European Geosciences Union General Assembly 2011 Vienna, Austria, 3 – 8 April 2011

European Geosciences UnionGeneral Assembly 2011

Vienna, Austria, 3 – 8 April 2011

IMPROVING HYDRAULIC MODELLING USING REMOTE SENSING-DERIVED

FLOOD EXTENT DATA

A. Tarpanelli, L. Brocca, S. Barbetta, F. Melone and T. Moramarco

National Research Council, Research Institute for Geo-Hydrological ProtectionVia Madonna Alta 126, 06128 Perugia, Italy

E-mail: [email protected]

National Research CouncilResearch Institute for Geo-Hydrological Protection

European Geosciences UnionGeneral Assembly 2011Vienna, Austria, 03 – 08 April 2011

Introduction Purpose Method Study Area Results Conclusions

a preliminary flood risk assessment

flood hazard maps and flood risk maps

flood risk management plans

European directive 2007/60/EC on the assessment and management of flood risk:

Evaluation of flood prone areas

Use of coupled hydrologic and hydraulic models for real-time applications (such as flood risk mitigation and warning activities)

uncertainties in modelling, observations and output




- TerraSAR-X- COSMO SkyMed - Radarsat-2 SpotLight

REMOTE SENSING

SPACE-BORNE MICROWAVE REMOTE SENSING

SYNTHETIC APERTURE RADAR (SAR)

integration within the hydraulic modelling

nearly all-weather, day and night capabilities




RIVER IMAGES EVENTS TOPICS AUTHORS

SEVERN (England)

SEVERN (England)

DEE (England)

THAMES(England)

ALZETTE (Luxembourg)

PO (Italy)

4 ASAR (ERS)

1 TERRASAR-X

1 ASAR (75m)1 SAR (12.5m)

1 SAR (12.5m)

1 SAR (12.5m)

1 ASAR (75m)

November 2000

July 2007

December 2006

December 1992

January 2003

June 2008

Flooded Area

Flooded Urban Area

Flooded Area

Flooded Area

Water Level assimilation

Flooded AreaWater level

Horritt et al., HYP, 2007

Mason et al., IEEE, 2010

Schumann and DiBaldassarre, Rsletter, 2010

Mason et al., JoH, 2009

Schumann et al., IEEE, 2007

DiBaldassarre et al., HYP2009




SEVERN (England)

SEVERN (England)

DEE (England)

THAMES(England)

ALZETTE (Luxembourg)

PO (Italy)

4 ASAR (ERS)

1 TERRASAR-X

1 ASAR (75m)1 SAR (12.5m)

1 SAR (12.5m)

1 SAR (12.5m)

1 ASAR (75m)

November 2000

July 2007

December 2006

December 1992

January 2003

June 2008

Flooded Area

Flooded Urban Area

Flooded Area

Flooded Area

Water Level assimilation

Flooded AreaWater level

Horritt et al., HYP, 2007

Mason et al., IEEE, 2010

Schumann and DiBaldassarre, Rsletter, 2010

Mason et al., JoH, 2009

Schumann et al., IEEE, 2007

DiBaldassarre et al., HYP2009

RIVER IMAGES EVENTS TOPICS AUTHORS

SEVERN RIVER

Width channel: 70 mWidth floodplain: 2 km Area= 6850 km2

DEE RIVER

Width channel: 60 mWidth floodplain: 200 m-2 km

ALZETTE RIVER

Width channel: 20 mWidth floodplain: 300 mArea = 404 km2

THAMES RIVER

Width channel: 60 mWidth floodplain: 1 – 2 km

PO RIVER

Width channel: 200-300 mWidth floodplain: 400 m-4 km




To evaluate the potential of low resolution ASAR image for the calibration of hydraulic modelling applied to a small basin (~90 km2) in Central Italy

Introduction Purposes Method Study Area Results Conclusions



Flooding area assessment by coupling hydrologic and hydraulic modelling1

Flooding area extent by ASAR image2Calibration of Manning by comparing

flooding area inferred by hydraulic model and the one obtained by ASAR3

Validation of Manning by using in-situ discharge records4




GEOGRAPHIC INFORMATION SYSTEM

RAINFALL-RUNOFF

MODELHYDRAULIC SIMULATIONS

Generally, the procedure for the estimation of flooded areas is defined through three different levels of analysis:

