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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 17, issue 4
Hydrol. Earth Syst. Sci., 17, 1297–1307, 2013
https://doi.org/10.5194/hess-17-1297-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 17, 1297–1307, 2013
https://doi.org/10.5194/hess-17-1297-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 02 Apr 2013

Research article | 02 Apr 2013

Assessment of shallow subsurface characterisation with non-invasive geophysical methods at the intermediate hill-slope scale

S. Popp, D. Altdorff, and P. Dietrich S. Popp et al.
  • UFZ, Helmholtz Centre for Environmental Research, Department Monitoring and Exploration Technologies, Leipzig, Germany

Abstract. Hill-slopes of several hectares in size represent a difficult scale for subsurface characterisation, as these landscape units are well beyond the scope of traditional point-scale techniques. By means of electromagnetic induction (EMI) and gamma-ray spectroscopy, spatially distributed soil proxy data were collected from a heterogeneous hill-slope site. Results of EMI mapping using the EM38DD showed that soil electrical conductivity (ECa) is highly variable at both temporal and spatial scales. Calibration of the integral ECa signal to a specific target like soil moisture is hampered by the ambiguous response of EMI to the clay-rich hill-slope underground. Gamma-ray results were obtained during a single survey, along with EMI measurements and selected soil sampling. In contrast to ECa, a noticeable correlation between Total Count and K emission data and soil-water content seemed to be present. Relevant proxy variables from both methods were used for k means clustering in order to distinguish between hill-slope areas with different soil conditions. As a result, we obtained a suitable partition of hill-slope that was comparable with a previously obtained zonation model based on ecological factors.

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