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Risk assessment framework for exposure of cargoand ports to natural hazards and climate extremes

Jasmine Siu Lee Lam & Jonatan A. Lassa

To cite this article: Jasmine Siu Lee Lam & Jonatan A. Lassa (2016): Risk assessment frameworkfor exposure of cargo and ports to natural hazards and climate extremes, Maritime Policy &Management, DOI: 10.1080/03088839.2016.1245877

To link to this article: http://dx.doi.org/10.1080/03088839.2016.1245877

Published online: 23 Nov 2016.

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Risk assessment framework for exposure of cargo and ports tonatural hazards and climate extremesJasmine Siu Lee Lam a and Jonatan A. Lassab

aSchool of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore;bInstitute of Catastrophe Risk Management, Nanyang Technological University, Singapore, Singapore

ABSTRACTThere is an increase in risks and catastrophic losses in maritime transportincluding ports and cargo. Significant losses have been associated withlarge scale natural hazards, such as earthquakes, tsunami, cyclones, andother extreme weather events. This paper identifies the main gaps inunderstanding maritime risks in transportation research. The gaps areattributed to insufficient empirical work available from the maritimetransport and logistics research community to guide multi-risk andnatural hazards impact assessment on seaport and cargo. In addition,disaster studies communities have barely made adequate efforts tounderstand and assess port and cargo risks arising from multi-hazardsand disaster events. This paper examines existing conceptual frameworksconcerning exposure and risk assessments of natural catastrophe’simpacts. Furthermore, the paper identifies trends and gaps in risk assess-ment frameworks in the field of disaster studies that can be beneficial formaritime risk research. The authors propose a new risk assessmentframework that can guide future research and multi-hazard risk assess-ment processes at different scales of maritime risks.

KEYWORDSMaritime transport; cargo;port; natural hazard; climateextreme; risk assessment

1. Introduction

Ports and shipping are exposed to higher risks due to rapid changing environments (Notteboomand Lam 2014; WEF 2013). United Nations Conference on Trade and Development (UNCTAD)’sWorld Maritime Report 2011 boldly highlights the extreme events such as floods and cyclones inAustralia and earthquakes in Japan become serious challenges to the world economy (UNCTAD2011). Natural hazards and extreme climate events can be considered as ‘non-traditional risk’despite long history of their effects on damages and losses in maritime transport. Over the pastdecades, there has been an increase in the number of natural hazards and catastrophic events(UNISDR 2009, 2011; IPCC 2011; EMDAT 2015; WEF 2013). While the number of death due tonatural hazards decreases, there is an increase in economic losses and the number of peopleaffected by natural hazards notably during the last four decades (EMDAT 2015).

Over 90% of global trade volumes are carried by sea. Maritime transport as a value drivensystem (Robinson 2002) and a capital-intensive industry is the backbone of global economicdevelopment (Berle, Asbjørnslett, and Rice 2011). The world food system depends on globalsupply chains served by maritime transport (Godfray et al. 2011). Therefore, seaports can beconsidered as critical infrastructure and lifelines for most countries. Climate extremes are likelyto affect maritime sectors because there is strong evidence of more-intense precipitation

CONTACT Jasmine Siu Lee Lam sllam@ntu.edu.sg School of Civil and Environmental Engineering, NanyangTechnological University, 50 Nanyang Avenue, Singapore, Singapore© 2016 Informa UK Limited, trading as Taylor & Francis Group

MARITIME POLICY & MANAGEMENT, 2016http://dx.doi.org/10.1080/03088839.2016.1245877

extremes over the last decades (Seung-Ki et al. 2011) and changing patterns in accumulatedcyclone energy notably in North Atlantic, Northwest Pacific and North Indian (Klotzbach2006; IPCC 2011). There is an increase in economic losses from weather- and climate-relateddisasters and the estimates of annual losses have been around US$ 200 billion during 1980–2010 (IPCC 2011).

An increase in risks from natural hazards means that maritime sectors are more exposed toboth geological hazards (e.g. tsunami-genic earthquakes) and climate extremes (e.g. supercyclones, hurricanes and coastal floods) (Lam and Su 2015). The good news is that since 1990s,awareness of the risks in the maritime sectors is also increasing. The maritime industry has beenadapting to the escalating risks by adopting a ‘risk-based “goal setting” regime’ (Wang 2006, 3).Existing literature suggests that risk management has been partly considered by maritime trans-port stakeholders. Wang (2006) argues that some international safety-related marine regulationshave been driven by the serious accidents where some of the accidents were associated withextreme weather. Steep increase in the international safety regulations for maritime transportduring 1980–2000 has been associated with the responses to natural catastrophe events (Aldertonand Leggate 2005).

Nevertheless, a recent global survey by Becker, Inoue, and Fischer (2012) from 93 worldseaports reveals the mismatch in seaports’ capital planning cycle which is often limited to only5–10 years. This is much shorter than the design lifespan of ports of about 30–50 years. Inaddition, recent climate models suggest that adaptation for ports’ planning should be between50–100 years. Proper practice in ports’ protection in Japan even suggests that port planningshould consider at least a 200-year return period of disasters such as tsunami and earthquakes(Normile 2012).

