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Dynamic Decision Making for Dam
and Levee Risk Management
Limin Zhang
Hong Kong University of Science and Technology
Wuhan University, 19 January 2015
2
Outline
Background
Dam-break emergency management process
A framework for dynamic decision making
Dynamic human risk analysis
Dynamic decision making for mitigating the risks of
Tangjiashan Landslide Dam
Summary
3
Five major perils (Swiss Re 2013)
4
The Pearl River Delta,
including Hong Kong,
Shenzhen, Macau and
Guangzhou, is home to
more than 42 million
people. Situated in one of
the world’s most disaster-
prone regions, floods and
typhoons put more people
at risk than in any other
metropolitan area in the
world.
It is the number one
metropolitan area for storm
surge, with 5.3 million
people affected, the third-
highest for cyclonic wind
damage (17.2 million), and
the fifth riskiest city for river
floods.
> 5 m
< 1 m
1–3 m
1–3 m
3–5 m
3–5 m
3–5 m
Flood arrival time and inundation depths –
Pearl River Delta (Breaching at 15.5 m level)
5
Instant
6 – 60 hours
> 60 hours
6Banqiao and Shimantan Dam in Henan Province, China,
failed in 1975 and killed more than 26,000 people
Levee failures in New Orleans during the
August 2005 Hurricane Katrina. Death toll:
1,464
Typhoon Haiyan made its landfall in the Philippines on 8 Nov.
2013. Fatalities: 6,340; Damage US$2.86 billion.
21 stations
Safety of cascading hydropower systems in China under extreme loading conditions
7
Xiluodu Concrete Gravity Arch Dam, 13860 MW, H = 285.5 m, V = 128x108 m3
Xiangjiaba Concrete Gravity Dam, 7750 MW, H = 162 m, V = 51.6x108 m3
8
Tangjiashan
Landslide Dam
Tangjiashan Landslide Dam. Height = 82 m, lake
volume = 316 million m3
(Xinhua News, 2008)
2014年8月3日鲁甸红石岩堰塞湖.
国家防总前方工作组调度堰塞湖上游的德泽水库关闸拦蓄减少入湖水量，缓解堰塞湖水位上涨压力，已拦蓄近5000万立方米。同时，调度堰塞湖下游天花板和黄角树电站预泄腾空库容近1亿立方米，为后期蓄滞堰塞湖下泄洪水做好准备。鲁甸、会泽、巧家、昭阳等4县（区）共疏散转移堰塞湖上下游受威胁群众13044人，其中堰塞湖上游3491人、下游9553人。
2014年08月12, 新华网
What is the dam-failure probability?
When will the dam fail?
How large will the flood be?
Who will be affected?
Scientific based flood risk management
How severe are the consequences?
When to evacuate the PAR?
How does monitoring information help the
decision making?
10
Outline
Background
Dam-break emergency management process
A framework for dynamic decision making
Dynamic human risk analysis
Dynamic decision making for mitigating the risks of
Tangjiashan Landslide Dam
Summary
Emergency management of dam breaks in space
11
Dam-breaching emergency management
12
Formation and
development
of dam
breaching (Hanson 2005)
Initia
tion p
hase
Develo
pm
ent p
hase
Failure by
overtopping
13Xu and Zhang, 2009
Failure by piping
(b2)(b2)
33
33--44
(a2)(a2)
44
坍塌坍塌
(b3)(b3)
55
55--66
(a3)(a3)
66
Initia
tion p
hase
Develo
pm
ent p
hase
Collapse
McCook, 2007
Dam-breaching emergency management
14
Time for issuing evacuation warning (tw)
Water level reaching dam crest
The breach develops to the upstream slope
The flood first arrives the area downstream (tf)
The peak of the flood or the moment that the flood may pose obvious threats to people
Breaching end
Breaching
development time
Flood rise time
(Rt)Breaching
formation time
Warning lead time or lead time Flood routing time
Warning time (Wt)
Emergency management of dam breaks in time
Breaching
formation timeBreaching
development time
Flood rise
time (Rt)
15
Evacuation process
Dissemination
of warning
Receipt of
warning
Flood
arrivalRemovalDam-break
signs
Time
Population
Phase 1 Phase 2 Phase 3 Phase 4 After occurence
Death
Warning
Flight
Hydrological
forecasting,
risk
assessment
and decision
making
ResponseEvacuation
