Behavioural choices in evacuations during floods: a preliminary study in Metropolitan Area of...

Behavioural choices in

evacuation during floods:

Azarel Chamorro Obra1

Wisinee Wisetjindawat2

Motohiro Fujita3

Nagoya Institute of Technology

Fujita Laboratory

A preliminary study in Metropolitan

Area of Valencia, Spain

50th PROCEEDINGS OF INFRASTRUCTURE PLANNING

1 Research Student

2 Assistant Professor

3 Professor

I. Metropolitan Area of

Valencia (MAV)

I. Location

II. Geography

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Europe


METROPOLITAN AREA OF VALENCIA (MAV)

Location

Metropolitan Area of Valencia

(MAV)

Spain



Location


Valencia (MAV)

I. Location

II. Geography

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions


(MAV)

Metropolitan Area of Valencia (red)



Location


Valencia (MAV)

I. Location

II. Geography

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions


(MAV)

Alluvial plain

Several gullies



Geography


Valencia (MAV)

I. Location

II. Geography

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions


(MAV)

Alluvial plain

Several gullies

Large lagoon (Albufera)



Geography


Valencia (MAV)

I. Location

II. Geography

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions


(MAV)

Alluvial plain

Several gullies

Large lagoon (Albufera)

More than 1,500,000 inhabitants



Geography


Valencia (MAV)

I. Location

II. Geography

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions


(MAV)

Extreme phenomenon: Cold Drop

Beginning of Autumn (September-October).

Occasionally 200-800 l/m2 in few hours


FLOOD HAZARD

Cold Drop


Valencia (MAV)

II. Flood Hazard

I. Cold Drop

II. Historical Records

III. Countermeasures

III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Historical Records

From year 1300 more than 48 large floods

were reported.


FLOOD HAZARD

Historical records


Valencia (MAV)

II. Flood Hazard

I. Cold Drop



III. Methodology

IV. Results

V. Discussion

VI. Conclusions

1300 1400 1500 1600 1700 1800 1900 2000

1300 1400 1500 1600 1700 1800 1900 2000


were reported.


FLOOD HAZARD

Historical records


Valencia (MAV)

II. Flood Hazard

I. Cold Drop



III. Methodology

IV. Results

V. Discussion

VI. Conclusions

THE Flood 1957

1300 1400 1500 1600 1700 1800 1900 2000


were reported.


FLOOD HAZARD

Historical records


Valencia (MAV)

II. Flood Hazard

I. Cold Drop



III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Valencia Flood, 1957


were reported.

Water heights in Valencia City, 1957


FLOOD HAZARD

Historical records


Valencia (MAV)

II. Flood Hazard

I. Cold Drop



III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Historical Records

In the last years,

vulnerability has

been greatly reduced.


FLOOD HAZARD

Countermeasures


Valencia (MAV)

II. Flood Hazard

I. Cold Drop



III. Methodology

IV. Results

V. Discussion

VI. Conclusions

However, for long

return period floods,

the risk for the

inhabitants is still

there

In the last years,

vulnerability has

been greatly reduced.


FLOOD HAZARD

Countermeasures


Valencia (MAV)

II. Flood Hazard

I. Cold Drop



III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Objective

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.


METHODOLOGY

Objective


Valencia (MAV)

II. Flood Hazard

III. Methodology

I. Objective

II. Survey

III. Statistical Analysis

IV. Results

V. Discussion

VI. Conclusions

Methodology

Data source: Internet survey

Sample: University students of the MAV

609 accepted responses


METHODOLOGY

Survey


Valencia (MAV)

II. Flood Hazard

III. Methodology

I. Objective

II. Survey


IV. Results

V. Discussion

VI. Conclusions

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.


METHODOLOGY

Survey


Valencia (MAV)

II. Flood Hazard

III. Methodology

I. Objective

II. Survey


IV. Results

V. Discussion

VI. Conclusions

Statistical analysis: Logistic regression

Binary (for 2 options)

Multinomial (for 3 options)


METHODOLOGY

Statistical analysis


Valencia (MAV)

II. Flood Hazard

III. Methodology

I. Objective

II. Survey


IV. Results

V. Discussion

VI. Conclusions

𝑃𝑖 =exp(𝑉𝑖)

𝑖𝑘 exp(𝑉𝑖)

𝑉𝑖 = 𝛼1𝑥𝑖,1 + 𝛼2𝑥𝑖,2 +⋯+ 𝛼𝑛𝑥𝑖,𝑛

4 main decisions in study:

