|Institution:||University of Illinois – Urbana-Champaign|
|Keywords:||Soil Shear Strength|
|Full text PDF:||http://hdl.handle.net/2142/72935|
The degradation of military training lands due to vehicular traffic presents a challenge for land managers trying to optimize training capacity while reducing impacts. The Optimal Allocation of Land for Training and Non-Training Uses (OPAL) Program aims to provide a model for land managers to predict impacts of training under a range of land management regimes utilizing soil, vegetation, and climatic data. In general, OPAL???s intended purpose is to help land managers optimize training land carrying capacity. As part of OPAL, the Vegetation And Soil Shear Tester (VASST) was developed as a new method of in-situ measurement for shear strength of vegetated soils. During this research, data on vegetation and soil parameters was collected concurrently with VASST measurements at five geographic locations to determine if the VASST effectively measured soil shear strength. Additionally, as part of this study, a Python program was developed to automate the process of conditioning and analyzing VASST outputs to reduce human bias and dramatically decrease processing times of raw data. Evaluating the VASST against calculated soil shear strength as well as other common in-situ strength measurements such as cone index, drop-cone value, and Clegg impact values, confirmed that the VASST shear measurements were moderately to strongly correlated with one another. An investigation into potential associations of soil parameters to strength measurements obtained with the VASST was conducted. VASST measures were taken in high plasticity (clayey) and non-plastic (sandy) soils where soil strengths were dictated by particle size, aboveground biomass, and root weight. Results also indicated that soil moisture content influenced VASST measured soil shear strength in high plasticity soils.