Sheltering
PAR
Demand time Flood rise time
Warning
transmitting
time
Response
timeEvacuation
time
16
Tangjiashan Landslide Lake Evacuation Plan唐家山堰塞湖应急疏散预案 (26 May 2008)
Evacuating 240,000 people between 27-30 May 2008
17
I-45 northbound north of Houston, 21 Sept. 2005. Photo: Shimoda
Thousands of hurricane Katrina survivors from New Orleans are bussed to refuge at a Red Cross shelter in the Houston Astrodome .FEMA photo/Andrea Booher Houston,TX.,9/1/2005
Formulating the evacuation process
Probability of successful evacuation
18
TL, T
FT TF
Probability of successful evacuation
Pf = P(T
F < T
L)Warning time
+ flood rise
time, TL
Demand time, TF
L
Human vulnerability in flood
1919
Abt (1989)
20
Outline
Background
Dam-break emergency management process
A framework for dynamic decision making
Dynamic human risk analysis
Dynamic decision making for mitigating the risks of
Tangjiashan Landslide Dam
Summary
21
Decision making – decision tree
Flood (P1)
No flood (1-P1)
Evacuation
costs
Flood
damages
0 D1
0
C1 d1
(d1<D1)
0
Oi2: Evacuation
Oi1: No evacuation
Oτ2: Evacuation
Oτ1: No evacuation
C2
(C2>C1)
d2
(d2<d1)
0
ti tτ tp
Delayed moment of
decision-making Moment of initiation
decision-making
t
0
C2
(C2>C1)
C1
Loss
of life
L1
0
l1
(l1<L1)
0
l2
(l2<l1)
0
Predicted moment of
flood
Flood (P2)
No flood (1-P2)
Flood (P1)
No flood (1-P1)
(Frieser, 2004)
The time effect is not sufficiently involved in flood time, failure
probability and flood consequences.
22
Dynamic decision framework
Proposed decision criteria
• If top ≤ t0, evacuate the population at risk (PAR) immediately;
• If t0 < top < tend, evacuate the PAR at top;
• If top ≥ tend, no evacuation is needed;
• If top is much larger than t0, the decision may be delayed for more information.
Flo
od
co
nse
qu
en
ce
s
Time of evacuation warning
Total loss
Loss of life
Flood damage
Evacuation costs
Optimal point
topt0 tend
23
Dynamic decision framework
f(t)
tt0 tend
Da
m fa
ilure
pro
ba
bili
ty
tw
Issue
warning
dt
tf
Possible
flood
Warning time
( )fP f t dt
0
( ) ( ) ( ) [ ( ) ( ) ( )] ( )t t t t
t
E L L t f t dt C W D W L W f t dt
The expected total losses
[ ( )] [ ( ) ( ) ( )] ( )t t tE L t C W D W L W f t dt
24
Dynamic decision framework
Discrete probability time series
P(t)
t
Issue
evacuation
warning
tw Warning timePre-warning After floodtf
Possible
flood
tendt0
0 0
( ) ( ) ( ) [ ( ) ( ) ( )] ( )t j j t t t j
j j
E L L t P t C W D W L W P t
25
Flood consequences
Evacuation cost• Initiation cost:
• GDP interruption:
( 3)i eva tC cP PAR W
( )( 4)365
PGDP t
GDPC PAR W
Flood damage (moveable properties)• Moveable properties:
• Immoveable properties (e.g. building damage) cannot
be reduced by evacuation
(1 )(1 )( )eva safe pD P P PAR M
Monetized loss of life
( )L pV GDP L
( )L LM V LOL
Predicted by
HURAM as
functions of
warning time
613,745 75 1.03 10 RMB
(Mianyang Bureau of Statistics, 2008)
(Frieser, 2004)
(Jonkman, 2007)
26
Outline
Background
Dam-break emergency management process
A framework for dynamic decision making
Dynamic human risk analysis
Dynamic decision making for mitigating the risks of
Tangjiashan Landslide Dam
Summary
27
Human risk analysis models
Empirical models: Lack of physical meaning
Physical models: Without studying the human vulnerability
Compromised models: Need considering inter-relationships among parameters
(Jonkman, 2007)
28
Factors influencing loss of life:
Bayesian network
Evacuation distance
Time of a day
Distance to dam site
Building story number
Dam breaching duration
Water depth
Flow velocity
Building type
Warning time
Flood rise time
Building damage
Evacuation Sheltering
