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Vehicle-related flood fatalities inGreeceMichalis Diakakisa & Giorgos Deligiannakisb

a Faculty of Geology and Geoenvironment, School of Sciences,National and Kapodistrian University of Athens, Panepistimioupoli,15784 Athensb Department of Earth and Atmospheric Sciences Mineralogy –Geology Laboratory, Agricultural University of Athens, 75 IeraOdosStr., GR 11855, Athens, GreecePublished online: 19 Sep 2013.

To cite this article: Michalis Diakakis & Giorgos Deligiannakis , Environmental Hazards(2013): Vehicle-related flood fatalities in Greece, Environmental Hazards, DOI:10.1080/17477891.2013.832651

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Vehicle-related flood fatalities in Greece

Michalis Diakakisa* and Giorgos Deligiannakisb

aFaculty of Geology and Geoenvironment, School of Sciences, National and Kapodistrian University ofAthens, Panepistimioupoli, 15784 Athens; bDepartment of Earth and Atmospheric Sciences Mineralogy –Geology Laboratory, Agricultural University of Athens, 75 IeraOdos Str., GR 11855, Athens, Greece

(Received 8 February 2013; final version received 1 August 2013)

This work focuses on the analysis of vehicle-related flood fatalities in Greece, in an effort toprovide a better understanding on the circumstances under which they occur. Therefore, aninventory of 60 fatalities associated with the use of vehicles, induced during 37 flood eventsbetween 1970 and 2010, was studied. To this end, we developed a database consisting ofvariables that provided a systematic description of the circumstances under which eachincident occurred, including details of the surrounding environment, the road infrastructure,specifics on the incident and demographic details of the involved individuals. Analysisshowed an increase in vehicle-related cases over the period of study, with the majority ofthe incidents occurring after 1990. Males, and individuals between 40 and 69 years old,showed an increased representation among both the drivers and the victims, although thelatter showed an overrepresentation of young individuals as well. Most events occurredduring nighttime and in rural areas of the country. With respect to the surroundings, mostcases occurred on paved road network and bridges that proved vulnerable to floodingphenomena. In a significant number of cases, fatal incidents occurred on paved rivercrossings, constructed on the riverbed of usually dry torrents or waterways. Drowning wasfound to be the primary cause of death. Analysis of the drivers’ actions, exactly before theincident, showed that in the majority of occasions, they chose to enter into flooded areas,either to travel across or to save someone, or recover something. In some cases, vehicleoccupants found themselves in a hazardous position when floodwaters rose unexpectedly,giving them no chance to avoid danger. It was therefore found that drivers, pursued anactive, rather than a passive, stance in the majority of incidents, attributed, in certainoccasions, to an underestimation of risk.

Keywords: flood fatalities; vehicles; drowning; Greece; flood mortality; accidents

1. Introduction

Floods are one of the most common natural hazards in the Mediterranean region, presenting a richrecord of events (Barrera, Llasat, & Barriendos, 2006; Gaume et al., 2009; Guzzetti & Tonelli,2004; Llasat et al., 2010a; Savvidou et al., 2008) and causing yearly a significant number of fatal-ities and extensive economic losses (Barrero, 2007, 2009; Jonkman & Kelman, 2005; Kunkel,Pielke, & Changnon, 1999; Priest et al., 2009). Greece is no exception to this regime, as the lit-erature shows an abundance of flooding phenomena across the country (Diakakis, 2010; Diaka-kis, Deligiannakis, & Mavroulis, 2011b; Koutroulis, Tsanis, & Daliakopoulos, 2010; Mimikou &

© 2013 Taylor & Francis

*Corresponding author. Email: diakakism@geol.uoa.gr

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Koutsoyiannis, 1995; Stathis, 2004). In the region, flash floods are a common type of disaster(Llasat, Llasat-Botija, Rodriguez, & Lindbergh, 2010b), occurring as high-intensity, short dur-ation storms (Bull, Kikrby, Shannon, & Hooke, 2000) cause overflowing of watercoursesleading occasionally to abrupt and violent change of fluvial conditions (Bracken, Cox, &Shannon, 2008; Dick, Anderson, & Sampson, 1997). These changes, occurring in a short time-frame, can potentially lead to miscalculation of risk by individuals, especially vehicle occupantsthat use the road network in the vicinity of these watercourses.

The literature indicates that vehicle-related incidents account for an important part of flood fatal-ities (Drobot, Benight, & Gruntfest, 2007b; Priest et al., 2009; Ruin, Gaillard, & Lutoff, 2007; Yale,Cole, Garrison, Runyan, & RiadRuback, 2003). French, Ing, Von Allmen, and Wood (1983)showed that 42% out of 177 fatalities caused by drowning in the United States were car-related.Ashley and Ashley (2008) calculated the same figure at 63% of all flood-induced deaths in theU.S. Comparison of their results and of the findings of Maples and Tienfenbacher (2009) regardingthe area of Texas, indicates an increase of vehicle-related fatalities in US over time. Staes, Orengo,Malilay, Rullan, and Noji (1994) found that 87% of the decedents of the 1992 flash floods in PuertoRico were vehicle-occupants. Rappaport (2000) suggested that a minimum of 23% of all loss of lifeassociated with Atlantic Tropical Cyclones in the United States, is attributed to individuals dying in,or attempting to abandon their vehicles. Jonkman and Kelman (2005) showed that 38.5% of a totalof 247 flood fatalities in Europe and the United States were vehicle-related. Coates (1999) foundthat 8.4% of fatal incidents in Australia are related to vehicles, a figure later revised to 48.5% byFitzGerald, Du, Jamal, Clark, and Hou (2010).

