Uncertainty analysis of predicted disturbance from off-road vehicular traffic in complex landscapes at fort hood |
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Authors: | Fang Shoufan Wente Stephen Gertner George Z Wang Guangxing Anderson Alan |
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Institution: | (1) W503 Turner Hall, 1102 South Goodwin, Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, Illinois 61801, USA, US;(2) USACERL, P.O. Box 9005, Champaign, Illinois 61820-1305, USA, US |
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Abstract: | The US Army Engineering Research Development Center (ERDC) uses a modified form of the Revised Universal Soil Loss Equation
(RUSLE) to estimate spatially explicit rates of soil erosion by water across military training facilities. One modification
involves the RUSLE support practice factor (P factor), which is used to account for the effect of disturbance by human activities
on erosion rates. Since disturbance from off-road military vehicular traffic moving through complex landscapes varies spatially,
a spatially explicit nonlinear regression model (disturbance model) is used to predict the distribution of P factor values
across a training facility. This research analyzes the uncertainty in this model's disturbance predictions for the Fort Hood
training facility in order to determine both the spatial distribution of prediction uncertainty and the contribution of different
error sources to that uncertainty. This analysis shows that a three-category vegetation map used by the disturbance model
was the greatest source of prediction uncertainty, especially for the map categories shrub and tree. In areas mapped as grass,
modeling error (uncertainty associated with the model parameter estimates) was the largest uncertainty source. These results
indicate that the use of a high-quality vegetation map that is periodically updated to reflect current vegetation distributions,
would produce the greatest reductions in disturbance prediction uncertainty. |
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Keywords: | : Support practice factor Disturbance Off-road vehicle traffic Uncertainty analysis Error budget RUSLE |
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