inside buildings
Flood severity
Loss of life
4 components (sub-networks)
15 nodes (parameters)
23 arcs/links (inter-relationships)
29
Quantification of evacuation component
Wt + Rt > Tt + St + Et
Uniform distributions Weibull distributions
Monte Carlo simulation
Available time Demand time
30
Sheltering and flood severity
(RESCDAM 2000)
Building damage• Slight damage: inundated
• Partial damage: damage on windows, doors and furniture
• Major damage: damage on structure
Flood severity
31
Quantifying the loss of life
2
ln( ) 1.649( ) ( )
0.562
0.643
D
hF h
R
2
ln( ) 3.376( ) ( )
1.188
0.637
D
hF h
R
Low flood severity
Medium flood severity
0
0.01
0.02
0.03
0.04
0.05
0 1 2 3 4 5
Water depth (m)
Fa
tality
ra
tio
Recorded data
Simulated curve
0
0.1
0.2
0.3
0.4
0.5
0 1 2 3 4 5 6
Water depth (m)
Fa
tality
ra
te
Recorded data
Simulated curve
32
The prior probabilities
(Using Hugin Lite 7.2, 2009)
Calculated fatality rates-general conditions
33
Flood
severity
Warning
time
(Minute)
Flood
severity
understanding
Fatality rate
Graham’s model (1999) This model
Suggested
value
Suggested
range
High No warning N/A 0.75 0.30 – 1.0 0.7707
15-60 Vague Use the values shown above
and apply to the number of
people who remain in the
dam failure floodplain after
warnings are issued.
0.4195
Precise
More than
60
Vague 0.0794
Precise
Medium No warning N/A 0.15 0.03 - 0.35 0.1071
15-60 Vague 0.04 0.01 - 0.08 0.0593
Precise 0.02 0.005 - 0.04
More than
60
Vague 0.03 0.005 - 0.06 0.0117
Precise 0.01 0.0 - 0.02
Low No warning N/A 0.01 0.0 - 0.02 0.0079
15-60 Vague 0.007 0.0 - 0.015 0.0045
Precise 0.002 0.0 - 0.004
More than
60
Vague 0.0003 0.0 - 0.0006 0.0009
Precise 0.0002 0.0 - 0.0004
34
Predictions of historical cases
(50 historical cases)
1.0E-05
1.0E-04
1.0E-03
1.0E-02
1.0E-01
1.0E+00
1.0E-05 1.0E-04 1.0E-03 1.0E-02 1.0E-01 1.0E+00
Recorded fatality rate
Pre
dic
ted
fa
tality
ra
te
The present model
Graham's model, 1999
D&M model, 1993
35
Application – Beichuan, Qp = 6500 m3/s
690
670
650
630
610200 400 600 800 1000
Ele
va
tio
n (
m)
Distance (m)
631.13
Bank
RiverResidential area
R1 R2 R4 R5R3
0
R0
R0
0 - 1.5
1.5 - 2
2 - 3
3 – 4.5
4.5 - 6
Residential
areaWater
depth (m)
0
R1
R2
R3
R4
R5
Buildings625
615.8
R6
6 - 6.13R6
Evacuation
distance (m)
0
0-75
75-100
100-150
150-225
225-300
300-306.5
Time of a
day
Breaching
time
Distance to
dam site
Water flow
velocity
Building type Building
story number
12:00-13:00 14 hours 3.5 km 1.14 m/s Brick 3
(With HEC-RAS)
36
Application – Subarea R6
(Using Hugin Lite 7.2, 2009)
37
Ranking important factors - Subarea R6
0.00
0.05
0.10
0.15
0.20
Eva Tod Fs Sib Wt D Rt Dbt Bsn V Bt Bd Dtd Ed
Parameters
Co
nd
itio
na
l p
rob
ab
ility o
f lo
ss o
f life
`
Eva = evacuation
Tod = time of a day
Fs = flood severity
Sib = sheltering inside building
Wt = warning time
D = water depth
Rt = flood rise time
Dtd = distance to dam site
Bsn = building story number
V = water flow velocity
Bt = building type
Bd = building damage
Dbt = dam breaching duration
Ed = evacuation distance
Water depth: 6-6.13 m
Evacuation
Time of a day
Warning time
Flood severity Water depth Building damage
38
Outline
Background
Dam-break emergency management process
A framework for dynamic decision making
Dynamic human risk analysis
Dynamic decision making for mitigating the risks of
Tangjiashan Landslide Dam
Summary
39
Application of Tangjiashan Landslide Dam
Dam site
Beichuan Town
Tongkou Town
Hanzeng
Town
Qinglian Town
Longfeng Town
Mianyang City
Shima Town
Fu R
iver
Fu R
iver
Tongko
u R
iver
Jian River
Jian river
To solve the problems:
• Is it necessary to evacuate the population at risk (PAR)?