Certain factors have been considered in the literature as crucial to the levels of risk developed ina vehicle-related flood situation. These factors include the age and gender of the drivers (Drobotet al., 2007b; Jonah, 1986; Ruin et al., 2007), their familiarity with the road network at the locationof the incident (Yale et al., 2003), their stance (active or passive) towards the imminent risk (Drobotet al., 2007b; FitzGerald et al., 2010; French et al., 1983), their mental and physical condition andtheir blood alcohol content (Jonkman & Kelman, 2005). Other factors concern drivers’ previousflood experiences, perception of warnings (Drobot et al., 2007a; Yale et al., 2003), understandingof the dangers inherent in driving through flooded roads (Drobot et al., 2007a) the vehicle type(Coles 2008) and the level of its submersion in floodwaters (Yale et al., 2003).

Concerning the drivers’ age, Jonah (1986) found that younger vehicle users tend to take morerisks while driving. Drobot et al. (2007b) and Becker, Johnston, Ronan, and Coomer (2008)showed that younger people are more likely to drive into floodwaters, most possibly due toincreased confidence in their own driving ability (Wright, Doody, Becker, & McClure, 2010).Drobot et al. (2007a, 2007b) found that drivers aged between 18 and 35 tend to be overrepre-sented, whereas Ruin et al. (2007) suggested that individuals between 25 and 45 years oldpresent the highest representation. On the contrary, it is suggested that older drivers present agreater tendency to avoid driving into perilous conditions, such as a flooded road (Ball et al.,1998; Becker et al., 2008).

With regard to the gender of victims and drivers, according to Coates (1999), French et al.(1983), Jonkman and Kelman (2005) and Stjernbrandt, Öström, Eriksson, and Björnstig (2008)males are overrepresented in vehicle crashes and drowning connected with floods. Severalauthors (Ashley & Ashley, 2008; Drobot et al., 2007b; Jonkman & Kelman, 2005) suggest thatthis phenomenon is attributed to their tendency to engage in riskier driving behaviours. Beckeret al. (2008) showed that males tend to be more confident than females to drive into floodwaters.Regarding the vehicle type, Coles (2008) suggest that occupants of bigger vehicles are more likelyto try travel across floodwaters. Regarding the timing of the incident, Jonkman and Kelman(2005) suggest that incidents are more abundant during nighttime, as situational judgment canbe hindered by darkness.

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Regarding the drivers’ actions at the time of the incident, FitzGerald et al. (2010) found that inthe majority (81.8%) of fatal incidents, vehicle occupants attempted to cross a watercourse,showing an active stance towards the imminent risk. French et al. (1983), Drobot et al.(2007b), Jonkman and Kelman (2005) and Ruin, Creutin, Anquetin, Gruntfest, and Lutoff(2009) also suggested that an important portion of drivers attempt to travel across waterwaysor low-lying areas susceptible to flooding. Among the possible explanations, it is suggestedthat drivers tend to underestimate the risks associated with flooding on their daily travel routes(Ruin et al., 2007), and that they may face difficulty in judging the depth of the water or theforce of the current crossing the road (FitzGerald et al., 2010; Yale et al., 2003), an assumptionsupported also by experimental studies (Abt, Wittler, Taylor, & Love, 1989).

The objective of this work, given the scarcity of information on flood fatalities in Greece, is toexamine the conditions under which these vehicle-related incidents occur, in order to improve ourunderstanding on the variables affecting road safety during flooding events.

2. Materials and methods

2.1. Data

Primary information on flood events was based on the Flood Database developed for the entireGreek territory by Diakakis, Mavroulis, and Deligiannakis (2012) for the period 1880–2010.This catalogue can be considered a complete inventory of flood fatalities and fatal flood eventsin Greece, as it encompasses all the available sources of related data in the country, including offi-cial agencies archives, scientific sources and the press. Accuracy of information was ensured bycross-referencing data between two or more independent sources. The inventory of Diakakis et al.(2012) contains detailed information on the location, number of fatalities and date of the floodevents. Their catalogue was used as the basic record upon which a database with details concern-ing the circumstances of vehicle-related flood casualties (in the period 1970–2010) was built.

