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A modified DRASTIC model for groundwater vulnerability assessment using connecting path and analytic hierarchy process methods

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Abstract

Groundwater plays a vital role in supporting water for the different needs of domestic, agricultural, and industrial sectors, and its vulnerability assessment to pollution is a valuable tool for establishing protective and preventive management. DRASTIC is a well-known GIS-based model for assessing groundwater vulnerability to pollution, which uses seven parameters including depth-to-water level, net recharge, aquifer media, soil media, topography, the impact of the vadose zone, and hydraulic conductivity. The predefined weights of DRASTIC parameters have made a barrier to its applicability for different regions with different hydroclimatic conditions. To overcome this problem, it has been suggested to apply analytic hierarchy process (AHP) method for modifying the model by adjusting the weights of the parameters. AHP is a widely used method to elicit experts’ judgments about different involving parameters through constructing pairwise comparison matrixes (PCMs). Since AHP calculates the weights by performing pairwise comparisons between the parameters, achieving consistent comparisons is difficult when the number of parameters increases. The objective of this research is to modify the DRASTIC model by integrating the connecting path method (CPM) and AHP. The proposed methodology involves asking experts to perform a number of pairwise comparisons between the parameters and then construct an incomplete PCM using the obtained information. To complete the missing values in the PCM, CPM is employed. The CPM is an effective approach that not only estimates missing judgments but also ensures minimal geometric consistency. The proposed method along with DRASTIC and pesticide DRASTIC models is applied to Khoy County, which is located in the northwest part of Iran. The efficiency of the proposed method was further confirmed through the results of the Pearson coefficient test conducted on nitrate concentrations. The test revealed correlation values of 0.47, 0.27, and 0.57 for DRASTIC, pesticide DRASTIC, and modified DRASTIC, respectively. These results demonstrated that the proposed method provides a more precise evaluation of groundwater vulnerability.

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References

  • Abunada Z, Kishawi Y, Alslaibi TM, Kaheil N, Mittelstet A (2021) The application of SWAT-GIS tool to improve the recharge factor in the DRASTIC framework: case study. J Hydrol 592:125613

    CAS  Google Scholar 

  • Ahmed S, Qadir A, Khan MA, Khan T, Zafar M (2021) Assessment of groundwater intrinsic vulnerability using GIS-based DRASTIC method in District Haripur, Khyber Pakhtunkhwa, Pakistan. Environ Monit Assess 193:1–17

    Google Scholar 

  • Allen C, Metternicht G, Wiedmann T (2016) National pathways to the Sustainable Development Goals (SDGs): a comparative review of scenario modelling tools. Environ Sci Policy 66:199–207

    Google Scholar 

  • 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 …

    Google Scholar 

  • Barzegar R, Asghari Moghaddam A, Adamowski J, Nazemi AH (2019a) Assessing the potential origins and human health risks of trace elements in groundwater: a case study in the Khoy plain, Iran. Environ Geochem Health 41:981–1002

    CAS  Google Scholar 

  • Barzegar R, Asghari Moghaddam A, Adamowski J, Nazemi AH (2019b) Delimitation of groundwater zones under contamination risk using a bagged ensemble of optimized DRASTIC frameworks. Environ Sci Pollut Res 26:8325–8339

    CAS  Google Scholar 

  • Bera A, Mukhopadhyay BP, 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

    CAS  Google Scholar 

  • Bhuvaneswaran C, Ganesh A (2019) Spatial assessment of groundwater vulnerability using DRASTIC model with GIS in Uppar odai sub-watershed, Nandiyar, Cauvery Basin, Tamil Nadu. Groundw Sustain Dev 9:100270

    Google Scholar 

  • Chen K, Kou G, Michael Tarn J, Song Y (2015) Bridging the gap between missing and inconsistent values in eliciting preference from pairwise comparison matrices. Ann Oper Res 235:155–175

    Google Scholar 

  • Curiel-Esparza J, Mazario-Diez JL, Canto-Perello J, Martin-Utrillas M (2016) Prioritization by consensus of enhancements for sustainable mobility in urban areas. Environ Sci Policy 55:248–257

