Experimental study on the influence of water depth on the evacuation speed of elderly people in flood conditions

International Journal of Disaster Risk Reduction 39 (2019) 101198

Contents lists available at ScienceDirect

International Journal of Disaster Risk Reduction journal homepage: www.elsevier.com/locate/ijdrr

Experimental study on the influence of water depth on the evacuation speed of elderly people in flood conditions

T

Hye-Kyoung Lee, Won-Hwa Hong∗, Youn-Ha Lee School of Architectural, Civil, Environmental and Energy Eng, Kyungpook National University, 80, Daehak-ro, Buk-gu, Deagu 702-701, Republic of Korea

A R T I C LE I N FO

A B S T R A C T

Keywords: Floods Evacuation speed Elderly people Water depth

In an aging population, the need for evacuation plans for the elderly becomes more urgent. However, there is a lack of data and research on the evacuation abilities of elderly people that could be the basis for evacuation planning. Therefore, in this study, the change in the evacuation speeds of seniors was measured in order to establish the standards for a safe evacuation plan for elderly people in the event of a water disaster. The 32 subjects (male-20, female-12) who participated in the experiment served as proxies for the elderly by wearing geriatric simulators that generated movement associated with the elderly. The speeds of male and female participants were measured separately in five water depths, ranging from 10 cm to 50 cm, while performing two types of movement (walking & running), with and without the use of assistive walking devices. Based on this data, we derived the regression equation for the evacuation speeds of the elderly at different water depths, and analyzed their evacuation capabilities. These findings were compared with the evacuation capabilities of young adults and were used to propose suggestions for evacuation plans that will better accommodate the elderly. The evacuation speed of the elderly in various depths of water can be used as basic data for further study, and the results of this analysis will aid decision making in evacuation planning.

1. Introduction Floods are the most damaging and frequent natural disasters in the world [1]. The Center for Research on the Epidemiology of Disaster (CRED) reported that 43.4% (3148) of all disasters in the last 10 years (1998–2017) were flood-related, while 45% (2.0 billion) of all disaster victims were affected by floods [2]. Due to the effects of climate change, the magnitude and frequency of floods are expected to increase [3]. International efforts to reduce or mitigate the impact of disasters have become increasingly focused human vulnerabilities [3]. According to the United Nations (UN), by 2050, 2 billion people over the age of 60 will account for 21% of the global population [4]. As of February 2019, Korea has a population of 51.81 million, of which 7.69 million are over the age of 65, thereby accounting for 14.85% of the total Korean population [5]. It has already an “aged society”, and in 2060, 41.0% of the population is expected to be over the age of 65 [5]. This makes it possible to predict that Korea will be the country with the largest population over the age of 65 in the world. As the number of elderly people increases, the human vulnerabilities due to flooding is also expected to increase. Therefore, aging is not only a personal issue, but also an important factor in developing public policies [6]. ∗

Since elderly people often experience a loss of physical function and don't always have the ability to adequately protect themselves, they are likely to suffer more during times of disaster. During Hurricane Katrina in the United States in 2005, it was found that 60% of those killed were elderly people over 65 years [7]. Following the Great East Japan Earthquake in 2011, people over the age of 60 accounted for 65% of the 2854 deaths [8]. Similarly, typhoon Rusa, which occurred in Korea in 2002 and was the natural disaster that recorded the highest daily precipitation (870.5 mm in Gangneung) since the commencement of meteorological observations in Korea, also resulted in the highest loss of life recorded for a flood in Korea. Rusa caused 246 deaths among the 63,035 flood victims, with elderly people aged over 61 years accounting for 47% of the total deaths [9]. This clearly indicates that the number of elderly deaths due to flooding is particularly high. Therefore, it is necessary to establish more effective flood evacuation plans which cater towards an aged society in order to minimize the loss of life in the elderly people [10]. Research on flood evacuation can be divided into two groups. There are studies which estimate evacuation time [11,12] or the appropriate positions for evacuation shelters [13–15] by using computer simulations, and there are those which calculate loss of life [16–18] and analyze evacuation options using actual data on the damage caused

Corresponding author. E-mail address: [email protected] (W.-H. Hong).

https://doi.org/10.1016/j.ijdrr.2019.101198 Received 9 February 2018; Received in revised form 5 April 2019; Accepted 28 May 2019 Available online 08 June 2019 2212-4209/ © 2019 Elsevier Ltd. All rights reserved.

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

than knee height). These experimental studies which consider water depth have had the aim of determining the maximum possible water depth for evacuation from an underground location via stairs. The evacuation subjects in these studies were young males and females in their 20s and 30s, and there has not yet been any experimental study that takes elderly people into account. In light of this, the present study assesses changes in the evacuation speeds of elderly people at different water depths. The evacuation speed of elderly people will be deduced through a comparison with the evacuation speed of young adults, and the data will be used to make suggestions regarding future evacuation plans that will better accommodate elderly people. The detailed research procedures are as follows. Section 2. This study assessed the gait characteristics and gait speed of elderly people, then measured and analyzed the evacuation speed of young adults according to water depth based on previous experiments. Section 3. Evacuation experiments were conducted to measure the evacuation speed of elderly people according to water depth. The experiments were conducted based on males and females wearing geriatric simulators in five different water depths, using two modes of movement (walking and running), with and without the use of assistive walking devices. Section 4. The evacuation speeds of simulated elderly people were analyzed according to gender, the two modes of movement, and the use of assistive walking devices. Then, factors that need to be considered for the evacuation of elderly people were deduced by comparing these results with the evacuation speeds of young adults. The concluding remarks are presented in Section 5. This study is significant in that it secures experimental data by conducting experiments on elderly people at a point in time when the consideration of weaker members of the population during disasters has become an important agenda due to the growth of aging populations globally. It also analyzes the evacuation abilities of elderly people in order to offer specific suggestions pertaining to the factors that must be considered during the evacuation of elderly people, who differ significantly from young adults.

Abbreviation GS UW AW Ym Yf Sm Sf

geriatric simulator unassisted walking assisted walking young adult males young adult females male seniors female seniors

[19–21]. Experimental studies are essential because studies that use computer simulations require the use of actual evacuation data in order to verify their validity. Previous studies which estimate the loss of life due to floods have typically explained the relationship between water depth and mortality rate based on actual flood incidents. Kawata and Tsuchiya [16] presented a mortality rate according to the scale of a flood based on storms that occurred in Japanese history (i.e. flood area multiplied by water depth), while Mizutani examined relationships between average water depth and mortality [17]. Boyd et al. [18] derived a mortality function from the flood events analysis. Water depth is an important factor in the estimation of loss of life due to floods which must be considered in evacuation plans. Moreover, because evacuees are typically rescued from water during a flood, if an evacuation involves walking on an evacuation path to the evacuation shelter, the evacuation speed and activities are likely to be influenced by water depth. However, experimental studies on evacuation activities which consider water depth have only recently been conducted in Korea and Japan. Kang [19] conducted an experiment by creating a model that adjusts water levels, and deduced that the maximum water depth and flow rate for safe evacuation are 55 cm and 0.9 m/s, respectively. In Japan, Ishigaki et al. [20] also conducted an experimental study using a fullscale model for safe evacuation in an underground area during inundation. In the results, 30 cm was the safe evacuation water depth and the maximum water depth for evacuation was 40 cm. These results differ from the 55 cm proposed by Kang [19], and while it is difficult to make a direct comparison due to the difference in experimental conditions, these results imply that evacuation may be possible at deeper water depths on flatlands than is possible on the stairs. Joo and Kim [21] conducted an experiment using full-scale models in order to assess the different abilities of male and female subjects to evacuate via stairs and to open doors in an underground area during inundation. The results showed that evacuation is difficult without a handrail when the water depth is 35 cm or higher (shin height), similar to the results of the study conducted by Ishigaki et al. [20]. It was also found that evacuation is difficult even with handrails at water depths of 45 cm (more