Detailed descriptions of these fatal incidents and information on victims were recovered frompress reports retrieved from the digital newspaper database of the Greek National Library (GreekNational Library, 2010) and the national newspapers microfilm archive of the Library of theHellenic Parliament (Greek National Newspapers Archive, 2010). Additional information onthe incidents was based on scientific articles focusing on some of the fatal flood events (Diakakis,2013; Diakakis, Andreadakis, & Fountoulis, 2011a; Lekkas, Lozios, Skourtsos, & Kranis, 1998;Mimikou & Koutsoyiannis, 1995; Mimikou, Baltas, & Varanou, 2002; Skilodimou, Livaditis,Bathrellos, & Verikiou-Papaspiridakou, 2003).

2.2. Methodology

Based on the inventory of Diakakis et al. (2012), we identified 151 deaths caused during 54 floodevents between 1970 and 2010. Among these deaths 60 were induced during 37 flood-relatedvehicle incidents.

Subsequently, a database of 60 entries was developed, each of which represented one fatality.A set of the following variables was used to provide a systematic and objective description of thecircumstances of every incident in the catalogue:

1. date2. exact location3. timing of the incident (i.e. whether it occurred during daylight or nighttime)4. type of vehicle involved (i.e. passenger car, tractor, Sports Utility Vehicle (SUV) or

pickup truck, coach or bus, truck)

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5. in-vehicle role of victim (i.e. driver or passenger)6. road type at the location of the incident (that is, paved road, unpaved road, concrete

bridge, artificial/concrete ford crossing or natural ford crossing)7. surrounding environment (i.e. urban or rural setting)8. driver’s age and gender9. victims’ age and gender10. driver’s familiarity with the road at the location of the incident (depending on the distance

to his or her permanent address)11. number of individuals in vehicle12. cause of death (i.e. drowning, physical injury, heart attack, electrocution)13. activity of the driver exactly before the time of the incident.

All fatalities included in this database were connected with the use of motor vehicles anddirectly attributed to flood events. Variables were chosen in a way that they address the vulner-ability factors discussed in the literature, for which there was data availability. Regarding thecause of death, possible classifications included drowning, heart attack (caused during theflood and attributed directly to the incident), physical trauma (individuals that died as a resultof physical injuries suffered during the flood or as their vehicle crashed or was swept by flood-waters) and electrocution (caused by contact of their car with floodwaters).

With respect to the distinction between rural and urban areas, the classification ‘urban’ wasused only in the case that the surrounding environment of the exact location of the incident con-sisted of human infrastructure.

To indicate the driver’s familiarity with the road at the location of the incident, two classifi-cations were selected. The driver was classified as ‘local’ in case his or her permanent residencewas less than 20 km in distance from the location of the incident. On the contrary, the driver wasclassified as ‘non-local’ in case his or her residence was more than 20 km away from the locationof the incident. The single distance value was selected as an indicator, due to lack of better infor-mation showing the driver’s familiarity with the road. Given the fact that drivers can be con-sidered familiar with roads within their daily itinerary (e.g. between home and work), thevalue of 20 km was selected as an average daily commuting distance suggested by Silva, Ross,and Farias (2009) and Ueda, Nakazawa, and Takafumi (2004).

With respect to the stance of the drivers exactly before the incident, their actions were studiedthrough the reports. Possible classifications included (a) travelling across waterways, (b) enteringfloodwaters to attempt rescue, (c) entering floodwaters to recover something, (d) driving or beingparked when floodwaters rose unexpectedly, (e) driving when floodwaters influenced the courseof the vehicle causing it to crash. The exact locations of the incidents were stored and plotted alsoin a GIS environment.

The formation of the database allowed the development of a systematic record of data, basedon evidence fragmented in several reports, and provided standardization of information. It alsoallowed easy cross-reference, comparison and quantitative analysis of data. After the databasedevelopment, simple mathematical operations were used to quantify percentages of possibleclassifications of each variable.

2.3. Uncertainties

In general, the completeness and the accuracy of the initial database (Diakakis et al., 2012) and ofthe data collected in this study are considered of an overall good quality. One of the sources ofuncertainty was the subjectivity of part of the data sources, attributed to their non-scientificnature (e.g. press articles). To deal with this issue, the variables selected to describe the incidents

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were specifically chosen in a way that they would not be subject to the reporter’s opinion. Inaddition, all information was cross-referenced between at least two sources. A second sourceof uncertainty derived from the temporal extent of the study period. It is evident that the findingsof this study may differ compared with the results arising from the examination of another period.It is important to note that as social and technological conditions gradually change with time, con-ditions and characteristics of flood casualties may be subject to change as well, even within thestudy period. In addition, this study focused on fatal cases only, as there are no data on non-fatalincidents. However, it would be desirable to compare these two categories.

3. Results and discussion

In the period studied, a total of 60 fatalities were identified, induced in 41 vehicle-related incidentsduring 37 flooding events across the country. Vehicle occupants ranged from 1 to 4 and in onecase 25, whereas survivors ranged from 0 to 3 and in one case 21. In total, 96 individualswere involved in the incidents, 36 of which survived. In 28 out of these 41 incidents, no individualwas recovered alive. Two individuals died attempting to rescue people inside cars while not beingthemselves inside in the first place.

Although significant variations were noted, an increase of these incidents was recorded over-time (Figure 1). In addition, it was found that 68.33% of the fatalities occurred in the second halfof the period in question, that is after 1990, whereas only 31.67% before this year.

