Validation of a probabilistic post-fire erosion model
Peter R. Robichaud A C , William J. Elliot A , Sarah A. Lewis A and Mary Ellen Miller B
+ Author Affiliations
- Author Affiliations
A US Department of Agriculture, Forest Service, Rocky Mountain Research Station, 1221 South Main Street, Moscow, ID 83843, USA.
B Michigan Technology Research Institute, Michigan Technological University, 3600 Green Court, Suite 100, Ann Arbor, MI 48105, USA.
C Corresponding author. Email: probichaud@fs.fed.us
International Journal of Wildland Fire 25(3) 337-350 https://doi.org/10.1071/WF14171
Submitted: 24 September 2014 Accepted: 18 January 2016 Published: 29 February 2016
Abstract
Post-fire increases of runoff and erosion often occur and land managers need tools to be able to project the increased risk. The Erosion Risk Management Tool (ERMiT) uses the Water Erosion Prediction Project (WEPP) model as the underlying processor. ERMiT predicts the probability of a given amount of hillslope sediment delivery from a single rainfall or snowmelt event on unburned, burned and recovering forest, range and chaparral hillslopes and the effectiveness of selected mitigation treatments. Eight published field study sites were used to compare ERMiT predictions with observed sediment deliveries. Most sites experienced only a few rainfall events that produced runoff and sediment (1.3–9.2%) except for a California site with a Mediterranean climate (45.6%). When sediment delivery occurred, pooled Spearman rank correlations indicated significant correlations between the observed sediment delivery and those predicted by ERMiT. Correlations were ρ = 0.65 for the controls, ρ = 0.59 for the log erosion barriers and ρ = 0.27 (not significant) for the mulch treatments. Half of the individual sites also had significant correlations, as did 6 of 7 compared post-fire years. These model validation results suggest reasonable estimates of probabilistic post-fire hillslope sediment delivery when compared with observations from eight field sites.
Additional keywords: erosion prediction, FS WEPP, post-fire assessment, probabilistic model.
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