2. Gait and evacuation speed 2.1. Gait speed of the elderly In addition to psychological decline, elderly people typically experience a loss of physical strength as they age, including muscle decline, issues with staying balanced, and reduced stamina and joint contracture [22]. These reduced physical and mental abilities lead to reduced gait speed. Gait speed was related to the survival of the elderly people [23,24] and it was reflected in health and physical function status [25,26]. In

Table 1 Normal gait speed [33]. Gender (age in years)

Source article (n)

Subjects (n)

Gait speed (m/s)

Grand mean (95%CI) range

Homogeneity Q (p)

male(20to29) male(30to39) male(40to49) male(50to59) male(60to69) male(70to79) male(80to99) female(20to29) female(30to39) female(40to49) female(50to59) female(60to69) female(70to79) female(80to99)

10 5 4 6 12 18 10 11 5 7 10 17 29 17

155 83 96 436 941 3671 1091 180 104 142 456 5013 8591 2152

1.358 1.433 1.434 1.433 1.339 1.262 0.968 1.341 1.337 1.390 1.313 1.241 1.132 0.943

1.217–1.474 1.320–1.538 1.270–1.470 1.122–1.491 1.033–1.590 0.957–1.418 0.608–1.221 1.082–1.499 1.256–1.415 1.220–1.420 1.110–1.555 0.970–1.450 0.830–1.500 0.557–1.170

3.255 (0.983) 1.169 (0.883) 2.609 (0.625) 4.721 (0.580) 15.217 (0.294) 12.848 (0.914) 4.159 (0.940) 5.307 (0.870) 0.785 (0.940) 5.666 (0.579) 12.291 (0.266) 11.515 (0.932) 16.775 (0.998) 11.428 (0.954)

CI: confidence interval. 2

(1.270–1.447) (1.316–1.550) (1.353–1.514) (1.379–1.488) (1.266–1.412) (1.210–1.322) (0.834–1.101) (1.239–1.443) (1.193–1.482) (1.339–1.411) (1.222–1.405) (1.183–1.300) (1.072–1.192) (0.852–1.034)

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

other words, decreased gait speed causes difficulties not only in everyday life, but also in the ability to evacuate to a safe location during emergencies, and is thus an important factor of survival during a disaster. In a study that compared the gait characteristics of young adults and elderly people, there was no distinct difference in terms of cadence (steps/min), but step length had become shorter for elderly people. This is believed to be caused by the fact that they tend to walk more safely and stably [27]. Elderly people also use assistive walking devices for safe walking (crutches, canes, telescope-style walking sticks, walkers, etc.). Assistive walking devices reduce pain and injury, secure gait stability, and increase confidence with respect to fall prevention, thereby helping elderly people walk safely [28]. As age increases, gait speed decreases by 0.2% per year up to age 63, and by 1.6% after the age of 63 [29]. The average walking and running speed in the elderly were, respectively, 20% and 17% less than in the young [30]. Bohannon et al. [31] conducted a meta-analysis on 41 relevant experimental papers in order to set a standard on normal gait speed. The results of normal gait speed according to age and gender are shown in Table 1. In addition, one of the major physical changes that older adults face is decreased vision. Static visual acuity (SVA) of older adults decreases to 80% of that of people in their 30s, from age 65 on [32], while the dynamic visual acuity (DVA) of older adults aged 65 or over is only 50% that of middle-aged people [33]. Night vision also decreases by 30% for older adults, and they need more than twice as long as young adults to recover their vision after viewing reflected light [34]. Decreased vision can be seen as a major causal factor in declining walking speed. Even though the geriatric simulator used for the experiment described in section 3. Had the function of restricting vision, our study conducted an experiment that takes only the spinal and joint decline of older adults into account, and analyzed the result of that experiment.

Table 3 Summary of 1st and 2nd experiments. 1st Experiment Walking

0 cm 10 cm 20cmrowhead 30 cm 40 cm 50 cm 60 cm

2nd Experiment Running

Walking

Running

Mean (m/s)

Std. (m/ s)

Mean (m/s)

Std. (m/ s)

Mean (m/s)

Std. (m/ s)

Mean (m/s)

Std. (m/s)

1.43 1.24 1.07 0.98 0.92 0.85 –

0.10 0.11 0.07 0.07 0.08 0.10 –

3.90 2.58 2.23 1.83 1.47 1.27 –

0.56 0.64 0.62 0.44 0.30 0.24 –

1.39 – 1.09 – 1.04 – 0.91

0.10 – 0.03 – 0.08 – 0.05

3.10 – 1.67 – 1.33 – 0.99

0.34 – 0.20 – 0.17 – 0.07

separate outlier correction was carried out(Table 3). In the results of the first and the second experiments, there was a difference in degree of speed, but the trend was similar. The results of the experiments are as follows [35,36]: 1) As water depth is increased, evacuation speed decreased for all participants both while walking and running. The regression formula for this is the following. - 1st: Walking speed: y = 1.362-0.011x (R2 = 0.785) Running speed: y = 3.419-0.048x (R2 = 0.685) - 2nd: Walking speed: y = 1.331-0.007x (R2 = 0.783) Running speed: y = 2.774-0.0033x (R2 = 0.810) 2) As water depth is increased, there was a drastic decrease in speed difference between walking and running. This shows that as water depth increases, there is no major difference between walking and running for evacuation. 3) The decrease in evacuation speed was greatest in the water depth range of 0 cm-10cm. This shows that the presence of inundation has a greater impact on evacuation speed than water depth. Therefore, it is important that safe walking evacuation must occur before inundation begins. Because there is no major difference in speed between walking and running once inundation begins, and because water depth increases, evacuation plans must be established so that evacuees can evacuate calmly while walking. 4) When evacuating at low water depths, evacuation speed was influenced by leg length, but as water depth grew deeper, differences in the ability to run and to perform other similar physical tasks had a greater influence leg length. 5) When establishing evacuation plans, it is more important to consider the potential fatigue of evacuees at lower water depths than at higher water depths, and when running rather than when walking (Fig. 1).

