京 都 大 学 防 災 研 究 所 年 報 第 50 号 B 平 成 19 年 4 月
Annuals of Disas. Prev. Res. Inst., Kyoto Univ., No. 50 B, 2007

Simplified Flood Inundation Model Integrating with Rainfall-runoff Processes

Nanshan ZHENG*, Yasuto TACHIKAWA* and Kaoru TAKARA*Department of Urban and Environmental Engineering, Kyoto University
SynopsisFlood hazard is the one of the most harmful disasters in the world, therefore it issignificant to obtain reliable information on flood characteristics for flood hazard
mitigation as well as flood vulnerability assessment. Hereby in order to obtain thetemporal-spatial distribution of flood hazard vulnerability, a grid cell based simplified
flood inundation simulation integrating with rainfall-runoff processes is developed in thisstudy for flood inundation simulation of large watersheds, which is based on 1-D channel
flow routing, and 2-D overland and slope flow routing simulation model. According toflood inundation simulation, flood characteristics can be analyzed, especially theflood-prone area is able to be identified and delineated. This paper describes thebackground of the model development and methodology.
Keywords: flood inundation, flood modeling, Geographical Information System

Recently a shift in paradigms is observed from

1. Introduction

a technical oriented flood protection towards flood
Flood events during previous years have raisedrisk management, and the emphasis of disaster risk

public, political and scientific awareness of flood

reductionrisk and flood prevention (Becker and Grunewald

approach to a vulnerability-led approach. Therefore2003), and flooding threats are likely to increase

it is necessary and significant to study on regional

given current climate change predictions. Many

vulnerability for flood hazard. Consequently, inmore intensive rainfall events happen, which

order to explore the spatial distribution of flood

suggests flooding becomes more frequent andhazard vulnerability, a grid cell based simplified

potentiallytheflood inundation simulation integrating with rainfall

occurrence of flood event has become common in

runoff processes is proposed. According to themany parts of the world, the needs to obtain reliable

simulation result, flood characteristics can beinformation on flood characteristics are increasing

analyzed,with the dramatically rising of people’s awareness.

flood-prone area.

causesgreaterdamage.

As

Whilst the increase of flood damage for singular

has changed

especially

Variousfrom anwhichhydrologic

canmodels,

impacts-led

identify

theespecially

event, partly caused by the tendency that muchcommercial software, have been developed in themore people live in floodplains or low-lying areas,

past to simulate flood inundation. In this research,

consequently results in society becomes more

physically based distributed modeling is focused forexposure to flood events.

flood vulnerability assessment in watershed scale－ 75 －region.

Inadditiontothedevelopmentof2-D model, which is to treat each cell as a storage

computational capacities, Digital Elevation Model

volume, and the change in cell volume over time is(DEM), digital data of soil type and land use

equal to the fluxes into and out of it. Whilst at theclassification, as well as Geographical Information

channel–floodplain interface, the exchange of flow

System (GIS), are used for hydrologic hazard

between channel network and floodplain orresearch.

low-lying area is simulated in response to therelative water surface elevation, that is to say,surface flow can be either away from river or into

2. Methodology

river (Figure 2) (Horritt M.S., Bates P.D., 2001).
2.1 Description of flood inundation simulation
Distributed temporal-spatial information offlood events is of the utmost importance for floodd2

d1

disaster mitigation as well as for flood vulnerability
assessment. A physically based flood inundationh2

h1

simulation model is developed in this study, which
is based on simplified process representation

g1

This model consists of a one-dimensional channel

g2

capable of simulating dynamic flood inundation.
flow and a two-dimensional overland flow model toenable simulation of flood water depth and hence
inundation extent (Figure 1).

Fig. 2 Flow between grid node 1 and 2 (d, depth ofwater in the cell; g, ground elevation; h, water

j-1

surface elevation in the cell).

j

2.2 Overland and channel flow
Overland flow can occur when the water depthon the floodplain exceeds the depression storagej+1

threshold. Generally overland flow can be governedby continuity and momentum equations (Equations
1 and 2). To solve the overland flow equations for

k-1

kk+1

continuity and momentum, explicit finite difference
method is selected. In general, each grid cell isFig. 1 Schematic drawing of 2-D overland flood

assumed as a homogeneous unit.

routing and channel routing scheme.

dh i , jdt

When the bankful flow depth is reached in aQup  Qdown  Q left  Q right'x'y

flood event, water ceases to be contained solely in
Q xi , j

the main river channel and water spills onto
adjacent floodplains. These floodplains act either as
temporary stores for this water or additional routes
for flow conveyance. In this process, the water
surface elevation for river segments is calculated

53r

h flow h i 1, j  h i , jn'x(1)

12'y(2)

