Abstract: Finding a correspondence between soil hydraulic properties, such as saturated hydraulic conductivity (Ks) and apparent electrical conductivity (ECa) as an easily measurable parameter, may be a way forward to estimate the spatial distribution of hydraulic properties at the field scale. In this study, the spatial distributions of Ks, of soil ECa measured by a DUALEM-21S sensor and of soil physical properties were investigated in a sandy grassland. To predict field scale Ks, the statistical relationship between co-located soil Ks, and EMI-ECa was evaluated. Results demonstrated the large spatial variability of all studied properties with Ks being the most variable one (CV = 86.21%) followed by ECa (CV >= 53.77%). A significant negative correlation was found between In-transformed Ks and ECa (r = 0.83; P <= 0.01) at two depths of exploration (0-50 and 0-100 cm). This site specific relation between In Ks and ECa was used to predict saturated hydraulic conductivity over 0-50 cm depth for the whole field. The empirical relation was validated using an independent dataset of measured Ks. The statistical results demonstrate the robustness of this empirical relation with mean estimation error MEE = 0.46 (cm h(-1)), root-mean-square estimation errors RMSEE = 0.74 (cm h(-1)), coefficient of determination r(2) = 0.67 and coefficient of model efficiency Ce = 0.64. The relationship was then used to produce a detailed map of Ks for the whole field. The result will allow model predictions of spatially distributed water content in view of irrigation management. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: The soil at industrial sites is frequently characterized by very heterogeneous properties, which are often related to physical disturbance and contamination. A conventional approach to characterize the soil, with only a limited number of invasive observations, fails to capture the full extent of soil heterogeneity. Proximal soil sensing provides efficient tools to record spatially dense soil information. Nevertheless, because the output of most sensors is affected by more than one soil property, the simultaneous characterization of different soil properties requires the use of multiple sensors. Here, we apply multi-receiver electromagnetic induction (EMI) and stepped frequency ground penetrating radar (GPR) to survey a former gasworks site in a seaport area of Belgium. We used the EMI and GPR sensors in a motorized system to obtain densely sampled measurements of apparent electrical conductivity, apparent magnetic susceptibility and contrasts in relative dielectric permittivity. Our study shows that the sensors give detailed information on the variation in these electromagnetic soil properties. Interpretation of the variation in terms of the stratification of the soil was hampered by localized anthropogenic disturbances. However, the sensors provided complementary information that enabled the identification, discrimination and accurate location of several of these localized disturbances, including underground utility services such as electric cables, buried structures such as the remains of foundations and contamination by salts. Because these represent typical targets in industrial site investigation, we conclude that multi-receiver EMI and stepped frequency GPR provide a useful set of tools to expedite the investigation of industrial sites.