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A New Flood Inundation Model

A New Flood Inundation Model. Yang Liu and Garry Pender School of Built Environment. Heriot Watt University. Contents. Introduction of rapid flood spreading model A new conceptual model for maximum velocity prediction and application to an artificial digital elevation model.

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A New Flood Inundation Model

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  1. A New Flood Inundation Model Yang Liu and Garry Pender School of Built Environment Heriot Watt University

  2. Contents • Introduction of rapid flood spreading model • A new conceptual model for maximum velocity prediction and application to an artificial digital elevation model. • Current work

  3. 1.1: Methods: Speed up the time consuming 2D SWEMs (TUFLOW, ISIS2D, MIKE21… Parallel Processing Meta Model Adaptive Grid Rapid Flood Spreading Model

  4. 1.2: Objectives of developing RFSM: • Short time to run (Typically < 5s) • A good overall agreement of the final water depth and flood extent predictions between SWEM and RFSM. • A good overall agreement of the maximum velocity prediction between SWEM and RFSM. Very useful to apply RFSM to probabilistic flood risk analysis (e.g. Bayesian Analysis) and real time forecasting.

  5. 1.3 Cellular Automata and RFSM (1) Definition: A cellular automata is a collection of cells on a grid of specified shape that evolves through a number of discrete time steps according to a set of rules based on the states of neighboring cells. (2) Differences: 2.1 Rapid Flood Spreading Model uses a large irregular cell to save the computational time. 2.2 Rapid Flood Spreading Model uses one iteration and simple merging process compared to CA iterations. Neighbours + rules References: (1) Wolfram, S. (1984) Cellular automata as models of complexity, Nature. 311: 419-24. (2) Parson, J.; Fonstad, M. (2007) A cellular automata model of surface water flow, Hydrological Processes, 21.

  6. Minimum Cell Plan area (Amin) Minimum Depth (Dmin) 1.4 Basic RFSM algorithm: • Pre-calculation An array of flood storage cells is constructed from DEM • Inundation A specified volume of flood water is distributed across the storage cells. An example of pre-calculation process Volume (cubm) Water level (m) An example of constant extra head (source: Krupka et al. 2007)

  7. 1.5 Existing RFSMs RFSMs HR Wallingford Julien Lhomme et al. Herriot Watt University Martin Krupka et al. and ISIS Fast (1) Krupka M., Wallis S., Pender S., Neélz S., 2007, Some practical aspects of flood inundation modelling, Transport phenomena in hydraulics, Publications of the Institute of Geophysics, Polish Academy of Sciences, E-7 (401), 129-135. (2) Lhomme J., Sayers P., Gouldby B., Samuels P., Wills M., Mulet-Marti J., 2008, Recent development and application of a rapid flood spreading model, River Flow 2008, September. (3) Liu Y, Pender G (2010) “A new rapid flood inundation model”, the first IAHR European Congress, Edinburgh, UK.

  8. 1.6 Two different spreading algorithms Next active grid Current active grid (b) (a) One-directional RFSM Multi-directional RFSM

  9. 1.7 Our improved RFSM • Rules to provide accurate prediction: • Water will spread from high location to lower locations (one directional or multiple directional spilling algorithms) and has merging process. • Dynamic Driving head based on inflow hydrograph • Area with High Manning value n on the floodplain using a small driving head Area 2 discharge Area 1 t

  10. 1.8 Model parameters and evaluation functions (1) (2) (3)

  11. 1.9 Application example Inflow Inflow hydrograph 3D plot 2D plot 17 flood cells

  12. 1.10 Compare RFSMs with ISIS2D Flood extent using ISIS2D after 10 hours Flood extent using MD-RFSM Flood extent using OD-RFSM

  13. 1.11 ISIS2D simulation:

  14. 1.12 One directional RFSM spilling process

  15. 1.12 Assumptions • Time Series water depth can be predicted approximately accurate using RFSM • Flow route needs to be predicted approximately accurate.

  16. Volume = vol Inflow at time Area of a big flood cell Inflow at time 2.1 Maximum Velocity prediction using a new conceptual model

  17. 2.2 Performance Comparison of the conceptual model and ISIS2D Maximum velocity using ISIS2D Average Maximum velocity for 17 regions using ISIS2D Average Maximum velocity predictions for 17 regions using our proposed model The conceptual model parameter C was calibrated using one ISIS2D simulation when peak value= 150cubm/s of sine inflow hydrograph.

  18. 2.3 Performance statistics

  19. 2.4 Current work about 2005 Carlisle flood event

  20. Flood extent predictions Using ISIS2D and RFSM Fig.2. Flood extent and water depth at 45.25 hours using RFSM. ( 5m grid resolution model will take 2 seconds to run) Fig1. Flood extent and water depth after 45.25 hours using ISIS2D. (15m grid resolution model will take more than 1 hour to run)

  21. Performance statistics

  22. 2.5 Current work • The proposed method has been applied to Thamesmead, London. • Test more locations. (3) Fast Rapid flood spreading Modelling using Cellular Automata. Targets: (1) Time series of water depth and velocity prediction. (2) Run time < 30 seconds using big irregular cells. Thank you!

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