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VALIDATIONOFAQUASI-2DHYDRODYNAMICRIVERFLOODMODELUSINGHISTORICALANDERS-SARDERIVEDFLOODMAPS

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XXXI IAHR CONGRESS 137

VALIDATION OF A QUASI-2D HYDRODYNAMIC RIVER FLOOD

MODEL USING HISTORICAL AND ERS-SAR DERIVED FLOOD MAPS

LUIS TIMBE, PATRICK WILLEMS and JEAN BERLAMONT

Laboratory of Hydraulics, K.U. Leuven, Kasteelpark Arenberg 40,

B-3001 Leuven, Belgium

(Tel: +32-16-321656, Fax: +32-16-321989, e-mail: Luis.Timbe@bwk.kuleuven.be,

Patrick.Willems@bwk.kuleuven.be)

Abstract

There is an increasing interest in river flood modelling due to the severe flood events in the

last decade throughout Europe, Asia and other parts of the world. Modelling of these events

can be performed using one-dimensional (1D) or two-dimensional (2D) hydrodynamic

models. Although 2D hydrodynamic model are the forefront for river flood modelling and

prediction, they are constrained by the high requirements of data and computational time. The

aim of this study is to test a quasi-2D modelling approach for the prediction of the flood

extent along floodplains. The model used was implemented for the river Dender in Belgium,

where floods occurred frequently during the past 10 years. The historical flood events of Dec.

1993 and Jan. 1995 were simulated using the river modelling system Mike 11/Mike GIS. The

model results were validated using historical flood maps delineated by water authorities and

ERS-SAR satellite radar derived flood maps. Both types of floodmaps delivered

complementary validation information. After detection and correction of the coarse model

inaccuracies, the model became accurate in the description of the spatial extent of floods and

its temporal evolution.

Keywords: DEM; Floods; Floodplain modeling; Hydrodynamic models; ERS-SAR

1. INTRODUCTION

Many recent studies have focused on river flood modelling due to the extreme flood events

occurred the last decade over the world (Badji and Dautrebande, 1997; van der Sande et. al.,

2002; Delmeire, 1997; Nachtnebe, 2003). Been flooding one of the most costly natural hazard

in human lives and infrastructure (Nachtnebe, 2003; Brown and Damery, 2002; Wolfgang,

2002; Oberstadler et al., 1997) its prediction and prevention has become an important issue in

the policy of water and environmental authorities

Nowadays, the availability of high resolution Digital Elevation Models (DEMs) to

represent the earth surface allows coupling hydraulic models with Geographic Information

Systems (GIS) to obtain the flood extent and water levels in floodplains. Many studies on

flood mapping have been conducted using 1D or 2D hydrodynamic models (Horritt and Bates,

138 September 11~16, 2005, Seoul, Korea

2002; Sinnakaudan et al., 2002; Bates et al., 1997; Ahmad and Simonovic, 1999). As stated

by Masson et al. (2002) the 2D hydraulic models are the state of the art for river flood

modelling. Although 1D models are accurate in the main river channel they are not valid for

over bank flow (Bates et al., 1997). Nevertheless, 2D hydrodynamic models are also

constrained by the high requirements for data, hardware and software.

A compromise solution between a 1D and 2D model is the quasi-2D approach. In this

approach the floodplains are modelled as separated river branches connected to the main river

by link channels. The link channels work as weirs, allowing the water overflow to the

floodplain when the water level exceeds the river embankment or dike. The aim of this

investigation is to test the quality of a quasi-2D hydrodynamic model for flood modelling

along floodplains for some historical flood events. The generated flood maps were validated

using historical and ERS SAR derived flood maps.

2. STUDY AREA

The study was performed for the river Dender located in the south-west part of Flanders

(Belgium) with a length of 50 km, and a contributing area of 708 km2 (see Fig. 1). Along the

river there are eight hydraulic structures (weir/sluice combinations) to regulate the water level.

Time series of hydrometric data (discharge/stage) were available at the upstream and

downstream boundaries and water levels upstream/downstream of the hydraulic structures.

