Swiss Re Mind the Risk

Mind the riskA global ranking of cities under threat from natural disasters

Swiss Re Mindtherisk 1

Preface

Forthefirsttimeinhumanhistorymorepeopleliveincitiesthaninruralareas.TheUnitedNationsexpects6.3billionpeopleor68%oftheworld’spopulationtobelivinginurbanareasby2050,withthehighestincreaseoccurringinhighgrowthmarkets.Manyofthesecitiesarelocatedonthecoastandarethreatenedbyfloods,storms,earthquakesandothernaturalhazards.

Thevibrancyofthesecitiesisakeydriverforeconomicdevelopment.However,thegrowingconcentrationofpeople,assetsandinfrastructurealsomeansthatthelosspotentialinurbanareasishighandrising.Atthesametimethegapbetweeneconomicandinsuredlossesislargebecauseinsurancepenetrationisrelativelylowandcityinfrastructureoftennotinsuredatall.Anotherreasonisthattheriskexposurefacedbytheworld’smetropolitanareasremainsunderexplored,largelyduetothelackofdetailedhazardinformationandpoordataquality.

Thispublicationseekstoaddressthisknowledgedeficitbyprovidingacomprehensiveanalysisofnaturaldisasterriskinlocationsaroundtheworld.BasedonSwissRe’sriskmodellingexpertiseandthelatesthazardinformationfromourCatNet®tool,itfocusesonthemostseverenaturaldisastersconfronting616oftheworld’slargesturbanareasandassessesthepotentialimpacttheyhaveonlocalresidentsandthewidereconomy.

Weknowfrompasteventsthatphysicalpreventionmeasuresalonedonotsufficetobuildaresilientcity,sincedamagefromthemostseverecatastrophescannotbefullyaverted.Animportantpartofresilienceishowwellurbansocietiesareabletocopewiththefinancialconsequencesofadisaster,whichincludesaccesstotherequisitefundingforrelief,recoveryandreconstruction.SwissRecanofferrisktransfersolutionsthathelpbridgethegapbetweeneconomicandinsuredlossesandreducethefinancialburdenonlocalcommunities.

Wehopethefindingsofthisstudywillgivefreshimpetustotheglobaldebateaboutstrengtheningtheresilienceofcitiesandencouragegovernments,citizensandtheinsuranceindustrytotakecollectiveactiontomitigatetherisksfacedbyurbancommunitiesaroundtheworld.

Matthias WeberGroupChiefUnderwritingOfficer

2 Swiss Re Mindtherisk


Tableofcontents

Preface 1

Part I – Introduction 5Citiesatrisk:anintroduction 5Riskanalysisof616metropolitanareas 6Ourapproachinfocus:ExamplePearlRiverDelta,China 8

Part II – Global findings 11Peoplepotentiallyaffected–aglobalranking 11Workingdayslost–aglobalranking 14Multipleperils–aglobalranking 18

Part III – Regional findings 21AsiaandOceania 21NorthandCentralAmerica 22Europe 23SouthAmerica 24Africa 25

Conclusion 26Buildingcityresilienceiscritical 26

Appendix 28


New Orleans under water after severe flooding caused by Hurricane Katrina in August 2005. Total damage amounted to USD 108 billion, the costliest natural disaster in US history.


PartI–Introduction

Citiesatrisk:anintroduction

HurricaneSandyhitNewYorkCityaftermakinglandfallinNewJerseyintheeveninghoursofMonday,29October2012.Sandyshowedushowsusceptiblemodernsocietiesandmetropolitanareasaretotheimpactofnaturalcatastrophes.AcrosstheeasternseaboardoftheUnitedStates,thehurricanekilled72peopleineightStatesandcausedUSD68billionindamage.InNewYorkState,48peoplelosttheirlivesandover300000homesweredestroyed.Besidesthesecasualties,thestorminundateddozensoftunnelsandsubwaystations.Evenresidentsofneighbourhoodsnotdirectlyaffectedwereunabletogettowork.Consequent-ly,shortlyafterthestorm,NewYorkGov-ernorAndrewCuomoconvenedtheNYS2100Commissiontoproviderecommen-dationsforamoreresilientNewYork.

