Assessment of Vulnerability in the Gonabad Plain using the DRASTIC Model

Document Type : Original Article

Authors

Department of Water and Environmental Engineering, Faculty of Civil Engineering, Shahrood University of Technology, Iran.

Abstract

Groundwater serves as a vital resource for agricultural, domestic, and industrial purposes, particularly in arid and semi-arid regions. The increasing pressure on groundwater resources, driven by population growth, climate change, and overexploitation, has rendered them increasingly susceptible to contamination from anthropogenic activities. Excessive use of chemical fertilizers in agriculture, improper disposal of urban and industrial wastewater, and leakage of pollutants from various sources are among the primary contributors to groundwater pollution. Assessing the vulnerability of these resources is essential for ensuring their quality and sustainability. Using the DRASTIC model, this study evaluates the groundwater vulnerability of the Gonabad Plain, situated in Khorasan Razavi Province, Iran. This model incorporates seven hydrogeological parameters: depth to the water table, net recharge, aquifer media, soil media, topography, unsaturated zone, and hydraulic conductivity. The DRASTIC index calculated for the study area ranges from 63 to 193. According to the results, the pollution risk levels in the region were classified as follows: 0.65% of the area had no pollution risk, 2.06% was categorized as very low risk, 21.67% as low risk, 34.62% as low to moderate risk, 33.52% as moderate to high risk, 6.66% as high risk, 0.8% as very high risk, and 0.006% was identified as thoroughly contaminated areas. The increased vulnerability index observed in the northern parts of the plain can be attributed to factors such as a shallower water table, gentle slopes (less than 2%), and coarse-grained soils in both the aquifer and the unsaturated zone. To validate the vulnerability assessment, nitrate concentration data from wells in the region, collected in 2021, were analyzed. The findings confirmed the accuracy of the DRASTIC model in identifying areas vulnerable to landslides. This study underscores the importance of localized assessments of groundwater vulnerability. It emphasizes the need for targeted management and monitoring strategies in high-risk regions to mitigate pollution and ensure the long-term sustainability of groundwater resources.

