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@ARTICLE{Altdorff:827237,
      author       = {Altdorff, Daniel and von Hebel, Christian and Borchard,
                      Nils and van der Kruk, Jan and Bogena, Heye and Vereecken,
                      Harry and Huisman, Johan Alexander},
      title        = {{P}otential of catchment-wide soil water content prediction
                      using electromagnetic induction in a forest ecosystem},
      journal      = {Environmental earth sciences},
      volume       = {76},
      number       = {3},
      issn         = {1866-6299},
      address      = {Berlin},
      publisher    = {Springer},
      reportid     = {FZJ-2017-01431},
      pages        = {111},
      year         = {2017},
      abstract     = {Mapping of soil water content (SWC) by electromagnetic
                      induction (EMI) is an established method to obtain
                      field-scale SWC information. However, the relationship
                      between SWC and the apparent electrical conductivity (ECa)
                      measured with EMI is complex and affected by several
                      confounding factors at the catchment scale such as variable
                      porosity (ϕ) and pore water electrical conductivity (σw).
                      In this study, we investigated these confounding factors
                      using a time-lapse EMI data set obtained in a forest
                      ecosystem with soils of low ECa and catchment-wide SWC data
                      provided by a wireless soil moisture sensor network. To
                      assess the impact of variable ϕ on the accuracy of SWC
                      estimates, we compared three different models to relate SWC
                      and ECa: (i) a linear regression model and two nonlinear
                      models based on Archie’s equation with (ii) constant ϕ
                      and (iii) variable ϕ. The linear model reached a prediction
                      accuracy of RMSE = 5.83 $vol\%,$ while the Archie models
                      increased the accuracy to RMSE = 4.55 $vol\%$ (constant ϕ)
                      and RMSE = 4.20 $vol\%$ (variable ϕ). Although we found
                      strong spatial similarities between SWC and ECa maps, the
                      temporal trends in SWC and ECa were inconsistent. This was
                      attributed to temporal variations in σw due to seasonal
                      changes in ion concentrations of the soil pore water. To
                      support this hypothesis, σw was calculated from the
                      measured ECa and the known soil saturation from SoilNet. The
                      resulting σw maps showed highly structured and consistent
                      patterns. We thus conclude that in addition to variation in
                      SWC and ϕ, spatiotemporal variations of σw affected the
                      ECa measured with EMI. These potentially confounding factors
                      in the interpretation of EMI measurements in terms of SWC
                      have not been sufficiently recognized in the literature so
                      far, and the results presented in this study indicate a
                      range of limitations for the use of EMI to monitor
                      spatiotemporal changes in SWC at test sites with low ECa.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000393021800013},
      doi          = {10.1007/s12665-016-6361-3},
      url          = {https://juser.fz-juelich.de/record/827237},
}