Along the river floodplains, a high resolution DEM based on Laseraltimetry (LiDAR) was

available; with a horizontal resolution of 4 m. This DEM was not accurate at the line elements

(e.g. river dike embankments, roads). It therefore was corrected particularly for the river dike

levels, for which the accuracy is important in the flood modelling and mapping applications.

Along the main river Dender, there was also a cross sections survey available, with cross-

sections approximately every 50 m. These were used to correct the DEM at the left and right

embankment tops. Also along the river bed the DEM was corrected to replace the water level

elevations by the real river bed elevations derived from the cross-sectional survey.

Fig. 1 Location of the Dender river basin and overlay with the Dender subbasins,

the main river network and the locations of the hydraulic structures

XXXI IAHR CONGRESS 139

3. METHODS

For the river Dender, a quasi-2D model has been set-up in previous studies (Willems et al.,

2001; Willems et al., 2002a,b) on the basis of the river modelling system Mike 11. Mike 11

solves the vertically integrated equations of Saint Venant for the conservation of momentum

and volume in a one-dimensional way:

qt

A

x

Q=

∂

∂+

∂

∂ (1)

02

2

=+∂

∂+

∂

∂

+∂

∂

ARC

QqQ

x

hgA

x

A

Q

t

Qα

(2)

where: Q is the discharge, A the flow area, q the lateral inflow, h the stage above datum, C

the Chezy resistance coefficient, R the hydraulic or resistance radius and α the momentum

distribution coefficient.

The hydrodynamic module of Mike 11 uses an implicit, finite difference scheme for

computation of unsteady flows in rivers and estuaries. In addition, critical and subcritical flow

conditions can also be described (DHI, 2002).

The quasi-2D approach means that the floodplains along the river are modelled using a

network of 1D river branches (hereafter called “floodbranches”) and spills (overflows) in

between the main river branch and the floodbranches to represent the river dikes. Spills may

also be used in between different floodplain areas.

In the first stage the potential flood risk zones for the Dender were identified based on the maps

of recent floods “ROG” for Flanders which describe the maximal spatial extent of historical

floods for the last 12 years (SADL, 2000). To setup the quasi-2D hydrodynamic model for the

Dender a first set of floodbranches were implemented for the floodplains along the ROG regions

(Fig. 2). The cross sections for these floodbranches were extracted from the DEM.

Fig. 2 Overlay of the DEM with the ROG maps for the upstream part of the Dender, together

with an illustration of the implementation of floodbranches in the quasi-2D

hydrodynamic model

140 September 11~16, 2005, Seoul, Korea

The Mike GIS interface was used to perform the flood mapping (the spatial 2D-mapping of

the water level simulation results in the quasi-2D model), by linking the Mike 11 results with

the geographic information system ArcView. The flood mapping is performed using a

weighted extrapolation routine on the water levels in the calculation nodes of the

hydrodynamic model results (DHI, 2001).

The flood model is validated, comparing the spatial extent results from the flood model

with the ROG flood maps for a number of historical events. The historical flood events of

December 1993 and January-February 1995 were simulated for the Dender basin. The

hydrodynamic model results were imported in the Mike GIS interfase to perform the flood

mapping at the peak moment, and to allow comparison with the ROG maps. At this level

coarse inaccuracies were detected and corrected when possible. The model was updated

adding floodbranches for areas where the model shows flooding, but which are not present in

the ROG maps. In the second phase, the model results were also compared with the flood

maps derived from ERS-SAR satellite images (Willems et al., 2003). The comparison was

made at the specific moments of the time acquisition of the images (Table 1). It has been

shown by Willems et al. (2003) that the ERS-SAR derived flood maps have significant

underestimations of the flooded areas due to water turbulence, wind effects and shallow water

problems. In section 4, it will become clear that these flood maps are, however, still very

useful for flood validation purposes.

Table 1. ERS SAR derived flood maps acquisitions

Flood event Date ERS-SAR Imagery

Event 1

Event 2

12/31/1993 23:00

02/02/1995 23:00

To measure the fit between the historical flood maps (observed) and the simulated flood

maps (modelled) the goodness-of-fit index presented by Bates and De Roo (2000) and Horrit

and Bates (2002) was used:

mod

mod

obs

obs

A AF

A A=

I

U (3)

where Aobs and Amod represent the total number of observed and predicted inundated pixels

respectively.