Recently, there is a serious call from academia for transport stakeholders to take proactiverational planning for natural hazards in supply chains (Knemeyer, Zinn, and Eroglu 2009).Despite the claim from Wang (2006) that maritime stakeholders have just been adopting therisk-based policy, our literature review reveals that research on maritime transport and marinecargo exposure to natural hazards has not been adequately developed. This field requires morescientific investigation and exploration. Maritime transport researchers can ask whether pre-sent world seaports, shipyards as well as other marine structures are able to stand againstfuture natural hazards and disaster risks in a longer time span. Boin, Kelle, and Whybark(2010) argue for the ‘missing element’ in the supply chain studies and call for the birth of anew field of study towards a more resilient supply chains system (see also Lam and Dai 2015;Mansouri, Roshanak, and Ali 2010). There is also a call for research on maritime risk in thekey zones of maritime global critical infrastructure such as Malacca Straits and major EastAsian ports in order to anticipate disruptions in the global supply chain as large scale maritimedisasters can have cascading effects on global trade and economic network (Kyoto Universityand IRGC 2011).

Hence, the objective of this paper is twofold. The first is to examine existing frameworks forrisk assessment in general and in particular exposure analysis of marine portfolios, primarilyexposure of marine cargo and port facilities to natural catastrophes. Furthermore, the studyidentifies trends and gaps in risk assessment concepts and framework in the field of disasterstudies that can be beneficial for maritime risk research. The second, the authors propose a newrisk assessment framework that can guide future research and multi-hazard risk assessmentprocess at different scales of maritime risks.

The rest of the paper is structured as follows: Section 2 highlights existing studies on exposures,vulnerabilities and risks of maritime transport to natural catastrophes. It also highlights researchgaps in both maritime transport and disasters studies concerning maritime risks. Section 3examines existing risk, exposure and vulnerability assessment frameworks. A new frameworkfor seaports is proposed in Section 4. Final remarks concerning implications and future researchagendas are given in Section 5.

2 J. S. L. LAM AND J. A. LASSA

2. An overview of maritime transport exposure to natural hazards and climateextremes

Catastrophe risks of maritime transport have been investigated and discussed by different fieldsand research communities where each field uses its own methods, concepts, frameworks andmodels of risk. We identified several key research clusters that recently demonstrate interests ininvestigating maritime catastrophe risks, namely operations management and supply chain orproduction economics, climate change, hazards and disaster studies, and transport studies ingeneral and in particular maritime transport. This section provides an up-to-date overview ofthese studies and identifies the research gaps.

2.1. Observed risk hierarchy in maritime transport

There has been a solid focus on regular operational risks made by maritime transport stake-holders. However, the stakeholders have a lack of awareness of exposure to natural hazards (Berle,Asbjørnslett, and Rice 2011). In addition, Berle, Asbjørnslett, and Rice’s (2011) observationconfirms the fact that there is a lack of methods for addressing and planning for ‘low-frequencyhigh-impact disruption scenarios’. Vilko and Hallikas (2012) and WEF (2013) have also providedsimilar findings concerning ‘low-frequency high-impact disruption scenarios’ in the context ofmaritime risks. With some modification, in Figure 1(a) we visualize Vilko and Hallikas’ (2012)and WEF (2013) observations concerning the fact that the maritime industry has paid attention tothe daily port, shipping, and cargo risks namely operational risks (e.g. ship collision in theapproach lane, lack of cargo-handling equipment, negligence) (Li, Yin, and Fan 2014a, 2014b)and supply risks (hazardous materials, lack of intermodal/multimodal equipment, bottlenecks intransportation routes, capacity problems in rail and road traffic, labor strikes at ports, etc.). In themiddle of Figure 1(a), there are security risks (e.g. organized crime, drunken driver, terrorism)(Pristrom et al. 2013), policy risks (e.g. problems with customs clearance), macro risks (e.g.financial crisis). WEF (2013) views ‘environmental risk’ as natural hazards, while Vilko andHallikas (2012) consider nuclear disasters nearby plants, oil catastrophe in shipping lanes andports, ice conditions in winter, fire, epidemic and climate change as major examples of environ-mental risk. However, climate change is loosely mentioned and barely explored. We propose thatthe term climate extremes would be more suitable as a hazard since climate change is a very long

Figure 1. (a) Risk Hierarchy in Maritime Transport. (b) Spectrums of risk sources.Source: (a) Authors. (b) Authors, adapted from Smith and Petley (2009), WEF (2013) and Bogardi et al. (2009).

MARITIME POLICY & MANAGEMENT 3

term process which may or may not pose real risks. In Figure 1(a), we add climate extremes andearthquakes/tsunamis to the list of Vilko and Hallikas (2012) to formulate the risk hierarchy.

