Integrating high-resolution magnetic surveys and metaheuristic optimization for quantitative characterization of subsurface magnetic sources in a municipal landfill

Landfill leachate poses a significant environmental risk by transporting toxic metals and organic contaminants into surrounding soil and groundwater. This study establishes a rapid, non-invasive geophysical framework for delineating potential subsurface leachate pathways using high-resolution magnetic surveying integrated with advanced magnetic data processing and metaheuristic optimization. A total of 246 magnetic measurements were acquired across the Benowo landfill, Surabaya, Indonesia, using a proton precession magnetometer. The data were processed through diurnal correction, International Geomagnetic Reference Field (IGRF) removal, upward continuation, Reduction-to-the-Pole (RTP) transformation, analytic signal, first vertical gradient, and horizontal gradient analyses to enhance anomaly localization and source-boundary delineation. The resulting RTP magnetic anomalies range from −8000 to +7200 nT and are concentrated predominantly in the northern and western sectors of the landfill. Representative anomalies were quantitatively interpreted through forward modeling optimized using the Flower Pollination Algorithm (FPA), which identified simplified spherical and cylindrical magnetic source bodies at depths of approximately 11–29 m. The optimization converged consistently with residual misfits below 0.1 nT, indicating stable numerical convergence and excellent agreement between the observed and modeled magnetic responses. The interpreted magnetic source distribution is spatially consistent with the known geological and hydrogeological framework of the study area and identifies preferential subsurface zones that may be associated with leachate migration. Although magnetic surveying alone cannot directly confirm contaminant occurrence or leachate composition, the identified anomaly zones provide objective targets for subsequent hydrochemical, borehole, or complementary geophysical investigations. These findings demonstrate that integrating magnetic surveying with metaheuristic optimization provides an effective, scalable, and non-invasive approach for landfill monitoring, environmental risk assessment, and groundwater protection.