Electrical Resistivity Tomography Protocol for Landfill Monitoring

Master Thesis (2017)
Author(s)

J.F. Chavez Olalla (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

Timo J. Heimovaara – Mentor

Dominique J.M. Tillard – Mentor

D.S. Draganov – Mentor

Faculty
Civil Engineering & Geosciences
Copyright
© 2017 Juan Chavez Olalla
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 Juan Chavez Olalla
Graduation Date
28-07-2017
Awarding Institution
Delft University of Technology
Faculty
Civil Engineering & Geosciences
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Abstract

Aftercare of sanitary landfills represents a burden for future generations, for emission potential of leachate and gases remains for hundred of years. Treatment methods have to be developed in order to accelerate waste degradation and reduce emission potential preferably within the time-span of one generation. Aeration seems a promising treatment method but as yet has to be proven effective as a methodology to enhance waste degradation at full scale. Water content plays a crucial role in evaluating aeration, but the highly heterogeneous nature of a landfill body poses a big uncertainty in quantifying it and therefore also quantifying the effectiveness of aeration in reducing emission potential. To improve understanding of water within a waste body, Electrical Resistivity Tomography ERT is to be used to indirectly measure water content by obtaining electric resistivity information. However, full scale landfills have large areas and therefore a protocol needs to be developed for generating an optimum survey strategy, so that high resolution information is obtained while covering a large area. This thesis presents such a protocol consisting of four parts. First, optimum spread and spacing are defined by building a Pareto front with resolution and covered area as objective criteria. Second, array is designed in the previously defined grid, with standard and non-standard four-electrode configurations, by using a goodness function applied to multiple channel acquisition systems. Third, array design is tested with synthetic models showing that smooth resistivity models are well captured by data inversion, but array design performs poorly in a sharp resistivity model. Finally, practical aspects namely injection time, polarization effects and unstable configurations which are usually overlooked, are shown to have significant influence in data quality. This protocol is intended as a systematic approach to generate an optimum ERT survey strategy which could be extended to other geophysical methods.

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