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.

Current work

1.1: Methods:

Speed up the time consuming 2D SWEMs (TUFLOW, ISIS2D, MIKE21…

Parallel Processing Meta ModelAdaptive Grid Rapid Flood Spreading Model

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.

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.

Neighbours + rules

(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.

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.

Breach

Cell 1

Cell 2

Cell 3

Cell 4

1z2z

3z

constzzz 321

An example of constant extra head (source: Krupka et al. 2007)

An example of pre-calculation process

Minimum Depth (Dmin)

Minimum Cell Plan area (Amin)

Water level (m)

Volume (cubm)

1.5 Existing RFSMs

RFSMs

Herriot Watt University

Martin Krupka et al.

and ISIS Fast

HR Wallingford

Julien Lhomme et al.

(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 gridCurrent active grid

(a)(b)

One-directional RFSM Multi-directional RFSM

1.7 Our improved RFSM

Rules to provide accurate prediction:

(1) Water will spread from high location to lower locations (one directional or multiple directional spilling algorithms) and has merging process.

(2) Dynamic Driving head based on inflow hydrograph

(3) Area with High Manning value n on the floodplain using a small driving head

t

dischargeArea 1

Area 2

1.8 Model parameters and evaluation functions

(1)

(2)

(3)

1.9 Application example

3D plot

2D plot

Inflow hydrograph

17 flood cells

Inflow

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

Area of a big flood cell

Volume = vol

Inflow at time

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

Fig1. Flood extent and water depth after 45.25 hours using ISIS2D.

(15m grid resolution model will take more than 1 hour to run)

Fig.2. Flood extent and water depth at 45.25 hours using RFSM.

( 5m grid resolution model will take 2 seconds to run)

Performance statistics

2.5 Current work

(1) The proposed method has been applied to Thamesmead, London.

(2) 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.