In terms of their spatial distribution, incidents occurred in various parts of the country, clus-tered mainly near the capital Athens and the region of Attica, and low lying areas (Figure 2).

With regard to the victims’ age, it was found that the observed distribution is significantlydifferent in comparison to the demographics of the country (ELSTAT, 2001). In detail, a χ2

test was applied to compare the observed (i.e. victims’ age) with the expected age distribution(i.e. the country’s general population). The χ2 statistic is defined from the following equation:

x2 =∑

i

0i − Ei( )zEi

where Oi is the observed number of fatalities in each age group i, and Ei is the expected number ofindividuals in an equally numbered group of people according to the country’s population

Figure 1. Temporal evolution of vehicle-related fatalities caused by flooding in Greece (1970–2010) andthe best-fitting line illustrating the positive temporal trend.

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distribution. The value of χ2 in this case was calculated at 22.93, showing an important differencebetween the observed and the expected values. The calculated value corresponds to a significancetesting probability value (p value) of 0.003. This leads to the rejection of the null hypothesis (H0),by which it was assumed that the observed age distribution does not differ significantly (pvalue<0.01) from the age distribution of the general population.

In addition, from Figure 3 it can be deduced that certain age groups of the victims present asignificant deviation from the excepted distribution. In detail, individuals younger than 10 andbetween 40 and 69 years old show an increased percentage in comparison with the general popu-lation. On the contrary, individuals between 10 and 39 years old show reduced percentages indi-cating an underrepresentation in comparison with the general population (Figure 3).

Concerning the age of the drivers involved in the incidents, comparison showed that individ-uals between 40 and 69 years old presented higher percentages than in the general population,indicating an overrepresentation. On the contrary, youngsters and elderly people, over 70 yearsold, showed smaller percentages than expected, given the country’s demographics (Figure 4).The vast majority of drivers were males (85.36%).

With regard to their in-vehicle role, victims were equally divided between drivers and passen-gers. Males showed an increased representation among victims (70%) (Figure 5a) and amongdriver-victims (86.36%). On the contrary, passenger-victims were found to be almost equally

Figure 2. Spatial distribution of vehicle-related fatalities caused by flooding in Greece (1970–2010).

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divided, between males (25.86%) and females (24.14%) (Figure 5a). These findings were similarto the ones of Ashley and Ashley (2008).

Regarding the timing of the incident within the day, it was found that 46.67% of the casesoccurred during nighttime, whereas 35% occurred in daylight. However, in this case, resultsshould be considered with caution, as there was a significant percentage of cases (18.34%) forwhich timing was not reported (Figure 5b).

Concerning the surrounding environment of the incidents, it was found that 70% of the casesoccurred in rural areas, whereas 23.33% in an urban setting. In 6.67% of the cases this detail wasnot reported (Figure 5c).

Drowning was found to be the primary cause of death (93.33%), followed by physical trauma(5%) and electrocution (1.67%) in significantly smaller portions (Figure 5d). No other causes ofdeath were identified.

Regarding the familiarity of the drivers with the area or place of the incident, it was found thatthe majority of the drivers (78.05%) were permanently living less than 20 km from the location ofthe incident. In only 14.63% of the cases drivers’ permanent address were more than 20 km

Figure 3. Age distribution of victims of vehicle-related flood incidents in Greece (1970–2010), in compari-son with the country’s population age distribution (ELSTAT, 2001).

Figure 4. Age distribution of drivers of vehicles involved in fatal incidents in Greece (1970–2010), in com-parison with the country’s population age distribution (ELSTAT, 2001).

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Figure 5. Distribution of cases with respect to (a) the victims’ gender and in-vehicle role, (b) the timing of the incident, (c) the surrounding setting, (d) the cause ofdeath, (e) the driver’s familiarity with the road and (f) the drivers’ gender.

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from the location of the incident (Figure 5e). In 7.32% of the cases, this detail was not reported. Itshould be noted that these results should be considered with caution, as the single-distance cri-terion can be used only as an indicator of the driver’s familiarity with the road. Further researchis needed to determine this parameter more accurately.

Regarding the type of vehicles it was found that 53.66% of the cases involved passenger cars,9.75% SUVs or pick-up trucks, 7.32% involved tractors, 4.88% trucks and 2.44% busses.However, in 21.95% of the occasions this detail was not reported (Table 1).

As far as the road type is concerned, in the majority of cases, the incidents occurred on a pavedroad (41.46%), in 19.51% on a bridge, in 9.76% on an artificial ford river crossing, in 4.88% on anatural ford or an off-road river crossing and in 2.44% on an unpaved road. In 21.95% of the casesthe road type was not reported (Table 1).

With respect to the actions of the drivers prior to each incident, it was found that in 51.22% ofthe cases drivers tried to travel across a waterway to reach a destination. In 24.39% of the cases,they were driving, or were parked when floodwaters rose unexpectedly, giving them no chance toavoid danger. In 7.32% of the cases, the drivers decided to enter the floodwaters to save someoneand in 2.44% to recover a vehicle. In 4.87% of the cases the vehicle crashed, influenced by flood-waters, injuring fatally at least one of the occupants. In 9.76% of these cases details on driveractions were not reported (Table 1). Road signs warning drivers of the risk ahead or promptingfor diversion were reported only in one case.

