Verifying Estimations of Tsunami Inundation …Verifying Estimations of Tsunami Inundation Velocity...

Verifying Estimations of Tsunami Inundation Velocity and Building Damage

by Tsunami Inundation Modeling

Laboratory of Remote Sensing and Geoinformatics for Disaster Management, IRIDeS, Tohoku University

2014.09.19 DLR-IRIDeS Joint Workshop

Satomi Hayashi, Bruno Adriano Graduate School of Engineering, Tohoku University

Erick Mas, Shunichi Koshimura International Research Institute of Disaster Science, Tohoku University

1 / 6�

Background

DLR-IRIDeS Joint Workshop 2014.09.19 1

F =1

2CDρu

2D : drag coefficient : water density : the current velocity : the inundation depth

CD

�

uD

Hydrodynamic force against structure It is important to obtain

tsunami velocities accurately for estimating structural damages.

Washed away

8 sec after flood 10 sec after flood

The 2011 Tohoku tsunami (At Fujitsuka, Wakabayashi-ku, Sendai)

Problems with measuring inland tsunami velocity

Simulation results have not been sufficiently validated.

»  Three methods: field survey, survivor video analysis, and numerical modeling.

Major factors in destruction of buildings

2 / 6�

Objective & Study Flow


STEP 1 Verification of Tsunami Inundation Modeling

Measured vel. Modeled vel. Comparison

Find problems with modeling and improve its reproducibility.

Improving tsunami inundation modeling with regard to tsunami inundation velocity in order to estimate destruction of building. Objective

STEP 2 Development of New Roughness Coefficient Model

Time-dependent building

destruction model

Tsunami fragility functions Reference values of structural destruction

Integration

Develop new composite equivalent roughness coefficient model reflecting the devastated buildings.


Time-dependentbuilding

destruction model

Tsunami fragility functions Reference values ofstructural destruction

Integration


3 / 6�

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Study Area & Tsunami Video


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Fujitsuka

Yuriage

Kozukahara Sendai

city

Natori city

Values of tsunami front and flow velocities were estimated by aerial video analysis.

»  Tsunami front velocity : the speed of tsunami front moving

»  Tsunami flow velocity : the speed of flow within flooding zone

STEP1

4 / 6�

Methodology of Aerial Video Analysis


STEP1

»  Calibrate and rectify by 2-D projective transformation.

»  Mapping the tsunami front and the debris on pre-event image.

Tsunami front vel. Tsunami flow vel.

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0 20 40 60 8010m

津波進行方向

�

15:55:46 15:55:42

15:55:50 15:55:52

15:55:54 15:55:56

15:56:03

15:56:02

15:56:01

Tsunami flood

vp =�x

�t

��

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4

5

6

4

5

6

0 2 4 6 81m

車

車

車

Δt = 1[s]

vf =�x

�t

��

��

��

»  The distance between two tsunami front lines is divided by the time.

»  The movement distance of floating objects per unit time.

Geometric Correction 1

Measure Tsunami Velocity 2

5 / 6�

Measured Value of Tsunami Velocities


Tsunami front vel. Tsunami flow vel.

»  Tsunami front velocities : 7 m/s »  Tsunami flow velocities : 8 m/s

Tsunami flow velocities reduced as the inland distance gets longer.

At Residential Area

At Rice Field

At Residential Area

At Rice Field Within 1 km inland from the shoreline, tsunami velocities reached …

STEP1

Distance from Coastline [m]

Fron

t Vel

ocity

[m/s

]


Fron

t Vel

ocity

[m/s

]


Flow

Vel

ocity

[m/s

]

6 / 6�

Simulation of The 2011 Tohoku Tsunami


Governing equation Non-linear shallow water theory

Numerical scheme Staggered leap-frog scheme

Grid size (Inland) 10 m × 10 m

Tsunami source Satake et al. (2013)

Roughness coefficient

�  The composite equivalent roughness coefficient model (Aburaya and Imamura, 2002； Imai et al., 2013)

�  Manning's roughness coefficient model (Kotani et al., 1998)

Tsunami numerical modeling

STEP1

Tsunami control forest

Buildings Surviving Washed-away

Case A (pre-disaster condition) ��

Case B (post-disaster condition) ��

Tsunami run-up modeling conditions

7 / 6�

10

8

6

4

2

0

18001600140012001000

6

5

4

3

2

1

0

28002600240022002000

Reproducibility of Tsunami Velocities


Tsunami front velocities

At Residential area At Rice field Case B (post-disaster)

Case A (pre-disaster)

»  The reproducibility of Case A is higher than Case B. Effects of structures and land use on tsunami inundation

characteristics are well reproduced.

»  Devastated buildings and drifting debris at tsunami front affect the tsunami penetration. Need to improve the tsunami front boundary conditions

including these resistances.

Fron

t Vel

ocity

[m/s

]

Fron

t Vel

ocity

[m/s

]

Distance from coastline [m] Distance from coastline [m]Distance from Coastline [m]

Fron

t Vel

ocity

[m/s

]


Fron

t Vel

ocity

[m/s

]

STEP1

8 / 6�

Reproducibility of Tsunami Velocities


»  The post-disaster condition is quite consistent with measured velocities.

The flow field can be well represented by the current tsunami inundation model.

10

8

6

4

2

0

2500200015001000

Case B (post-disaster) Case A (pre-disaster)

Measured

Distance from coastline [m]

Flow

vel

ocity

[m/s

]Tsunami flow velocities

Need to model the tsunami front boundary conditions considering the devastated buildings and the drifting debris.