• When is the optimal time to evacuate the PAR?
• What is the minimum total consequences?
• How does new monitoring information help the
decision making?
40
Breaching model of landslide dams
Bt
Bb
Hb
Hd
Hd = dam height
Hb = breach depth
Bt = breach top width
Bb = breach bottom width
River
Landslide
Landslide dam
River
Dam width
Dam
le
ngth
Control variables
• Dam height (Hd)
• Lake volume (Vl)
• Dam width (Wd)
• Dam volume (Vd)
• Dam Erodibility (E)
Breaching parameters
• Peak outflow rate (Qp)
• Breach depth (Hb)
• Breach top width (Wt)
• Breach bottom width (Wb)
• Breaching time (Tb)
41
Dynamic decision framework
Dam failure probability
DamReservoir
t
H
Water level
Hcr
Ht
t
V
Vcr
Vt
Lake volume
( ) 1 ( )t cr t crP V V P V V
Overtopping failure t cr t crH H V V
( )t t t t oV V Q Q t
42
Dam failure probability as a time series
0
50
100
150
200
250
300
350
2008/5/15 2008/5/20 2008/5/25 2008/5/30 2008/6/4 2008/6/9 2008/6/14
Time
La
ke
vo
lum
e (
millio
n m
3)
Records
Predictions
Lower bound of 95% confidence interval
Upper bound of 95% confidence interval
Vcr = 316 million m3
0
0.2
0.4
0.6
0.8
1
2008/6/5 2008/6/10 2008/6/15 2008/6/20 2008/6/25
Time
Da
m fa
ilu
re p
rob
ab
ility
Cumulative probability
Discrete probability
( ) 1 ( ) 1 ( )cr Vtt cr t cr
Vt
V MP V V P V V
1 20.463 0.181t t t tQ Q Q a
Autoregressive model, AR(2):
43
Empirical models for breach parameters
Full-parameter model
(5 control variables)
Simplified model
(3 control variables )
Breaching
parameter
Breach bottom width
Breach top width
Breach depth
Peak outflow rate
Failure time
1/3-1.417 -0.265 -0.471
1/ 2 5/ 2
1/31.569
( ) ( ) ( )
( )
p d d d
d c d d
al
d
Q H H V
g H H W H
Ve
H
1/30.882 -0.041 -0.099
1/30.139
( ) ( ) ( )
( )
b d d d
c c d d
al
d
H H H V
H H W H
Ve
H
1/30.752 0.315 -0.243
1/30.682
( ) ( ) ( )
( )
t d d d
c c d d
al
d
W H H V
H H W H
Ve
H
1/3
1/3
0.004( ) 0.050( ) 0.044 ( )
0.088( )
b d d d
d c d d
l
d
W H H V
H H W H
Va
H
1/30.262 -0.024 -0.103
1/30.705
( ) ( ) ( )
( )
b d d d
r c d d
al
d
T H H V
T H W H
Ve
H
1/3-1.371 1.536
1/ 2 5/ 2( ) ( )
p ad l
d c d
Q H Ve
g H H H
1/30.923 0.118( ) ( ) ab d l
c c d
H H Ve
H H H
1/30.911 0.271( ) ( ) at d l
c c d
W H Ve
H H H
1/3
0.003( ) 0.070( )b d l
d c d
W H Va
H H H
1/30.293 0.723( ) ( ) ab d l
r c d
T H Ve
T H H
44
Physically based modeling of dam breaching
fu f f
L0
Bc0
ff f f
Chang and Zhang 2010
F(failure | overtopping)
= f (e, Cu, PI, P, S, Rh)
Failure by overtopping
4545
Time line of the Tangjiashan event
12 May 15 23 1 June 7
The dam formed
The dam geometric parameters were identified
The geological conditions of the dam were obtained
A division channel was constructed
The water level reached the division channel
6:00
Breaching started
Breaching finished
Stage 1 Stage 2 Stage 3 Timeline
20:00
10 June
Stage 1 Stage 3Stage 2
Jian River
Stage 1
600
700
800
900
0 100 200 300 400 500 600 700 800 900
600
700
800
900
1000
1100
Gravelly soil
Strongly weathering cataclasite
Weakly weathering cataclasite Breach
Gravels with soil
Original
slope before
slide
752.2
m
Ele
va
tio
n (
m)
Distance (m)
Ele
va
tio
n (
m)
Stage 2 Stage 3
4646
Time line of the Tangjiashan event
Geometric parameters of the dam
Dam height 82 m
Dam width 802 m
Dam length 611 m
Dam volume 20.4 million m3
Lake capacity 316 million m3
12 May 15 23 1 June 7