4. Discussion

Analysis of the actions of drivers exactly before the incidents showed that the majority of cases,60.96% in total, pursued an active stance towards flood risk, by either trying to cross a water-course or by entering floodwaters to recover someone or something. This active stance (identifiedalso by Coates, 1999) indicates that drivers underestimated the risk involved in entering flood-waters, as suggested in the literature (FitzGerald et al., 2010; Rappaport, 2000; Yeo & Blong,2010). It is also possible that the vehicle occupants decided to drive into the floodwaters dueto a false sense of security developed when an individual is inside a vehicle, as proposed byDrobot et al. (2007b). This assumption is supported also by the complete absence of motorcyclesin the incidents, although they comprised an average of 13.8% of the vehicles in Greece (ELSTAT,2012) between 1985 and 2011. In addition, it is possible that drivers have a difficulty to appreciatethe road conditions such as the depth and velocity of floodwaters, and the influence they could

Table 1. Distribution of cases with respect to the road and vehicle type and the drivers’ actions before theincident.

Road type Vehicle type Actions before incident

Paved road 41.46% Passenger car 53.66% Traveled across waterway 51.22%Bridge 19.51% SUV/Pickup

truck9.75% Driving or being parked when

water rose unexpectedly24.39%

Artificial ford rivercrossing

9.76% Tractor 7.32% Entering floodwaters to savesomeone

7.32%

Natural fordcrossing

4.88% Truck 4.88% Car crash influenced byfloodwaters

4.87%

Unpaved road 2.44% Bus 2.44% Entering floodwaters to recovervehicle

2.44%

Not reported 21.95% Not reported 21.95% Not reported 9.76%Total 100.00% Total 100.00% Total 100.00%

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potentially have on the stability of their vehicle. This assumption is supported by the experimentaldifficulty to determine hazardous depth and velocity of floodwaters shown by Abt et al. (1989).Considering these findings, it is recommended that education efforts concerning road safety incase of flooding should be enhanced (e.g. short seminars), especially for higher-risk populationgroups highlighted in this work. Information on the risk of flooding for vehicle occupantsshould be included in driving lessons and the Greek Traffic Code training manual issued bythe Ministry of Transportation.

Gender distribution results are consistent with most previous studies. The high representationof males is attributed to their tendency to engage in riskier activities suggested also in the litera-ture (Ashley & Ashley, 2008, Becker et al., 2008; Drobot et al., 2007b; Jonkman &Kelman,2005).

Although the majority of population and vehicles in Greece are clustered in urban areas(ELSTAT, 2009), vehicle-related flood fatalities occur mostly in a rural setting, a conclusionreached also by Stjernbrandt et al. (2008) for Sweden. This fact can be attributed to a series offactors including poorer road maintenance, road-lighting conditions and road signage in ruralareas. In addition, it is possible that rescue and emergency professionals and traffic wardenscannot reach incident locations as quickly as in urban areas.

Regarding the age of drivers, findings of the literature were not verified in this study. Onepossible explanation for the increased representation of drivers between 40 and 69 years old isthe larger number of drivers of this age in the general population, although specific data arenot available. Underrepresentation of individuals younger than 19 years old is attributed to thefact that 18 is the minimum driving age in the country.

Regarding the vehicle types involved in the fatal incidents, it is noted that passenger cars,SUVs and pickup trucks sum up a percentage of 63.41% of the total, almost equalling theiraverage 63% out of all motor vehicles in the country (ELSTAT, 2012) during the period 1985–2011. On the other hand, trucks showed a far smaller percentage than their average 22.5%among all motor vehicles in Greece (ELSTAT, 2012) during the period 1985–2011. Finally, nocases of motorcycle-related incidents are identified although they record an average 13.8%among motor vehicles in Greece, between 1985 and 2011 (ELSTAT, 2012).

Analysis showed that the majority of vehicle-related incidents occurred on paved roads adja-cent to waterways, on bridges and on artificial ford river crossings, indicating that the level ofsafety of the existing road infrastructure at similar locations is not adequate and should be re-examined. Taking into account the fact that among 60 vehicle-related cases, only in one occasiontemporary warning signs restricting traffic towards a flooded area were reported, it is apparent thatsteps should be taken to improve road signage. In addition, the results showed a high percentageof nighttime incidents, a fact probably related, as suggested in the literature (Jonkman & Kelman,2005), to the increased difficulty of individuals to appreciate the rapidly changing road conditionsand to estimate the depth and velocity of floodwaters under darkness. Based on these findings, it isrecommended that the authorities should map and examine all high-risk locations on the roadnetwork as highlighted in this study. In addition, steps should be taken to improve road lightingand permanent warning signage in these locations stressing the risks associated with flooding.Temporary traffic restrictions should be also considered as a precautionary measure duringemergencies.

