Projects per year
Abstract
This paper evaluates the results of benchmark testing a new inertial formulation of the St. Venant equations, implemented within the LISFLOOD-FP hydraulic model, using different high resolution terrestrial LiDAR data (10 cm, 50 cm and 1 m) and roughness conditions (distributed and composite) in an urban area. To examine these effects, the model is applied to a hypothetical flooding scenario in Alcester, UK, which experienced surface water flooding during summer 2007. The sensitivities of simulated water depth, extent, arrival time and velocity to grid resolutions and different roughness conditions are analysed. The results indicate that increasing the terrain resolution from 1 m to 10 cm significantly affects modelled water depth, extent, arrival time and velocity. This is because hydraulically relevant small scale topography that is accurately captured by the terrestrial LIDAR system, such as road cambers and street kerbs, is better represented on the higher resolution DEM. It is shown that altering surface friction values within a wide range has only a limited effect and is not sufficient to recover the results of the 10 cm simulation at 1 m resolution. Alternating between a uniform composite surface friction value (n = 0.013) or a variable distributed value based on land use has a greater effect on flow velocities and arrival times than on water depths and inundation extent. We conclude that the use of extra detail inherent in terrestrial laser scanning data compared to airborne sensors will be advantageous for urban flood modelling related to surface water, risk analysis and planning for Sustainable Urban Drainage Systems (SUDS) to attenuate flow.
Original language | English |
---|---|
Pages (from-to) | 4015-4030 |
Number of pages | 16 |
Journal | Hydrology and Earth System Sciences |
Volume | 17 |
Issue number | 10 |
DOIs | |
Publication status | Published - 28 Oct 2013 |
Fingerprint
Dive into the research topics of 'Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Developing enhanced impact models for integration with next generation NWP and climate outputs
Bates, P. D. (Principal Investigator)
1/09/10 → 1/09/14
Project: Research