Berle, Rice, and Asbjørnslett (2011) and Vilko and Hallikas (2012) confirm the ‘risk hierarchy’phenomenon in many local communities where there are tensions between ‘high-probability lowconsequence events’ versus ‘low-probability high consequence events’ in the context of maritimerisk management. From disaster studies, Bogardi et al. (2009) find the tension between theeveryday risks (such as poverty and urgent daily needs) versus prioritized long return periodevents such as tsunamis and super cyclones.

Referring to Figure 1(b), the spectrum of risk sources can be used to explain the natural andhuman systems (Smith and Petley 2009). Some hazards are considered as voluntary becausethey are more likely to be manmade. The involuntary hazards are the natural ones, while somehazards are considered as ‘in-between’ events such as climate extremes related hazards whichare caused by complex interactions of human intervention and natural response. So far thestakeholders in maritime transport have paid more attention to the voluntary and manmadehazards while there is more to be done in the management of involuntary and natural hazards(Vilko and Hallikas 2012). Hazards can also be classified as intensive or extensive. Intensivehazards refer to the fact that natural hazards such as earthquakes and tsunami often concen-trate on a specific spatial reality. Extensive hazards are defined as diffused events (Smith andPetley 2009) or events that occur more frequently elsewhere at smaller scales (UNSIDR 2009,2011).

2.2. Impact of natural hazards on ports and cargo shipping

Evidence on disruptions of seaports because of natural hazards has been observed globallythroughout human history. There is strong evidence that natural hazards and disasters disruptedmaritime transport infrastructure and facilities. However, systematic records of the events remainlacking. Famous events include, for example, the Vesuvius eruption that buried Pompeii port anddestroyed Naples ports (De Carolis and Patricelli 2003). The 1755 Great Lisbon Earthquake – thefirst modern disaster as once argued by Dynes (1997) – is one of the examples of how naturalhazards could fundamentally halt the progress of an international port and its competitivenessduring the eighteenth century. The history suggests that long term investment in ports that areexposed to certain natural hazards need to be evaluated systematically.

Some recent disasters in modern times had created serious damages and losses in ports. Forinstance, the MW 6.9 earthquake hit the port city of Kobe, Japan on 17 January 1995. In additionto the city’s damage, the earthquake triggered disasters that created systemic risks as it disruptedinternational supply chains such as shocks in computer production in Europe (Waters 2011). TheKobe seaport stopped operating for 2 months (Waters 2011) as it was heavily damaged (Chang2000, 2010; Werner, Dickenson, and Taylor 1997; Werner 1998). Total economic loss is over US$100 billion in damage (Chang 2010). Chang (2010) provides quantitative evidence that Kobe’seconomic performance such as income per capita and regional gross income during 1991–2004experienced negative trend. Kobe earthquake had accelerated the decreasing rate of Kobe seaport’scompetitiveness. The seaport was ranked at sixth globally in 1994 but later it was ranked 14th in1997 and today it is ranked 28th in 2011. Cargo traffic, especially the container transshipments in1995 at the port of Kobe fell down 60% from the 1994's level. There was a small increase from the1995’s level during 1996–2000 but since then, container transshipment call at Kobe was plungedmore than 95% from the 1994's level (Chang 2010). Kobe’s share of cargo traffic has beenpermanently lost to other Japanese seaports.

The Indian Ocean Tsunami in 2004 caused transoceanic impact which created heavy damagesand losses at ports from Aceh ports (Indonesia) to other 15 countries’ coasts. Some traditional andsmall ports in faraway coasts such as Xaafuun Peninsula in Somalia (or 5000 km from the tsunamisource in Indonesia) also experienced damages (Synolakis and Kong 2006).

4 J. S. L. LAM AND J. A. LASSA

The most recent incident is the Great Tohoku Tsunami (MW 9) occurred on 11 March 2011which triggered tsunamis that hit many coastal cities in Japan. Tsunami run-up and heights insome of the spots reached up to 39 m (Mimura et al. 2011). Damage and loss assessment reportsreveal that the total economic loss resulting from the tsunami-genic earthquake could be between16 and 25 trillion yen (i.e. US$ 200–303 billion) (Dunbar et al. 2011). Munich Re reports that theoverall earthquakes and weather-related catastrophes in 2011 are the costliest year ever, recorded atotal natural catastrophe losses at about US$ 380 billion and total insured losses of US$ 105 billion(www.munichre.com). The Tohoku earthquake in March 2011 damaged not only Japaneseseaports but also long distance seaports in California. A recent finding suggests that the totaleconomic loss for California State was US$ 48 million (www.coastal.ca.gov).

2.3. Impact of climate extremes on global seaports

Coastal and port cities are also likely to be more exposed to climate extremes. The detailsconcerning the impact of climate extremes are reported by IPCC (2011), showing that therewill be increasing losses from hurricanes in the United States and the Caribbean and other seabasins. Using global data of 2005, Hanson et al. (2011) note that 13 out of 20 most populatedworld cities were port cities. Recent climate extremes at port cities that led to catastrophic damagecan be exemplified by Katrina disasters where New Orleans in the United States experiencedserious disruption and world record economic losses for 2005. In Asia, the extremes wereexemplified by Pakistan floods in 2010 and Bangkok floods in 2011 where the events madenational records in terms of historical damage and losses.