The dam formed
The dam geometric parameters were identified
The geological conditions of the dam were obtained
A division channel was constructed
The water level reached the division channel
6:00
Breaching started
Breaching finished
Stage 1 Stage 2 Stage 3 Timeline
20:00
10 June
Stage 1 – Empirical models for breaching simulation
Stage 1 Stage 3Stage 2
4747
Time line of the Tangjiashan event
12 May 15 23 1 June 7
The dam formed
The dam geometric parameters were identified
The geological conditions of the dam were obtained
A division channel was constructed
The water level reached the division channel
6:00
Breaching started
Breaching finished
Stage 1 Stage 2 Stage 3 Timeline
20:00
10 June
200 400 600 800 1000 1200 14000600
700
650
750
800
740.4m Gravelly soil
Strongly weathered cataclasite
Weakly weathered cataclasite
Bedrock
752.2 m
Ele
vati
on (
m)
Distance (m)
Stage 2 – DABA (physical) model (Chang and Zhang 2010)
High erodibility
Stage 1 Stage 3Stage 2
600
700
800
900
0 100 200 300 400 500 600 700 800 900
600
700
800
900
1000
1100
Gravelly soil
Strongly weathering cataclasite
Weakly weathering cataclasite Breach
Gravels with soil
Original
slope before
slide
752.2
m
Ele
vatio
n (
m)
Distance (m)
Ele
vatio
n (
m)
48
Time line of the Tangjiashan event
Parameters of the division channel
Channel depth 12 m
Channel width 25 m
Channel length 611 m
Excavation soil volume 20.4 million m3
Lake capacity after the construction of the channel
247 million m3
12 May 15 23 1 June 7
The dam formed
The dam geometric parameters were identified
The geological conditions of the dam were obtained
A division channel was constructed
The water level reached the division channel
6:00
Breaching started
Breaching finished
Stage 1 Stage 2 Stage 3 Timeline
20:00
10 June
Wt
Wb
Hb
Hd
Hd = dam height
Hb = spillway depth
Wt = spillway width
Wb = spillway width
Stage 3 – DABA (physical) model (Chang and Zhang 2010)
Stage 1 Stage 3Stage 2
49
0
0.01
0.02
0.03
2008/6/3 0:00 2008/6/8 0:00 2008/6/13 0:00 2008/6/18 0:00 2008/6/23 0:00
Time
Dis
cre
te d
am
-bre
ak p
rob
ab
ility
Prediction of dam failure probability
Dam-failure probabilities as a time series
Stage 3
Stage 2Stage 1
50
Uncertainty of breaching parameters
Scenario Low erodibility Medium erodibility High erodibility
Number of cases 15 31 6
Probability 0.116 0.596 0.288
Qp in stage 1 2,160 7,100 35,610
Stage 1 (empirical model)
Stages 2 and 3 (physical model)
m.5 m.5m1.5 m1.5
S1
S2
S3
S4
S5
Scenario S1 S2 S3 S4 S5
Probability 0.067 0.242 0.382 0.242 0.067
Quantile m1.83 m.89 m m.89 m1.83
Qp in stage 2 5,570 9,120 14,700 25,180 39,090
Qp in stage 3 2,450 4,050 6,540 10,420 17,260
m: predicted by DABA
: obtained by statistics
51
0
10000
20000
30000
40000
0 10 20 30 40 50 60
Time (hour)
Pe
ak o
utflo
w r
ate
(m
3/s
)
High erodibility (0.228)
Medium erodibility (0.596)
Low erodibility (0.116)
Stage 1
0
10000
20000
30000
40000
0 10 20 30 40 50 60
Time (hour)
Pe
ak o
utflo
w r
ate
(m
3/s
)
High erodibility (0.228)
Medium erodibility (0.596)
Low erodibility (0.116)
Stage 1
Floods in the three stages
Stage 1
0
10000
20000
30000
40000
0 10 20 30Time (hour)
Pe
ak o
utflo
w r
ate
(m
3/s
)
Scenario 5
Scenario 4
Scenario 3
Scenario 2
Scenario 1
Scenario 5 (0.067)
Scenario 4 (0.242)
Scenario 3 (0.382)
Scenario 2 (0.242)
Scenario 1 (0.067)
Stage 2
