A New Flood Inundation Model
Yang Liu and Garry Pender
School of Built Environment
Heriot Watt University
Contents
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

Introduction of rapid flood spreading model
A new conceptual model for maximum velocity
prediction and application to an artificial digital
elevation model.
Current work
1.1: Methods:
Speed up the time consuming 2D
SWEMs (TUFLOW, ISIS2D, MIKE21…
Parallel Processing
Adaptive Grid
Rapid Flood
Spreading Model
Meta Model
1.2: Objectives of developing RFSM:

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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.
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.
Neighbours + rules
2.2 Rapid Flood Spreading Model uses
one iteration and simple merging process
compared to CA iterations.
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.
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.

Minimum
Depth
(Dmin)
An example of pre-calculation process
Breach
Minimum
Cell Plan
area (Amin)
z1  z 2  z 3  const
 z1
z 2
Volume (cubm)
z 3
Cell 1
Cell 2
Cell 3
Cell 4
An example of constant extra head (source: Krupka et al. 2007)
Water level (m)
1.5 Existing RFSMs
RFSMs
Herriot Watt University
HR Wallingford
Martin Krupka et al.
Julien Lhomme 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.
1.6 Two different spreading algorithms
Next active grid
Current active grid
(a)
One-directional RFSM
(b)
Multi-directional RFSM
1.7 Our improved RFSM

(1)
(2)
(3)
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
1.8 Model parameters and evaluation functions
(1)
(2)
(3)
1.9 Application example
Inflow
Inflow
hydrograph
3D plot
2D plot
17 flood
cells
1.10 Compare RFSMs with ISIS2D
Flood extent using ISIS2D
after 10 hours
Flood extent using MD-RFSM
Flood extent using OD-RFSM
1.11 ISIS2D simulation:
1.12 One directional RFSM spilling process
1.12 Assumptions


Time Series water depth can be predicted
approximately accurate using RFSM
Flow route needs to be predicted approximately
accurate.
2.1 Maximum Velocity prediction using a new conceptual model
Volume = vol
Inflow at time
Area of a big
flood cell
Inflow at time
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.
2.3 Performance statistics
2.4 Current work about 2005 Carlisle flood
event
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)
Performance statistics
2.5 Current work
(1)
(2)
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.