Hanson et al.’s (2011) scenarios of exposed assets and wealth at the port cities suggest that by2070, 8 of the top 20 port cities are located in OECD countries such as United States (four cities:Miami, New York, New Orleans and Virginia Beach), Japan (two cities: Tokyo and Nagoya), andNetherlands (Amsterdam and Rotterdam). Asia contributes 12 cities to the top 20. Chinadominates the list with six cities (Guangzhou, Shanghai, Tianjin, Hong Kong, Ningbo, andQingdao). Importantly, the speed of change in the increase of exposed assets is tremendous(Hanson et al. 2011). By percentage, Ningbo will likely to rise 12,000%, Dhaka and Kolkata willrise more than 6000%, while Bangkok, and Jakarta are likely to rise above 2500% in terms ofexposed assets at ports. Based on the economic loss estimation due to extreme wind events doneby Zhang and Lam (2015), it is also expected that Chinese ports such as Shanghai, Ningbo, andShenzhen face increasing exposure as cargo and shipping volumes increase.

The problem is that, in general, there is insufficient port planning to natural hazards andadaptation. Based on the global survey from 93 ports, Becker, Inoue, and Fischer (2012) find thatmost ports have less than 10 years of planning horizon. As market evolves, port policy makersexpand their facilities such as by building terminals, berths and land acquisition. Only a smallpercentage of seaports have forthcoming projects adapting to natural hazards. In fact, most portsonly consider natural forces such as coastal flooding and they have already built infrastructure toprotect port operations through building new breakwaters or storm barriers that would mitigateflooding and wave damage. However, their hazards scenarios are short term. Becker, Inoue, andFischer (2012) highlight the fact that only 3 (without mentioning exactly where) out of 93 portsrepresenting 3.2% planned to build protective structures while 22% made no plans to developwithin the next 10 years.

2.4. Research gaps

Based on the literature survey, there is a pressing demand for building resilience of maritimetransport (Lam and Bai 2016). The call has barely been addressed by researchers by conductingmulti-risk assessment in the transportation context. Gurning and Cahoon (2011) is one of the fewwho analyze multi-mitigation scenarios anticipating maritime disruptions arising from different

MARITIME POLICY & MANAGEMENT 5

hazards. They provide a framework which treats hazards as stimulators (e.g. severe weather states,tsunamis, and earthquakes) which can lead to disruptions, and then in turn create loss of earningsand loss of economic benefits. Cox, Prager, and Rose (2011) employ some concepts such asresilience and vulnerability from disaster and hazards studies to demonstrate the need fortransportation system resilience measures. They suggest tools for prospective resilience measuresfor decision-makers. However, their study is exclusively focused on terrorism (Londonbombings).

It has been long observed that transport risk is associated with climate and weather (Andrey2010). Even though it was obvious for civil engineers and ports designers to consider climatevariables (such as wind velocity, floods’ return periods, and tidal waves history) to be calculated inthe ports’ infrastructure reliability, our literature review suggests that more scientific researchconcerning multi-hazard risk assessment should be made systematically.

3. Examining risk, exposure, and vulnerability assessment frameworks

Supply chain literature defines risk as undesired consequences and a function of probability of lossand the significant of its consequences (Vilko and Hallikas 2012). The risk is presumablyoperationalized at the sea-land interface of the maritime transportation system which includesport environment and navigable waterways (vessel, terminal operations, intermodal connectionpoint, road, rail, pipelines, bridges) and public infrastructure (highway, rail, pipeline system)(Berle, Asbjørnslett, and Rice 2011). This section provides insights from disaster studies research.

Disaster studies communities use different approaches to define risks. Natural hazards such asvolcano eruption also take place in the other planets within our Solar System (and also outside ourgalaxy – see Glaze, Baloga, and Wimert 2011). Regardless of the scale of the events, they aresimply natural happenings. There will be neither disasters nor catastrophes if the events cause noloss to human system on earth. Therefore, talking disasters is always anthropocentric. This level ofunderstanding has been long maintained in the field of disasters studies. Existing literaturechallenges the term natural disaster – it is often mentioned in quotation ‘natural disaster’ tostress the important findings in early 1970s to reject the term ‘natural disaster’ through taking thenaturalness out of natural disasters (O’Keefe, Westgate, and Wisner 1976; Wisner et al. 2004).

Alexander (1993, 4) defines ‘natural disaster’ as ‘some rapid instantaneous or profound impactof the natural environment upon socioeconomic system’. Four definitions of a ‘natural hazard’ areconsidered by Alexander: a naturally occurring man-made geologic condition or phenomenonthat presents a risk or is a potential danger to life or property; an interaction of people and naturegoverned by the coexistence state of adjustment of the human use system and the state of naturein the natural events system; ‘those elements in the physical environment [which are] harmful toman and caused by forces extraneous to him’; and the probability of occurrences within aspecified period of time and within a given area of a potentially damaging phenomenon(Alexander 1993, 4). The highlight is the interaction between human life and natural phenomena.Such an interaction has increased since humans as a society have become dependent on thesesystems, thus a natural hazard could become disastrous to humans.

