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United States Department of Agriculture

Agricultural Research Service

Title: A Probabilistic Approach to Modeling Erosion for Spatially Varied Conditions

Authors
item Elliot, W - FOREST SERVICE
item Robichaud, P - FOREST SERVICE
item Hall, D - FOREST SERVICE
item Cuhuciyan, C - WASHINGTON STATE UNIV
item Pierson, Frederick
item Wohlgemuth, P - FOREST SERVICE

Submitted to: American Society of Agricultural Engineers
Publication Type: Trade Journal
Publication Acceptance Date: July 30, 2001
Publication Date: N/A

Interpretive Summary: In the years following a major forest disturbance, such as fire, the erosion rate is greatly influenced by spatial and temporal variability in weather, in soil properties, and in vegetation. This paper presents a method to incorporate these variabilities into the estimates of soil erosion. The effect of vegetation on soil erodibility is combined with variation in weather and spatially variable soil conditions to predict the probabilities of single storm and annual soil erosion rates in the years following the disturbance. By redefining the probability distributions of the soils, erosion during the recovering years, and impacts of mitigation on erosion can be determined from the same initial set of computer runs.

Technical Abstract: In the years following a major forest disturbance, such as fire, the erosion rate is greatly influenced by variability in weather, in soil properties, and in spatial distribution. This paper presents a method to incorporate these variabilities into the erosion rate predicted by the Water Erosion Prediction Project model. It appears that it is not necessary to describe both the soil and the vegetation effects of the disturbance. Incorporating the vegetation effects on soil erodibility, and its associated variability, is sufficient-when combined with weather and spatial variability-to-predict the probabilities of single storm and annual soil erosion rates in the years following the disturbance. By redefining the probability distributions of the soils, erosion during the recovering years, and impacts of mitigation on erosion can be determined from the same initial set of computer runs.

Last Modified: 7/28/2014
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