Abstract
Abstract. 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.
Highlights
The Digital Elevation Model (DEM) is a digital representation of the ground surface topography or terrain which often is represented as a Cartesian grid, a triangulated irregular network (TIN) or as contour-based flow nets (Moretti and Orlandini, 2008)
Some non-depression DEM cells within D8’s concept may become depressions during the 2-D surface flow process, due to the inconsistency between D4 drainage used in 2-D surface runoff models and sink removal algorithms designed to work in combination with D8 flow direction algorithms
It shows that the Type B depression is unlikely eliminated by the traditional 1-D depression filling algorithm which may cause problems when used in 2-D surface flow models that make use of 2-D diffusive wave approximation to propagate the surface water into the river channel
Summary
The Digital Elevation Model (DEM) is a digital representation of the ground surface topography or terrain which often is represented as a Cartesian grid, a triangulated irregular network (TIN) or as contour-based flow nets (Moretti and Orlandini, 2008). One possible approach as suggested by Zhu (2009) is to extend the river network to those Type B sinks by adding some arbitrary tributaries able to drain the ponded water back to the river This method was shown to be very efficient in terms of retrieve water from the sinks. Wang and Liu (2006) proposed an efficient 1-D depression filling algorithms for high resolution DEMs. The main advantage of this algorithm is that it can simultaneously determine flow paths and spatial partition of watersheds in one pass of processing by employing the innovative concepts of spill elevation and using least-cost search for optimal flow paths. We propose a new method in this paper aiming to effectively fill the Type B depression for 2-D overland flow modelling by modifying and extending the fundamental computational concept of Wang and Liu (2006)’s 1-D filling algorithms. The MIKE SHE model (DHI, 2007), in particular its overland flow module, is chosen as a typical 2-D surface flow model, to analyse and assess the performance of the new depression filling algorithm
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