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[1] We report on a laboratory experiment that investigates the effect of soil surface roughness on the identification of the soil electromagnetic properties from full-wave inversion of ground-penetrating radar (GPR) data in the frequency domain. The GPR system consists of an ultrawide band stepped-frequency continuous-wave radar combined with an off-ground monostatic horn antenna. Radar measurements were performed above a rectangular container filled with a loose sandy soil subject to seven water contents and four random surface roughnesses, including a smooth surface as reference. Compared to previous studies, we have reduced the modeling error of the GPR signal for the smooth surface case thanks to improved antenna transfer functions by solving an overdetermined system of equations based on six model configurations instead of only three. Then, the continuously increasing effect of surface roughness on the radar signal with respect to frequency is clearly observed. In close accordance with Rayleigh's criterion, both the radar signal and the inversely estimated parameters are not significantly affected if the surface protuberances are smaller than one eighth of a wavelength. In addition, when this criterion is not respected, errors are made in the estimated parameters, but the inverse solution remains stable. This demonstrates the promising perspectives for application of GPR for noninvasive water content estimation in agricultural and environmental field applications.

Abstract:The degree of hydrological connectivity is mainly determined by the spatial organisation of heterogeneity. A meaningful and aggregate abstraction of spatial patterns is one of the promising means to gain fundamental insights into this complex interaction and can, moreover, be used as a tool to acquire a profound understanding of the major controls of catchment hydrology. In order to disclose such controls, pattern-process relationships and the explanatory power of landscape metrics were tested by simulating the runoff of differently patterned virtual basins, generated by neutral landscape models and fractal networks and solved by a surface hydrological model composed of kinematic wave routing and Green-Ampt infiltration. A total of 23 landscape metrics quantified the spatial patterns and were subsequently related to the functional connectivity, assessed as the proportion of internal runoff generation constituting the hydrological response at the outlet. Landscape metrics allowed the identification of dominant features of heterogeneity that explained the observed connectivity, and to disclose changes in control with class abundance. Therefore, landscape metrics are a useful tool for basin comparison and classification in terms of the dominant processes and the corresponding model structure requirements.

methods, intensive efforts have been undertaken to supplement the scarcity of hydrogeological data with densely We combine electromagnetic inversion of ground penetrating radar sampled geophysical data (Beres and Haeni, 1991; Ru-(GPR) signals with hydrodynamic inverse modeling to identify the effective soil hydraulic properties of a sand in laboratory conditions.

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