Hydrogeophysical characterization of subsurface processes and properties in the critical zone

Friday, 18 December 2015: 08:00
3014 (Moscone West)
Harry Vereecken1, Johan Alexander Huisman1,2, Daniel Altdorf1, Christian von Hebel1, Nils Gueting1, Anja Klotzsche1 and Jan Van Der Kruk1, (1)Agrosphere Institute (IBG-3) Forschungszentrum Jülich, Deutschland, Germany, (2)Forschungszentrum Jülich, Agrosphere (IBG 3), Jülich, Germany
Hydrogeophysical methods are ideally suited to characterize subsurface hydrologic structures and processes within the critical zone. Recent improvements in the acquisition and inversion of Ground Penetrating Radar (GPR) and ElectroMagnetic Induction (EMI) data now enable to characterize the subsurface in terms of spatially distributed information on soil and hydrologic properties, and to monitor hydrological processes using time-lapse measurements. We will illustrate these new developments by presenting three example cases. The first case illustrates the potential of using GPR full-waveform inversion techniques to obtain detailed information on subsurface porosity. For this purpose, we used cross-borehole GPR measurements along a series of longitudinal and transversal transects at the test site Krauthausen. The obtained information is key for modelling flow and solute transport because the high resolution of the GPR inversion results allows to study the effect of hydraulic connectivity on solute transport. In the following two cases, we illustrate the potential of multi-receiver electromagnetic induction (EMI) sensors that enable the imaging of the soil at different depths. The second case deals with the mapping of peat land properties at the field scale. We used multi-coil offset EMI measurements to provide spatial estimates of SOC content, bulk density, and SOC stock. Together with laser scanning elevation and soil core reference data, regression equations were built predicting SOC content, bulk density, and SOC stocks. EMI-derived explanatory variables were shown to strongly determine the prediction quality of the regression equations. In the last example, we investigated the origin of observed leaf area index (LAI) patterns that indicate crop performance. Using multi-coil offset EMI, we obtained a moderate to excellent spatial consistency of ECa and LAI patterns. It was concluded from these EMI measurements that improved crop performance was related to a higher water storage capacity as well as a higher subsoil clay content. Overall, these two case studies clearly showed that this new generation of EMI devices can be used to obtain quantitative information about dominant features in subsurface layering up to a depth of 2 m for areas up to several hectares in a fast and non-invasive manner.