    Google Scholar 

  • Falowo OO, Bamoyegun OA (2023) AHP GIS-supported overlay/index models in Okeigbo, southwestern Nigeria, for groundwater susceptibility zonation. HydroResearch 6:184–202

    Google Scholar 

  • Ghavami SM (2020) A web service based advanced traveller information system for itinerary planning in an uncertain multimodal network. Geocarto Int 35:1553–1569

    Google Scholar 

  • Goyal D, Haritash A, Singh S (2021) A comprehensive review of groundwater vulnerability assessment using index-based, modelling, and coupling methods. J Environ Manag 296:113161

    Google Scholar 

  • Haidery A, Umar R, Saba N (2023) Approaches for groundwater vulnerability assessment in relation to pollution potential: a critical evaluation and challenges. J Geol Soc India 99:1149–1157

    Google Scholar 

  • Harker PT (1987) Incomplete pairwise comparisons in the analytic hierarchy process. Math Model 9:837–848

    Google Scholar 

  • Jahangirzadeh H, Ghanbarzadeh Lak M (2021) Developing a decision-making model to enhance artificial aquifer recharge site selection through floodwater spreading based on GIS and ELECTRE I. Water Resour Manag 35:5169–5186

    Google Scholar 

  • Khullar S, Singh N (2022) Water quality assessment of a river using deep learning Bi-LSTM methodology: forecasting and validation. Environ Sci Pollut Res 29:12875–12889

    CAS  Google Scholar 

  • Kumar A, Pant S (2022) Analytical hierarchy process for sustainable agriculture: an overview. MethodsX 10:101954

    Google Scholar 

  • Lakshminarayanan B, Ramasamy S, Anuthaman SN, Karuppanan S (2022) New DRASTIC framework for groundwater vulnerability assessment: bivariate and multi-criteria decision-making approach coupled with metaheuristic algorithm. Environ Sci Pollut Res 29:4474–4496

    Google Scholar 

  • Machiwal D, Jha MK, Singh VP, Mohan C (2018) Assessment and mapping of groundwater vulnerability to pollution: current status and challenges. Earth Sci Rev 185:901–927

    Google Scholar 

  • Mallik S, Bhowmik T, Mishra U, Paul N (2021) Local scale groundwater vulnerability assessment with an improved DRASTIC model. Nat Resour Res 30:2145–2160

    Google Scholar 

  • Mehta D, Patel P, Sharma N, Eslamian S (2023) Comparative analysis of DRASTIC and GOD model for groundwater vulnerability assessment. Model Earth Syst Environ:1–24

  • Metwally M, Armanuos A, Zeidan B (2023) Comparative study for assessment of groundwater vulnerability to pollution using DRASTIC methods applied to central Nile Delta, Egypt. Int J Energy Water Resour 7:175–190

    Google Scholar 

  • Neshat A, Pradhan B, Dadras M (2014) Groundwater vulnerability assessment using an improved DRASTIC method in GIS. Resour Conserv Recycl 86:74–86

    Google Scholar 

  • Nunnelley KG, Smith JA (2020) Nanotechnology for filtration-based point-of-use water treatment: a review of current understanding. In: Waste Management: Concepts, Methodologies, Tools, and Applications, 1603-1625

    Google Scholar 

  • Oke SA (2020) Regional aquifer vulnerability and pollution sensitivity analysis of drastic application to Dahomey Basin of Nigeria. Int J Environ Res Public Health 17:2609

    CAS  Google Scholar 

  • Omeje ET, Obiora DN, Okeke FN, Ibuot JC, Ugbor DO, Omeje VD (2023) Investigation of aquifer vulnerability and sensitivity analysis of modified drastic and sintacs models: a case study of Ovogovo Area, Eastern Nigeria. Acta Geophys 71:2439–2464

    Google Scholar 

  • Pacheco F, Pires L, Santos R, Fernandes LS (2015) Factor weighting in DRASTIC modeling. Sci Total Environ 505:474–486

    CAS  Google Scholar 

  • Panagopoulos A (2021) Water-energy nexus: desalination technologies and renewable energy sources. Environ Sci Pollut Res 28:21009–21022

