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
DLR-IRIDeS Joint Workshop 2014.09.19 2
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.
STEP 2 Development of New Roughness Coefficient Model
Time-dependentbuilding
destruction model
Tsunami fragility functions Reference values ofstructural destruction
Integration
Develop new composite equivalent roughness coefficient model reflecting the devastated buildings.
3 / 6�
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Study Area & Tsunami Video
DLR-IRIDeS Joint Workshop 2014.09.19 3
(c) NHK
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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
DLR-IRIDeS Joint Workshop 2014.09.19 4
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
��������
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» 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
DLR-IRIDeS Joint Workshop 2014.09.19 5
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
]
Distance from Coastline [m]
Fron
t Vel
ocity
[m/s
]
Distance from Coastline [m]
Flow
Vel
ocity
[m/s
]
6 / 6�
Simulation of The 2011 Tohoku Tsunami
DLR-IRIDeS Joint Workshop 2014.09.19 6
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
DLR-IRIDeS Joint Workshop 2014.09.19 7
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
]
Distance from Coastline [m]
Fron
t Vel
ocity
[m/s
]
STEP1
8 / 6�
Reproducibility of Tsunami Velocities
DLR-IRIDeS Joint Workshop 2014.09.19 8
» 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.
Distance from Coastline [m]
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
DLR-IRIDeS Joint Workshop 2014.09.19 9
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 velocities in order to estimate building destruction. 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.
STEP 2 Development of New Roughness Coefficient Model
Time-dependentbuilding
destruction model
Tsunami fragility functions Reference values ofstructural destruction
Integration
Develop new composite equivalent roughness coefficient model reflecting the devastated buildings.
STEP 1 Verification of Tsunami Inundation Modeling
Measured vel. Modeled vel.Comparison
Find problems with modeling and improve its reproducibility.
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)
DLR-IRIDeS Joint Workshop 2014.09.19 10
STEP2
11 / 6�
Methodology of New Model
Calculating the number of buildings being simultaneously damaged from fragility curves
1
DLR-IRIDeS Joint Workshop 2014.09.19 11
The Time-dependent building destruction model
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�
Methodology of New Model
DLR-IRIDeS Joint Workshop 2014.09.19 12
The Time-dependent building destruction model
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
Distance from Coastline [m]
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
DLR-IRIDeS Joint Workshop 2014.09.19 13
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.
DLR-IRIDeS Joint Workshop 2014.09.19 14
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
DLR-IRIDeS Joint Workshop 2014.09.19 15
» 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