Where h i , j is the water free surface height at thegrid cell ( i, j ); 'x and 'y are grid cell dimensions,using the 1-D channel flow model solution. The

which are equal; n is the Manning’s friction
coefficient; Q x and Q y are the volumetric flow

overland surface flow routing is calculated by therates between grid cells, Q y is defined analogously－ 76 －

to equation (2), whose sign depends on the flow
direction; Q up , Qdown , Q left and Q right are theprovide model inflow and outflow boundary

flow rates (either positive or negative) from the up,

parameter for each model cell (often based ondown, left and right adjacent cells, respectively,
which can be represented by Q x or Q yground surface conditions and determined byaccordingly. The flow depth, hflow , represents theThis research focuses on watershed/catchment,

depth through which water can flow between two

there are generally two types of data sets that havecells.

been used: spatial and non-spatial data. Spatial data

conditions; (3) an estimate of effective friction

remote sensing data) and (4) validation data.

Similarly, channel flow is also able to be

include digital elevation model (DEM), channel

represented by continuity and momentum equations

network, watershed boundary, soil type and land use(Equations 3 and 4). In the watershed it isclassification. In this program, it will make full use

convenientof SRTM DEM data and some other remote sensingtorepresent

channelflowasone-dimensional.
wQ wA
wx wtS0 

Where,data,(3)qn 2 P 4 3Q 2A

10 3ª wh º« »¬ wx ¼

andwatershed/catchment

and channel cross-sectional data. Actually weather
data also can be recorded as the same as spatial data.

is distance along theThese data sets are available which are able to belongitudinal axis; A is cross-sectional area; Q is

edited and preprocessed before they are used in

the volumetric flow rate in the channel; q is lateralflood inundation simulation program.

flow into or out of the channel; P is wettedperimeter of channel flow; S 0 is bed slope.

3.2 Approachtis time;link

Non-spatial data are inflow discharge, weather data

(4)0channelboundary mask data will be generated by DEM.

xThe objective of this research is to develop an
integrated flood inundation simulation model to3ˊModel development

predict and assess flood hazard. Here a loose
coupling method of program development is

3.1 Data sets and pre-processing
Flood inundation models require four key data

selected. In such case, GIS and flood inundation

principally: (1) topographic data or DEM tosimulation model remain separate, but loosely

construct the model grid; (2) bulk flow data tolinked through data input and output.
Topography/DEM

Land use classification

Soil type
Flow direction

Interception

Precipitation

Infiltration

Water storage

Cross-section

Flow accumulation

Channel link/NodeHydrologic processes
Channel routing

Overland routing

Catchment boundary

Flood inundation simulation
Fig. 3 Flowchart of data processing and modelling procedure.

－ 77 －Catchment mask

The program is developed according to Fig. 3

this program, the channel characteristics are(Chow et al, 1998; David R. Maidment, 1993)

represented by rectangle or trapezoid, and drainage

under the environment of Microsoft Visual C++ andnetwork is extracted from DEM data, only a simple

Windows XP operating system, the initial input data

treatment of river channel is incorporated. Therefore

such as DEM, catchment mask and channel link are

it is easier to be handled in data poor environmentorganized by GIS, and simulation output from theespecially where limited channel information ismodel consists of the water depth in each grid cellavailable. Furthermore the mechanism can beat each given time step, which also can be

improved in terms of stage-discharge relationshipvisualized by GIS. And in the model, the hydrologic(Tachikawa, Y. et al., 2004) in further research.

processes including precipitation, infiltration andinterception are considered, however at the present

References

the evapotranspiration process is neglected. The
channel cross-sectional parameters required to run

Becker, A. and Grunewald, U. (2003): Flood risk inthe simulation are channel width, depth, slope andCentral Europe, Science, vol. 300, pp.1099.

Manning’s friction coefficient. Here the width andHorrittM.S.,Bates

P.D.

(2001):

Predicting

depth of river channel are assumed to be uniform

floodplain inundation: raster-based modelling

along one channel segment.

versus the finite-element approach, Hydrological
Processes, 15, pp. 825-842.
Tachikawa, Y., Nagatani, G., and Takara (2004):

4. Conclusions

Development of stage-discharge relationshipIn this research, the route and procedure ofequation incorporating saturated- unsaturated

simplified flood inundation simulation program

flow mechanism, Annual Journal of Hydraulicintegrating

Engineering, JSCE, 48, pp. 7-12.

withrainfall-runoff

processesforwatershed scale context are constructed to simulate

Chow, Ven Te, Maidment, David R. and Mays,

flooding over a digital elevation model which isLarrysignificant

McGraw-Hill Book Company.

offlood vulnerability

assessment.

Simulation may be of watershed/catchment scaleDavidflooding where floodplain and river are coupled. InW.
R.

(1988):

Maidment

Applied(1993):

Hydrology,Handbook

ofHydrology, MCGRAW-HILL INC..

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