H51G-0692:
Remote Sensing-based Models of Soil Vulnerability to Compaction and Erosion from Off-highway Vehicles

Friday, 19 December 2014
Miguel L Villarreal1, Robert H Webb2, Laura Norman3, Jennifer Psillas4, Abigail Rosenberg5, Shinji Carmichael2, Roy Petrakis6 and Philip Sparks6, (1)US Geological Survey, Western Geographic Science Center, Menlo Park, CA, United States, (2)USGS Arizona Water Science Center, Tucson, AZ, United States, (3)US Geological Survey, Western Geographic Science Center, Tucson, AZ, United States, (4)University of Arizona, School of Natural Resources and the Environment, Tucson, AZ, United States, (5)USMC, Yuma, AZ, United States, (6)University of Arizona, Tucson, AZ, United States
Abstract:
Intensive off-road vehicle use for immigration, smuggling, and security of the United States-Mexico border has prompted concerns about long-term human impacts on sensitive desert ecosystems. To help managers identify areas susceptible to soil erosion from vehicle disturbances, we developed a series of erosion potential models based on factors from the Revised Universal Soil Loss Equation (RUSLE), with particular focus on the management factor (P-factor) and vegetation cover (C-factor). To better express the vulnerability of soils to human disturbances, a soil compaction index (applied as the P-factor) was calculated as the difference in saturated hydrologic conductivity (Ks) between disturbed and undisturbed soils, which was then scaled up to remote sensing-based maps of vehicle tracks and digital soils maps. The C-factor was improved using a satellite-based vegetation index, which was better correlated with estimated ground cover (r2 = 0.77) than data derived from regional land cover maps (r2 = 0.06). RUSLE factors were normalized to give equal weight to all contributing factors, which provided more management-specific information on vulnerable areas where vehicle compaction of sensitive soils intersects with steep slopes and low vegetation cover. Resulting spatial data on vulnerability and erosion potential provide land managers with information to identify critically disturbed areas and potential restoration sites where off-road driving should be restricted to reduce further degradation.