The results should be considered with caution due to the limited sample examined. Systematicdata collection in international level would be desirable, to extend the sample of incidents andpossibly the period of study to reduce the associated uncertainties. It would be also necessaryto record all potential vulnerability factors in a standardized manner as many authors suggest(Jonkman & Kelman, 2005; Legome, Robins, & Rund, 1995).

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5. Conclusions

In this work, an inventory of 60 vehicle-related flood fatalities was developed and studied in aneffort to investigate the circumstances under which these incidents occurred. Analysis showedthat the incidents occurred mostly during nighttime and in rural areas of the country. Fatalitiesin most instances occurred as people decided to enter floodwaters to reach a destination, torescue someone or recover something, pursuing in this way an active rather than a passivestance towards risk. Males are showing an overrepresentation in both victims and drivers ofthe vehicles. With comparison to the age distribution of the general population, individualsbetween 40 and 69 years old presented high percentages in both victims and drivers of thevehicles. Persons younger than 10 years old showed overrepresentation only among thevictims. All other age groups showed underrepresentation in both drivers and victims. Driverswere found to be in most cases familiar with the road network at the location of the incident asthe majority of them resided in the vicinity of these locations. Drowning was the primarycause of death among victims. Analysis showed that the incidents occurred mostly on pavedroad network, bridges and artificial ford crossings, indicating an inadequacy of signage andsafety levels in the existing road infrastructure. Considering the results, education efforts targetedto high-risk groups, identified in this work, road lighting and signage improvements and roaddesign re-examination in high-risk locations should be strongly considered.

ReferencesAbt, S. R.,Wittler, R. J., Taylor, A., & Love, D. J. (1989). Human instability in a high flood hazard zone. Journal

of the American Water Resources Association, 25, 881–890. doi:10.1111/j.1752-1688.1989.tb05404.xAshley, S. T., & Ashley, W. S. (2008). Flood fatalities in the United States. Journal of Applied Meteorology

and Climatology, 47, 805–818. doi:10.1175/2007JAMC1611.1Ball, K., Owsley, C., Stalvey, B., Roenker, D., Sloane, M. E., & Graves, M. (1998). Driving avoidance and

functional impairment in older drivers. Accident Analysis and Prevention, 30, 313–322. doi:10.1016/j.bbr.2011.03.031

Barrera, A., Llasat, M. C., & Barriendos, M. (2006). Estimation of extreme flash flood evolution inBarcelona County from 1351 to 2005. Natural Hazards Earth System Sciences, 6, 505–518.doi:10.5194/nhess-6-505-2006

Barrero, J. I. (2007). Major flood disasters in Europe: 1950–2005. Natural Hazards, 42, 125–148.doi:10.1007/s11069-006-9065-2

Barrero, J. I. (2009). Normalised flood losses in Europe: 1970-2006. Natural Hazards Earth SystemSciences, 9, 97–104. doi:10.5194/nhess-9-97-2009

Becker, J., Johnston, D., Ronan, K., & Coomer, M. (2008). Flood risk perceptions, education and warning infour communities in the Hawkesbury- Nepean Valley, New South Wales, Australia – Data report for afollow-up questionnaire. Australia: Institute of Geological and Nuclear Sciences Limited.

Bracken, L. J., Cox, N. J., & Shannon, J. (2008). The relationship between rainfall inputs and flood gener-ation in south-east Spain. Hydrological Processes, 22, 683–696. doi:10.1002/hyp.6641

Bull, L. J., Kikrby, M. J., Shannon, J., & Hooke, J. M. (2000). The impact of rainstorms on floods in ephem-eral channels in southeast Spain. Catena, 38, 191–209. doi:10.1016/S0341-8162(99)00071-5

Coates, L. (1999). Flood fatalities in Australia, 1788–1996. Australian Geographer, 30, 391–408.doi:10.1080/00049189993657

Coles, A. R. (2008). Managing flash floods: risk perception from a cultural perspective (Unpublishedmaster’s thesis). University of Arizona, Arizona.

Diakakis, M. (2010). Flood history analysis and its contribution to flood hazard assessment: The case ofMarathonas, Greece. Bulletin of the Geological Society of Greece, 43, 1323–1334. Retrieved fromhttp://geolib.geo.auth.gr/digeo/index.php/bgsg/article/view/6847/6605

Diakakis, M. (2013). An inventory of flood events in Athens, Greece, during the last 130 years. Seasonalityand spatial distribution. Journal of Flood Risk Management. doi:10.1111/jfr3.12053

Diakakis, M., Andreadakis, E., & Fountoulis, G. (2011a). Flash flood event of Potamoula, Greece.Hydrology, geomorphic effects and damage characteristics. In N. Lambrakis, G. Stournaras, & K.Katsanou (Eds.), Advances in the research of aquatic environment 1 (pp. 163–170). Berlin: Springer.