𝑈1: Evacuation decision:

Leaving

Staying

𝑈2: Destination

Shelter

Others

𝑈3: Transportation

By car

Others

𝑈4: Departure time

Early departure

Regular departure

Late departure


METHODOLOGY

Statistical analysis


Valencia (MAV)

II. Flood Hazard

III. Methodology

I. Objective

II. Survey


IV. Results

V. Discussion

VI. Conclusions

Results: 𝑼𝟏: Evacuation decision

38%

62%

Evacuation decision

Staying Leaving

Model 1: Evacuating decision

N=609


RESULTS

Model 1


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


RESULTS

Model 1

Evacuating

Staying

Evacuating decision


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

Dependent

variableIndependent 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

RESULTS

Model 1

Evacuating

Staying

Evacuating decision

N=609

Hit ratio: 63.22%

Dependent


T

value

U1:

Evacuating









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

Evacuating

Staying

Evacuating decision

N=609

Hit ratio: 63.22%

Dependent


T

value

U1:

Evacuating








RESULTS

Model 1


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

Dependent


T

value

U1:

Evacuating








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

Model 1: Evacuating decision

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)


RESULTS

Model 1


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

Model 2: Destination

N=376

27%

73%

Destination

Going to a shelter

Not going to a shelter


RESULTS

Model 2


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

Results: 𝑼𝟐: Destination50th PROCEEDINGS OF INFRASTRUCTURE PLANNING

RESULTS

Model 2


Going to a shelter

Other placesI. 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


N=376

Hit ratio: 77.66%


Dependent

variableIndependent 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**

Going to a shelter

Other places


RESULTS

Model 2


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


N=376

Hit ratio: 77.66%

Going to a shelter

Other places

Dependent


U2: Going to a

shelter







RESULTS

Model 2


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


Dependent


U2: Going to a

shelter






RESULTS

Model 2


N=376

Hit ratio: 77.66%

Going to a shelter

Other placesI. 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


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.


RESULTS

Model 2


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

Model 3: Transportation

N=376

72%

19%

7%

2%

Transportation

Car

Walking

Public

transportation

Others


RESULTS

Model 3


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


RESULTS

Model 3


By car

OthersI. 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


N=376

Hit ratio: 82.12%


Dependent


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*

By car

Others


RESULTS

Model 3


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


N=376

Hit ratio: 82.12%

By car

Others

Results: 𝑼𝟑: Transportation


Dependent


T

value

U3: Leaving by

car






RESULTS

Model 3


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


N=376

Hit ratio: 82.12%


Dependent


T

value

U3: Leaving by

car





By car

Others


RESULTS

Model 3


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


“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.



RESULTS

Model 3


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

Model 4: Departure time

N=376

31%

47%

23%

0%

20%

40%

60%

80%

100%

Early Departure

(>10h)*

Regular Departure

(10-2h)*

Late Departure

(<2h)*

*Hours before storm


RESULTS

Model 4


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


Early Departure

Regular Departure

Late Departure


RESULTS

Model 4


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


N=376

Hit ratio: 65.42%


Dependent


U4: Early

Departure



Being well-prepared -1.328 -2.013**

Being aware of threat 2.189 1.908*

U4: Regular

Departure


Being a female 1.485 1.935*

Being well-prepared -1.445 -2.254**

Being aware of threat 2.010 1.754*

Early Departure

Regular Departure

Late Departure


RESULTS

Model 4


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

Results: 𝑼𝟒: 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).


RESULTS

Model 4


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

In summary

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.


DISCUSSION


Valencia (MAV)

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Conclusions

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:


CONCLUSION


Valencia (MAV)

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Conclusions






Raise the awareness level.


CONCLUSION


Valencia (MAV)

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Conclusions







Provide more information about floods.


CONCLUSION


Valencia (MAV)

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Conclusions







Provide more information about floods.

Training inhabitants to be prepared for

future events.


CONCLUSION


Valencia (MAV)

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Conclusions

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.


CONCLUSION


Valencia (MAV)

II. Flood Hazard

III. Methodology

IV. Results

V. Discussion

VI. Conclusions

Thank you for your attention

Behavioural choices in

evacuation during floods:

Azarel Chamorro Obra1

Wisinee Wisetjindawat2

Motohiro Fujita3

Nagoya Institute of Technology

Fujita Laboratory

A preliminary study in Metropolitan

Area of Valencia, Spain


1 Research Student

2 Assistant Professor

3 Professor

Behavioural choices in evacuations during floods: a preliminary study in Metropolitan Area of...

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