An effective depression filling algorithm for DEM-based 2-D surface flow modelling
The surface runoff process in fluvial/pluvial flood modelling is often simulated employing a two-dimensional (2-D) diffusive wave approximation described by grid based digital elevation models (DEMs). However, this approach may cause potential problems when using the 2-D surface flow model which exchanges flows through adjacent cells, with conventional sink removal algorithms which also allow for flow exchange along diagonal directions, due to the existence of artificial depression in DEMs. In this paper, we propose an effective method for filling artificial depressions in DEM so that the problem can be addressed. We firstly analyse two types of depressions in DEMs and demonstrate the issues caused by the current depression filling algorithms using the surface flow simulations from the MIKE SHE model built for a medium-sized basin in Southeast England. The proposed depression-filling algorithm for 2-D overland flow modelling is applied and evaluated by comparing the simulated flows at the outlet of the catchment represented by DEMs at various resolutions (50 m, 100 m and 200 m). The results suggest that the existence of depressions in DEMs can substantially influence the overland flow estimation and the new depression filling algorithm is shown to be effective in tackling this issue based upon the comparison of simulations for sink-dominated and sink-free DEMs, especially in the areas with relatively flat topography.