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Forestry Sciences Laboratory - Moscow, Idaho
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Soil & Water
Engineering Publications

Project Leader:
William J. Elliot
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Probabilistic soil erosion modeling using the Erosion Risk Management Tool (ERMiT) after wildfires.

Robichaud, P.R.; Elliot, W.J.; Wagenbrenner, J.W. 2011. Probabilistic soil erosion modeling using the Erosion Risk Management Tool (ERMiT) after wildfires. ISELE Paper Number 11039. International Symposium on Erosion and Landscape Evolution. 18-21 September 2011, Anchorage, Alaska. ASABE Publication Number 711P0311cd. 9 p.

Keywords: ERMiT, Wildfire, Erosion, WEPP, Postfire, Validation

Links: pdf PDF [105 KB]

Abstract: The decision of whether or not to apply post-fire hillslope erosion mitigation treatments, and if so, where these treatments are most needed, is a multi-step process. Land managers must assess the risk of damaging runoff and sediment delivery events occurring on the unrecovered burned hillslope. We developed the Erosion Risk Management Tool (ERMiT) to address this need. ERMiT is a web-based application that uses the Water Erosion Prediction Project (WEPP) technology to estimate sediment delivery, in probabilistic terms, on burned and recovering forest, range, and chaparral lands with and without the application of mitigation treatments. User inputs are processed by ERMiT to combine rain event variability with spatial and temporal variability of soil burn severity and soil properties, which are then used as WEPP input parameter values. Based on 20 to 40 individual WEPP runs, ERMiT produces a distribution of single sediment delivery rates with a probability of occurrence for each of five postfire years. In addition, sediment delivery rate distributions are generated for postfire hillslopes that have been treated with seeding, straw mulch, and erosion barriers such as contour-felled logs or straw wattles. Using postfire sediment data from 21 small instrumented watersheds (< 14 ha), we compared each storm.s measured sediment delivery to the ERMiT-predicted delivery. Observed delivery rates were within the predicted range of values 77 percent of the time, with 14 percent of the observed values being greater than the estimated range, and 9 percent being less than the predicted range. Most of the under predictions were associated with studies in the Colorado Front Range. The ERMiT tool tended to over predict sediment delivery in the Northern Rockies and in California. Only 3 percent of the observed delivery events were associated with snow melt processes, whereas 36 percent of the predicted values were influenced by snow melt. Based on these results, we are considering improvements such as incorporating erodibility values for more forest soil types, adjusting the weather characteristics in the climate generator, and reducing the occurrence of snow melt erosion response. Postfire assessment teams are actively using the ERMiT model for making hillslope mitigation treatment decisions based on the probability of damaging sediment delivery occurring after a wildfire.

Moscow FSL publication no. 2011h