2.2. Evacuation speed of young adults according to the water depth Before conducting the experiments on the changes in the evacuation speeds of the elderly in different water depths, two experiments were conducted on the changes in the evacuation speeds of young adults evacuees at different water depths (Tables. 2 and 3). In the first and the second experiments, the site used was an outdoor swimming pool in Daegu with a length of 25 m and a width of 15 m. The first experiment was conducted on 20 men in their 20s and 30s (average age of 27.2 years). The experiment involved measuring their evacuation speeds using two modes of movement (walking and running) while making two return trips across 25 m of the experimental area at each of the 5 different water depths (10, 20, 30, 40, 50 cm). The second experiment was conducted on 12 women, ranging from those in their teens to those in their 30s (average age of 23.92 years). The experiment involved measuring the evacuation speed using two modes of movement (walking and running), while making two 25 m return trips of the experimental area at 3 different water depths (20, 40, and 60 cm) (Fig. 1). As the number of participants was small and extreme experimental values did not appear in the first and second experiments, no Table 2 Summary of 1st and 2nd experiments.

1st Experiment (2015.9)

2nd Experiment (2016.5)

Outdoor swimming pool in Deagu, korea (25 m × 15 m) Participant

Method

gender average age average heights number water depth type distance measurement

male 27.20 173.6 cm (8.0 cm) 20 10 m,20 m,30 m,40 m,50 cm walking, running 25 m × 4 times = 100 m speed [m/s]

3

female 23.92 163.8 cm (4.86 cm) 12 20 m,40 m,60 cm walking, running 25 m × 4 times = 100 m speed [m/s]

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

Fig. 1. 1st and 2nd experiments [35,36].

3. Experiment

3.2. Geriatric simulator

3.1. Overview and method

Although it is preferable to take measurements of actual elderly people to accurately assess their walking abilities, it is difficult to conduct a walking experiments with elderly participants. This is because there are issues relating to physical strength and the risk of accidents due to repetitive testing, and this poses problems for securing stable data that can be used to design evacuation plans. As a result, experiments that measure the walking activities from the elderly typically occur by attaching a geriatric simulator (GS) to younger individuals. The geriatric simulator can be easily worn over clothes, and because it is made up of separate devices for each body part, the effect of these parts on experimental results can be assessed separately. Moreover, because these devices are distributed internationally at an affordable price, it is possible to conduct additional experiments with other researchers or to conduct experiments using more subjects. The GS is typically used in field of aged care, in education, and in studies related to developing products and services for the elderly [37,38]. In a study on evacuation, Furukawa et al. [39] verified the validity of using pseudo-elderly people instead of actual elderly people through an experiment that compared the walking activities of actual elderly people and pseudo-elderly people. In the results, the pseudoelderly people were found to be able to properly represent actual elderly people in tests that measure walking activities. The following precautions were proposed when conducting a test that measures walking activities.

The purpose of the evacuation experiment in this study was to assess changes in evacuation speed and the characteristics of evacuation activities for seniors (male and female) according to water depth upon inundation. As such, interventions in the form of environmental factors (flow rate, wind, etc.) aside from water depth were removed as much as possible. The experiment was also conducted under the assumption that evacuees would have to walk in order to evacuate to the evacuation shelter without the help of other modes of transport, such as cars or bicycles. The experimental site was an outside swimming pool with a length of 10 m and width of 6 m (Fig. 2). The site made it possible to adjust water depth, allowed for a set water depth without an incline, had no change in flow rate, and thus enabled accurate experiment results to be acquired without obstruction of the experiment. The experiment involved having make two return trips across 10 m of the experimental site using two different modes of movement (walking and running) and at 5 different water depths (10 cm, 20 cm, 30 cm, 40 cm, 50 cm). To minimize influence between experimental subjects during the experiment, the subjects performed the experiment in groups of 5–6 people at a time. The test was performed 4 times for men (20 subjects = 5 people × 4 times) and 2 times for women (12 subjects = 6 people × 2 times), and all subjects were barefoot during the test. Subjects rested for more than 20 min between the tests to minimize the effect of physical fatigue. Before the experiment, 4 experimental observation cameras (CCTV) were installed and recorded by a DVR. The recorded videos were used to measure the movement time of each test subject. The measured time was converted into speed using the total distance of travel and was then analyzed accordingly (Fig. 3).

1) Because hand and foot restraints and the use of canes have a greater impact on gait speed than reduced hearing or vision during horizontal walking, it is important to walk properly while using a cane when wearing the simulator. 2) Since gait speed becomes more consistent after walking at least five times with the simulator, stable data can be acquired after having subjects practice walking around five times before the actual test. 3) If a person wearing the simulator and a normal individual are in

Fig. 2. Experimental site and test area. 4

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

Fig. 3. Experiment scenes recorded on CCTV.

close proximity, there is a tendency for the person wearing the simulator to following the normal individual's gait. Therefore, it is best to separate those who are wearing the simulator from normal individuals. The GS used in this experiment was made in Korea, and employed in this experiment so that the physical changes (loss of function) experienced by elderly people could be replicated in younger subjects. The main function of a GS is to allow younger individuals to experience the physical state of elderly people by restricting spinal function, joint function, vision, hearing, and grip. The configuration of the simulator is shown in Table 4. During the test, the waist-locking device, knee joint fixation device, elbow joint fixation device, and the walking stick components of the GS were worn by test subjects in their 20s and 30s in order to restrict spinal function and joint functions related to walking (test subjects wearing the GS are called “seniors” in the study to differentiate them from elderly people) (Figs. 4 and 5). The experiment was conducted by dividing subjects into an unassisted walking group (UW: 16 subjects/male 10, female 6) and an assisted walking group (AW: 16 subjects/male-10, female- 6) according to whether the assistive walking devices were used. To secure stable data, the test subjects performed a preliminary walking test about 5 times before the actual test, and normal individuals were separated from those wearing the simulator in accordance with the precautions proposed by Furukawa et al. [39]. Fig. 4. Components of geriatric simulator.

3.3. Experiment participants weight of 71.60 kg. Compared to the average body size of men in their 20s and 30s recorded in the Korean body size survey presented by Statistics Korea [40], the average height of subjects was at 101.30% and weight was at 96.4% of the average. The female subject group had an average height of 166.18 cm and an average weight of 59.27 kg. Compared to the average body size of women in their 20s and 30s from the same Korean body size survey, the average height of subjects was at

Test subjects included 32 physically healthy participants, 20 male (average age of 26.95 years) and 12 female (average age of 25.73 years). Test subjects had no history of neurological or orthopedic illness that would influence their balance or mobility, and had no experience with evacuation from inundation. Table 5 shows the physical characteristics of test subjects. The male subject group had an average height of 175.75 cm and an average Table 4 Configuration of geriatric simulator. Equipment

N

Contents

Function

Use

① ② ③ ④ ⑤ ⑥ ⑦

1 2 2 1 2 1 1

Uncomfortable waist, neck and back Limit knee joint movement Limit elbow joint movement Uncomfortable walking Hearing loss Visual experience such as cataract and glaucoma Limit the ability to hold by hand