Stage 1
0
10000
20000
30000
40000
0 10 20 30Time (hour)
Pe
ak o
utflo
w r
ate
(m
3/s
)
Scenario 5
Scenario 4
Scenario 3
Scenario 2
Scenario 1
Scenario 5 (0.067)
Scenario 4 (0.242)
Scenario 3 (0.382)
Scenario 2 (0.242)
Scenario 1 (0.067)
Stage 2
0
5000
10000
15000
20000
0 10 20 30Time (hour)
Pe
ak o
utflo
w r
ate
(m
3/s
)
Scenario 5 (0.067)
Scenario 4 (0.242)
Scenario 3 (0.382)
Scenario 2 (0.242)
Scenario 1 (0.067)
Stage 3
0
5000
10000
15000
20000
0 10 20 30Time (hour)
Pe
ak o
utflo
w r
ate
(m
3/s
)
Scenario 5 (0.067)
Scenario 4 (0.242)
Scenario 3 (0.382)
Scenario 2 (0.242)
Scenario 1 (0.067)
Stage 3
52
Evaluation of consequences
(With VBA in
Excel)
Monetized loss of life
Evacuation cost
Flood damage
Warning time
53
Decision making – Beichuan
0
100
200
300
2008/6/14 0:00 2008/6/15 0:00 2008/6/16 0:00 2008/6/17 0:00 2008/6/18 0:00 2008/6/19 0:00
Time
Flo
od
co
nse
qu
en
ce
s (
RM
B m
illio
n)` Evacuation cost
Flood damage
Monetized loss of life
Total consequence
Optimum time to evacuate
the PAR: 16 June 08:00
with a total consequence
of RMB41.93 million
Stage 1
0
100
200
300
2008/6/14 0:00 2008/6/15 0:00 2008/6/16 0:00 2008/6/17 0:00 2008/6/18 0:00 2008/6/19 0:00
Time
Flo
od
co
nse
qu
en
ce
s (
RM
B M
illio
n)` Evacuation cost
Flood damage
Monetized loss of life
Total consequence
Optimum time to evacuate
the PAR: 15 June 21:00
with a total consequence of
RMB41.60 million
Stage 2
0
100
200
300
2008/6/5 0:00 2008/6/6 0:00 2008/6/7 0:00 2008/6/8 0:00 2008/6/9 0:00 2008/6/10 0:00
TimeF
loo
d c
on
se
qu
en
ce
s (
RM
B m
illio
n)` Evacuation cost
Flood damage
Monetized loss of life
Total consequence
Optimum time to evacuate
the PAR: 7 June 00:00
with a total consequence of
RMB36.20 million
Stage 3
All people (0.03 million)
were evacuated by 1 June
54
Decision making – Mianyang
0
200
400
600
800
2008/6/15 0:00 2008/6/17 0:00 2008/6/19 0:00 2008/6/21 0:00 2008/6/23 0:00
Time
Flo
od
co
nse
qu
en
ce
s (
RM
B m
illio
n)`
Optimum time to evacuate
the PAR: 19 June 10:00
with a total consequence of
RMB370.10 million
Stage 1
Total losses
Monetized loss of life
Evacuation costs
Flood damage
0
200
400
600
800
2008/6/15 0:00 2008/6/17 0:00 2008/6/19 0:00 2008/6/21 0:00 2008/6/23 0:00
Time
Flo
od
co
nse
qu
en
ce
s (
Millio
n R
MB
)`
Optimum time to evacuate
the PAR: 18 June 18:00
with a total consequence of
RMB380.88 million
Stage 2
Total losses
Monetized loss of life
Evacuation costs
Flood damage
No flooding is
predicted in Stage 3
in Miangyang City
0.2 million people were evacuated by 1 June
55
Summary
Understanding the dam/levee break emergency management –
probabilistic formulation of the process
Framework of dynamic decision making for dam/levee risk
management – basis for scientific decision; – the dam failure
probability as a time series and the flood consequences as functions
of the warning time.
Consequences of dam-break floods - evacuation costs, flood damage
and loss of life.
Rapid evaluation of human risk - HURAM, a model for simulating
human-flood interactions using Bayesian networks.
The decision making - a process depending on information available.
Dynamic decision making for the emergency management of
Tangjiashan Landslide Dam - three stages with different levels of
hydrological, geological and social-economic information.
56
Thanks for your attention
