Enhanced GPR data interpretation to estimate in situ water saturation in a landfill

Abstract

Research was completed to show that using the complex refractive index model (CRIM) to interpret GPR data can improve the estimation of in situ water content of the waste in the landfill. Literature shows that the Topp equation is normally used to analyse GPR data, despite the fact it fails to consider porosity and other properties of the landfill material or soil that can affect the electromagnetic properties of the material. The application of (CRIM) overcomes these limitations and more. Previously measured field GPR data were reanalyzed with CRIM and supported by synthetic GPR data to show that CRIM provides a better prediction of the water content of the landfill material. Further enhancement of GPR data interpretation was implemented by optimizing the frequency of the GPR scan and determining the ideal offset separation distance between the transmitter and the receiver using sensitivity tests. The sensitivity tests were based on synthetic 2D surface based-reflection GPR data sets generated by MATLAB®. The sensitivity results showed that the optimum frequency was 1 GHz, with an ideal offset distance of 0.75 m. After using the optimized values, it was possible to obtain a percentage of error of 1% between modelled water saturation and GPR measured water saturation.

Keywords: CRIM; GPR; Landfill; MATLAB®; Topp equation; Water content.