The index F lies in the range [0-1] satisfying the general criterion to measure model

performance. The numerator represents the common pixels in both the observed and predicted

flood maps, while the denominator is the union of both flood maps. F is equal to zero when

there is no overlap between the observed and predicted flooded area, and is equal to one when

both flooded areas are exactly the same.

XXXI IAHR CONGRESS 141

4. RESULTS AND DISCUSSION

The ROG historical flood maps were collected from different sources: photos, newspapers,

the footprint/trace left by the flood, notes taken by water authorities; therefore their

delineation is not always that accurate. When a comparison is made with topography,

discrepancies are often found in the sense that flooded areas are missed or overestimated. An

attempt to improve the accuracy of the ROG maps was made by Massari (2004) calculating

the mean elevation along the boundary of the ROG together with a confidence interval. Later

these elevations were plotted as inundation depth in Mike GIS to get new corrected ROG

maps. The corrected historical maps were used for the final validation of the quasi-2D model.

The flood mapping based on interpolation and extrapolation of water levels gives accurate

results only for areas where water levels have been simulated by the quasi-2D hydrodynamic

model. The initial simulated flood maps revealed some areas where additional floodbranches

were needed. When the water level in the river channel exceeds the embankment or dike, the

flooded area can be largely overestimated if no floodbranch is implemented along this area.

This is due to the extrapolation routine. The floodbranch therefore had to be enlarged when

the flooded area was larger than the area covered by the floodbranch.

Another problem found was the presence of gaps in the DEM. Due to the grid resolution of

4 m, the line elements such as dikes, roads, railways are not accurate (they can contain unreal

gaps). The model is very sensible to this problem and just a few cells can cause a large

overestimation. This problem was avoided along the river embankments integrating the cross

section survey with the DEM. Another problem encountered was the underestimation of the

flooded area because of line elements stopping the water level extrapolation in the DEM,

while in reality the water can flow under these elements. This mistake is common at roads and

railways, with the presence of brook culverts. This problem could be solved implementing a

culvert or another hydraulic structure in the hydrodynamic model.

4.1. FLOOD EVENT OF DECEMBER 1993

Fig. 3 presents the final flood mapping results for the river reach between chainages 10470

m and 25050 m. This region presents most of the floods along the Dender. As can be seen the

predicted flooded area (Fig. 3b) at the peak moment and the corrected ROG (Fig. 3a) show on

the average a good agreement, with a value F equal to 0.56. In general there is an

underestimation of the flooded area by the model. This can be explained by the inaccuracies

in the boundary delineation of the ROG maps. Even after correction there remains a high

uncertainty on the delineated boundary for these maps. Fig. 3a presents also an overlay with

the ERS-SAR derived flood map. The ERS-SAR acquisition was just after the peak moment,

and it shows that in some areas the model is more correct than the ROG data, see for instance

the area neighbouring the Idegem weir. At the right side of the Dender, the ERS-SAR map

confirms the flood in this floodplain while in the ROG map this zone is missing. Also at the

142 September 11~16, 2005, Seoul, Korea

downstream part (close to chainage 25050) the ERS-SAR image shows a larger flooded area

(and closer to the model results) than the ROG.

The floodplain of Denderbellebroek (see Fig. 4) is a natural flood storage area affected by

the tidal influence of the downstream Dender boundary along the river Schelde and it is

flooded quite frequently. For the flood event of Dec. 1993 there is no information for this area

in the ROG map, but according to the model results this area is completely flooded. For

comparison reasons, the predicted flooded area in Fig. 4a is plotted at the same time moment

than the derived ERS-SAR flood map. As mentioned before the ERS-SAR acquisition is not

at the peak moment; therefore we can presume an underestimation of the flood extent in the

ERS-SAR derived flood map. Based on a comparison with the topography, it was furthermore

concluded that the flooded area detected by ERS-SAR in this region was underestimated even

for the time moment given. After correction based on the floodplain topography, similar

flooded area was reached as the model results.

