Profile cone penetrometer data used to distinguish between soil materials

Citation
S. Grunwald et al., Profile cone penetrometer data used to distinguish between soil materials, SOIL TILL R, 62(1-2), 2001, pp. 27-40
Citations number
31
Categorie Soggetti
Agriculture/Agronomy
Journal title
SOIL & TILLAGE RESEARCH
ISSN journal
01671987 → ACNP
Volume
62
Issue
1-2
Year of publication
2001
Pages
27 - 40
Database
ISI
SICI code
0167-1987(200110)62:1-2<27:PCPDUT>2.0.ZU;2-S
Abstract
In young glaciated landscapes the variability of soil materials imparts a m ajor control on crop growth and yield and environmental quality associated with production agriculture. Two common soil materials found on these glaci ated landscapes are glacial till and reworked loess. Soil materials can be characterized by a combination of physical and morphological soil attribute s. We hypothesized that penetration resistance is the response signal to a complex of multiple soil attributes and can be used as an integrating indic ator to map soil materials. Our objective was to test the ability of a prof ile cone penetrometer to map soil materials at lands cape-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 Mo llic 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. W e utilized point elevation data collected with a differential global positi oning system to create a digital elevation model and derive slope and compo und topographic index to subdivide the study area into landform element cla sses. We used expert knowledge to characterize soil materials and subsequen tly measured soil attributes to identify soil materials. A hierarchical clu ster analysis was used to group cone index profiles. Combining the sparse s oil material data with the dense cone index and landform element data resul ted in soil material information covering, the entire study area. The spati al distribution of soil materials was visualized using a three-dimensional soil layer model. The proposed method is associated with large uncertaintie s in some areas and can be recommended only for coarse mapping of contrasti ng soil materials such as glacial till and reworked loess at landscape-scal e, when used in combination with landform. element data. (C) 2001 Elsevier Science B.V. All rights reserved.