Use of upscaled elevation and surface roughness data in two-dimensional surface water models

In this paper, we present an approach that uses a combination of cell-block- and cell-face-averaging of high-resolution cell elevation and roughness data to upscale hydraulic parameters and accurately simulate surface water flow in relatively low-resolution numerical models. The method developed allows channelized features that preferentially connect large-scale grid cells at cell interfaces to be represented in models where these features are significantly smaller than the selected grid size. The developed upscaling approach has been implemented in a two-dimensional finite difference model that solves a diffusive wave approximation of the depth-integrated shallow surface water equations using preconditioned Newton–Krylov methods. Computational results are presented to show the effectiveness of the mixed cell-block and cell-face averaging upscaling approach in maintaining model accuracy, reducing model run-times, and how decreased grid resolution affects errors. Application examples demonstrate that sub-grid roughness coefficient variations have a larger effect on simulated error than sub-grid elevation variations.

► We have developed a method for upscaling high-resolution data in coarsely gridded two-dimensional models. ► Channelized features imbedded in coarse grid cells have the greatest effect on model errors. ► Approaches used to calculate compound-composite roughness coefficients need to be carefully considered when upscaling high-resolution data. ► Application of the upscaling approach is demonstrated using several test cases.