Fig. 3 Flood maps at the region between chainages 10470 m - 25050 m a) corrected ROG at

the peak moment and ERS-SAR derived flood map at 12/31/1993 23:00, b) Mike

11/Mike GIS at the peak moment

XXXI IAHR CONGRESS 143

Fig. 4 Flood maps for the floodplain Denderbellebroek, chainages: 43994-46300 at

12/31/1993 23:00, a) ERS-SAR derived flood map, b) Mike 11/Mike GIS

4.2. FLOOD EVENT JANUARY 1995

The simulated event at the end of January 1995 has a higher return period than the event of

December 1993. The model results for this event are similar than the previous one in terms of

agreement with the ROG map. Fig. 5 presents the results for the area between chainage 10470

m – 25050 m. The F value equals 0.59. In contrast with the ERS-SAR image of Dec. 1993,

for the flood event of Jan. 1995 the ERS-SAR image acquisition was 3 days after the peak

moment. For this reason, the additional comparison with the ERS-SAR derived flood map

was less useful. Only for the Denderbellebroek floodplain, where the residence time of the

flooded water is long, the comparison with the ERS-SAR made sense.

144 September 11~16, 2005, Seoul, Korea

Fig. 5 Flood maps at the region between Idegem and Pollare, a) corrected ROG at the peak

moment, b) Mike 11/Mike GIS at the peak moment

Fig. 6 Flood maps for the floodplain Denderbellebroek, chainages: 43994-46300, a) ROG and

Mike 11/Mike GIS at the peak moment, b) ERS-SAR and Mike 11/Mike GIS at

2/2/1995 23:00

The comparison between the predicted model results at the peak moment and the ROG

derived flood map is shown for the Denderbellebroeck in Fig. 6a. As can be seen the results

XXXI IAHR CONGRESS 145

are quite accurate, with F close to 1. Fig. 6b presents the overlay of Mike 11/Mike GIS model

results with the ERS-SAR derived flood map at the same time moment as the ERS-SAR

acquisition. For this floodplain once again there is a good match between the model results

and the ERS-SAR based flood map. For this event the underestimation of the ERS-SAR

derived flood map is less than for the Dec. 1993 event, possibly due to the higher water level

in the floodplain.

5. CONCLUSIONS

The results of flood mapping using a quasi-2D flood model show in general a good

agreement with available historical flood information. The flood modelling approach uses a

1D physically based hydrodynamic model, with river branches on the floodplain connected to

the main river. In comparison with a full 2D model this approach has the advantage of lower

requirements for data and computational time.

Historical flood maps were useful to identify the potential flood risk zones along the river,

where floodbranches needed to be implemented in the quasi-2D flood model. ERS-SAR

derived flood maps based on satellite radar data systematically underestimate the flooded

areas. Some problems of radar based images for detecting water bodies have been confirmed

in previous studies (Horrit and Bates, 2002; Oberstadler, 1997; Smith, 1997) because of

meteorological conditions and land cover, i.e. when the water surface in not smooth due to

wind or turbulence, or due to some land cover type. Regardless of their inaccuracies (mostly

underestimations) ERS-SAR derived flood maps have shown to be useful complementary

information for the validation and refinement of flood simulation models. They provide

information on the zones along the river where some flooding occurred and an approximation

of the spatial extent. In some cases ERS-SAR flood maps can be the only source of

information.

Comparing the simulation results of the flood model with the different flood maps the

model could be evaluated and the inaccuracies identified. The most sensitive factor is the

wrong representation of the line elements in the DEM. This problem can be avoided

correcting the DEM using measured topographical elevations along river embankments, dikes,

roads and railways (e.g. cross-sectional survey). The agreement between the predicted and

observed flooded area using the F coefficient with a value close to 0.6 for both studied

historical flood events is acceptable taking into account the quality of the historical maps. As

seen, the ERS-SAR images can help in identifying additional flooded areas not present in the

other historical flood information (the ROG flood maps in this case), and therefore to improve

the F coefficient.

ACKNOWLEDGEMENTS

The work is supported by the Selective Bilateral Agreements with Latin American

Universities, through the PhD scholarship of L. Timbe and by the Fund for Scientific

146 September 11~16, 2005, Seoul, Korea

Research-Flanders (F.W.O.-Vlaanderen), through the postdoctoral scholarship of P. Willems.

The data were made available and the model set-up supported with projects by the Flemish

Water Administration AWZ.

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