Yayu Indriati Arifin
Department of Geology, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Bone Bolango, Gorontalo 96128

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Improved groundwater vulnerability assessment through MIF-based DRASTIC model for sustainable environmental management Nurfaika; Yayu Indriati Arifin; Nina Safitri
Interaction, Community Engagement, and Social Environment Vol. 4 No. 1: (July) 2026
Publisher : Institute for Advanced Science Social, and Sustainable Future

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61511/icese.v4i1.2026.3747

Abstract

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.