@article{WalterLueckHelleretal.2019,
  author    = {Walter, J. and L{\"u}ck, Erika and Heller, C. and Bauriegel, Albrecht and Zeitz, Jutta},
  title     = {Relationship between electrical conductivity and water content of peat and gyttja},
  series = {Near surface geophysics},
  volume    = {17},
  journal   = {Near surface geophysics},
  number    = {2},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1569-4445},
  doi       = {10.1002/nsg.12030},
  pages     = {169 -- 179},
  year      = {2019},
  abstract  = {The application of electrical resistivity tomography to peatlands supports conventional coring by providing data on the current condition of peatlands, including data on stratigraphy, peat properties and thickness of organic deposits. Data on the current condition of drained peatlands are particularly required to improve estimates of carbon storage as well as losses and emissions from agriculturally used peatlands. However, most of the studies focusing on electrical resistivity tomography surveys have been conducted on natural peatlands with higher groundwater levels. Peatlands drained for agriculture have not often been studied using geophysical techniques. Drained sites are characterized by low groundwater levels and high groundwater fluctuations during the year, which lead to varying levels of water saturation. To validate better electrical resistivity tomography surveys of drained peatlands, the aim of this laboratory study is to investigate the influence of varying water saturation levels on electrical conductivity (reciprocal of resistivity) for a variety of peat and gyttja types, as well as for different degrees of peat decomposition. Results show that different levels of water saturation strongly influence bulk electrical conductivity. Distinct differences in this relationship exist between peat and gyttja substrates and between different degrees of peat decomposition. Peat shows an exponential relationship for all degrees of decomposition, whereas gyttja, in particular organic-rich gyttja, is characterized by a rather unimodal relationship. The slopes for the relationship between electrical conductivity and water content are steeper at high degrees of decomposition than for peat of low degrees of decomposition. These results have direct implications for field electrical resistivity tomography surveys. In drained peatlands that are strongly susceptible to drying, electrical resistivity tomography surveys have a high potential to monitor the actual field water content. In addition, at comparable water saturations, high or low degrees of decomposition can be inferred from electrical conductivity.},
  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}
}