2019 CSCE Annual Conference - Laval (Greater Montreal)

2019 CSCE Annual Conference - Laval (Greater Montreal) Conference

Estimating In Situ Water Content in a Landfill using GPR

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Mrs. Aseel Dawrea, School of Engineering/U of Guelph (Presenter)
Dr. Richard Zytner, School of Engineering, University of Guelph
Dr. John Donald, School of Engineering/U of Guelph

The ability to estimate and evaluate in situ water content is fundamental to the effective operation of a landfill, as water content has a direct impact on decomposition of the waste and ultimately landfill gas generation. Currently it is a challenge to measure water content in situ without serious disruptions to the landfill operation or without destructive testing post closure. Ground penetrating radar (GPR) is a technology that can estimate the water content of landfill in situ.  The challenge to using GPR in landfill applications is the selection of an appropriate mathematical relationship that represents the electromagnetic wave as it propagates through the landfill mass.  Specifically, a mathematical relationship is needed to connect the dielectric permittivity of the solid waste with volumetric water content of the soil.  Having this relationship will improve the analysis of the GPR data, increasing the accuracy of the water content estimation.  This in turn will provide better data on the potential amount of landfill gas to be generated by a specific landfill.

Previous GPR work by the research group centred on predicting water content through the application of the Topp equation to analyse GPR data.  The Topp equation is empirical and has limited effectiveness as it relies only on two parameters, dielectric constant and water content, where simplification meant that the other soil properties were not considered.  The predicted water content values are then overestimated.  In order to improve accuracy of water content predictions with GPR, research was completed on using a foundational volumetric mixing model that was simplified to give the complex refractive index model (CRIM).  CRIM was then used to analyse GPR images to estimate water content. Additional study was done to determine if the water content predictions could be further improved, by identifying the optimum frequency and offset distance required for GPR measurements.

The results show that CRIM can provide more accurate water content estimations when compared to the standard Topp equation approach.  A statistical analysis (T-test) was used to make the comparisons. The optimum conditions for water content measurements were determined for an antenna frequency of 1 GHz with an offset distance between the transmitter and receiver of 3m.