Submitted to: Trans American Geophysical Union
Publication Type: Abstract only
Publication Acceptance Date: 12/5/2005
Publication Date: 12/5/2005
Citation: Robichaud, P.R., Ellion, W.J, Pierson, F.B., Hall, D.E., and Moffet, C.A. 2005. Predicting Postfire Hillslope Erosion with a Web-Based Probabilistic Model. Eos Transactions of the American Geophysical Union, 86(52), Fall Meeting Supplement, Abstract H34C-06. (CD-ROM) Interpretive Summary:
Technical Abstract: Modeling erosion after major disturbances, such as wildfire, has major challenges that need to be overcome. Fire-induced changes include increased erosion due to loss of the protective litter and duff, loss of soil water storage, and in some cases, creation of water repellent soil conditions. These conditions increase the potential for flooding, and sedimentation, which are of special concern to people who live and manage resources in the areas adjacent to burned areas. A web-based Erosion Risk Management Tool (ERMiT) has been developed to predict surface erosion from postfire hillslopes and to evaluate the potential effectiveness of various erosion mitigation practices. The model uses a probabilistic approach that incorporates variability in weather, soil properties, and burn severity for forests, rangeland, and chaparral hillslopes. The Water Erosion Prediction Project (WEPP) is the erosion prediction engine used in a Monte Carlo simulation mode to provide event-based erosion rate probabilities. The one-page custom interface is targeted for hydrologists and soil scientists. The interface allows users to select climate, soil texture, burn severity, and hillslope topography. For a given hillslope, the model uses a single 100-year run to obtain weather variability and then twenty 5- to 10-year runs to incorporate soil property, cover, and spatial burn severity variability. The output, in both tabular and graphical form, relates the probability of soil erosion exceeding a given amount in each of the first five years following the fire. Event statistics are provided to show the magnitude and rainfall intensity of the storms used to predict erosion rates. ERMiT also allow users to compare the effects of various mitigation treatments (mulches, seeding, and barrier treatments such as contour-felled logs or straw wattles) on the erosion rate probability. Date form rainfall simulation and concentrated flow (rill) techniques were used to parameterize ERMiT for these varied conditions. Model validation efforts are ongoing at nine paired watershed sites around the western US.