337-345.

World Health Organization (WHO) (1984) Guideline of drinking quality. World Health Organization, Washington.