Improved groundwater vulnerability assessment through MIF-based DRASTIC model for sustainable environmental management
DOI:
https://doi.org/10.61511/icese.v4i1.2026.3747Keywords:
DRASTIC model, groundwater vulnerability, MIF, nitrate contaminationAbstract
Background: Groundwater serves as a fundamental resource for drinking, agriculture, and industrial processes, yet anthropogenic activities and environmental changes increasingly threaten its sustainability. This study, conducted in the Limboto Alluvial Plain, Indonesia, aimed to identify and map groundwater vulnerability by enhancing the traditional DRASTIC framework through the integration of the Multi-Influencing Factor (MIF) method. The implementation of the MIF method is proposed to improve the accuracy of the weighing system in evaluating the groundwater vulnerability. Methods: Seven thematic layers—depth to water, net recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity—were generated and integrated using Geographic Information Systems (GIS). The research replaced the conventional static weighting system with a dynamic MIF approach to systematically evaluate the interdependencies between hydrogeological parameters. The model's accuracy was empirically validated using nitrate concentration proxies to correlate high-risk zones with actual contamination levels. Findings: The study revealed three distinct vulnerability classes: low, moderate, and high. High-vulnerability zones were primarily identified in the central and southern regions, characterized by shallow water tables and highly permeable media. Validation results showed a strong correlation between these delineated high-risk zones and elevated nitrate concentrations, confirming the model's reliability in predicting sensitive areas. Conclusion: The study strongly recommends adopting this enhanced MIF-DRASTIC framework as a robust tool for sustainable groundwater management and land-use planning. It provides policymakers with a precise tool for mitigating contamination in alluvial contexts, though further longitudinal data could refine the model's temporal accuracy. Novelty/Originality of this article: This research is novel because it systematically addresses the inherent limitations of the static DRASTIC model by introducing dynamic weighting through the MIF approach. It uniquely integrates hydrogeological interdependencies within the Limboto Alluvial Plain, offering a more site-specific and refined methodology for groundwater protection that is more adaptable than traditional frameworks.
References
Agbotsou, K. E., Indeti, C., Anand, A. V. S. S., Ani, M., Rao, E. N. D., & Gnandi, K. (2026). GIS-based assessment of fissured hard rock aquifer vulnerability: Application of the PaPRI model to gneiss migmatitic terrains of Togo, West Africa. Journal of African Earth Sciences, 237, 106042. https://doi.org/10.1016/j.jafrearsci.2026.106042
Akbar, M. U., Mirchi, A., Arshad, A., Mansaray, A., Ullah, A. S., & Madani, K. (2025). A dynamic DRASTIC-based approach for multi-hazard groundwater vulnerability mapping. Geoscience Frontiers, 16(5), 102117. https://doi.org/10.1016/j.gsf.2025.102117
Aller, L., Lehr, J. H., Petty, R., & Bennett, T. (1987). DRASTIC: A standardized system to evaluate groundwater pollution potential using hydrogeologic setting. Journal of the Geological Society of India, 29(1). https://doi.org/10.17491/jgsi/1987/290112
Ashagrie, W. A., Tarkegn, T. G., Ray, R. L., Tefera, G. W., Demessie, S. F., Tsegaye, L., Adem, A. A., Worqlul, A. W., van Oel, P. R., Adgo, E., Haileslassie, A., Dile, Y. T., Mekonnen, M., & Chukalla, A. D. (2025). Assessing the vulnerability of groundwater to pollution under different land management scenarios using the modified DRASTIC model in Bahir Dar City, Ethiopia. Heliyon, 11(4), e42660. https://doi.org/10.1016/j.heliyon.2025.e42660
Awaleh, M. O., Omar, G. M., Adan, A. B. I., Najafzadeh, M., Marlin, C., Al-Aghbary, M., Robleh, M. A., Iltireh, A. D., Al-Jawad, J., Waberi, M. M., Ragueh, R. R., Ragueh, B. E., Dabar, O. A., Ahmed, M. M., Chirdon, M. A., Adaneh, A. E., Ibrahim, N. H., Egueh, N. M., Guireh, I. A., & Elmi, O. I. (2026). Groundwater vulnerability assessment of the Djibouti aquifer system (East Africa Rift System): A comparative study of DRASTIC, Hybrid-DRASTICs, and DRASTIC-based multi-objective evolutionary algorithm. Groundwater for Sustainable Development, 32, 101564. https://doi.org/10.1016/j.gsd.2025.101564