Also pointing out the interaction with humans, Burton, Kates, and White (1993) argue thatdisaster risk is a result of interaction between human–infrastructure systems and natural systems.The human–infrastructure system is associated with the term vulnerability which is eitherundefined or treated loosely as weakness of the transport network (Nagurney and Qiang 2009).In 1982, the United Nations Office for Disaster Relief (UNDRO) defined risk as R = EVH, where Edenotes the element at risks measured by level of exposure of exposed population, properties, andvaluable economic assets, V denotes vulnerability function such as economic, social, and environ-mental vulnerability, H denotes a natural hazard function which can be manifested in floods,tropical cyclones, tsunamis, and earthquakes (Alexander 1993). The 1982 UNDRO’s approach torisk and vulnerability assessment remains influential today.

6 J. S. L. LAM AND J. A. LASSA

There are different theoretical models for disaster risk assessment at global scale as categorizedin Table 1 and Figure 2. Similar to the UNDRO model, Global Earthquake Model (GEM) definesrisk and impact as a function of three components: hazard, exposure, and vulnerability (or namelytriple helix – see Figure 2(c)). GEM defines a hazard as the probability levels of hazard occurrence.For instance, in the context of seismic hazard it can be the probability level of ground shakingresulting from earthquakes, within a given time span. Vulnerability is defined as the probability ofloss given a level of ground shaking for physical vulnerability, or through indicators that envelopthe socioeconomic factors known to be the driving forces of vulnerability. Exposure is theelements at risk (people, value, and assets) being exposed to natural hazards (GEM 2015).

World Risk Index, developed by United Nations University provides a slightly differentfunction: Risk equals E*V, where E is the exposure to natural hazards, and V is the vulnerabilitycomprising average values of susceptibility (or likelihood of suffering harm), lack of copingcapacity to reduce negative consequences during a disaster, and lack of adaptive capacity (forlong-term strategies for societal change). Each component of vulnerability received a weightingfactor 0.33 (UNU-EHS 2014).

In a rather established research tradition, especially in natural hazard and disaster risk researchcommunities, ‘exposure’ is defined as the number of element or unit (e.g. of people, valuablegoods/infrastructure, and activities) that is likely to experience and potentially be adverselyaffected by natural hazards (Peduzzi et al. 2009).

UNDP (2004) defines ‘vulnerability’ as a condition or process resulting from physical, social,economic and environmental factors that determine the likelihood and scale of damage from theimpact of a given hazard. Disaster Risk Index (DRI) developed by UNDP (2004) is known as thefirst human vulnerability assessment exercise on a global scale, namely, a country-by-countrycomparison of human vulnerability and exposure to earthquakes, tropical cyclones, and floodhazards. The DRI consists of two indicators: the first is the Relative Vulnerability Index (RVI),which compares national data for exposed populations with recorded mortality. The second is thesocioeconomic indicators of vulnerability at the national level, which refer to GDP per capita and

Table 1. Recent applications of global scale disaster risk assessment.

Type of assessment Risk function and/or indicators

Model asshown inFigure 2 Reference

Global port climateextreme exposure

Present and future exposure, global sea level rise, andexposed assets in GDP by elevation and extremewater levels

(a) Hanson et al. (2011),Nicholls et al. (2008)

Global disaster riskmapping

Hazard (earthquakes: peak ground acceleration,liquefaction, wind forces), vulnerability and exposure(GDP, human development index, asset specificssuch critical infrastructures)

(c) GEM and Syner-G (www.vce.at/SYNER-G) 2015

World Risk Index Exposure to natural hazards; vulnerabilities measuredby susceptibility (public infrastructure, poverty),coping capacities (government and authority) andadaptive capacities (education, adaptation,investment)

(b) UNU-EHS (2014)

Disaster risk index Relative Vulnerability Index and social–economicindicators (GDP, Human development index)

(b) UNDP (2004)

Global disaster riskhotspots

Hazards hotspots (geographic distribution of hazards)and element at risks (exposed people and assets).

(a) Arnold et al. (2005)

Global exposure andvulnerability towardsnatural hazards

Frequency of a given hazard that may occur at a unit(e.g. population) in a given exposed area and socio–politico–economical context of this population.

(a) Peduzzi et al. (2009)

Source: Compiled by authors.

MARITIME POLICY & MANAGEMENT 7

density of population. Hanson et al. (2011) adopts a similar concept to demonstrate global climatechange exposure assessment of ports and cities.

Global Disaster Risk Hotspots (GDRH) is another model developed for the sub-national scalefor individual hazard analysis. The GDRH model includes assessment of disaster mortality data,economic losses, and the risk of economic loss as a proportion of GDP. In addition to theseindicators, GDRH includes social–economic vulnerability indicators such as gross domesticproduct per inhabitant at purchasing power parity, Human Poverty Index (HPI), total debtserviced (percentage of the exports of goods and services), inflation, annual food prices, andunemployment (percentage of total labor force) (see Arnold et al. 2005).