Spinal/Joint Spinal/Joint Spinal/Joint Spinal/Joint Hearing Vision Sensory

o o o o x x x

Waist locking device Knee joint fixation device Elbow joint fixation device T-pole Ear plug Goggles Gloves

5

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

Fig. 5. Wearing geriatric simulator.

caused by wearing the GS was −18.64% for walking and −40.24% for running. For females the average walking speed without the GS was 1.31 m/s and the average running speed was 2.65 m/s. While wearing the GS, the average walking speed was 1.10 m/s and the average running speed was 1.55 m/s. Therefore, the rate of decrease resulting from the GS was −16.32% for walking and −41.42% for running. Based on normal gait speed (Table 1), the male subjects wearing the GS was between 80 and 99s (0.834 m/s-1.101 m/s), and the female subjects wearing the GS was between 70-79s (1.072 m/s-1.192 m/s). The rate of decrease in speed while wearing the GS was 16.32–18.64% for walking and 40.24–41.42% for running for both males and females, which shows that regardless of gender, the average speed reduction rate due to wearing GS was similar. Upon comparing the rate of decrease in speed in the unassisted walking (UW) group (16 subjects/male-10, female-6) and the assisted walking (AW) group (16 subjects/male-10, female-6), both walking and running speed decreased for both groups while wearing the GS (Fig. 6). When walking, the UW group showed a 5.34–15.28 (%) decrease while the AW group showed a 22.01–27.30 (%) decrease, demonstrating that the AW group experienced a greater decrease. When running, the UW group showed a 35.16–37.94 (%) decrease while the AW group showed a 45.32–44.90 (%) decrease, once again demonstrating that the AW group experienced a greater decrease in speed. While wearing the GS, the average speeds of subjects according to their use of assistive walking devices (UW and AW) and modes of movement (walking and running) were 1.03 (AWwalking) < 1.10(UW-walking) < 1.47 (AW-running) < 1.81(UWrunning) for males and 0.95 (AW-walking) < 1.25(UW-walking) < 1.43 (AW-running) < 1.68(UW-running) for females.

Table 5 Physical characteristics of test subjects. N

male

female

average height [cm] average weight[kg] average height [cm] average weight[kg]

Experimenter

Korean(20s-30s)

Rate

Mean

Std.

Mean

Std.

20

175.75

5.35

173.50

5.49

101.30%

12

71.60 166.18

9.46 4.42

74.25 160.53

1.11 5.20

96.43% 103.54%

59.27

6.05

56.8

0.92

104.35%

103.54% and weight was at 104.35% of the average. Upon measuring body size, subjects were found to be in the standard group that is within ± 5% of the average body size for Koreans according to the survey. Prior to the evacuation experiment, the gait speeds of subjects were measured before and after wearing the GS to find out the decrease in gait speed caused by wearing the GS. Measurements were taken of subjects performing two different modes of movement (walking and running) whilst making two return trips across a walkway of 10 m (10 m x 4 = 40 m) with a water depth of 0 cm. As the number of participants was small and extreme experimental values did not appear in the first and second experiments, no separate outlier correction was carried out. The results (Table 6) showed that all test subjects (32 subjects/male20, female-12) showed a decrease in their walking and running speeds while wearing the GS. For males, the average walking speed without the GS was 1.31 m/s and the average running speed was 2.74 m/s. While wearing the GS, average walking speed was 1.07 m/s and average running speed was 1.64 m/s. Therefore, the rate of decrease Table 6 The speed changes due to elderly simulator. N

male female

average average average average

walking running walking running

speed[m/s] speed[m/s] speed[m/s] speed[m/s]

20 12

Before

After

Reduction rate

Mean

Std.

Mean

Std.

1.31 2.74 1.31 2.65

0.10 0.45 0.11 0.36

1.07 1.64 1.10 1.55

0.15 0.33 0.17 0.20

6

−18.64% −40.24% −16.32% −41.42%

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

Fig. 6. Comparing the rate of decrease in speed due to wearing of GS.

4. Results

female) and the use of assistive walking devices (UW and AW). Additionally, it examines the differences in evacuation characteristics and evacuation speeds of young adult and senior evacuees by comparing this experiment (changes in the evacuation speed of seniors according to water depths) with previous experiments (changes in evacuation speed of young adults according to water depths).

This study provides fundamental information on the evacuation speed of seniors which can be used to establish evacuation plans that are appropriate for the elderly. This section analyzes the test results according to gender (male and

Fig. 7. Evacuation speed for male and female seniors according to water depth. 7

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

walking group (UW: male-10, female-6) and the assisted walking group (AW: male-10, female-6). The analysis of changes in the evacuation speed seniors using assistive walking devices can be used as basic data for selecting a suitable evacuation distance, or for designating an evacuation shelter when establishing flood evacuation plans appropriate for elderly people who have difficulty walking unassisted. The Mann-Whitney U test was performed in order to assess whether or not there was a statistically significant difference in the evacuation speeds of seniors at different water depths for the UW group and the AW group. In the results, the p-value was less than the significance level of 0.05 for male seniors, except at a water depth of 0 cm. Hence, there is a statistically significant difference in speed according to water depth between the UW group and AW group (Table 8). Upon analyzing the changes in the evacuation speeds of seniors at different water depths between the UW group and AW group (Fig. 8), the speed of the PW group for male and female seniors was less than that of the UW group at all water depths. This shows that seniors who use assistive walking devices are at a disadvantage, compared to those who are able to walk on their own during flood evacuations, and that seniors who use assistive walking devices must be taken into account when establishing evacuation measures for the elderly. The results of the differences in speeds between two groups for male and female seniors in this experiment follow.

4.1. Analysis of the evacuation speed of seniors according to gender Fig. 7 shows data on the recorded evacuation speeds for male and female seniors according to water depth. Evacuation speed was measured through two modes of movements (walking and running). It can be seen that, as water depth increases, the evacuation speed of seniors decreases, both while walking and running. Table 7 shows a comparison of the decrease in speed by water depth for male and female seniors. There was no major difference in the walking or running speeds of male and female seniors at each water depth. However, male seniors showed slightly faster running speeds across all water depths, while female seniors showed faster walking speeds, except at water depths of 10 cm and 20 cm. A similar trend occurred in the decreasing rate of speed in different water depths. Compared to the speeds recorded at 0 cm, there was a 46.96%–48.07% decrease in speed when the water depth was 50 cm for both walking and running. At a water depth of 30 cm, running speed (male-1.07 m/s, female-1.01 m/s) decreased to a speed that was similar to the walking speed recorded at a water depth of 0 cm (male-1.07 m/s, female-1.10 m/s). Moreover, as water depth increased, the difference between walking and running (male: 0.57 m/s→0.29 m/s, female:0.45 m/s→0.21 m/s) decreased. This shows that there is no major difference in the evacuation speed between male and female seniors in terms of evacuating once inundation begins, and no major difference between speeds achieved when walking or running during an evacuation. However, walking evacuations seem to be more beneficial for female seniors than for male seniors. When all seniors were walking, there was a drastic decrease in speed for a water depth of 0 cm-10cm and a water depth of 40 cm-50cm (male:10 cm-13.36%, 50 cm-15.85%; female: 10 cm: 18.35%, 50 cm:18.19%). When running, there was the greatest decrease in speed from 0 cm to 10cm (male-21.03%, female-21.18%). Since the greatest decrease in speed occurred in a water depth of 0 cm-10cm for both walking and running, it is suggested that the presence of flood water has a greater impact on evacuation speed than does water depth. The fact that speed decreased drastically at a water depth of 40 cm-50cm for walking seniors is supportive of the findings of previous studies [21–23] that the maximum water depth for safe evacuation is between 40 cm and 55 cm.

