Gravimetric water distribution assessment from geoelectrical methods (ERT and EMI) in municipal solid waste landfill

The gravimetric water content of the waste material is a key parameter in waste biodegradation. Previous studies suggest a correlation between changes in water content and modification of electrical resistivity. This study, based on field work in Mont-Saint-Guibert landfill (Belgium), aimed, on one hand, at characterizing the relationship between gravimetric water content and electrical resistivity and on the other hand, at assessing geoelectrical methods as tools to characterize the gravimetric water distribution in a landfill. Using excavated waste samples obtained after drilling, we investigated the influences of the temperature, the liquid phase conductivity, the compaction and the water content on the electrical resistivity. Our results demonstrate that Archie's law and Campbell's law accurately describe these relationships in municipal solid waste (MSW). Next, we conducted a geophysical survey in situ using two techniques: borehole electromagnetics (EM) and electrical resistivity tomography (ERT). First, in order to validate the use of EM, EM values obtained in situ were compared to electrical resistivity of excavated waste samples from corresponding depths. The petrophysical laws were used to account for the change of environmental parameters (temperature and compaction). A rather good correlation was obtained between direct measurement on waste samples and borehole electromagnetic data. Second, ERT and EM were used to acquire a spatial distribution of the electrical resistivity. Then, using the petrophysical laws, this information was used to estimate the water content distribution. In summary, our results demonstrate that geoelectrical methods represent a pertinent approach to characterize spatial distribution of water content in municipal landfills when properly interpreted using ground truth data. These methods might therefore prove to be valuable tools in waste biodegradation optimization projects. (C) 2016 Elsevier Ltd. All rights reserved.