Smith and Petley (2009) coined to term risk as double helix (Figure 2(a,b)) to illustrate the viewconcerning DNA code of risks as a joined and intertwined strands of DNA that underpindisasters. One strand represents social system (vulnerability) and the other represents naturalsystems (hazards). The two elements hazards and vulnerability are interwoven and interlinked likea DNA double helix – disasters arise from the complexity between them (Smith and Petley 2009).Paleo (2009) suggests exposure as part of vulnerability concepts and components (Figure 2(a)).

Figure 2(a,b) visualize the risk models displayed in Table 1. There are four risk scenarios. R1denotes risk that is a function of perfect match between hazards, exposure and vulnerability (ordisaster risks arise from a perfect match between hazards event, exposed assets/people andvulnerability of assets/people). R1 is the core of risks to be measured. R2 represents the fact likeexposed buildings in Tokyo could stand against earthquakes in March 2011 since resilience of thebuildings is higher than the seismic force translated to the buildings. R3 and R4 are ambiguous

Figure 2. Different disaster risk functions: double helix and triple helix.Source: Authors.

8 J. S. L. LAM AND J. A. LASSA

concepts because modelers often prefer double helix as an easy approach to separate vulnerabilityand exposure (assets at risks). However, they can be useful in illustrating the richness of risk astriple helix concept. R3 can be exemplified by vulnerability of port platforms that may fail fromregular dynamic loads (especially those not from the seismic activity) or fatigue of structures dueto regular dynamic loads on the platforms (such as mobile loads from trucks on the ports’platforms). Other examples can also be attributed to the real risk that is rooted not from tsunamiforces but due to failure to anticipate regular high tides in the design of ports. R4 shows thatexposure as an embedded concept to vulnerability, which exemplifies the vulnerability of a portsystem or structure which may experience failure or collapse. The port may fail to cope withregular forces for instance in fatigue due to long term gravity forces (life and dead loads) over thatmay be rooted in either poor design or poor construction.

Figure 2(c) is called triple helix. Recent practice of risk as Triple Helix can be seen in IPCC(2011), GEM and Kakderi, Raptakis, and Pitilakis (2009). Despite World Risk Index 2014 uses R1model (Figure 2(b)) where exposure is viewed as part of hazards, GEM seems to favor theillustrations described in Figure 2(a,c). Peduzzi et al. (2009) use R1 (regardless of Figure 2(a) or2(b)) to consider exposure and natural hazards: in case of risk of asset losses, the element at risk isthe exposed assets. The element at risk is the exposure function. Hazard refers to the frequency ofreturning period at a given magnitude. Borrowing from Wisner et al. (2004), Peduzzi et al. (2009)provide quantitative vulnerability measures as the degree of loss to each element should a hazardof a given intensity, frequency, and duration occur.

4. A framework for risk assessment at seaports

After examining the various frameworks earlier, the study has established the distinction andrelationship between natural hazards, exposure, and vulnerability. Our analysis reveals that thereare different developed risk assessment models to be used for maritime transport exposure tonatural hazards. The reason behind this is due to the fact that various models were developed toanswer different needs, hazards and purposes. Different academic disciplines use different ter-minologies and definitions. In addition, the purpose of risk assessment determines the requireddata and models. For instance, for the insurance industry, the main objective for risk assessment isto calculate quantitative risks that can be used for risk transfer policy and insurance premiumcalculation. For governments, a risk assessment may serve different societal and economic goalsincluding social and environmental protection, risk reduction measures, allocation of resourcesfor protection and investment as well as devising a more realistic public-private partnership inrisk management.

Regardless of the difference in models, a systematic classification of the exposed elements andhazards is important for maritime risk assessment. The exposed elements can be classified as (1)building (warehouse, office buildings, maintenance buildings, passenger terminals, traffic controlbuildings); (2) utility systems (electric power system, water system, waste-water system, naturalgas system, liquid fuel system, communication system, fire-fighting system); (3) transportationinfrastructure (road system, railway system, bridges) (Kakderi, Raptakis, and Pitilakis 2009). Thenthe types of hazards can be identified with details on hazard indicators and scales of intensity, asshown in Table 2. With this understanding, the following illustration deepens the discussion byspecifying risk quantification with a focus on ports.

It should be noted that exposure is not a standalone concept. Exposure is always embedded toeither hazards or vulnerability as discussed in Section 3. Figure 2(a,b) show that risk is a functionof hazards (can be in terms of the likelihood of a tsunami inundation and/or run-up) that may hita specific location at ports consisting of cargo terminals, warehouses, and others. For this, the risk(R) of an exposed maritime transport asset to a single hazard (H) such as tsunami is multiplied bythe ability of the asset to withstand tsunami forces. This can be hypothesized as such:

MARITIME POLICY & MANAGEMENT 9

R ¼ H tsunamið Þ � Exposed asset � Vul asset : (1)