Belalite, H., Athamena, A., Kebaili, F. K., Cheniti, H., Azab, M., Accouche, O., Ziad, S., Athamena, M., & Aouissi, H. A. (2026). Hybrid DRASTIC-EBKRP-Hydrochemistry approach for groundwater vulnerability assessment in a semi-arid context under agricultural pressure. Desalination and Water Treatment, 326, 101739. https://doi.org/10.1016/j.dwt.2026.101739
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. https://doi.org/10.1016/j.chemosphere.2022.135831
Bordbar, M., Khosravi, K., Jun, C., Kim, D., Bateni, S. M., Safarzadeh, M., Moghaddam, H. K., & Azizi, S. (2025). Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorithms. Results in Engineering, 26, 104674. https://doi.org/10.1016/j.rineng.2025.104674
Bouiss, H., Jilali, A., Bengamra, S., & Ourarhi, S. (2024). Groundwater vulnerability and risk assessment coupled with hydrogeochemical analysis in the Taza aquifer (Morocco). Groundwater for Sustainable Development, 26, 101242. https://doi.org/10.1016/j.gsd.2024.101242
Cheng, Z., Lu, G., Wu, M., Li, Z., Deng, Y., Wu, J., Hao, Y., Mo, C., Li, Q., Wu, J., Wu, J., & Hu, B. X. (2024). Quantification and visualization of groundwater contamination prevention regionalization based on analytic hierarchy process method (AHP) in Guangdong-Hong Kong-Macao Greater Bay Area, South China. Journal of Hydrology, 628, 130521. https://doi.org/10.1016/j.jhydrol.2023.130521
Dasgupta, R., Banerjee, G., Hidayetullah, S. M., Saha, N., Das, S., & Mazumdar, A. (2024). A comparative analysis of statistical, MCDM and machine learning based modification strategies to reduce subjective errors of DRASTIC models. Environmental Earth Sciences, 83(7), 11515. https://doi.org/10.1007/s12665-024-11515-3
Deka, D., Ravi, K., & Nair, A. M. (2025). Impact of urbanisation on groundwater vulnerability in shallow aquifer system of Assam: A DRASTIC approach. Urban Climate, 59, 102299. https://doi.org/10.1016/j.uclim.2025.102299
Ganwer, S., Sinha, M. K., Multaniya, A. P., & Ghodichore, N. (2024). Introducing reverse Multi Influencing Factor technique in DRASTIC model for groundwater vulnerability assessment. Groundwater for Sustainable Development, 25, 101106. https://doi.org/10.1016/j.gsd.2024.101106
Hamideh, G., & Mojgan, E. (2026). Assessment of groundwater vulnerability to heavy metals in four aquifers using machine learning algorithms. Journal of Contaminant Hydrology, 277, 104853. https://doi.org/10.1016/j.jconhyd.2026.104853
Ikpe, E. O., Ekanem, A. M., George, N. J., Thomas, J. E., & Udosen, N. I. (2025). GOD - and DRASTIC - based valuation of groundwater vulnerability to contamination of hinterland aquifers of northern part of Akwa Ibom State, Nigeria. Results in Earth Sciences, 3, 100104. https://doi.org/10.1016/j.rines.2025.100104
Iqbal, M. A., Salam, M. A., Nur-E-Alam, M., Rubaida, N. J., Rahman, H., & Uddin, M. F. (2024). Monitoring groundwater vulnerability for sustainable water resource management: A DRASTIC-based comparative assessment in a newly township area of Bangladesh. Groundwater for Sustainable Development, 27, 101373. https://doi.org/10.1016/j.gsd.2024.101373
Liu, Y., Qian, H., Gao, Y., Li, S., Shi, X., Cao, Z., Long, Q., He, Y., Ma, Y., Wu, P., & Shen, Y. (2025). Identifying nitrate pollution of groundwater based on aquifer vulnerability and surface nitrogen loads in the Northern Foot of the Qinling Mountains, China. Journal of Hazardous Materials, 495, 138939. https://doi.org/10.1016/j.jhazmat.2025.138939
Loganathan, S., & Sathiyamoorthy, M. (2024). Assessing groundwater contamination risk in industrial zone of Ranipet district, Southern India: A modified DRASTIC and Fuzzy-AHP approach. Results in Engineering, 23, 102772. https://doi.org/10.1016/j.rineng.2024.102772
Männik, M., Bikše, J., Karro, E., & Marandi, A. (2025). A framework for assessing groundwater vulnerability and pollution risk in transboundary aquifers: Insights from the Estonian-Latvian transboundary area. Journal of Hydrology: Regional Studies, 60, 102525. https://doi.org/10.1016/j.ejrh.2025.102525
Magesh, N. S., Chandrasekar, N., & Soundranayagam, J. P. (2012). Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geoscience frontiers, 3(2), 189-196. https://doi.org/10.1016/j.gsf.2011.10.007
Moharir, K. N., Pande, C. B., Tolche, A. D., Varade, A. M., Sammen, S. S., Khalid, M., Yadav, K. K., Alreshidi, M. A., Albakri, G. S., & Elsahabi, M. (2026). Development of groundwater potential zones and soil erosion mapping with planning based on aquifer modeling, AHP and geospatial techniques. Physics and Chemistry of the Earth, Parts A/B/C, 143, 104304. https://doi.org/10.1016/j.pce.2026.104304
