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In precision agriculture geoelectrical methods have shown their capability to detect spatial variation of important physico-chemical soil parameters in an efficient way. Nevertheless, relationships between the electrical parameters (electrical conductivity or resistivity) and other soil properties are not always consistent over different fields. This can, to some extent, be due to the characteristics of instruments used for soil mapping. However, a limited amount of research has addressed this issue. In this study, seven instruments for mobile mapping (continuous geoelectrical measurements) available on the market were tested (ARP 03, CM-138, EM38, EM38-DD, EM38-MK2, OhmMapper and Veris 3100). Instruments were employed on a sandy site in north-east Germany. Measurements were compared to a profile, which has been investigated with a high accuracy reference. Additional investigations were conducted concerning the influences of temperature drift, seasonal variations and soil properties on soil EC. Marked differences between the instruments were found with respect to depth of investigation, accuracy and handling that have to be taken into account when geoelectrical surveys are planned or interpreted. Regarding depth of investigation and robustness of the measurements, ARP 03 and Veris 3100 seem to be the most suitable instruments for precision agriculture.
The intention of the presented study is to gain a better understanding of the mechanisms that caused the bimodal rainfall-runoff responses which occurred up to the mid-1970s regularly in the Schafertal catchment and vanished after the onset of mining activities. Understanding, this process is a first step to understanding the ongoing hydrological change in this area. It is hypothesized that either subsurface stormflow, or fast displacement of groundwater, could cause the second delayed peak. A top-down analysis of rainfall-runoff data, field observations as well as process modelling are combined within a rejectionistic framework. A statistical analysis is used to test whether different predictors. which characterize the forcing. near surface water content and deeper subsurface store, allow the prediction of the type of rainfall-runoff response. Regression analysis is used with generalized linear models Lis they can deal with non-Gaussian error distributions Lis well its a non-stationary variance. The analysis reveals that the dominant predictors are the pre-event discharge (proxy of state of the groundwater store) and the precipitation amount, In the field campaign, the subsurface at a representative hillslope was investigated by means of electrical resistivity tomography in order to identify possible strata as flow paths for subsurface stormflow. A low resistivity in approximately 4 in depth-either due to a less permeable layer or the groundwater surface-was detected. The former Could serve as a flow path for subsurface stormflow. Finally, the physical-based hydrological model CATFLOW and the groundwater model FEFLOW are compared with respect to their ability to reproduce the bimodal runoff responses. The groundwater model is able to reproduce the observations, although it uses only an abstract representation of the hillslopes. Process model analysis as well Lis statistical analysis strongly suggest that fast displacement of groundwater is the dominant process underlying the bimodal runoff reactions.