Recent tsunami-genic earthquakes in Tsukuba Japan (2011), Indian Ocean Tsunami 2004 andKobe earthquake (1995) suggest that maritime transport elements or assets can be hit rathersimultaneously by both earthquakes (e.g. foreshocks, main earthquakes, and high aftershocks)followed by a tsunami. For this, the quantitative expression can be made as

R ¼ H tsunamiþ earthquakesð Þ � Exposed asset � Vul asset : (2)

The actual manifestation of risk can be the number of cargo loss per event, which can bemeasured by metric tons or TEUs or real monetary values depending on data availability.Exposure assessment requires time dimension, e.g. how long an event of a particular naturalhazard occurs in a certain element of a seaport (see Table 2). For aggregation of risk, this can bethe number of maximum cargo and valuable assets at certain periods. For instance, assuming thatseaports in the Philippines, Japan, and Taiwan also experience multi hazards such as tsunami,earthquakes, cyclones, and coastal floods, the risk function is largely modified by the number ofhazards and the nature of exposure of the assets (flood zone versus tsunami inundation scenarios)and the vulnerability of the structures of seaport elements.

R ¼Xn

i

HEð ÞV: (3)

Exposures to multi-hazards can be expressed in Equation (3), where E is exposure, that is, aseaport element that is exposed, which is assumed to face different types of natural hazards (H),where i denotes the hazard indicator (from Table 2). V is vulnerability measured by a singleelement such as physical reliability of seaport structures. We define vulnerability as the reverse ofresilience. Vulnerability can be reduced only to physical vulnerability of the existing seaportelements. However, existing concepts such as UNU-EHS (2014) can be used to demonstratevulnerability indicators such as susceptibility, cf. Table 1 and Section 3, lack of coping capacity toreduce negative consequences during a disaster and lack of adaptive capacity for long-termstrategies of ports (see Becker, Inoue, and Fischer 2012).

Hence, based on a comprehensive examination of the existing literature and information on pastcatastrophes, the framework and data required for a comprehensive seaport risk assessment isproposed as five key steps of exposure analysis as seen in Table 3. We suggest that exposure is anoverarching variable. Exposure indicators include data on assets and values of ports, volume and values

Table 2. Hazard indicators for risk assessment of different hazards.

Selectedhazards (H) Hazard indicators (i)

Scales ofintensity Reference

Tsunamis Inundation (areas and elevation) Low–high Løvholt et al. (2011)Run-up (areas and elevation) Low–high Løvholt et al. (2011)Tsunami sources Far–near field Løvholt et al. (2011)

Earthquakes Peak ground acceleration (areas) Low–highgravity (g)

Werner (1998), Werner, Dickenson, and Taylor(1997)

Liquefaction (potential liquefaction areasbased on type of soils)

Low–highgravity (g)

Werner (1998), Werner, Dickenson, and Taylor(1997), Chang (2000)

Cyclones Wind speed (km/h) 1–5 Australian Cyclone Severity IndexHurricanes Wind speed (km/h) 1–5 The Saffir–Simpson ScaleCoastal floods Present flood inundation scenarios (areas

and elevation)Low–high Hanson et al. (2011)

Future flood inundation scenarios (areasand elevation)

Low–high Hanson et al. (2011)

Multi-hazards Spatial units (empirical areas affected) Low–high Gurning and Cahoon (2011)

Source: Compiled by authors.

10 J. S. L. LAM AND J. A. LASSA

of cargo, global ports database, potential inundation and run-up of tsunami, seasonal ships, and fleetsat targeted ports. Natural hazard includes data such as global active faults seismic sources database,global seismic maps and history, global cyclone history and tracks, local flood history and localliquefaction map at targeted ports. Vulnerability indicators mainly focus on physical vulnerabilitysuch as liquefaction reliability of port structures. It is also essential to assess risk management measuresincluding emergency/crisis management measures, fire mitigation measures, number of safety inci-dents, port management quality, insurance cover, and existence of disaster recovery planning.

Researchers have made clear messages that analyzing the future risks such as climate extremescannot be simply based on past events database because of the limitation of recorded events anddata (Hanson et al. 2011). Modern port development such as container systems and intermodaldevelopment have just started in 1960s. Amid a lack of recorded data from past events before1960s, we suggest to use scenario based exposure analysis (e.g. Hallegatte et al. 2011).

One of the key challenges is data availability at smaller units and higher resolution data.On a positive note, amid the lack of historical data, computer-generated data for certain

Table 3. Proposed risk assessment framework for exposure of cargo and ports to natural hazards and climate extremes.

