4.7 Article

Identifying subsoil variation associated with gilgai using electromagnetic induction

Journal

GEODERMA
Volume 295, Issue -, Pages 34-40

Publisher

ELSEVIER
DOI: 10.1016/j.geoderma.2017.01.029

Keywords

Apparent electrical conductivity; Vertisol; Gilgai; Proximal sensing; EM38

Categories

Funding

  1. National Science Foundation [EAR 0911317]

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Proximal sensing, such as electromagnetic induction, has been used to map the spatial distribution of soil properties; however, the response of these instruments to short-interval variability associated with Vertisols has not been studied. Meter-scale circular landscape features called gilgai, which are associated with surface and subsurface variability, make sampling these soils difficult, especially if the surface has been plowed. The EM38 is an electromagnetic induction tool with a relatively small spatial footprint (1 m(2)), which may be fine enough to identify subsoil variability associated with gilgai. In 2011, an EM38 survey was conducted for a 40 by 50 m field with intact circular gilgai in the Texas Blackland Prairies. Soil properties including gravimetric water content, bulk density, inorganic C content, and electrical conductivity of the soil solution were measured. In 2012, half of the field was plowed, and another EM38 survey was conducted. The EM38 was able to locate subsurface variability in soil properties between microhighs and microlows under both intact and plowed conditions. Semi-variance of soil properties increased with increasing distance and reached maximum variance at 3 m, corresponding to the average diameter of gilgai features. The overall variability across the study site decreased after plowing, Water content and inorganic C content were the primary soil properties that forced the response of the EM38 in these landscapes, and the partial correlation coefficient suggests the effects of water content and inorganic C content on EM38 response are independent. In calcareous Vertisols, the EM38 can be used to identify subsurface variability and may be useful in developing sampling schemes for Vertisol classification, soil sampling, and fine-scale digital soil mapping. (C) 2017 Published by Elsevier B.V.

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