|Parsons, A. - UNIV LEICESTER, UK|
|Wainwright, J. - KING'S COLLEGE, LONDON UK|
|Abrahams, A. - SUNY, BUFFALO, NY|
Submitted to: Hydrological Processes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 1, 1996
Publication Date: N/A
Interpretive Summary: Surface runoff modeling, using systematic processes to have water traverse a hillslope from top to bottom, has been the goal of hydrologists and soil erosion experts for years. A process based runoff model would lead to more accurate models of soil erosion prediction and landscape evolution. A previously developed shrubland hillslope flow model was found to be somewhat portable to another site but was sensitive to data inputs and siz of areas being modeled. It is concluded that process-based modeling of hillslope runoff may not be a realistic tool for predicting soil erosion, but is one that may be useful for identification of areas where we poorly understand erosion processes. Such models help define the research agenda for soil erosion studies.
Technical Abstract: A distributed dynamic, process based model for interrill overland flow that has previously been shown to predict accurately both total runoff and runoff hydraulics for a site on shrubland is assessed in terms of (1) its portability, (2) its sensitivity to the quality of data inputs, and (3) its sensitivity to the size of cell used in the model. It is found that the model can be used at another site, but only after modifications to take into account local controls of runoff routing. The model has limited portability and is sensitive to both the quality of data input and the size of the cell. Data input cannot be reduced by use of stochastic distribution of model parameters without significant loss of accuracy in model predictions, particularly of runoff hydraulics. Large cells produce poorer predictions of the runoff hydrograph. It is concluded that process-based modeling of interrill runoff may not be a realistic tool lfor predicting soil erosion, but is one that may be useful for identification of areas where we poorly understand erosion processes. Such models help define the research agenda for soil erosion studies.