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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 22, issue 4 | Copyright
Hydrol. Earth Syst. Sci., 22, 2551-2573, 2018
https://doi.org/10.5194/hess-22-2551-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 25 Apr 2018

Research article | 25 Apr 2018

Soil hydraulic material properties and layered architecture from time-lapse GPR

Stefan Jaumann1,2 and Kurt Roth1,3 Stefan Jaumann and Kurt Roth
  • 1Institute of Environmental Physics, Heidelberg University, Im Neuenheimer Feld 229, 69120 Heidelberg, Germany
  • 2HGS MathComp, Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
  • 3Interdisciplinary Center for Scientific Computing, Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany

Abstract. Quantitative knowledge of the subsurface material distribution and its effective soil hydraulic material properties is essential to predict soil water movement. Ground-penetrating radar (GPR) is a noninvasive and nondestructive geophysical measurement method that is suitable to monitor hydraulic processes. Previous studies showed that the GPR signal from a fluctuating groundwater table is sensitive to the soil water characteristic and the hydraulic conductivity function. In this work, we show that the GPR signal originating from both the subsurface architecture and the fluctuating groundwater table is suitable to estimate the position of layers within the subsurface architecture together with the associated effective soil hydraulic material properties with inversion methods. To that end, we parameterize the subsurface architecture, solve the Richards equation, convert the resulting water content to relative permittivity with the complex refractive index model (CRIM), and solve Maxwell's equations numerically. In order to analyze the GPR signal, we implemented a new heuristic algorithm that detects relevant signals in the radargram (events) and extracts the corresponding signal travel time and amplitude. This algorithm is applied to simulated as well as measured radargrams and the detected events are associated automatically. Using events instead of the full wave regularizes the inversion focussing on the relevant measurement signal. For optimization, we use a global–local approach with preconditioning. Starting from an ensemble of initial parameter sets drawn with a Latin hypercube algorithm, we sequentially couple a simulated annealing algorithm with a Levenberg–Marquardt algorithm. The method is applied to synthetic as well as measured data from the ASSESS test site. We show that the method yields reasonable estimates for the position of the layers as well as for the soil hydraulic material properties by comparing the results to references derived from ground truth data as well as from time domain reflectometry (TDR).

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Ground-penetrating radar (GPR) is a noninvasive and nondestructive measurement method to monitor the hydraulic processes precisely and efficiently. We analyze synthetic as well as measured data from the ASSESS test site and show that the analysis yields accurate estimates for the soil hydraulic material properties as well as for the subsurface architecture by comparing the results to references derived from time domain reflectometry (TDR) and subsurface architecture ground truth data.
Ground-penetrating radar (GPR) is a noninvasive and nondestructive measurement method to...
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