Predicting unsaturated soil strength of coarse-grained soils for mobility assessments

Abstract

Accurately estimating surficial soil moisture and strength is integral to determining vehicle mobility and is especially important over large spatial extents at fine resolutions. While methods exist to estimate soil strength across landscapes, they are empirical and rely on class average soil behavior. The Strength of Surficial Soils (STRESS) model was developed to estimate moisture-variable soil strength with a physics-based approach. However, there is a lack of field data from a diverse landscape to evaluate the STRESS model. To test the STRESS model, a field study was conducted in northern Colorado. Soil moisture and strength were measured on 10 dates. Data from the surficial layer (0–5 cm) were used to test the STRESS model and determine if soil strength trends could be estimated from topographical and soil textural differences. High variability was observed in soil strength measurements stemming from fine-scale terrain features and user variability. Observations show lower soil strengths for greater soil moistures, steeper slopes, higher vegetation, and lower soil fines content. STRESS estimated rating cone index values with a mean relative error of 37.5 %, while a pre-existing model had a mean relative error of 47.4 %. The STRESS model outperforms the current RCI prediction method, but uncertainty remains large.