Stochastic simulation of soil strength/compaction and assessment of corn yield risk using threshold probability patterns

Soil compaction can suppress crop yields. Thus, compaction indices such as cone penetration resistance (PR) can be useful to farmers and researchers interested in identifying areas in the field where soil strength/compaction, or governing soil properties reflected by PR measurements, might be problematic to crop yield. The general aim of this paper was to apply stochastic simulation to spatially delimit critically important soil strength patterns, the spatial disposition and uncertainty of those patterns, and to determine if broad strength/compaction spatial units defined via PR threshold probability patterns could be used to reflect corn yield variability under different rotation, tillage, and trafficking management treatments. Shallow (3–15 cm depth) linear PR patterns were strongly anisotropic while deeper patterns (25–40 cm depth) were more regionalized in character. Stochastic simulation produced very strong global patterns of low (2 MPa) PR values. Broad spatial units defined on the basis of these patterns were used to generate corn yield risk maps. It was found that yields, under the various treatments, reflected the risk patterns in an expected way 75% of the time over 5 years of observation. That is, under similar management treatments, lower risk areas (areas where there was lower probability of soil strength exceeding 2 MPa in the top 3 to 15 cm of the soil) produced higher yields than higher risk areas (areas where there was higher probability of soil strength exceeding 2 MPa in the top 3 to 15 cm of soil).