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This article in SSSAJ

  1. Vol. 71 No. 6, p. 1740-1747
    Received: May 3, 2006

    * Corresponding author(s): ulrich.weller@ufz.de
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Mapping Clay Content across Boundaries at the Landscape Scale with Electromagnetic Induction

  1. U. Weller *a,
  2. M. Zipprichb,
  3. M. Sommerb,
  4. W. Zu Castellc and
  5. M. Wehrhand
  1. a Helmholtz Centre for Environ. Research-UFZ, Dep. of Soil Physics, Theodor Lieser Str. 4, 06120 Halle (Saale), Germany
    b ZALF-Leibniz Centre for Agric. Landscape Res., Institute of Soil Landscape Research, Eberswalder Str. 84, 15374 Müncheberg, Germany and Univ. of Potsdam, Institute of Geoecology, PO Box 601553, D-14415 Potsdam, Germany
    c GSF-National Res. Centre for Environment and Health, Institute of Biomathematics and Biometry, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany
    d ZALF-Leibniz Centre for Agric. Landscape Res., Institute of Soil Landscape Research, Eberswalder Str. 84, 15374 Müncheberg, Germany


Detailed information on soil textural heterogeneity is essential for land management and conservation. It is well known that in individual fields, measurement of the soil's apparent electrical conductivity (ECa) offers an opportunity to map the clay content of soils with free drainage under a humid climate. At the catchment scale, however, units of different land management and differing sampling dates add variation to ECa and constrain the mapping across field boundaries. We analyzed their influence and compared three approaches for applying electromagnetic induction (EMv) to clay-content mapping at the landscape scale across the boundaries of individual fields and different sampling dates. In the study region, a separate calibration of the relation between clay and ECa for each field and sampling date (fieldwise calibration) yielded satisfactory clay-content predictions only if the costly precondition of sufficient calibration points for each field was fulfilled. We propose a method (nearest-neighbors ECa correction) for unifying ECa across boundaries based only on the ECa data themselves, and the assumption of continuity of textural properties at field boundaries, which was fulfilled in the landscape studied. Prediction is calibrated once for the entire landscape, which allows a reduced set of calibration points. The coefficient of determination for predicting clay content (here, including silt <4 μm) was improved from R 2 = 0.66 (no correction for land use and sampling date) to R 2 = 0.85 (n = 46). With the method developed, ECa offers a powerful and cheap method of clay-content mapping in agricultural landscapes.

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