Wildfires

Targeted Forestry Management in the Lake Tahoe Basin with WEPPcloud and PI-VAT

The growing size and frequency of wildfires in the Western US has pressed a sense of urgency on the Forest Service, other land management agencies and many municipalities on developing fuel management and post-fire mitigation plans. With fuel management practices there is a risk that the management process itself (e.g. thinning and prescribed fire) might lead to more long term erosion compared to doing nothing and gambling that the forest will not be burned by a wildfire. After a wildfire occurs, managers must balance the risk of post-fire erosion with the expense required to protect the soil from an extreme event with an agricultural or wood-based mulch. In the Tahoe basin, we have been using a site-specific, process-based erosion model, WEPPcloud, to identify landscape positions that are most susceptible to erosion by thinning operations or under post-fire wildfire conditions. The WEPPcloud model was used to evaluate the probability of erosion under current undisturbed conditions, various timber harvesting scenarios, prescribed fire, and post-wildfire conditions. The distribution of soil burn severity for future wildfires was simulated using a trained geostatistical approach based on historic regional wildfires. Using WEPPcloud and a newly developed post-processing R shiny app, PI-VAT, which allows prioritization and targeting analysis across multiple watersheds and multiple treatment scenarios, we map the specific hillslopes that are most sensitive to disturbance and provide an optimization approach to guide managers and land use planners in selecting the areas which provide the greatest reduction in sediment load through erosion mitigation activities. Using various statistical analyses, we identify the key soil, vegetative, topographic, and climatic factors that best describe the distributed soil erosion potential following fuel management throughout the basin. Through this analysis we provide recommendations to guide future fuel management based on measurable landscape characteristics. We analyzed sensitive landscape characteristics such as slope length, soil steepness, soil depth, and mean annual precipitation, among other variables, and their effects on soil erosion. Results are displayed in a variety of interactive graphs, tables and descriptive text which aid managers in interpretation. The WEPPcloud analysis and interpretation with the PI-VAT tool was applied to the Lake Tahoe basin to assess the key soil and landscape characteristics driving soil erosion in the basin. Of particular interest to managers in the basin was the sensitivity between soil erosion and slope steepness. The analysis revealed slope steepness, slope length, and annual precipitation drive much of the variability and suggest spatially explicit timber harvest recommendations based on these factors would minimize the risk of erosion following timber harvest for fuel management. These tools provide managers with access to complex result into easy-to-use information for decision making.