A Filtering Approach to the Estimation of Model Parameters in the Vegetative Canopy Model

Abstract

The drag-force model for canopy flows has difficulty in preparing appropriate drag coefficients C_D to the canopy layer, even if its geometrical structure is quite simple. To overcome this problem, we employed a unique approach in our past studies where a microscopic fully-resolved simulation of the target flow on a fine grid (called preliminary analysis) is performed to extract a proper C_D for the target canopy layer in advance of the macroscopic prediction on a coarse grid together with the drag-force model (main analysis). This approach can clarify what is essential or less essential information in the model parameters for a better prediction of canopy flows. In the present study, under the framework of this approach, we try to incorporate the dependence of the canopy density X on the spatial resolution of the main analysis into the drag force model. The influence becomes especially significant in sparse canopies. Here, we introduce two modifications to our past approach. First, we choose C_DX instead of C_D as the model parameter to be extracted from the preliminary analysis results. Second, in the model parameter extraction process, we apply spatial filtering to the data obtained from the preliminary analysis to remove high-wavenumber components that cannot be represented on the coarse grid. Application of the method has demonstrated an improved accuracy in the prediction of an open-channel flow with patched vegetation zones.