Flow

Vel

ocity

[m/s

]

STEP1

Front Vel.

The pre-disaster condition was the most consistent to yield good estimates of tsunami front velocity.

Flow Vel.

The reproducibility of tsunami flow velocity was quite good in the post-disaster condition.

9 / 6�

Objective & Study Flow



Measured vel. Modeled vel. Comparison


Improving tsunami inundation modeling with regard to tsunami inundation velocities in order to estimate building destruction. Objective


Time-dependent building

destruction model

Tsunami fragility functions Reference values of structural destruction

Integration



Time-dependentbuilding

destruction model

Tsunami fragility functions Reference values ofstructural destruction

Integration



Measured vel. Modeled vel.Comparison


10 / 6�

Methodology of New Model

Roughness coefficients are gradually changed in response to the time variation of building damage.

The Time-dependent building destruction model

»  Combining tsunami fragility functions and reference values of structural destruction with the tsunami numerical modeling.

Sea

T = t1

Land

Sea Sea

T = t1 + Δt

Sea

Land

　 Tsunami fragility functions

1 　 Reference values for

structural destruction

2

1.0

0.8

0.6

0.4

0.2

0.0121086420

Wooden

RC

Steel

Inundation Depth [m]

Dam

age

Prob

abili

ty

RC �

Steel

Wooden

Wooden h …

Steel F …

RC u …

The composite equivalent roughness coefficient

Building Adriano et al. (2014) Hayashi et al. (2013)

Narita and Koshimura (2013) Suppasri et al. (2012)


STEP2

11 / 6�


Calculating the number of buildings being simultaneously damaged from fragility curves

1



T = t1

Building

Dam

age

Prob

abili

ty

RC �Steel

Wooden 1.0

0.8

0.6

0.4

0.2

0.0121086420

1.0

0.8

0.6

0.4

0.2

0.0121086420

1.0

0.8

0.6

0.4

0.2

0.0121086420

Inundation Depth [m]

Wooden

Steel

Sendai city Natori city Sendai & Natori city

Hayashi et al. (2013) ; Narita and Koshimura (2013) ; Suppasri et al. (2012)

»  Count the number of exposed buildings in 1m intervals of inundation depth. »  The multiplication of the number of exposed buildings and the damage probability . (Adriano et al., 2014)

NN

P(x1,�, xi )

The number of buildings being simultaneously damaged was calculated.

STEP2

12 / 6�




Selecting devastated buildings by reference values for structural destruction

2

Sendai city Natori city

Wooden Inundation depth h 3.5 m （MLIT, 2011）

Inundation depth h 1.5 m （MLIT, 2011）

Steel Inundated parallel area

AC 6.8 × h （Matsutomi et al., 2013）

Inundated parallel area AC 6.8 × h

（Matsutomi et al., 2013）

RC Inundated parallel area

AC 6.8 × h （Matsutomi et al., 2012）

Inundated parallel area AC 6.8 × h

（Matsutomi et al., 2012）

»  Determine the reference values for structural destruction by surveyed data and preceding studies.

Selected the appropriate buildings and washed out in descending hydrodynamic

force order. Matsutomi et al. (2012 ; 2013)

Inundated parallel area

Tsunami Flow

ACh

6.8 m Building

Tsunami flow

STEP2

13 / 6�

10

8

6

4

2

0

44004300420041004000

Recent Progress of New Model


Flow

Vel

ocity

[m/s

] Post-disaster

Pre-disaster

New model

Measured (at 3～8 sec after flood)

Elapsed Time [sec]

Flow

Vel

ocity

[m/s

]

»  The result of tsunami flow velocity shows high accuracy in new model.

»  The peak value has not reach the measured value at F1 area.

Tsunami flow velocity was underestimated at F1 area.

Devastated buildings could not be estimated well.

Tsunami flow velocities Time series data of flow velocity

at F1 area


10

8

6

4

2

0

2500200015001000

Measured New Model ( Ave.)

Measured New model (Ave.)

STEP2

14 / 6�

140°57'E

38°11'N

0 500250m

Damage InspectionWashed-awaySurviving

(b)140°57'E

38°11'N

0 500250m

Damage InspectionWashed-awaySurviving

(a)GTD (MLIT, 2011) Model result

Recent Progress of New Model

Need to model the tsunami front boundary conditions considering the drifting debris in built-up area.


Distribution of devastated buildings

Sendai Natori Washed-away 476 2187

Surviving 318 1252

Sendai Natori Washed-away 393 1266

Surviving 401 2173

STEP2

Sendai Sendai

Natori Natori

15 / 6�

Summary


»  The model accuracy with regard to tsunami front and flow velocities increased when the roughness coefficient was determined by responding to actual land use.

»  The tsunami inundation velocities could not be reproduced well at some inland areas.

Verification of Tsunami Inundation Modeling

We need to develop new composite equivalent roughness coefficient model reflecting the devastated buildings.

»  By combining tsunami fragility functions and reference values for structural destruction, we developed the time-dependent building destruction model.

»  The number of devastated buildings could not be reproduced well in Natori city (built-up area).

Need to model the tsunami front boundary conditions considering the drifting debris in built-up area.

Development of New Roughness Coefficient Model

Verifying Estimations of Tsunami Inundation …Verifying Estimations of Tsunami Inundation Velocity...

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