Please cite this article as: M. Jacome, V. Costanzo-Alvarez, M. Aldana et al., A methodology to characterize a sanitary landfill combining, through a numerical approach, a geoelectrical survey with methane point-source concentrations. Environmental Technology & Innovation (2020) 101225, https://doi.org/10.1016/j.eti.2020.101225. Environmental Technology & Innovation xxx (xxxx) xxx Contents lists available at ScienceDirect Environmental Technology & Innovation journal homepage: www.elsevier.com/locate/eti A methodology to characterize a sanitary landfill combining, through a numerical approach, a geoelectrical survey with methane point-source concentrations Maria Jacome a , Vincenzo Costanzo-Alvarez b,∗ , Milagrosa Aldana c , Pamela Patraskovic d , Chris Drielsma d , Daniela Galatro b , Cristina Amon b a Faculty of Applied Sciences and Technology, Humber Institute of Technology and Advanced Learning, Toronto, Canada b Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada c Departamento de Ciencias de la Tierra, Universidad Simón Bolívar, Caracas, Venezuela d DGI Geoscience Inc, Toronto, Canada article info Article history: Received 13 July 2020 Received in revised form 22 October 2020 Accepted 23 October 2020 Available online xxxx Keywords: Aquifer Landfill Leachate Methane DC resistivity survey Induced Polarization (IP) Fuzzy logic Neural networks abstract Among the different natural sources of drinking water, aquifers are the most exposed to the environmental pressures posed by old landfills. Conventional monitoring methods to follow up the migration of leachate into groundwater and the generation of biogases in landfills are costly, time-consuming, and only provide a partial picture of these complex systems. Alternatively, we present the results of a non-invasive and cost- effective methodology applied to a non-engineered (i.e., no gas or liquid recovery systems) closed landfill in southern Ontario. The study combines, through a numerical approach, data from a direct current (DC) resistivity and an Induced Polarization (IP) survey, with measurements of methane concentrations taken over the landfill. We used a Dipole–Dipole array along four regional Lines of approximately 300 meters each, cutting crosswise and throughout the strike of the site. The interpretation of the inverted resistivity and IP data allowed us to recognize and describe some hydrogeological features that went unnoticed by using conventional monitoring techniques. We also applied a hybrid algorithm that incorporates fuzzy logic to neural networks (ANFIS) for causal variable forecasting of surface methane concentrations, using geoelectrical proxies of leachate accumulation as antecedent parameters (i.e. minimum resistivity and their corresponding IP values). The ANFIS provided a statistically significant inference of the main tendencies of methane concentrations along the surveyed Lines. Some coarse inferences appear to be locally associated with IP bright spots of anomalous metal ion content. Overall, a better inference seems to be hampered by the uncertainties involved in the generation of biogas and its upward flow through the soil cover. These results substantiate the feasibility of employing surface methane concentration data as a first diagnostic test to characterize the areal extent of the leachate plume underground. © 2020 Elsevier B.V. All rights reserved. 1. Introduction The Ontario Clean Water Act of 2006 safeguards existing and future water supplies and identifies possible activities that could be considered threats to the so-called Source Protection Regions. According to this Law, some of the drinking ∗ Corresponding author. E-mail address: v.costanzo@utoronto.ca (V. Costanzo-Alvarez). https://doi.org/10.1016/j.eti.2020.101225 2352-1864/© 2020 Elsevier B.V. All rights reserved.