Environmental Hazards 11

Dow

nloa

ded

by [

Mic

halis

Dia

kaki

s] a

t 04:

27 2

1 Se

ptem

ber

2013

Diakakis, M., Deligianakis, G., & Mavroulis, S. (2011b). Flooding in Peloponnese, Greece: A contributionto flood hazard assessment. In N. Lambrakis, G. Stournaras, & K. Katsanou (Eds.), Advances in theresearch of aquatic environment 1 (pp. 163–170). Berlin: Springer.

Diakakis, M., Mavroulis, S., & Deligiannakis, G. (2012). Floods in Greece, a statistical and spatial approach.Natural Hazards, 62, 485–500. doi:10.1007/s11069-012-0090-z

Dick, G., Anderson, R., & Sampson, D. (1997). Controls on flash flood magnitude and hydrograph shape,Upper Blue Hills badlands, Utah. Geology, 25, 45–48. doi:10.1130/0091-7613(1997)025&lt;0045:COFFMA>2.3.CO;2

Drobot, S., Gruntfest, E., Barnes, L. R., Benight, C., Schultz, D. M., & Demuth, J. (2007a). Driving under theinfluence of weather: Perceptions of flash floods and vehicle safety. In Proceedings of the 16thConference on Applied Climatology, San Antonio, TX, 14–18 January 2007.

Drobot, S. D., Benight, C., & Gruntfest, E. C. (2007b). Risk factors for driving into flooded roads.Environmental Hazards, 7, 227–234. doi:10.1016/j.envhaz.2007.07.003

ELSTAT. (2001). Population Census 2001: De facto population, Area and population by range, density andelevation zones. Athens, Greece: Hellenic Statistical Authority.

ELSTAT. (2009). Motor vehicles in circulation, by category, use and region in Greece. Athens, Greece:Hellenic Statistical Authority.

ELSTAT. (2012). Motor vehicles in operation, by category and use: 1985–2011. Athens, Greece: HellenicStatistical Authority.

FitzGerald, G., Du, W., Jamal, A., Clark, M., & Hou, X. (2010). Flood fatalities in contemporary Australia(1997–2008). Emergency Medicine Australasia, 22, 180–186. doi:10.1111/j.1742-6723.2010.01284.x

French, J., Ing, R., Von Allmen, S., & Wood, R. (1983). Mortality from flash floods: A review of NationalWeather Service reports, 1969–81 (Public Health Reports). 98, 584–588. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1424497/

Gaume, E., Bain, V., Bernardara, P., Newinger, O., Barbuc, M., Bateman, A.,…Viglione, A. (2009). A com-pilation of data on European flash floods. Journal of Hydrology, 367, 70–78. doi:10.1016/j.jhydrol.2008.12.028

Greek National Library. (2010). E-efimeris: Digital newspapers collection of the Greek National Library.Retrieved 10 January 2011, from http://www.nlg.gr/digitalnewspapers/ns/main.html

Greek National Newspapers Archive. (2010). National Newspapers Microfilm Database of the Library of theHellenic Parliament. Greece: Hellenic Parliament.

Guzzetti, F., & Tonelli, G. (2004). Information system on hydrological and geomorphological catastrophes inItaly (SICI): A tool for managing landslide and flood hazards. Natural Hazards and Earth SystemSciences, 4, 213–232. doi:10.5194/nhess-4-213-2004

Jonah, B. A. (1986). Accident risk and risk-taking behaviour among young drivers. Accident Analysis andPrevention, 18, 255–271. doi:10.1016/0001-4575(86)90041-2

Jonkman, S. N., & Kelman, I. (2005). An analysis of the causes and circumstances of flood disaster deaths.Disasters, 29, 75–97. doi:10.1111/j.0361-3666.2005.00275.x

Koutroulis, G., Tsanis, I. K., & Daliakopoulos, I. N. (2010). Seasonality of floods and their hydrometeoro-logic characteristics in the island of Crete. Journal of Hydrology, 394, 90–100. doi:10.1016/j.jhydrol.2010.04.025

Kunkel, K. E., Pielke, Jr. R. A., & Changnon, S. A. (1999). Temporal fluctuations in weather and climateextremes that cause economic and human health impacts: A review. Bulletin of the AmericanMeteorological Society, 80, 1077–1098. doi:10.1175/1520-0477(1999)080&lt;1077:TFIWAC>2.0.CO;2

Legome, E., Robins, A., & Rund, D. A. (1995). Injuries associated with floods: the need for an internationalreporting scheme. Disasters, 19, 50–54. doi:10.1111/j.1467-7717.1995.tb00332.x

Lekkas, E., Lozios, S., Skourtsos, E., & Kranis, H. (1998). Floods, geodynamic environment and humanintervention. The case of Corinth (Greece). Risk Analysis. In C. A. Brebbia, J. L. Rubio, & J. L. Uso(Eds.), Computational mechanics publications 2 (pp. 135–144). Southampton: Wit Press.