4.2.1. Male seniors (UW group and AW group) For male seniors, at a water depth of 0 cm, the speed of the AW group was 6.36% less than the UW groups while walking and 18.78% less than the UW group while running, which shows the differences in the speeds between two groups is larger when running than when walking. At a water depth of 50 cm, the speed of the AW group was about 23.81% less than the UW group while walking and 25.51% less than the UW group while running. As water depth increased, the difference in speeds between two groups tends to increase both when walking (6.36%→23.8%) and when running (18.78%→25.51%). Moreover, the rate of change in speed for both groups was greatest when the depth was raised from 0 cm to 10 cm (7.78% while walking and 8.55% while running).

4.2. Analysis of the evacuation speed of seniors with and without assistive walking devices

4.2.2. Female seniors (UW group and AW group) For female seniors, the speed of the AW group at a water depth of 0 cm was about 24.60% less than the UW group while walking and 14.88% less than the UW group while running, which shows that the difference in speeds between two groups when walking than when running. While there was a greater difference in speed between the two

In order to assess the changing characteristics and evacuation speeds of seniors using assistive walking devices, an experiment was conducted which divided subjects into two groups: the unassisted

Table 7 Comparison of the decrease in average speed by water depth for male and female seniors. male seniors

(a) walking 0 cm 10 cm 20 cm 30 cm 40 cm 50 cm (b) running 0 cm 10 cm 20 cm 30 cm 40 cm 50 cm

female seniors

Vm-Vf [m/s]

Vm [m/s]

Std. [m/s]

RR [%]

CRR [%]

Vf [m/s]

Std. [m/s]

RR [%]

CRR [%]

1.07 0.92 0.87 0.80 0.73 0.56

0.15 0.11 0.10 0.09 0.12 0.10

13.36% 5.49% 6.56% 6.34% 15.85%

13.36% 18.85% 25.41% 31.75% 47.60%

1.10 0.90 0.86 0.82 0.77 0.57

0.17 0.12 0.14 0.14 0.15 0.13

18.35% 3.65% 3.44% 4.26% 18.19%

18.35% 22.00% 25.44% 29.69% 47.88%

−0.03 0.03 0.01 −0.02 −0.05 −0.01

1.64 1.29 1.22 1.07 0.96 0.85

0.33 0.26 0.26 0.19 0.17 0.16

21.03% 4.51% 9.16% 6.98% 6.39%

21.03% 25.54% 34.70% 41.68% 48.07%

1.55 1.21 1.07 1.01 0.93 0.78

0.20 0.18 0.10 0.10 0.13 0.13

21.18% 8.24% 3.50% 5.24% 8.79%

21.18% 29.43% 32.92% 38.16% 46.96%

0.09 0.09 0.15 0.06 0.03 0.07

*Vm: average speed of male seniors, Vf: average speed of female seniors, RR: reduction rate, CRR: cumulative reduction rate. 8

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

Table 8 Mann-Whitney test for evacuation speed according to water depth of UW and AW groups. water depth (a) male seniors walking speed [m/s]

0 cm 10 cm 20 cm 30 cm 40 cm 50 cm

running speed [m/s]

0 cm 10 cm 20 cm 30 cm 40 cm 50 cm

(b) female seniors walking speed [m/s]

0 cm 10 cm 20 cm 30 cm 40 cm 50 cm

running speed [m/s]

0 cm 10 cm 20 cm 30 cm 40 cm 50 cm

Group

N

Mean

Std.

MR

MWU

Z

p-value

UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

1.10 1.03 0.99 0.85 0.92 0.81 0.87 0.72 0.82 0.64 0.63 0.48 1.81 1.47 1.50 1.09 1.43 1.00 1.23 0.91 1.11 0.81 0.98 0.73

0.06 0.20 0.08 0.78 0.08 0.08 0.07 0.04 0.07 0.06 0.08 0.04 0.26 0.32 0.22 0.04 0.21 0.05 0.12 0.05 0.09 0.04 0.13 0.05

11.50 9.50 14.5 6.5 14.05 6.95 14.95 6.05 15.45 5.55 15.15 5.85 13.40 7.60 15.50 5.50 15.50 5.50 15.50 5.50 15.50 5.50 15.50 5.50

40.00

-.756

.449

10.00

−3.032

.002**

14.50

−2.688

.007**

5.50

−3.31

.001**

.50

−3.746

.000***

3.50

−3.526

.000***

21.00

−2.193

.028*

.000

−3.787

.000***

.000

−3.780

.000***

.000

−3.785

.000***

.000

−3.782

.000***

.000

−3.782

.000***

UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW UW AW

6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6

1.26 0.95 1.00 0.79 0.99 0.73 0.94 0.69 0.90 0.65 0.69 0.45 1.68 1.43 1.34 1.07 1.14 1.00 1.08 0.95 1.02 0.83 0.89 0.68

0.058 0.08 0.05 0.05 0.05 0.05 0.06 0.04 0.08 0.05 0.03 0.06 0.15 0.18 0.12 0.08 0.08 0.05 0.08 0.07 0.08 0.10 0.09 0.04

9.50 3.50 9.50 3.50 9.50 3.50 9.50 3.50 9.50 3.50 9.50 3.50 8.83 4.17 9.17 3.83 9.25 3.75 9.00 4.00 9.17 3.83 9.50 3.50

.000

−2.908

.004**

.000

−2.887

.004**

.000

−2.892

.004**

.000

−2.908

.004**

.000

−2.887

.004**

.000

−2.82

.004**

4.000

−2.258

.024*

2.000

−2.562

.010*

1.500

−2.651

.008**

3.000

−2.406

.016*

2.000

−0.567

.010*

.000

−2.903

.004**

*p < 0.05, **p < 0.01,***p < 0.001.