Nosair, A. M., Samra, R. E. S., Hassan, R., & Gemail, K. (2026). Groundwater sustainability challenges in urban deltas: A DRASTIC-GIS and hydrogeophysical approach for assessing the Nile Delta aquifer for sustainable management. Journal of Contaminant Hydrology, 277, 104823. https://doi.org/10.1016/j.jconhyd.2025.104823
Ourarhi, S., Kadiri, M., Barkaoui, A. E., Bouiss, H., Amar, I., & Zarhloule, Y. (2024). Assessment of risk intensity in the triffa plain aquifer: Integration of hazard quantification, land use analysis, dynamic vulnerability GCITF, and DRASTIC method. Groundwater for Sustainable Development, 26, 101291. https://doi.org/10.1016/j.gsd.2024.101291
Oyda, Y., Hatiye, S. D., & Jothimani, M. (2025). Groundwater vulnerability mapping in the Maze Zenti catchment, Ethiopia: Integrating the DRASTIC model with an entropy-weighted modification in a GIS environment. Scientific African, 30, e02983. https://doi.org/10.1016/j.sciaf.2025.e02983
Rubio-Arellano, A. B., Ramos-Leal, J. A., Almanza-Tovar, O. G., Vázquez-Báez, V. M., & Morán-Ramírez, J. (2025). Assessment of aquifer vulnerability and water quality: Validated using groundwater flow origin-based regression analysis. Groundwater for Sustainable Development, 30, 101478. https://doi.org/10.1016/j.gsd.2025.101478
Seraiche, L., Dougha, M., Ghodbane, M., Selmane, T., Ferhati, A., & Djemiat, D. E. (2025). Groundwater vulnerability assessment in semi-arid regions using GIS-based DRASTIC models and FUZZY AHP: South Chott Hodna. Desalination and Water Treatment, 323, 101380. https://doi.org/10.1016/j.dwt.2025.101380
Sifi, S., Zaghdoudi, S., Abdo, H. G., & Aydi, A. (2026). Sensitivity analysis of multiple groundwater vulnerability models for enhancing resource management in the Menzel Bourguiba aquifer system, northern Tunisa. Hydrogeology Journal, 34, 101564. https://doi.org/10.1007/s10040-025-03013-y
Umar, M., Khan, S. N., Arshad, A., Aslam, R. A., Khan, H. M. S., Rashid, H., Pham, Q. B., Nasir, A., Noor, R., Khedher, K. M., & Anh, D. T. (2022). A modified approach to quantify aquifer vulnerability to pollution towards sustainable groundwater management in Irrigated Indus Basin. Environmental Science and Pollution Research, 29(18), 27257–27278. https://doi.org/10.1007/s11356-021-17882-9
Usman, A. O., Ezeh, C. C., Abraham, E. M., Azuoko, G. B., Chima, C. J., Onyeneke, L., Chinwuko, A. I., Iheme, K. O., & Ikeazota, I. I. (2025). Aquifer characterization and DRASTIC vulnerability assessment within the low-permeable Enugu shale formation, Anambra Basin, Nigeria using electrical resistivity method. Scientific African, 29, e02804. https://doi.org/10.1016/j.sciaf.2025.e02804
Wang, C., Liu, M., Han, Y., Chen, S., Zhang, F., Qiu, R., ... & Liu, J. (2025). Assessing the impacts of irrigation and soil types on the water balance and groundwater depletion in an irrigation district of the North China Plain based on a coupled SWAT-MODFLOW model. Agricultural Water Management, 321, 109890. https://doi.org/10.1016/j.agwat.2025.109890
Williams, S. A., Megdal, S. B., Zuniga-Teran, A. A., Quanrud, D. M., & Christopherson, G. (2025). Mapping Groundwater Vulnerability in Arid Regions: A Comparative Risk Assessment Using Modified DRASTIC Models, Land Use, and Climate Change Factors. Land, 14(1), 58. https://doi.org/10.3390/land14010058
Xiong, H., Li, Y., Xiong, R., He, H., Tan, J., Yang, S., Liu, H., Song, X., & Guo, X. (2025). Integrating aquifer vulnerability and explainable machine learning for spatial prediction of groundwater fluoride. Groundwater for Sustainable Development, 31, 101517. https://doi.org/10.1016/j.gsd.2025.101517
Yang, Y., & Zhao, J. (2025). Forecasting the Spatio-Temporal Evolution of Groundwater Vulnerability: A Coupled Time-Series and Hydrogeological Modeling Approach. Water (Switzerland), 17(21), 3033. https://doi.org/10.3390/w17213033
Zhao, B., Chen, L., Hou, X., Hu, Y., Zhang, M., Ou, Q., Wang, H., Yin, X., & Shi, X. (2026). Comparative assessment of groundwater heterogeneity and vulnerability in coal mine limestone aquifer under complex geological structures and mining disturbances. Journal of Environmental Chemical Engineering, 14(3), 122830. https://doi.org/10.1016/j.jece.2026.122830
Zhu, G., Xue, P., Wu, X., Zhang, B., Tong, B., Zhai, Y., Zhu, G., & Ma, R. (2024). Mapping key areas to protect high-value and high-vulnerability groundwater from pollution load: Method for management. Journal of Environmental Management, 371, 123155. https://doi.org/10.1016/j.jenvman.2024.123155
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