@article{GebbersLueckDabasetal.2009,
  author    = {Gebbers, Robin and Lueck, Erika and Dabas, Michel and Domsch, Horst},
  title     = {Comparison of instruments for geoelectrical soil mapping at the field scale},
  issn      = {1569-4445},
  doi       = {10.3997/1873-0604.2009011},
  year      = {2009},
  abstract  = {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.},
  language  = {en}
}
@article{WalterLueckBauriegeletal.2015,
  author    = {Walter, Judith and Lueck, Erika and Bauriegel, Albrecht and Richter, C. and Zeitz, Jutta},
  title     = {Multi-scale analysis of electrical conductivity of peatlands for the assessment of peat properties},
  series = {European journal of soil science},
  volume    = {66},
  journal   = {European journal of soil science},
  number    = {4},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {1351-0754},
  doi       = {10.1111/ejss.12251},
  pages     = {639 -- 650},
  year      = {2015},
  abstract  = {Peatlands store large amounts of carbon. This storage function has been reduced through intensive drainage, which leads to the decomposition of peat, resulting in a loss of carbon. Measurements of the real (sigma) and imaginary part (sigma) of electrical conductivity can deliver information on peat properties, such as the pore fluid conductivity (sigma(w)), cation exchange capacity (CEC), bulk density ((b)), water content (WC) and soil organic matter (SOM) content. These properties change with the peat's degree of decomposition (DD). To explore the relationships between the peat properties, sigma, sigma and DD, we focused on three different types of survey and scales. First, point measurements were made with a conductivity probe at various locations over a large area of northeast Germany to determine the degree of correlation between sigma and DD. Second, nine of these locations were selected for sampling to determine which of the properties sigma(w), CEC, (b), WC and SOM predominantly influence sigma and sigma. This multisite dataset includes the entire range of DD and was analysed in the laboratory. Third, one site was selected for a survey of sigma including sampling, to identify which properties mainly control sigma in a single-site approach. Statistical analysis revealed that for the multisite laboratory dataset, sigma(w) has the strongest effect on sigma, followed by CEC, whereas sigma is mainly determined by CEC. In a single-site approach, WC followed by CEC had a dominant effect on sigma. No clear correlation could be observed between (i) DD and peat properties and (ii) DD and sigma or sigma. This is because of the complex changes in properties with increasing DD.},
  language  = {en}
}
@article{BronstertCreutzfeldtGraeffetal.2012,
  author    = {Bronstert, Axel and Creutzfeldt, Benjamin and Gr{\"a}ff, Thomas and Hajnsek, Irena and Heistermann, Maik and Itzerott, Sibylle and Jagdhuber, Thomas and Kneis, David and Lueck, Erika and Reusser, Dominik and Zehe, Erwin},
  title     = {Potentials and constraints of different types of soil moisture observations for flood simulations in headwater catchments},
  series = {Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards},
  volume    = {60},
  journal   = {Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards},
  number    = {3},
  publisher = {Springer},
  address   = {New York},
  issn      = {0921-030X},
  doi       = {10.1007/s11069-011-9874-9},
  pages     = {879 -- 914},
  year      = {2012},
  abstract  = {Flood generation in mountainous headwater catchments is governed by rainfall intensities, by the spatial distribution of rainfall and by the state of the catchment prior to the rainfall, e. g. by the spatial pattern of the soil moisture, groundwater conditions and possibly snow. The work presented here explores the limits and potentials of measuring soil moisture with different methods and in different scales and their potential use for flood simulation. These measurements were obtained in 2007 and 2008 within a comprehensive multi-scale experiment in the Weisseritz headwater catchment in the Ore-Mountains, Germany. The following technologies have been applied jointly thermogravimetric method, frequency domain reflectometry (FDR) sensors, spatial time domain reflectometry (STDR) cluster, ground-penetrating radar (GPR), airborne polarimetric synthetic aperture radar (polarimetric SAR) and advanced synthetic aperture radar (ASAR) based on the satellite Envisat. We present exemplary soil measurement results, with spatial scales ranging from point scale, via hillslope and field scale, to the catchment scale. Only the spatial TDR cluster was able to record continuous data. The other methods are limited to the date of over-flights (airplane and satellite) or measurement campaigns on the ground. For possible use in flood simulation, the observation of soil moisture at multiple scales has to be combined with suitable hydrological modelling, using the hydrological model WaSiM-ETH. Therefore, several simulation experiments have been conducted in order to test both the usability of the recorded soil moisture data and the suitability of a distributed hydrological model to make use of this information. The measurement results show that airborne-based and satellite-based systems in particular provide information on the near-surface spatial distribution. However, there are still a variety of limitations, such as the need for parallel ground measurements (Envisat ASAR), uncertainties in polarimetric decomposition techniques (polarimetric SAR), very limited information from remote sensing methods about vegetated surfaces and the non-availability of continuous measurements. The model experiments showed the importance of soil moisture as an initial condition for physically based flood modelling. However, the observed moisture data reflect the surface or near-surface soil moisture only. Hence, only saturated overland flow might be related to these data. Other flood generation processes influenced by catchment wetness in the subsurface such as subsurface storm flow or quick groundwater drainage cannot be assessed by these data. One has to acknowledge that, in spite of innovative measuring techniques on all spatial scales, soil moisture data for entire vegetated catchments are still today not operationally available. Therefore, observations of soil moisture should primarily be used to improve the quality of continuous, distributed hydrological catchment models that simulate the spatial distribution of moisture internally. Thus, when and where soil moisture data are available, they should be compared with their simulated equivalents in order to improve the parameter estimates and possibly the structure of the hydrological model.},
  language  = {en}
}
@article{GraeffZeheReusseretal.2009,
  author    = {Gr{\"a}ff, Thomas and Zehe, Erwin and Reusser, Dominik and Lueck, Erika and Schroeder, Boris and Wenk, Gerald and John, Hermann and Bronstert, Axel},
  title     = {Process identification through rejection of model structures in a mid-mountainous rural catchment : observations of rainfall-runoff response, geophysical conditions and model inter-comparison},
  issn      = {0885-6087},
  doi       = {10.1002/Hyp.7171},
  year      = {2009},
  abstract  = {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.},
  language  = {en}
}