who can walk on their own, Sm (AW): Male seniors who use a walkingstick, Sf(UW): Female seniors who can walk on their own, Sf(AW): Female seniors who use a walking-stick) during a flood. For cases of six experiments on males, a correlation analysis was performed on the changes in evacuation speed according to mode of movement in different water depths using the Statistical Package for the Social Sciences (SPSS) program. The results showed that evacuation speed had a strong negative correlation with increased water depth for both walking (Ym:–0.886, Sm(UW):-0.878, Sm (AW):-0.862) and running (Ym:–0.828, Sm(UW):-0.865, Sm (AW):-0.830). The correlation was significant at a level of 0.01. For cases of six experiments on females, the results showed that evacuation speed had a strong negative correlation to water depth for both walking (Yf:-0.885; Sf(UW):-0.893, Sf(AW):-0.908) and running (Yf:-0.900, Sf(UW):-0.884, Sf(AW): −0.894). The correlation was significant at a level of 0.01. Fig. 9 shows the results of the regression analysis using the experimental data. The evacuation speeds at different water depths were obtained using the regression formula, and the evacuation speeds of young adults

groups for male seniors when running than when walking across all water depths, there was a greater difference in speed between the two groups for female seniors when walking. However, as water depth increased, the difference in speeds between the two group grew both for walking (24.60%→34.78%) and for running (14.88%→23.60%), as it did with male seniors. 4.3. Comparison of evacuation speeds according to age A regression formula was deduced for the evacuation speed at different water depths by using the test results from both this experiment (changes in the evacuation speed of seniors at different water depths) and the preliminary test which was conducted twice (changes in evacuation speed of young adults at different water depths). This regression formula was used to calculate evacuation speed, and a comparative analysis was then conducted on the impact of water depth on the evacuation speeds of young adults (Ym: Young adult males, Yf: Young adult females) and seniors (Sm(UW): Male seniors 9

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

As a result, it was confirmed that the flood evacuation planning needs to designate the shelter location and the evacuation route considering the evacuation speed of the elderly people who have a lower evacuation speed than young adults. 5. Discussion & conclusions The objective of this study was to propose guidelines to establish an evacuation plan for seniors by using evacuation speed data obtained from an evacuation experiment. The previous studies on floods and water depth have typically focused on the estimation of the loss of life, and most experimental studies on water depth and evacuation are of a relatively recent origin. Even these recent studies are limited in their coverage because they only measure the maximum water depth for evacuation; further, they were conducted in subterranean experimental conditions, and featured young adults alone as the participants. To fill the existing gap in the literature, this study conducted an evacuation experiment on flatland above ground level to assess the evacuation abilities of elderly evacuees at different water depths. Owing to potential safety challenges caused by experiments that use elderly participants, 32 subjects (20 males and 12 females) in their 20s and 30s participated in this experiment by wearing geriatric simulators. The evacuation speeds were measured according to the following characteristics of the participants: gender (male or female); mode of movement (walking or running); and whether assistive walking devices were used in five different water depths, ranging from 10 cm to 50 cm. The evacuation abilities of the elderly were, then, analyzed on the basis of the recorded speeds of subjects wearing geriatric simulators; their evacuation abilities were compared with those of young adults to deduce the differences. The results of the experiment and the factors to be considered while establishing evacuation plans for the elderly are as follows. As the water depth increased, both the walking and running evacuation speed of seniors decreased. There was no major difference in the speed of male and female seniors at each water depth; further, the decrease in speed with increase in water depth was also similar for the male and female seniors. The greatest decrease in speed, for both walking and running, was observed when the water depth was increased from 0 cm to 10 cm; as the water depth was increased, the difference between the walking and running speed decreased. These results shows that the evacuation speed of seniors is affected more by the existence or absence of a flood, rather than by the scale of the flood. Therefore, safe evacuation of seniors should start before the flooding occurs. Further, the evacuation should be planned in such a manner that seniors can walk and evacuate calmly; this is because when the flood depth increases after the start of flooding, there is little difference between the running and walking speeds. The evacuation speeds of both male and female seniors who used assistive walking devices (UW) were slower than those of seniors who did not use assistive walking devices (AW) at the various water depths. Further, as the water depth increased, the difference in speed between the UW group and AW group was found to increase. This shows that seniors who use AW are at a disadvantage when compared with those who are able to walk on their own during flood evacuations; further, seniors using UW must be taken into account when establishing the evacuation measures for the elderly. This study measured the evacuation speed of seniors using T-pole as the assistive walking device. Further research on the evacuation ability and characteristics of seniors, such as their physical movement ability and the type of assistive walking device (T-pole, walker, rollator, etc.) used will help to establish concrete evacuation plans. It is well known that young adults can move faster than seniors. However, this study tried to determine how fast seniors can evacuate in comparison to young adults. An ideal evacuation in the event of a flood is to escape by running when the water depth is less than 40 cm. When evacuating from the water depth for safe evacuation, the maximum gap

Fig. 8. The changes in the evacuation speeds of seniors at different water depths for the UW and AW group.

(Ym, Yf) and seniors (Sm(UW), Sm (AW), Sf(UW), Sf(AW)) were compared in Table 9. When walking, Sm(UW) and Sm (AW) were able to evacuate at a speed that was 81.15% and 72.36% of Ym, respectively, at a water depth of 10 cm. However, as water depth increased, the speed of Sm (UW) approached the speed of Ym whilst the speed of Sm (AW) decreased to 42.74% of the speed of Ym at a water depth of 80 cm. Sf(UW) and Sf(AW) were able to evacuate at speeds that were 87.31% and 66.46% of Yf, respectively, at a water depth of 10 cm. When walking at a water depth of 80 cm, Sf(UW) and Sf(AW) were able to evacuate at speeds of 61.09% and 36.06% of Yf, respectively. As water depth increased, the difference between the evacuation speeds of senior and young adults is so great that it is difficult to evacuate seniors as compared to young adults. When running, the speeds of Sm(UW) and Sm (AW) were 53.73% and 40.93% of the speed of Ym, respectively, at a water depth of 10 cm, showing that there was a major difference in speed between Ym and Sm when running and walking. However, as water depth increased, the difference in speed was reduced, and at a water depth of 60 cm the speeds of Sm(UW) and Sm (AW) rose to 144.53% and 102.60% of Ym, respectively. Sf(UW) and Sf(AW) were able to evacuate at speeds that were 57.36% and 48.40% of Yf, respectively, at a water depth of 10 cm. However, as water depth increased, the difference in speed decreased initially, then the speed of Sf(UW) increased to 121.12% of Yf at a water depth of 70 cm, and at a water depth of 80 cm the speed of both Sf(UW) and Sf(AW) increased to 314.96% and 203.73% of Yf, respectively. However, it is impossible to achieve evacuation by running when the water depth is over the maximum water depth for safe evacuation (40–55 cm), and in case of real floods, the ideal evacuation is to escape by running when the water depth is safe for evacuation (less than 40 cm). When evacuating by running at a water depth of less than 40 cm, Sm(UW) evacuation speed is 53.73.36%–73.32% of Ym evacuation speed, and Sm (AW) is 40.93–54.24% of Ym evacuation speed. Similarly, Sf (UW) evacuation speed and the Sf (AW) evacuation speed is 57.36–67.54% and 48.40%–54.54%, respectively, of Yf evacuation speed. 10

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

Fig. 9. The regression analysis between evacuation speed and water depth.

speed becomes slower than the average evacuation speed of seniors. The reason for this is thought to be the fatigue caused the quick action taken by the young adults to evacuate. This result somewhat contradicts the general notion that young adults can move faster than seniors, and suggests that the evacuation plans that are established should consider the fatigue in young adults, as well as seniors.