Key steps Variables Indicators Data

Step 1. Hazards identification Climatic hazards Cyclone history andscenario;storm surge history andscenario

Historical climate data (e.g.recorded cyclone tracks);historical damage and loss

Geological hazards Earthquake impact historyand scenarioTsunami inundationhistory and scenario

Seismic maps; historicalearthquake and tsunamirecord

Step 2. Identify physicalvulnerability of portsincluding present and futureeffectiveness

Earthquake mitigationmeasures

Physical/structural behaviorunder seismic influence

Earthquake scenario (e.g. peakground acceleration)

Wind mitigation measures Structural andinfrastructural behaviorunder extreme wind

Wind scenario inundationscenario

Tsunami counter measures Structural andinfrastructural behaviorduring tsunamis

Tsunami inundation scenario;Potential sea currentbehavior

Liquefaction reliability ofport structures

Potential liquefactionanalysis

Liquefaction history; Soilbehavior data

Step 3. Identify risk managementmeasures at seaports andbeyond

Emergency preparedness,crisis management andcontingency planning

Contingency plans; riskmanagement plans

Contingency planningdocuments; Crisismanagement documents

Fire mitigation measures(e.g. for post-earthquakes)

Fire incident history; Fireincident document

Port management quality Existing index/rankingDisaster recovery planning Disaster recovery plans Recovery planning

documentsRisk transfers Insurance cover Insurance empirical dataIncident command systems Safety incident history Past incident lists

Step 4. Identify assets and assetvaluation

Cargo volume and value Existing and projected cargovolume and value

Cargo statistics; Shipmentand transshipmentstatistics

Total values of ports Economic valuation of portassets

Detailed valuation of eachcomponent of portfacilities and infrastructure

Total wealth of port cities Economic valuation of portsand port cities

Wealth statistics; welfarestatistics; economic growth

Port dependent work force Human resources Disaggregated statistics onlabor force; highly skillsworkers, etc.

Step 5. Exposure analysis [total risk] Exposure analysis Exposure of port elementsto different hazards andvulnerability scenarios

Analyze potential exposedassets; aggregation of risk

Source: Authors.

MARITIME POLICY & MANAGEMENT 11

hazards can be obtained by specialists. Modelled/simulated data can be used to calculaterelative exposure level of seaports to certain threats from natural hazards. Table 3 presentsthe projected needs for risk assessment of seaports to multi-hazards at various scales whichwill be useful for risk analysts and port decision makers. Previous gross analysis such asLøvholt et al. (2011) conduct a global scale tsunami exposure assessment by consideringcoastal areas with different elevation facing different scenarios of tsunami inundation.Hanson et al. (2011) investigate the exposed assets and people living in coastal cities thatare likely to experience coastal flooding and climate extremes, breakdown by elevation.However, Løvholt et al. (2011) and Hanson et al. (2011) basically ignored vulnerability astheir research questions address a gross assessment of the areas and assets/people that arepotentially affected by natural hazards. Despite some contributions from previous studiesconcerning the real need to take natural hazards into port risk management, global studiesmay provide limited benefits for seaport level decision making. Being different from theliterature, the proposed framework includes vulnerability and also outlines various groups ofvariables in a systematic manner.

5. Conclusions and recommendations for future research

Exposure is an intermediary concept that seeks to explain harmful outcomes of the processesbetween natural hazards (natural system) and the infrastructure/built environment context(human system). By ‘nature’, any seaport infrastructure system and marine cargo shipping hasbeen exposed to one or more (natural) forces capable of creating damages and losses. Some areconsidered normal and seasonal events such as heavy rainfall combined by fog which create poorvisibility for shipping. These are normal parameters of climate variability. Some can be consideredextreme events that occur incidentally based on certain return periods (from annual, decadal,century and millenniums). The extreme events often lead to catastrophic outcomes and may causeheavy disruption. This paper adds value to maritime policy and research by critically assessing theconcepts and existing conceptual frameworks.

We argue for a risk assessment meaningful for seaports and shipping managers and widerstakeholders. Assessment models should provide clearer and sharper guidance pertaining to realworld risk management and risk reduction decision making along maritime transport and supplychains. Different scales of analysis and different scenarios should be provided. For instance,despite some level of uncertainty, cyclones do not occur randomly because level of exposuresmust also relate to its spatiality in certain latitude as shown in the historical cyclone tracks occurat a particular time. Therefore, the scenarios should include a seasonal timeframe when certaincargo quantity of TEUs or tonnages is situated in a particular time (e.g. monthly peak seasoninstead of annual aggregation) in a particular seaport.

We conclude that new and comprehensive risk assessment frameworks for marine exposure todifferent natural hazards are needed to answer different needs of risk management decisionmaking at different levels. The proposed framework in Section 4 presents an original contributionthat can be used as one of the alternative frameworks for future agendas concerning catastrophicrisk assessment of seaports at different scales.

Each risk assessment model can suggest different policy implications in maritime transportpolicy. Present exercises in risk assessment have been largely limited to a single natural hazardapproach. Therefore, for future research agenda, one can assess multi-hazard scenarios andthe impacts on maritime transport. In addition, research can be extended to investigate theinterplay between existing human-made hazards and multi-hazards and their impact on bothmaritime transport and supply chains. Social–economic and political implications of multi-stressors and complex interplay between the hazards can be considerable and are importanttopics which deserve more research.

12 J. S. L. LAM AND J. A. LASSA

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported by the Willis Towers Watson via the Nanyang Technological University – Institute ofCatastrophe Risk Management (NTU – ICRM).

ORCID

Jasmine Siu Lee Lam http://orcid.org/0000-0001-7920-2665

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