Llasat, M. C., Llasat-Botija, M., Prat, M. A., Porcu, F., Price, C., Mugnai, A., … Nicolaides, K. (2010a).High-impact floods and flash floods in Mediterranean countries: the FLASH preliminary database.Advances in Geosciences, 23, 47–55. doi:10.5194/adgeo-23-47-2010

Llasat, M. C., Llasat-Botija, M., Rodriguez, A., & Lindbergh, S. (2010b). Flash floods in Catalonia: A recur-rent situation. Advances in Geosciences, 26, 105–111. doi:10.5194/adgeo-26-105-2010

Maples, L. Z., & Tiefenbacher, J. P. (2009). Landscape, development, technology and drivers: The geogra-phy of drownings associated with automobiles in Texas floods, 1950–2004. Applied Geography, 29,224–234. doi:10.1016/j.apgeog.2008.09.004

12 M. Diakakis and G. Deligiannakis

Dow

nloa

ded

by [

Mic

halis

Dia

kaki

s] a

t 04:

27 2

1 Se

ptem

ber

2013

Mimikou, M., Baltas, E., & Varanou, E. (2002). A study of extreme storm events in the Greater Athens area,Greece. In A. Snorasson, H. P. Finnsdotir, & M. Moss (Eds.), The extremes of the extremes: extraordi-nary floods (pp. 161–166). Oxfordshire: IAHS-AISH Publication.

Mimikou, M., & Koutsoyiannis, D. (1995). Extreme floods in Greece: The case of 1994. Paper presented atthe US – Italy Research Workshop on the Hydrometeorology, Impacts and Management of ExtremeFloods, Perugia, Italy.

Priest, S., Wilson, T., Tapsell, S., Penning-Rowsell, E., Viavattene, Ch., & Wilson, T. (2009). Building amodel to estimate risk to life for European flood events – final report (Report No. T10-07-10).Middlesex: Middlesex University.

Rappaport, E. N. (2000). Loss of life in the United States associated with recent Atlantic tropical cyclones.Bulletin of the American Meteorological Society, 81, 2065–2073. doi:10.1175/1520-0477(2000)081&lt;2065:LOLITU>2.3.CO;2

Ruin, I., Creutin, J. D., Anquetin, S., Gruntfest, E., & Lutoff, C. (2009). Human vulnerability to flash floods:addressing physical exposure. In P. Samuels, S. Huntington, W. Allsop, & J. Harrop (Eds.), Flood riskmanagement: Research and practice (pp. 1005–1012). London: Taylor & Francis.

Ruin, I., Gaillard, J. C., & Lutoff, C. (2007). How to get there? Assessing motorists’ flash flood risk percep-tion on daily itineraries, Environmental Hazards, 7, 235–244. doi:10.1016/j.envhaz.2007.07.005

Savvidou, K., Nicolaides, K. A., Michaelides, S. C., Orphanou, A., Charalambous, M., & Adamou, S.(2008). A study of the flood events in Cyprus. Advances in Science and Research, 2, 127–131.doi:10.5194/asr-2-127-2008

Silva, C., Ross, M., & Farias, T. (2009). Evaluation of energy consumption, emissions and cost ofplug-in hybrid vehicles. Energy Conservation and Management, 50, 1635–1643. doi:10.1016/j.enconman.2009.03.036

Skilodimou, H., Livaditis, G., Bathrellos, G., & Verikiou-Papaspiridakou, E. (2003). Investigating the flood-ing events of the urban regions of Glyfada and Voula, Attica, Greece: A contribution to urban geomor-phology. Geografiska Annaler, 85, 197–204. doi:10.1111/1468-0459.00198

Staes, C., Orengo, J. C., Malilay, J., Rullan, J., & Noji, E. (1994). Deaths due to flash floods in Puerto Rico,January 1992. Implications for prevention. International Journal of Epidemiology, 23, 968–975.doi:10.1093/ije/23.5.968

Stathis, D. (2004). Extreme rainfall-events and flood-genesis in Greece. Paper presented at the 7thPanhellenic Geographical Conference of the Hellenic Geographical Society (7PGC/HGS), Mytilene.

Stjernbrandt, A., Öström, M., Eriksson, A., & Björnstig, U. (2008). Land motor vehicle-related drownings inSweden. Traffic Injury Prevention, 9, 539–543. doi:10.1080/15389580802339150

Ueda, H., Nakazawa, K., & Takafumi, H. (2004). Reducing the environmental load by encouraging a modalshift in commuting. In L. Ubertini (Ed.), Environmental modelling and simulation (pp. 30–35). USVirgin Islands: Acta Press.

Wright, K., Doody, B. J., Becker, J., & McClure, J. (2010). Pedestrian and motorist flood safety study: Areview of behaviours in and around floodwater and strategies to enhance appropriate behaviour.Australia: Institute of Geological and Nuclear Sciences Limited.

Yale, J. D., Cole, T. B., Garrison, H. G., Runyan, C. W., & RiadRuback, J. K. (2003). Motor vehicle-relateddrowning deaths associated with inland flooding after Hurricane Floyd: A field investigation. TrafficInjury Prevention, 4, 279–284. doi:10.1080/714040485

Yeo, S. W., & Blong, R. J. (2010). Fiji’s worst natural disaster: The 1931 hurricane and flood. Disasters, 34,657–683. doi:10.1111/j.1467-7717.2010.01163.x

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