between the evacuation speed of a senior (Sm [AW]) and that of a young adult is at a water depth of 10 cm, when the speed is 40.93% of a young adult's evacuation speed. These results indicate that evacuation planning for seniors should take into account the fact that their evacuation speed is different from that of younger adults. Further, when young adults evacuate by running in deep water (60 cm or over), their 11

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

Table 9 Estimate of the evacuation speeds using regression equation. evacuation speeds when walking (m/s)

(a) males 10 cm 20 cm 30 cm 40 cm 50 cm 60 cm 70 cm 80 cm (b) females 10 cm 20 cm 30 cm 40 cm 50 cm 60 cm 70 cm 80 cm

evacuation speeds when running (m/s)

Ym (a)

Sm(UW) (b)

Sm(AW) (c)

(d)=(b)/(a)

(e)=(c)/(a)

Ym (a)

Sm(UW) (b)

Sm(AW) (c)

(d)=(b)/(a)

(e)=(c)/(a)

1.252 1.142 1.032 0.922 0.812 0.702 0.592 0.482

1.016 0.936 0.856 0.776 0.696 0.616 0.536 0.456

0.906 0.806 0.706 0.606 0.506 0.406 0.306 0.206

81.15% 81.96% 82.95% 84.16% 85.71% 87.75% 90.54% 94.61%

72.36% 70.58% 68.41% 65.73% 62.32% 57.83% 51.69% 42.74%

2.939 2.459 1.979 1.499 1.019 0.539 0.059 −0.421

1.579 1.419 1.259 1.099 0.939 0.779 0.619 0.459

1.203 1.073 0.943 0.813 0.683 0.553 0.423 0.293

53.73% 57.71% 63.62% 73.32% 92.15% 144.53% 1049.15% −109.03%

40.93% 43.64% 47.65% 54.24% 67.03% 102.60% 716.95% −69.60%

1.261 1.191 1.121 1.051 0.981 0.911 0.841 0.771

1.101 1.011 0.921 0.831 0.741 0.651 0.561 0.471

0.838 0.758 0.678 0.598 0.518 0.438 0.358 0.278

87.31% 84.89% 82.16% 79.07% 75.54% 71.46% 66.71% 61.09%

66.46% 63.64% 60.48% 56.90% 52.80% 48.08% 42.57% 36.06%

2.444 2.114 1.784 1.454 1.124 0.794 0.464 0.134

1.402 1.262 1.122 0.982 0.842 0.702 0.562 0.422

1.183 1.053 0.923 0.793 0.663 0.533 0.403 0.273

57.36% 59.70% 62.89% 67.54% 74.91% 88.41% 121.12% 314.93%

48.40% 49.81% 51.74% 54.54% 58.99% 67.13% 86.85% 203.73%

This study provides basic data about evacuation speeds in diverse conditions (water depth, age, gender, mode of movement, and the use of assistive walking devices) by conducting experiments. Then, on the basis of the data collected, the characteristics of the evacuation behaviour of seniors and young adults are described, and considerations for evacuation planning are suggested. The suggestions based on the analysis will help in decision making for evacuation planning. However, the present study did not consider any environmental factor affecting evacuation (e.g., wind speed, slope, flow velocity, debris in water), except water depth. The evacuation speed can also be influenced by various other factors (e.g., body size, physical movement ability, presence of dependents, and helpful behaviours during evacuation), but only gender and age were considered in this study. Further, the measurement data should be used cautiously, considering that the experiment was conducted with young adults wearing geriatric simulators instead of actual seniors. Not considering the diverse factors mentioned above means that the actual evacuation speed may be lower than the results of the study suggest; in other words, the measured speeds should be seen as the upper limits during evacuation. If the limitations of this study can be overcome and various experimental studies on evacuation speed and behaviour can be performed based on the data provided by this study, it could lead, in the future, to a reduction in not only the vulnerability caused by disasters, but also the loss of lives of seniors.

[6] [7]

[8]

[9] [10]

[11]

[12]

[13]

[14]

[15]

[16] [17]

Acknowledgments [18]

This work was supported by Korea Environment Industry & Technology Institute(KEITI) though Water Management Research Program, funded by Korea Ministry of Environment(MOE)(79609).

[19]

[20]

References [1] S.N. Jonkman, Global perspectives on loss of human life caused by floods, Nat. Hazards 34 (2005) 151–175, https://doi.org/10.1007/s11069-004-8891-3. [2] W. Pascaline, R. House, D. McClean, R. Below, Economic Losses, Poverty and Disasters 1998-2017, (2018), https://doi.org/10.1111/j.1469-7610.2010.02280.x. [3] D. Kvočka, R.A. Falconer, M. Bray, Flood hazard assessment for extreme flood events, Nat. Hazards 84 (2016) 1569–1599, https://doi.org/10.1007/s11069-0162501-z. [4] United Nations Department of Economic and Social Affairs, Population Division, World Population Prospects: the 2017 Revision, (2017), https://doi.org/10.1017/ CBO9781107415324.004. [5] The population statistics, Korean Statistical Information Service, 2019, http://kosis. kr/statHtml/statHtml.do?orgId=101&tblId=DT_1BPA002&vw_cd=&list_id=&

[21]

[22] [23]

[24]