1data acquisition into a Geographic Information System (GIS) of the geomorphologic characteristics of the basin, the geometric properties of the river branches and the hydro-meteorological quantities. 2 3hydraulic analysis

addressed to flooding area estimation.

hydrological analysis aimed to estimate the design discharge hydrograph of the tributaries




Hydro-meteorological data

Geometric and hydraulic properties of river reaches and flooding prone areas (topographical surveys, laser scanning surveys, inspections)

Historical flood events


Geomorphological characteristics of the basin (Geolithological map, soil map, land cover map)

-50 0 50 100 150250

252

254

256

258

260

262

264

266

marker 2

marker 3marker 1

quot

a (m

s.l.

m.)

distanza (m)

Ponte su Stradain Loc. Villa Capitini

Larghezza = 5.60 ml.




1jj,0 QY

ijY

kjY

i ijj QQ

Output discharge hydrograph

ROUTING MODEL

Routing Diffusive Function

Yij Qij

LUMPED MODEL for SUB-BASINS DRAINING DIRECTLY into the CHANNEL

Rainfall Infiltration

Infiltration model

IUH Linear Reservoir

Direct discharge

hydrograph Ykj

Effective Rainfall

LUMPED MODEL for SUB-BASIN with the

OUTLET along the MAIN CHANNEL Rainfall Infiltration

Infiltration model

GIUH

Direct discharge

hydrograph Yij

Effective Rainfall

RAINFALL-RUNOFF MODEL

Semi-distributed conceptual

model,MISD model

(Corradini et al., 1995)




One-dimensional modellingMIKE11

HYDRAULIC SIMULATIONS

the model simulates the flow propagation along rivers and channels

networks

the steady and unsteady flow conditions are

described solving the De Saint Venant equations through an implicit, finite

differences scheme known as “double sweep method” (Abbott and Ionescu, 1986)

some available tools, such as link channels and flood cells, allow to develop a “quasi two-dimensional”

approach able to represent properly the embankments overflow and the water

propagation over the floodplains




One-dimensional modellingMIKE11

HYDRAULIC SIMULATIONS

FLOODED AREA




FLOODED AREA

Visual interpretation(Oberstadler et al., 1997)

Histogram threshold method(Deshmukh and Shinde, 2005)

Histogram texture variance(Sali and Wolfson, 1992)

Euclidean distance(Kokare et al., 2003)

HTV

HT

ED

VI

IMAGE-PROCESSINGTECHNIQUES Bates et al., JoH, 2006Schumann et al., IEEE, 2009Di Baldassarre et al., JoH, 2009

FLOODING AREA FROM ASAR IMAGE




FLOOD INUNDATION MAPS

HYDRAULIC MODEL ASAR IMAGE

MANNING CALIBRATION




GENNA RIVER

BASIN CHARACTERISTICSTotal Area = 92 km2

Mean slope = 9.73%Length main channel = 20 km

Mean annual precipitation = 1100 mmMean channel width = 15 m

Floodplains width= 50 - 350 m

Implementation of hydrological and hydraulic models1




GENNA RIVER

A Digital Terrain Model (DTM) is available at a resolution of 3 m

Water channel bathymetry was characterized from a survey consisting of 84 cross sections (~1 every 250 m) conducted in 2007 by CNR

Survey of 14 bridges is conducted in 2007 by CNR

Ponte su Via Settevalliin Loc. M.na della Misericordia

Larghezza = 7.60 ml.




ENVISAT ASAR image 75 m resolution acquired on 28th November 2010 at 20:55

Trasimeno Lake

Genna River


Extraction of flood extent areas from ASAR image2




ASAR IMAGE CHANGE DETECTION

November 28, 2010 November 28, 2010

November 25, 2010

The images were first geo-referenced.

The four image processing techniques to extract the flooded area

were applied




0.0

1 0.0

2 0.0

3 0.0

4 0.0

5 0.0

6 0.0

7 0.0

8 0.0

9

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

n ch

anne

l

n floodplainASARImage

Change detection

Comparison between flood inundation maps3

HTV HT

ED VI

HTV HT

ED VI




ASAR IMAGE F1 values

HTV HT

ED VI

HTV HT

ED VI




ASAR IMAGE F2 values

HTV HT

ED VI

HTV HT

ED VI




CHANGE DETECTION F1 values

HTV HT

ED VI

HTV HT

ED VI




CHANGE DETECTION F2 values

HTV HT

ED VI

HTV HT

ED VI




F1 – Histogram Threshold

n channel

n floodplain




Optimum Manning’s values: 0.045 m-1/3 for the channel

0.060 m-1/3 for the floodplain

Validation with in situ observation4




n channel n floodplainimage 0.04 0.09

change detection 0.05 0.07

in-situ calibration 0.045 0.06

DISCHARGE WATER LEVELObserved Observed

in-situ calibration in-situ calibration

F1 – Histogram Threshold




• The possibility to calibrate hydraulic modelling by using low resolution ASAR image even for a small basin has been addressed

• The visual interpretation and histogram threshold are found to be the two best techniques for deriving flooded area

• The estimated manning coefficient for the channel and floodplain are in good accordance with the ones estimated by using in situ observation.

