The Metropolitan Area of Valencia (in the Mediterranean coast of Spain) suffers yearly heavy rains due to a cut-off low phenomenon called “Cold Drop”. There are historical records showing that floods due to long return period downpours led to catastrophic situations. Until now, the flood management in the region has been analysed from an economic impact perspective. Even though the economic analysis is important and necessary, the humanitarian perspective analysis is required to plan future events preparedness and response. This paper aims to model the behaviour choices of the inhabitants of the region in case of the issue of an evacuation alert due to long return period flood inundations. To do so, a questionnaire survey has been conducted to ask the inhabitants of the region as a case of study. A total of six hundred responses from inhabitants have been analysed by using logistic regression models. A model for each of the four main variables has been developed. Results have shown the threat awareness and the family attributes as the most important variables to influence choice decisions during evacuation. Taking into consideration the obtained results, it could be possible to establish a draft plan in order to improve local government response for future flood events.

1. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Behavioural choices in
evacuation during floods:
A preliminary study in Metropolitan
Area of Valencia, Spain
Azarel Chamorro Obra1
Wisinee Wisetjindawat2
Motohiro Fujita3
Nagoya Institute of Technology
Fujita Laboratory
1 Research Student
2 Assistant Professor
3 Professor

2. I. Metropolitan Area of
Valencia (MAV)
I. Location
II. Geography
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions
50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
METROPOLITAN AREA OF VALENCIA (MAV)
Location
Europe

3. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Metropolitan Area of Valencia
METROPOLITAN AREA OF VALENCIA (MAV)
(MAV)
Location
Spain
I. Metropolitan Area of
Valencia (MAV)
I. Location
II. Geography
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

4. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Metropolitan Area of Valencia
METROPOLITAN AREA OF VALENCIA (MAV)
(MAV)
Location
Metropolitan Area of Valencia (red)
I. Metropolitan Area of
Valencia (MAV)
I. Location
II. Geography
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

5. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Metropolitan Area of Valencia
METROPOLITAN AREA OF VALENCIA (MAV)
(MAV)
 Alluvial plain
 Several gullies
Geography
I. Metropolitan Area of
Valencia (MAV)
I. Location
II. Geography
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

6. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Metropolitan Area of Valencia
METROPOLITAN AREA OF VALENCIA (MAV)
(MAV)
 Alluvial plain
 Several gullies
 Large lagoon (Albufera)
Geography
I. Metropolitan Area of
Valencia (MAV)
I. Location
II. Geography
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

7. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Metropolitan Area of Valencia
METROPOLITAN AREA OF VALENCIA (MAV)
(MAV)
 Alluvial plain
Geography
 Several gullies
 Large lagoon (Albufera)
 More than 1,500,000 inhabitants
I. Metropolitan Area of
Valencia (MAV)
I. Location
II. Geography
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

8. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Metropolitan Area of Valencia
FLOOD HAZARD
(MAV)
 Extreme phenomenon: Cold Drop
Cold Drop
 Beginning of Autumn (September-October).
 Occasionally 200-800 l/m2 in few hours
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
I. Cold Drop
II. Historical Records
III. Countermeasures
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

9. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Historical Records
FLOOD HAZARD
 From year 1300 more than 48 large floods
were reported.
Historical records
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
I. Cold Drop
II. Historical Records
III. Countermeasures
III. Methodology
IV. Results
V. Discussion
VI. Conclusions
1300 1400 1500 1600 1700 1800 1900 2000

10. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
FLOOD HAZARD
Historical records
 From year 1300 more than 48 large floods
were reported.
1300 1400 1500 1600 1700 1800 1900 2000
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
I. Cold Drop
II. Historical Records
III. Countermeasures
III. Methodology
IV. Results
V. Discussion
VI. Conclusions
THE Flood 1957

11. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
FLOOD HAZARD
Historical records
 From year 1300 more than 48 large floods
were reported.
1300 1400 1500 1600 1700 1800 1900 2000
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
I. Cold Drop
II. Historical Records
III. Countermeasures
III. Methodology
IV. Results
V. Discussion
VI. Conclusions
Valencia Flood, 1957

12. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
FLOOD HAZARD
Historical records
 From year 1300 more than 48 large floods
were reported.
Water heights in Valencia City, 1957
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
I. Cold Drop
II. Historical Records
III. Countermeasures
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

13. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Historical Records
FLOOD HAZARD
 In the last years,
vulnerability has
been greatly reduced.
Countermeasures
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
I. Cold Drop
II. Historical Records
III. Countermeasures
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

14. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
FLOOD HAZARD
 In the last years,
vulnerability has
been greatly reduced.
 However, for long
return period floods,
the risk for the
inhabitants is still
there
Countermeasures
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
I. Cold Drop
II. Historical Records
III. Countermeasures
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

15. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
FLOOD HAZARD
 In the last years,
vulnerability has
been greatly reduced.
 However, for long
return period floods,
the risk for the
inhabitants is still
there
Countermeasures
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
I. Cold Drop
II. Historical Records
III. Countermeasures
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

16. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Objective
METHODOLOGY
 To model the behavioural choices of the
inhabitants of the region in case of the issue of
an evacuation alert due to long return period
inundations:
1. To find a relationship between significant
variables and main decisions.
2. To assess the response from inhabitants
during an evacuation.
Objective
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
I. Objective
II. Survey
III. Statistical Analysis
IV. Results
V. Discussion
VI. Conclusions

17. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Methodology
METHODOLOGY
 Data source: Internet survey
 Sample: University students of the MAV
 609 accepted responses
Survey
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
I. Objective
II. Survey
III. Statistical Analysis
IV. Results
V. Discussion
VI. Conclusions

18. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
METHODOLOGY
 Data source: Internet survey
 Sample: University students of the MAV
 609 accepted responses
 Survey scenario:
 Evacuation alert has been issued due to
incoming floods expected for 2 or more days.
 At least, heights from 50 cm are expected.
 Individuals are initially in their homes.
 Inhabitants have 12 hours to evacuate before
the storm.
 Shelter locations are well-known by
inhabitants.
Survey
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
I. Objective
II. Survey
III. Statistical Analysis
IV. Results
V. Discussion
VI. Conclusions

19. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
METHODOLOGY
Statistical analysis: Logistic regression
 Binary (for 2 options)
 Multinomial (for 3 options)
Statistical analysis
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
I. Objective
II. Survey
III. Statistical Analysis
IV. Results
V. Discussion
VI. Conclusions
푃푖 =
exp(푉푖)
푘 exp(푉푖)
푖
푉푖 = 훼1푥푖,1 + 훼2푥푖,2 + ⋯ + 훼푛푥푖,푛

20. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
METHODOLOGY
4 main decisions in study:
 푈1: Evacuation decision:
 Leaving
 Staying
 푈2: Destination
 Shelter
 Others
Statistical analysis
 푈3: Transportation
 By car
 Others
 푈4: Departure time
 Early departure
 Regular departure
 Late departure
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
I. Objective
II. Survey
III. Statistical Analysis
IV. Results
V. Discussion
VI. Conclusions

21. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Results: 푼ퟏ: Evacuation decision
 Model 1: Evacuating decision
Evacuation decision
38%
62%
Staying Leaving
 N=609
RESULTS
Model 1
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

22. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
Model 1
Evacuating
Staying
 Evacuating decision
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

23. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Dependent
variable
Independent variable α
T
value
U1:
Evacuating
Being a female 0.6328 3.72**
Have experienced floods -0.3766 -2.43**
Living in Valencia City 0.2937 2.15**
Living below 4th floor 0.3326 2.13**
Being high informed 0.4829 1.99**
**>95% confidence interval
*>90% confidence interval
RESULTS
Model 1
Evacuating
Staying
 Evacuating decision
 N=609
 Hit ratio: 63.22%
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

24. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
Model 1
Evacuating
Staying
 Evacuating decision
 N=609
 Hit ratio: 63.22%
Dependent
variable
Independent variable α
T
value
U1:
Evacuating
Being a female 0.6328 3.72**
Have experienced floods -0.3766 -2.43**
Living in Valencia City 0.2937 2.15**
Living below 4th floor 0.3326 2.13**
Being high informed 0.4829 1.99**
**>95% confidence interval
*>90% confidence interval
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

25. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Evacuating
Staying
 Evacuating decision
 N=609
 Hit ratio: 63.22%
Dependent
variable
Independent variable α
T
value
U1:
Evacuating
Being a female 0.6328 3.72**
Have experienced floods -0.3766 -2.43**
Living in Valencia City 0.2937 2.15**
Living below 4th floor 0.3326 2.13**
Being high informed 0.4829 1.99**
**>95% confidence interval
*>90% confidence interval
RESULTS
Model 1
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

26. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Dependent
variable
Independent variable α
T
value
U1:
Evacuating
Being a female 0.6328 3.72**
Have experienced floods -0.3766 -2.43**
Living in Valencia City 0.2937 2.15**
Living below 4th floor 0.3326 2.13**
Being high informed 0.4829 1.99**
**>95% confidence interval
*>90% confidence interval
RESULTS
Model 1
Evacuating
Staying
 Evacuating decision
 N=609
 Hit ratio: 63.22%
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

27. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 1: Evacuating decision
Model 1
 Females are more likely to evacuate than males.
Researches conducted in US claimed that this is
due to “constructed gender differences and
perceived risk”1.
 "Have experienced floods" is not a factor that
leads people to evacuate. It can be considered as
a belief of low need to evacuate (there has never
been an evacuation) and might also be due to
the young age of the respondents (lack of
experience).
1 J.M. Bateman et al (2002)
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

28. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 2: Destination
 N=376
Destination
27%
73%
Going to a shelter
Not going to a shelter
Model 2
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

29. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Results: 푼ퟐ: Destination
RESULTS
Model 2
 Model 2: Destination
Going to a shelter
I. Metropolitan Area of Other places
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

30. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 2: Destination
 N=376
 Hit ratio: 77.66%
Model 2
Going to a shelter
Other places
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α T value
U2: Going to a
shelter
Floods for more than 4 days 0.3556 5.659**
Having children -0.8844 -3.774**
Being aware of threat -1.031 -2.521**
Having elders -0.5191 -2.154**
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

31. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
 Model 2: Destination
 N=376
 Hit ratio: 77.66%
Going to a shelter
Other places
Dependent
variable
Independent variable α T value
U2: Going to a
shelter
Floods for more than 4 days 0.3556 5.659**
Having children -0.8844 -3.774**
Being aware of threat -1.031 -2.521**
Having elders -0.5191 -2.154**
**>95% confidence interval
*>90% confidence interval
RESULTS
Model 2
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

32. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
 Model 2: Destination
 N=376
 Hit ratio: 77.66%
Going to a shelter
Other places
Dependent
variable
Independent variable α T value
U2: Going to a
shelter
Floods for more than 4 days 0.3556 5.659**
Having children -0.8844 -3.774**
Being aware of threat -1.031 -2.521**
Having elders -0.5191 -2.154**
**>95% confidence interval
*>90% confidence interval
RESULTS
Model 2
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

33. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Model 2
Going to a shelter
I. Metropolitan Area of Other places
**>95% confidence interval
*>90% confidence interval
 Model 2: Destination
 N=376
 Hit ratio: 77.66%
Dependent
variable
RESULTS
Independent variable α T value
U2: Going to a
shelter
Floods for more than 4 days 0.3556 5.659**
Having children -0.8844 -3.774**
Being aware of threat -1.031 -2.521**
Having elders -0.5191 -2.154**
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

34. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 2: Destination
Model 2
 The only variable that encourage inhabitants to
go to a shelter is “floods for 4 or more days”.
This probably means that only individuals who
do not have another place to go would go to
shelter.
 Large families (“Having Children” and “Having
elders”) are prone to go to other places. The
reason could be the special care and necessities
required by them, and the belief that could be
not provided correctly in shelters.
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

35. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
 Model 3: Transportation
 N=376
72%
19%
2%
7%
Transportation
Car
Walking
Public
transportation
Others
RESULTS
Model 3
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

36. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
Model 3
 Model 3: Transportation
By car
I. Metropolitan Area of Others
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

37. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 3: Transportation
 N=376
 Hit ratio: 82.12%
By car
Others
Model 3
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α
T
value
U3: Leaving by
car
Going with the family 2.259 9.223**
Going to shelter -2.953 -9.698**
Living in “Horta Sud” 1.468 1.717*
Picking up a relative 0.4725 1.686*
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

38. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Results: 푼ퟑ: Transportation
RESULTS
 Model 3: Transportation
 N=376
 Hit ratio: 82.12%
By car
Others
Model 3
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α
T
value
U3: Leaving by
car
Going with the family 2.259 9.223**
Going to shelter -2.953 -9.698**
Living in “Horta Sud” 1.468 1.717*
Picking up a relative 0.4725 1.686*
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

39. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 3: Transportation
 N=376
 Hit ratio: 82.12%
By car
Others
Model 3
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α
T
value
U3: Leaving by
car
Going with the family 2.259 9.223**
Going to shelter -2.953 -9.698**
Living in “Horta Sud” 1.468 1.717*
Picking up a relative 0.4725 1.686*
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

40. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
 Model 3: Transportation
 “Going with the family” is in a high relationship
of car usage, since automobile is the most
efficient option when different members are
moving together.
 Individuals who go to a shelter are not likely to
use the car, probably because the lack of
parking space and proximity.
**>95% confidence interval
*>90% confidence interval
RESULTS
Model 3
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

41. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
 Model 4: Departure time
 N=376
31%
47%
23%
100%
80%
60%
40%
20%
0%
Early Departure
(>10h)*
Regular Departure
(10-2h)*
Late Departure
(<2h)*
*Hours before storm
RESULTS
Model 4
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

42. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
 Model 4: Departure time
Early Departure
Regular Departure
Late Departure
RESULTS
Model 4
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

43. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 4: Departure time
 N=376
 Hit ratio: 65.42%
Model 4
Early Departure
Regular Departure
Late Departure
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α T value
U4: Early
Departure
Going with the family 2.252 4.431**
Being a female 1.787 2.313**
Being well-prepared -1.328 -2.013**
Being aware of threat 2.189 1.908*
U4: Regular
Departure
Going with the family 3.28 6.620**
Being a female 1.485 1.935*
Being well-prepared -1.445 -2.254**
Being aware of threat 2.010 1.754*
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

44. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 4: Departure time
 N=376
 Hit ratio: 65.42%
Model 4
Early Departure
Regular Departure
Late Departure
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α T value
U4: Early
Departure
Going with the family 2.252 4.431**
Being a female 1.787 2.313**
Being well-prepared -1.328 -2.013**
Being aware of threat 2.189 1.908*
U4: Regular
Departure
Going with the family 3.28 6.620**
Being a female 1.485 1.935*
Being well-prepared -1.445 -2.254**
Being aware of threat 2.010 1.754*
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

45. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 4: Departure time
 N=376
 Hit ratio: 65.42%
Model 4
Early Departure
Regular Departure
Late Departure
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α T value
U4: Early
Departure
Going with the family 2.252 4.431**
Being a female 1.787 2.313**
Being well-prepared -1.328 -2.013**
Being aware of threat 2.189 1.908*
U4: Regular
Departure
Going with the family 3.28 6.620**
Being a female 1.485 1.935*
Being well-prepared -1.445 -2.254**
Being aware of threat 2.010 1.754*
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

46. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 4: Departure time
 N=376
 Hit ratio: 65.42%
Model 4
Early Departure
Regular Departure
Late Departure
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α T value
U4: Early
Departure
Going with the family 2.252 4.431**
Being a female 1.787 2.313**
Being well-prepared -1.328 -2.013**
Being aware of threat 2.189 1.908*
U4: Regular
Departure
Going with the family 3.28 6.620**
Being a female 1.485 1.935*
Being well-prepared -1.445 -2.254**
Being aware of threat 2.010 1.754*
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

47. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
RESULTS
 Model 4: Departure time
 N=376
 Hit ratio: 65.42%
Model 4
Early Departure
Regular Departure
Late Departure
**>95% confidence interval
*>90% confidence interval
Dependent
variable
Independent variable α T value
U4: Early
Departure
Going with the family 2.252 4.431**
Being a female 1.787 2.313**
Being well-prepared -1.328 -2.013**
Being aware of threat 2.189 1.908*
U4: Regular
Departure
Going with the family 3.28 6.620**
Being a female 1.485 1.935*
Being well-prepared -1.445 -2.254**
Being aware of threat 2.010 1.754*
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

48. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Results: 푼ퟒ: Departure time
RESULTS
 Model 4: Departure time
 Families are more likely to departure in the
central hours (regular departure).
 As expected, individuals who consider
themselves “aware of threat” try to evacuate as
soon as possible.
 On the contrary, those who think that are “well-prepared”
are prone to leave near the storm
beginning (late departure).
Model 4
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
I. Model 1
II. Model 2
III. Model 3
IV. Model 4
V. Discussion
VI. Conclusions

49. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
In summary
DISCUSSION
 Experience is not a key factor to lead people to
evacuate. Nevertheless, it is necessary to take in
account that the sample is compounded by
young people who probably do not have enough
experience.
 Family characteristics are the most important
personal attributes for those who decide to
evacuate. This variable greatly affects the
“destination”, “transportation” and “departure
time” decision.
 Those who are more aware of threat and high
informed have safer attitudes: they are prone to
evacuate more and faster.
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

50. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Conclusions
CONCLUSION
 If a successful evacuation want to be achieved
in future events, it is necessary to focus on the
consciousness related variables (the only ones
that can be externally influenced). Then it
would be necessary to:
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

51. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Conclusions
CONCLUSION
 If a successful evacuation want to be achieved
in future events, it is necessary to focus on the
consciousness related variables (the only ones
that can be externally influenced). Then it
would be necessary to:
 Raise the awareness level.
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

52. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Conclusions
CONCLUSION
 If a successful evacuation want to be achieved
in future events, it is necessary to focus on the
consciousness related variables (the only ones
that can be externally influenced). Then it
would be necessary to:
 Raise the awareness level.
 Provide more information about floods.
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

53. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Conclusions
CONCLUSION
 If a successful evacuation want to be achieved
in future events, it is necessary to focus on the
consciousness related variables (the only ones
that can be externally influenced). Then it
would be necessary to:
 Raise the awareness level.
 Provide more information about floods.
 Training inhabitants to be prepared for
future events.
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

54. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Conclusions
CONCLUSION
 From the point of view of the behavioural
attitude of the surveyed, it can be stated that an
evacuation would be a feasible measure in case
of large flood.
 In further researches a more representative
sample of the whole population should be
surveyed in order to extrapolate results.
However, this study provides a good starting
point.
I. Metropolitan Area of
Valencia (MAV)
II. Flood Hazard
III. Methodology
IV. Results
V. Discussion
VI. Conclusions

55. Thank you for your attention

56. 50th PROCEEDINGS OF INFRASTRUCTURE PLANNING
Behavioural choices in
evacuation during floods:
A preliminary study in Metropolitan
Area of Valencia, Spain
Azarel Chamorro Obra1
Wisinee Wisetjindawat2
Motohiro Fujita3
Nagoya Institute of Technology
Fujita Laboratory
1 Research Student
2 Assistant Professor
3 Professor