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

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. Copyright © 2003 John Wiley & Sons, Ltd.

[1]  Stephen E. Darby,et al.  Effect of Riparian Vegetation on Flow Resistance and Flood Potential , 1999 .

[2]  Yong Wang,et al.  Understanding the radar backscattering from flooded and nonflooded Amazonian forests: Results from canopy backscatter modeling☆ , 1995 .

[3]  Adriano Camps,et al.  Dual-beam interferometry for ocean surface current vector mapping , 2001, IEEE Trans. Geosci. Remote. Sens..

[4]  P. Bates,et al.  Predicting floodplain inundation: raster‐based modelling versus the finite‐element approach , 2001 .

[5]  Donald R. Thompson,et al.  Ocean surface features and currents measured with synthetic aperture radar interferometry and HF radar , 1996 .

[6]  Paul D. Bates,et al.  Optimal use of high‐resolution topographic data in flood inundation models , 2003 .

[7]  J. Hervouet.  TELEMAC modelling system: an overview , 2000 .

[8]  D. Mason,et al.  Image processing of airborne scanning laser altimetry data for improved river flood modelling , 2001 .

[9]  D. Mason,et al.  Flood boundary delineation from Synthetic Aperture Radar imagery using a statistical active contour model , 2001 .

[10]  M. S. Horritt,et al.  Development of physically based meshes for two‐dimensional models of meandering channel flow , 2000 .

[11]  Fawwaz Ulaby,et al.  Relating Polaization Phase Difference of SAR Signals to Scene Properties , 1987, IEEE Transactions on Geoscience and Remote Sensing.

[12]  P. Bates,et al.  Integration of high-resolution topographic data with floodplain flow models. , 2000 .

[13]  M. Fathi-Maghadam,et al.  Nonrigid, Nonsubmerged, Vegetative Roughness on Floodplains , 1997 .

[14]  William J. Plant,et al.  measuring stream discharge by non‐contact methods: A Proof‐of‐Concept Experiment , 2000 .

[15]  Rhj Sellin,et al.  INTERNAL AND EXTERNAL VALIDATION OF A TWO-DIMENSIONAL FINITE ELEMENT CODE FOR RIVER FLOOD SIMULATIONS. , 1998 .

[16]  David C. Mason,et al.  Obtaining accurate maps of topography and vegetation to improve 2D hydraulic flood models , 2001, SPIE Remote Sensing.

[17]  Delwyn Moller,et al.  Radar‐derived interferometric surface currents and their relationship to subsurface current structure , 1998 .

[18]  N. Kouwen,et al.  Friction Factors for Coniferous Trees along Rivers , 2000 .

[19]  P. Bates,et al.  A two-dimensional finite-element model for river flow inundation , 1993, Proceedings of the Royal Society of London. Series A: Mathematical and Physical Sciences.

[20]  A. Becker,et al.  Disaggregation, aggregation and spatial scaling in hydrological modelling , 1999 .

[21]  R. H. Meade,et al.  Exchanges of sediment between the flood plain and channel of the Amazon River in Brazil , 1998 .

[22]  Paul D. Bates,et al.  The importance of spatial resolution in hydraulic models for floodplain environments , 1999 .

[23]  V. T. Chow.  Open-channel hydraulics , 1959 .

[24]  P. Bates,et al.  INITIAL COMPARISON OF TWO TWO-DIMENSIONAL FINITE ELEMENT CODES FOR RIVER FLOOD SIMULATION. , 1995 .

[25]  Steven Businger,et al.  Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program. , 2000 .

[26]  Steven J. Owen,et al.  A Survey of Unstructured Mesh Generation Technology , 1998, IMR.

[27]  Keith Beven,et al.  Changing ideas in hydrology — The case of physically-based models , 1989 .

[28]  Roland Romeiser,et al.  Numerical study on the along-track interferometric radar imaging mechanism of oceanic surface currents , 2000, IEEE Trans. Geosci. Remote. Sens..

[29]  K. Kraus,et al.  Determination of terrain models in wooded areas with airborne laser scanner data , 1998 .