The aim of this paper is to present an alternative method for the analysis of resistivity data. The methodology was developed during a study to evaluate if electrical resistivity can be used as a tool for analysing subsurface gas dynamics and gas emissions from landfills. The main assumption of this study was that variations in time of resistivity data correspond to variations in the relative amount of gas and water in the soil pores. Field measurements of electrical resistivity, static chamber gas flux and weather data were collected at a landfill in Helsingborg, Sweden. The resistivity survey arrangement consisted of nine lines each with 21 electrodes in an investigation area of 16 x20 m. The ABEM Lund Imaging System provided vertical and horizontal resistivity profiles every second hour. The data were inverted in Res3Dinv using L-1-norm-based optimization method with a standard least-squares formulation. Each horizontal soil layer was then represented as a linear interpolated raster model. Different areas underneath the gas flux measurement points were defined in the resistivity model of the uppermost soil layer, and the vertical extension of the zones could be followed at greater depths in deeper layer models. The average resistivity values of the defined areas were calculated and plotted on a time axis, to provide graphs of the variation in resistivity with time in a specific section of the ground. Residual variation of resistivity was calculated by subtracting the resistivity variations caused by the diurnal temperature variations from the measured resistivity data. The resulting residual resistivity graphs were compared with field data of soil moisture, precipitation, soil temperature and methane flux. The results of the study were qualitative, but promising indications of relationships between electrical resistivity and variations in the relative amount of gas and water in the soil pores were found. Even though more research and better data quality is necessary for verification of the results presented here, we conclude that this alternative methodology of working with resistivity data seems to be a valuable and flexible tool for this application.
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