Aller L, & Thornhill J (1987) DRASTIC: A standardized system for evaluating ground water pollution potential using hydrogeologic settings. Robert S. Kerr Environmental Research Laboratory, Office of Research and Development, US Environmental Protection Agency
Barzegar R, Moghaddam A A, Deo R, Fijani E, & Tziritis E (2018) Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms. Science of the Total Environment 621:697-712
Bera A, Mukhopadhyay B P, & Das S (2022) Groundwater vulnerability and contamination risk mapping of semi-arid Totko river basin, India using GIS-based DRASTIC model and AHP techniques. Chemosphere 307:135831
Civita M (1990) Legenda unificata per le Carte della vulnerabilita dei corpi idrici sotterranei/ Unified legend for the aquifer pollution vulnerability Maps. Studi sulla Vulnerabilita degli Acquiferi
Das A, Maiti S, Naidu S, & Gupta G (2017) Estimation of spatial variability of aquifer parameters from geophysical methods: a case study of sindhudurg district, Maharashtra, India. Stochastic Environmental Research and Risk Assessment 31:1709-1726
Debeljak M, & Džeroski S (2011) Decision trees in ecological modelling. Modelling complex ecological dynamics: An introduction into ecological sodelling for students, teachers & scientists 197:209
Foster S S D (1987) Fundamental concepts in aquifer vulnerability, pollution risk and protection strategy. In Van Dui- Jvenbooden W, Van Waegeningh Hg (eds) Vulnerability of soil and groundwater to pollutants. Proc Inf TNO Comm Hydrol Res, The Hague 38:69–86
Gharekhani M, Nadiri A A, Asghari Moghaddam A, & Sadeghfam S (2021) Investigation of contamination risk using optimized DRASTIC-L method with genetic algorithm in salmas alain Aquifer. Irrigation and Water Engineering 11(4):160-174 (In Persian)
Hosseini F S, Choubin B, Mosavi A, Nabipour N, Shamshirband S, Darabi H, Torabi Haghighi A (2020) Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method. Science of The Total Environment 711:135161
Jafari S M, & Nikoo M R (2016) Groundwater risk assessment based on optimization framework using DRASTIC method. Arabian Journal of Geosciences 9:1-14
Nadiri A A, Aghdam F, Razzagh S, Barzegar R, Jabraili-Andaryan N, & Senapathi V (2022) Using a soft computing OSPRC risk framework to analyze multiple contaminants from multiple sources; A case study from Khoy Plain, NW Iran. Chemosphere 308:136527
Nadiri A A, Gharekhani M, Khatibi R, Sadeghfam S, & Moghaddam A A (2017) Groundwater vulnerability indices conditioned by supervised intelligence committee machine (SICM). Science of the Total Environment 574:691-706
Nadiri A A, Jabraili N, & Gharekhani M (2019) Comparison of different combination methods ability on groundwater vulnerability assessment in Qorveh-Dehgolan palin aquifer. Iranian journal of Ecohydrology 6(3):821-836 (In Persian)
Nadiri A A, Sadeghfam S, Gharekhani M, Khatibi R, & Akbari E (2018) Introducing the risk aggregation problem to aquifers exposed to impacts of anthropogenic and geogenic origins on a modular basis using ‘risk cells’. Journal of Environmental Management 217:654-667
Nadiri A A, Sedghi Z, & Khatibi R (2021) Qualitative risk aggregation problems for the safety of multiple aquifers exposed to nitrate, fluoride and arsenic contaminants by a ‘Total Information Management’framework. Journal of Hydrology 595:126011
Neshat A, Pradhan B, & Javadi S (2015) Risk assessment of groundwater pollution using Monte Carlo approach in an agricultural region: an example from Kerman plain, Iran. Computers, Environment, and Urban Systems 50:66-73
Nobre R C M, Rotunno Filho O C, Mansur W J, Nobre M M M, & Cosenza C A N (2007) Groundwater vulnerability and risk mapping using GIS, modeling and a fuzzy logic tool. Journal of Contaminant Hydrology 94(3-4):277-292
Rajput H, Goyal R, & Brighu U (2020) Modification and optimization of DRASTIC model for groundwater vulnerability and contamination risk assessment for Bhiwadi region of Rajasthan, India. Environmental Earth Sciences 79:1-15
Razzagh S, Nadiri A A, Khatibi R, Sadeghfam S, Senapathi V, & Sekar S (2021) An investigation to human health risks from multiple contaminants and multiple origins by introducing ‘Total Information Management’. Environmental Science and Pollution Research 28:18702-18724
Ribeiro L (2000) Desenvolvimento de um ındice para avaliar a susceptibilidade. ERSHA-CVRM, 1:8
Scanlon BR, Healy R W, & Cook P G (2002) Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeology Journal 10:18–39
Sener E, & Davraz A (2013) Assessment of groundwater vulnerability based on a modified DRASTIC model, GIS and an analytic hierarchy process (AHP) method: The case of Egirdir Lake basin (Isparta, Turkey). Hydrogeology Journal 21(3):701-714
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
Stempvoort D V, Ewert L, & Wassenaar L (1993) Aquifer vulnerability index: a GIS-compatible method for groundwater vulnerability mapping. Canadian Water Resources Journal 18(1):25-37
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
Wang Y, & Witten I H (1996) Induction of model trees for predicting continuous classes. (Working paper 96/23). Hamilton, New Zealand: University of Waikato, Department of Computer Science
Xiong H, Wang Y, Guo X, Han J, MA C, & Zhang X (2022) Current status and future challenges of groundwater vulnerability assessment: A bibliometric analysis. Journal of Hydrology 615:128694
)