• Future work will incorporate the uncertainty in deriving flooded area from both satellite image and hydraulic models.

• Moreover, we will wait for high resolution satellite images products (TerraSAR-X, COSMO-Sky-Med) with revisit time of a few hours!!! They are welcome!




THANKS FOR YOUR ATTENTION

Bates, P.D., Wilson, M.D., Horritt, M.S., Mason, D.C., Holden, N., Currie, A., 2006. Reach scale floodplain inundation dynamics observed using airborne synthetic aperture radar imagery: data analysis and modelling . Journal of Hydrology, 328 (1-2), 306-318.Corradini, C., Melone, F., Ubertini, L., 1995. A semi-distributed model for direct runoff estimate, Proc. IASTED International Conference, Modeling and Simulation, Pittsburgh, Pennsylvania, April 27-29 1995; 541-545.Deshmukh, K.S., Shinde, G.N., 2005. An adaptive color image segmentation. Electronic Letters on Computer Vision and Image Analysis, 5 (4), 12-23.Di Baldassarre G., Schumann, G., Bates, P.D., 2009. A technique for the calibration of hydraulic models using uncertain satellite observations of flood extent. Journal of Hydrology, 367, 276–282.Di Baldassarre, G., Schumann, G., Bates, P.D., 2009. Near real time satellite imagery to support and verify timely flood modelling. Hydrological Processes, doi: 10.1002/hyp.7229.Horritt, M.S., Di Baldassarre, G., Bates, P.D., Brath, A., 2007. Comparing the performance of 2-D finite element and finite volume models of floodplain inundation using airborne SAR imagery. Hydrological Processes 21, 2745-2759 (ISSN: 0885-6087)Kokare, M. Chatterji, B.N., Biswas, P.K., 2003. Comparison of similarity metrics for texture image retrieval. In: Proceedings of the IEEE 10th Conference on Convergent Technologies for Asia-Pacific Region, October 2003, vol.2. IEEE, Bangalore, India, pp. 571-575.Mason, D.C., Bates, P.D., Dall’ Amico, J.T., 2009. Calibration of uncertain flood inundation models using remotely sensed water levels

Journal of Hydrology, Volume 368 (1-4), 224-236.Mason D.C., Speck, R., Devereux, B., Schumann, G., Neal, J.C., Bates, P.D., 2010. Flood detection in Urban Areas Using TerraSAR-

X, IEEE Transactions on Geoscience and Remote Sensing 48 (2), 882-894.Oberstadler, R., Hnsch, H., Huth, D., 1997. Assessment of the mapping capabilities of ERS-1 SAR data for flood mapping: a case study in Germany. Hydrological Processes 10, 1415-1425.Sali , E., Wolfson, H., 1992. Texture classification in aerial photographs and satellite data. Internationsl Journa of Remote Sensing 13, 3395-3408.Schumann, G., Hostache, R., Puech, C., Hoffman, L., Matgen, P., Pappenberger, F., Pfister, L.,2007. High-resolution 3D flood information from radar imagery for flood hazard management. IEEE Transactions on Geoscience and Remote Sensing 45 (6), 1715-1725.Schumann, G., Di Baldassarre, G., Bates, P.D., 2009. The utility of space-borne radar to render maps of observed possibility of inundation. IEEE Transactions on Geoscience and Remote Sensing 45 (6), 1715-1725.Schumann, G. and Di Baldassarre, G.(2010) 'The direct use of radar satellites for event-specific flood risk mapping', Remote Sensing

Letters, 1(2), 75-84. DOI: 10.1080/01431160903486685

European Geosciences Union General Assembly 2011 Vienna, Austria, 3 – 8 April 2011

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Transcript of European Geosciences Union General Assembly 2011 Vienna, Austria, 3 – 8 April 2011