Keywords


Agyare, A., Anornu, G. K., & Kabo-bah, A. T. (2017). Assessing the vulnerability of aquifer systems in the Volta river basin: a case-study on Afram Plains, Ghana. Modeling Earth Systems and Environment, 3, 1141-1159.
Amir Ahmadi, A., Ebrahimi, M., Zanganeh, M., & Akbari, E. (2013). Investigation of  DRASTIC model on GIS. Journal of Geography and Environmental Hazards, 2(6), 37-56.
Ascott, M., Gooddy, D. C., Wang, L., Stuart, M. E., Lewis, M., Ward, R., & Binley, A. M. (2017). Global patterns of nitrate storage in the vadose zone. Nature Communications, 8(1), 1416.
Asghari Moghddam, A., Fakhri, M. S., & Najib, M. (2016). Zoning of Groundwater Pollution Potential of Marand Plain Aquifer Using from AVI, DRASTIC and Methods at GIS Environment. Journal of Geography and Planning, 19(54), 19-41.
Aslam, R. A., Shrestha, S., & Pandey, V. P. (2018). Groundwater vulnerability to climate change: A review of the assessment methodology. Science of the Total Environment, 612, 853-875.
Bentekhici, N., Benkesmia, Y., Bouhlala, M. A., Saad, A., & Ghabi, M. (2024). Mapping and assessment of groundwater pollution risks in the main aquifer of the Mostaganem plateau (Northwest Algeria): utilizing the novel vulnerability index and decision tree model. Environmental Science and Pollution Research, 31(32), 45074-45104.
Daly, D., Dassargues, A., Drew, D., Dunne, S., Goldscheider, N., Neale, S., Popescu, I., & Zwahlen, F. (2002). Main concepts of the" European approach" to karst-groundwater-vulnerability assessment and mapping. Hydrogeology Journal, 10, 340-345.
Gogu, R. C., & Dassargues, A. (2000). Current trends and future challenges in groundwater vulnerability assessment using overlay and index methods. Environmental geology, 39, 549-559.
Hosseiny, S. H., Bozorg-Haddad, O., & Bocchiola, D. (2021). Water, culture, civilization, and history. In Economical, Political, and Social Issues in Water Resources (pp. 189-216). Elsevier.
Li, B., Yang, Z., & Xu, X. (2019). Examining China's water pressure from industrialization driven by consumption and export during 2002–2015. Journal of Cleaner Production, 229, 818-827.
Meegoda, J. N., Chande, C., & Bakshi, I. (2025). Biodigesters for Sustainable Food Waste Management. International Journal of Environmental Research and Public Health, 22(3), 382.
Mensah, D. O., Appiah-Adjei, E. K., & Asante, D. (2023). Groundwater pollution vulnerability assessment in the Assin municipalities of Ghana using GIS-based DRASTIC and SINTACS methods. Modeling Earth Systems and Environment, 9(2), 2955-2967.
Mirzaei, S., Naderi Khorasgani, M., Beigi, H., & Mohammadi, G. (2012). Vulnerability assessment of the Shahrekord plain groundwater using DRASTIC model. Iranian Water Researches Journal, 6(2), 143-151.
Nakhaei, M., Amiri, V., & Rahimi-Shahrebabaki, M. (2013). Assessment of groundwater vulnerability and sensitivity analysis in Khatoon Abad aquifer using a GIS based DRASTIC model. Advanced Applied Geology, 3(2), 1-10.
Nakhostin Rouhi, M., Rezaei Moghaddam, M. H., & Rahimpour, T. (2017). Groundwater vulnerability zonation using DRASTIC and SI models in GIS (Case Study: Ajabshir Plain). Iranian journal of Ecohydrology, 4(2), 587-599.
Ouedraogo, I., Defourny, P., & Vanclooster, M. (2018). Application of random forest regression and comparison of its performance to multiple linear regression in modeling groundwater nitrate concentration at the African continent scale. Hydrogeology Journal.
Rama, F., Busico, G., Arumi, J. L., Kazakis, N., Colombani, N., Marfella, L., Hirata, R., Kruse, E. E., Sweeney, P., & Mastrocicco, M. (2022). Assessment of intrinsic aquifer vulnerability at continental scale through a critical application of the drastic framework: The case of South America. Science of the Total Environment, 823, 153748.
Ravindra, K., & Mor, S. (2019). Distribution and health risk assessment of arsenic and selected heavy metals in Groundwater of Chandigarh, India. Environmental pollution, 250, 820-830.
Şener, E. (2023). Appraisal of groundwater pollution risk by combining the fuzzy AHP and DRASTIC method in the Burdur Saline Lake Basin, SW Turkey. Environmental Science and Pollution Research, 30(8), 21945-21969.
Strang, V. (2015). Water: Nature and culture. Reaktion Books.
Taghavi, N., Niven, R. K., Kramer, M., & Paull, D. J. (2023). Comparison of DRASTIC and DRASTICL groundwater vulnerability assessments of the Burdekin Basin, Queensland, Australia. Science of the Total Environment, 858, 159945.
Voudouris, K., Kazakis, N., Polemio, M., & Kareklas, K. (2010). Assessment of intrinsic vulnerability using the DRASTIC model and GIS in the Kiti aquifer, Cyprus. European water, 30(1), 13-24.
Vrba, J., & Zaporozec, A. (1994). Guidebook on mapping groundwater vulnerability.
Wang, J., He, J., & Chen, H. (2012). Assessment of groundwater contamination risk using hazard quantification, a modified DRASTIC model and groundwater value, Beijing Plain, China. Science of the Total Environment, 432, 216-226.
Zhang, Y., Qin, H., An, G., & Huang, T. (2022). Vulnerability assessment of farmland groundwater pollution around traditional industrial parks based on the improved DRASTIC Model—A case study in Shifang City, Sichuan Province, China. International Journal of Environmental Research and Public Health, 19(13), 7600.
Zwahlen, F. (2003). Vulnerability and risk mapping for the protection of carbonate (karst) aquifers. Office for Official Publications of the European Communities Luxembourg.