Two‐dimensional hydraulic flood modelling using a finite‐element mesh decomposed according to vegetation and topographic features derived from airborne scanning laser altimetry

Abstract

Abstract:Airborne scanning laser altimetry (LiDAR) is an important new data source that can provide two-dimensional river flood models with spatially distributed floodplain topography for model bathymetry, together with vegetation heights for parameterization of model friction. Methods are described for improving such models by decomposing the model's finite-element mesh to reflect floodplain vegetation features such as hedges and trees having different frictional properties to their surroundings, and significant floodplain topographic features having high height curvatures. The decomposition is achieved using an image segmentation system that converts the LiDAR height image into separate images of surface topography and vegetation height at each point. The vegetation height map is used to estimate a friction factor at each mesh node. The spatially distributed friction model has the advantage that it is physically based, and removes the need for a model calibration exercise in which free parameters specifying friction in the channel and floodplain are adjusted to achieve best fit between modelled and observed flood extents. The scheme was tested in a modelling study of a flood that occurred on the River Severn, UK, in 1998. A satellite synthetic aperture radar image of flood extent was used to validate the model predictions. The simulated hydraulics using the decomposed mesh gave a better representation of the observed flood extent than the more simplistic but computationally efficient approach of sampling topography and vegetation friction factors on to larger floodplain elements in an undecomposed mesh, as well as the traditional approach using no LiDAR-derived data but simply using a constant floodplain friction factor. Use of the decomposed mesh also allowed velocity variations to be predicted in the neighbourhood of vegetation features such as hedges. These variations could be of use in predicting localized erosion and deposition patterns that might result in the event of a flood.

High-Accuracy Elevation Data at Large Scales from Airborne Single-Pass SAR Interferometry

“…Although for LiDAR data, automated algorithms to remove Earth surface features are routinely and successfully applied (e.g., Cobby et al, 2001Cobby et al, , 2003, SAR height data prove far more challenging given the inherent errors in the data and only limited progress has been achieved over recent years, often using ancillary data sets or models (e.g., Baugh et al, 2013).…”

Channel Representation in Physically Based Models Coupling Groundwater and Surface Water: Pitfalls and How to Avoid Them

“…For example, Cobby et al (2003) refine the mesh in areas of significant variations of roughness. Bates et al (2003) build an optimized mesh that incorporates "topographically significant points" and use, as CaviedesVoullième et al (2012), vertical curvature as an indicator of areas to refine.…”

Development of fragility curves for railway embankment and ballast scour due to overtopping flood flow

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