Abstract

Quantitative understanding of soil water movement is essential to develop methods that allow for a more sustainable use of limited freshwater resources. In this study, methods are developed that allow to estimate the spatial distribution of these materials, their effective soil hydraulic material properties, and the effect of unrepresented model errors on these properties. To acquire the necessary data, a 2D subsurface architecture (ASSESS) was forced with a fluctuating groundwater table. The resulting hydraulic dynamics were essentially monitored with time domain reflectometry (TDR) and ground-penetrating radar (GPR). Based on the TDR data, the effect of unrepresented model errors on estimated soil hydraulic material properties is analyzed with a structural error analysis. This method compares inversions of increasingly complex models, since the required model complexity for a consistent description of the measurement data is application-dependent and unknown a priori. It is demonstrated that the method can indicate unrepresented model errors and quantify their effects on the resulting material properties. Based on the GPR data, a new heuristic event detection and association algorithm was developed that allows to identify and to extract relevant information from GPR data. It is demonstrated for synthetic and measured data that this approach provides reasonably accurate estimates for the spatial distribution of materials and their soil hydraulic material properties.

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