    CAS  Google Scholar 

  • Piscopo G (2001) Groundwater vulnerability map explanatory notes—Castlereagh Catchment. NSW Department of Land and Water Conservation, Australia

    Google Scholar 

  • Polemio M, Casarano D, Limoni PP (2009) Karstic aquifer vulnerability assessment methods and results at a test site (Apulia, southern Italy). Nat Hazards Earth Syst Sci 9:1461–1470

    Google Scholar 

  • Qiu Y, Ma C, Qian J, Wang X (2021) Comparison of different groundwater vulnerability evaluation models of typical karst areas in north China: a case of Hebi City. Environ Sci Pollut Res 28:30821–30840

    CAS  Google Scholar 

  • 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. Environ Earth Sci 79:1–15

    Google Scholar 

  • Rezaei Moghaddam MH, Nakhostin Rouhi M, Sarkar S, Rahimpour T (2018) Groundwater vulnerability assessment using the DRASTIC model under GIS platform in the Ajabshir Plain, southeast coast of Urmia Lake, Iran. Arab J Geosci 11:1–15

    Google Scholar 

  • Saravanan S, Pitchaikani S, Thambiraja M, Sathiyamurthi S, Sivakumar V, Velusamy S, Shanmugamoorthy M (2023) Comparative assessment of groundwater vulnerability using GIS-based DRASTIC and DRASTIC-AHP for Thoothukudi District, Tamil Nadu India. Environ Monit Assess 195:57

    CAS  Google Scholar 

  • SCI (2016): Population of Khoy County The Statistical Center of Iran

    Google Scholar 

  • Şener E (2023) Appraisal of groundwater pollution risk by combining the fuzzy AHP and DRASTIC method in the Burdur Saline Lake Basin, SW Turkey. Environ Sci Pollut Res 30:21945–21969

    Google Scholar 

  • Shakoor A, Khan ZM, Farid HU, Sultan M, Ahmad I, Ahmad N, Mahmood MH, Ali MU (2020) Delineation of regional groundwater vulnerability using DRASTIC model for agricultural application in Pakistan. Arab J Geosci 13:1–12

    Google Scholar 

  • Shrestha S, Semkuyu DJ, Pandey VP (2016) Assessment of groundwater vulnerability and risk to pollution in Kathmandu Valley, Nepal. Sci Total Environ 556:23–35

    CAS  Google Scholar 

  • Taghavi N, Niven RK, Paull DJ, Kramer M (2022) Groundwater vulnerability assessment: a review including new statistical and hybrid methods. Sci Total Environ 822:153486

    CAS  Google Scholar 

  • 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

    Google Scholar 

  • Velmurugan A, Swarnam P, Subramani T, Meena B, Kaledhonkar M (2020) Water demand and salinity. In: Desalination-challenges and opportunities

    Google Scholar 

  • Venkatesan G, Pitchaikani S, Saravanan S (2019) Assessment of groundwater vulnerability using GIS and DRASTIC for upper Palar River basin, Tamil Nadu. J Geol Soc India 94:387–394

    CAS  Google Scholar 

  • Wan S, Dong J (2021) A novel extension of best-worst method with intuitionistic fuzzy reference comparisons. IEEE Trans Fuzzy Syst 30:1698–1711

    Google Scholar 

  • 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

    Google Scholar 

  • Wu X, Li B, Ma C (2018) Assessment of groundwater vulnerability by applying the modified DRASTIC model in Beihai City, China. Environ Sci Pollut Res 25:12713–12727

    CAS  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Surveying Engineering, University of Zanjan, Zanjan, Iran

    Ali Miron Baki & Seyed Morsal Ghavami

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  1. Ali Miron Baki
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  2. Seyed Morsal Ghavami
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Contributions

The study conception and design were created by SMG. Material preparation, data collection, and analysis were performed by AMB. The first draft of the manuscript was written by SMG.

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Correspondence to Seyed Morsal Ghavami.

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Baki, .M., Ghavami, S.M. A modified DRASTIC model for groundwater vulnerability assessment using connecting path and analytic hierarchy process methods. Environ Sci Pollut Res 30, 111270–111283 (2023). https://doi.org/10.1007/s11356-023-30201-8

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