Abstract

In young glaciated landscapes the variability of soil materials imparts a major control on crop growth and yield and environmental quality associated with production agriculture. Two common soil materials found on these glaciated landscapes are glacial till and reworked loess. Soil materials can be characterized by a combination of physical and morphological soil attributes. We hypothesized that penetration resistance is the response signal to a complex of multiple soil attributes and can be used as an integrating indicator to map soil materials. Our objective was to test the ability of a profile cone penetrometer to map soil materials at landscape-scale. The study site was located in southern Wisconsin, USA, on soils developed in reworked loess material overlying glacial till, which are classified as Typic or Mollic Hapludalfs and Typic Argiudolls. We collected a dense data set of cone index profiles from a 2.73 ha area on a 10 m grid up to depths of 1.3 m. Additionally, we collected soil cores randomly at 21 penetration locations and analyzed these by layer for texture, bulk density, and water content. We utilized point elevation data collected with a differential global positioning system to create a digital elevation model and derive slope and compound topographic index to subdivide the study area into landform element classes. We used expert knowledge to characterize soil materials and subsequently measured soil attributes to identify soil materials. A hierarchical cluster analysis was used to group cone index profiles. Combining the sparse soil material data with the dense cone index and landform element data resulted in soil material information covering the entire study area. The spatial distribution of soil materials was visualized using a three-dimensional soil layer model. The proposed method is associated with large uncertainties in some areas and can be recommended only for coarse mapping of contrasting soil materials such as glacial till and reworked loess at landscape-scale, when used in combination with landform element data.

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