12

scrId=&seqNo=&lang_mode=ko&obj_var_id=&itm_id=&conn_path=E1 accessed March 2019. N. Muramatsu, H. Akiyama, Japan: super-aging society preparing for the future, Gerontol. 51 (2011) 425–432, https://doi.org/10.1093/geront/gnr067. R.M. Zoraster, Vulnerable populations: hurricane Katrina as a case study, Prehospital Disaster Med. 25 (2010) 74–78, https://doi.org/10.1017/ S1049023X00007718. N. Mimura, K. Yasuhara, S. Kawagoe, H. Yokoki, S. Kazama, Damage from the Great East Japan Earthquake and tsunami - a quick report, Mitig. Adapt. Strategies Glob. Change 16 (2011) 803–818, https://doi.org/10.1007/s11027-011-9297-7. Korea Meteorological Administration, Typhoon White Book, (2011). R. ELDAR, The needs of elderly persons in natural disasters: observations and recommendations, Disasters 16 (1992) 355–358, https://doi.org/10.1111/j.14677717.1992.tb00416.x. A.J. Pel, S.P. Hoogendoorn, M.C.J. Bliemer, Evacuation modeling including traveler information and compliance behavior, Procedia Eng. 3 (2010) 101–111, https:// doi.org/10.1016/j.proeng.2010.07.011. J. Kim, Y. Kuwahara, M. Kumar, A DEM-based evaluation of potential flood risk to enhance decision support system for safe evacuation, Nat. Hazards 59 (2011) 1561–1572, https://doi.org/10.1007/s11069-011-9852-2. K. Kim, P. Pant, E. Yamashita, Integrating travel demand modeling and flood hazard risk analysis for evacuation and sheltering, Int. J. Disaster Risk Reduct. (2017), https://doi.org/10.1016/j.ijdrr.2017.10.025. S. Kongsomsaksakul, C. Yang, A. Chen, Shelter location-allocation model for flood evacuation planning, J. East Asia Soc. 6 (2005) 4237–4252, https://doi.org/10. 11175/easts.6.4237. H.D. Sherali, T.B. Carter, A.G. Hobeika, A location-allocation model and algorithm for evacuation planning under hurricane/flood conditions, Transp. Res. Part B Methodol. 25 (1991) 439–452, https://doi.org/10.1016/0191-2615(91)90037-J. Y.K. Yoshito Tsuchiya, Risk to life, warning systems, and protective construction against past storm surges in Osaka Bay, Nat. Disaster Sci. 3 (1981) 33–55. S.N. Jonkman, J.K. Vrijling, A.C.W.M. Vrouwenvelder, Methods for the estimation of loss of life due to floods: a literature review and a proposal for a new method, Nat. Hazards 46 (2008) 353–389, https://doi.org/10.1007/s11069-008-9227-5. E. Boyd, M. Levitan, I. van Heerdan, Further Specification of the Dose-Relationship for Flood Fatality Estimation, (2005), pp. 1–15. S.-H. Kang, Study on refuge behavior and its critical inundation depth in low area, J. Korean Soc. Civ. Eng. 23 (6B) (2003) 561–565 https://scholar.google.co.kr/ scholar?hl=ko&as_sdt=0%2C5&q=Study+on+Refuge+Behavior+and+Its +Critical+Inundation+Depth+in+Low+Area&btnG=. T. Ishigaki, Y. Onishi, Y. Asai, K. Toda, H. Shimada, Evacuation criteria during urban flooding in underground space, 11th Int. Conf. Urban Drain, 2008, p. 7 https://scholar.google.co.kr/scholar?hl=ko&as_sdt=0%2C5&q=Evacuation +criteria+during+urban+flooding+in+underground+space&btnG=. J. Joo, T.-H. Kim, An experimental study on evacuation ability during underground space inundation, J. Korean Soc. Hazard Mitig. 15 (2015) 189–196, https://doi. org/10.9798/KOSHAM.2015.15.2.189. Rein Tideiksaar, Falls in Older People: Prevention and Management, Health Professions Press, 2002. M. Cesari, S.B. Kritchevsky, A.B. Newman, E.M. Simonsick, T.B. Harris, B.W. Penninx, J.S. Brach, F.A. Tylavsky, S. Satterfield, D.C. Bauer, S.M. Rubin, M. Visser, M. Pahor, Added value of physical performance measures in predicting adverse health-related events: results from the health, aging and body composition study, J. Am. Geriatr. Soc. 57 (2009) 251–259, https://doi.org/10.1111/j.15325415.2008.02126.x. G. V Ostir, Y.-F. Kuo, I.M. Berges, K.S. Markides, K.J. Ottenbacher, Measures of

International Journal of Disaster Risk Reduction 39 (2019) 101198

H.-K. Lee, et al.

[25]

[26] [27]

[28]

[29]

[30] [31]

[32]

safety, Accid. Anal. Prev. (1995), https://doi.org/10.1016/0001-4575(94)00077-Y. [33] R. Klein, Age-related eye disease, visual impairment, and driving in the elderly, Hum. Factors (1991), https://doi.org/10.1177/001872089103300504. [34] P.L. Olson, Problems of nighttime visibility and glare for older drivers, SAE Tech. Pap. Ser. 1988, https://doi.org/10.4271/881756. [35] H.-K. Lee, W.-H. Hong, Y.-H. Lee, A study on the evacuation speed changes according to the depth of water, J. Archit. Inst. Korea Plan. Des. 32 (2016) 75–82, https://doi.org/10.5659/JAIK_PD.2016.32.3.75. [36] H.-K. Lee, W.-H. Hong, J.-S. Baek, An analysis of the effects of water depth on the evacuation speed of women, J. Archit. Inst. Korea Plan. Des. 36 (2) (2016) 1767–1770. [37] E. Schwalbach, S. Kiernan, Effects of an intergenerational friendly visit program on the attitudes of fourth graders toward elders, Educ. Gerontol. 28 (2002) 175–187, https://doi.org/10.1080/036012702753542490. [38] H.-S. Oh, H.-S. Jeong, Implementation and evaluation of gerontological nursing education program: consist of knowledge about nursing care for elderly and elderly simulation experience, J. Korea Acad. Coop. Soc. 13 (2012) 1654–1664, https:// doi.org/10.5762/KAIS.2012.13.4.1654. [39] Y. Furukawa, S. Tsuchiya, S. Inahara, Y. Hasemi, Reproducibility of Group Evacuation Behavior of the Elderly by, AOFST 7 Symp, (2007), pp. 1–14 http:// www.iafss.org/publications/aofst/7/116. [40] Korean Statistical Information Service, Korean Body Size Statistics, (2015) http:// kosis.kr/statHtml/statHtml.do?orgId=115&tblId=TX_115190170&vw_cd=MT_ ZTITLE&list_id=115_11519&seqNo=&lang_mode=ko&language=kor&obj_var_ id=&itm_id=&conn_path=MT_ZTITLE.

lower body function and risk of mortality over 7 Years of follow-up, Am. J. Epidemiol. 166 (2007) 599–605, https://doi.org/10.1093/aje/kwm121. G. Abellan Van Kan, Y. Rolland, S. Andrieu, J. Bauer, O. Beauchet, M. Bonnefoy, M. Cesari, L.M. Donini, S. Gillette-Guyonnet, M. Inzitari, F. Nourhashemi, G. Onder, P. Ritz, A. Salva, M. Visser, B. Vellas, Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force, J. Nutr. Health Aging 13 (2009) 881–889, https://doi.org/10.1007/s12603-009-0246-z. S. Studenski, Gait speed and survival in older adults, J. Am. Med. Assoc. 305 (2011) 50, https://doi.org/10.1001/jama.2010.1923. D.A. Winter, A.E. Patla, J.S. Frank, S.E. Walt, Biomechanical walking pattern changes in the fit and healthy elderly, Phys. Ther. 70 (1990) 340–347, https://doi. org/10.1093/ptj/70.6.340. F. Aminzadeh, N. Edwards, Exploring seniors' views on the use of assistive devices in fall prevention, Publ. Health Nurs. 15 (1998) 297–304, https://doi.org/10.1111/ j.1525-1446.1998.tb00353.x. R.J. Dobbs, A. Charlett, S.G. Bowes, C.J.A. O’Neill, C. Weller, J. Hughes, S.M. Dobbs, Is this walk normal? Age Ageing 22 (1993) 27–30, https://doi.org/10. 1093/ageing/22.1.27. R.J. Elble, S.S. Thomas, C. Higgins, J. Colliver, Stride-dependent changes in gait of older people, J. Neurol. 238 (1991) 1–5, https://doi.org/10.1007/BF00319700. R.W. Bohannon, A. Williams Andrews, Normal walking speed: a descriptive metaanalysis, Physiotherapy 97 (2011) 182–189, https://doi.org/10.1016/j.physio. 2010.12.004. Y. Mori, M. Mizohata, Characteristics of older road users and their effect on road

13