Initswake,Sandyleft8.5millionpeoplewithoutelectricityacrosstheTri-Statearea.1Scoresofresidents,companiesandlocalauthoritieshadtowaitforweekstogettheirpowerback.TheNewYorkStockExchangeclosedtradingfortwofulldays,airlinescancelledmorethan12000flightsandabout70%ofallEastCoastoilrefinerieswereshutdown.Gasstationsacrosstheregionstayedclosedfordays.

Theeventnotonlygeneratedenormousreconstructioncostsforthecity.ItalsohadasignificantimpactontheUSecono-mysincethemetropolitanareaofNewYorkproducesabout8%ofthenation’stotaleconomicoutput.WhileHurricaneSandylaidbarethedisasterriskfacedbyaworldcitylikeNewYork,itisworthnot-ingthatSandywaslittlemorethanan

averagestormwhenmeasuredintermsofwindforce.BearinginmindthatNewYorkisnotamongthecitiesmostexposedtonaturaldisasters,weareremindedofthefactthatthingscouldgetalotworsewhenthenextmajorhurri-canehits.

Citiesaretightlywovenintotheglobalrisklandscapebecausetheyarehighlyinterconnectedandintegratedinaglobal,digitisedeconomy.Perhapsmorethananything,Sandyshowedushowvulnera-bleourcitiesare,andhowfastabreak-downofcriticalinfrastructurecanhappen,particularlyinareaswithahighconcen-trationofpeopleandproperties.Thisiswhytheneedfordisastermanagementisnowheremoreurgentthanintheworld’ssprawlingurbancentres.

Whilenaturalcatastrophescausedaver-ageeconomiclossesofUSD60–100bil-lionannually,asinglelarge-scaledisasterintheheartofabigmetropolitancentrecansurpassthisfiguresignificantly.2Re-centeventsshowedhowrealtheriskisinsomeoftheworld’smostpopulatedregions.WithanestimatedUSD210to300billionintotaleconomiclosses,the2011TohokuearthquakealongthenortheasternseaboardofJapanwasthecostliestcatastropheever.FloodingaroundBangkok,Thailand,inthesameyearbrokeanewrecordforbeingthemostexpensivefreshwaterfloodinhistory,causingUSD47billionineconomiclosses.

Rapidgrowththatoutpacesplanning,flawsinzoninglawsandconstructionfailurescanallexacerbatetheriskofnaturalhaz-ardstourbancommunities.Whenaneventdoesoccurinsuchcircumstances,itdrivesupthecostsfordisasterrecov-eryandincreasestheburdenonpublicbudgets.Allofthiscombinedraisesthepressureoncityauthoritiestoprovideserviceswhichnotonlymakeurbancommunitiesfunctionmoresmoothlybutalsomakethemmoreresilientwhenadisasterstrikes.Understandingtherisksfacedbycitiesisanecessaryfirststeptobetterpreparethemforfuturecatastrophes.

Theimpactofanaturaldisasterinadenselypopulatedareacanbecatastrophic.Thisiswhydisasterplanningisnowheremoreurgentthanintheworld’sbigurbancentres.

1Source:http://news.msn.com/us/new-york-new-jersey-put-dollar71b-price-tag-on-sandy

2sigmaNo2/2013:Naturalcatastrophesandman-madedisastersin2012


Riskanalysisof616metropolitanareas

Theworld’sbigandsprawlingcitiesarecentresofeconomicactivityandgrowth.Butmanyofthemarealsohighlyexposedtonaturalhazards.Asmorepeoplemovetothecitiesandbusinessesinvestintheirlocaleconomy,morelivesandassetsconcentrateindisaster-proneareas.By2050,thenumberofpeopleresidingincitieswillhavereached6.3billion,ac-cordingtotheUnitedNations.Strength-eningtheresilienceofthesecommunitiesisthereforebecomingamatterofurgency.

Toassesstheriskexposurefacedbyurbanpopulationsaroundtheworld,weinvesti-gatedthelosspotentialof616majormetropolitanareasusingSwissRe’spro-prietaryhazarddataonfiveperils:earth-quake,storm,stormsurge,tsunamiandriverflood.Wechosethelargesturbanagglomerationsbasedonthemostrecentpopulationdataandidentifiedcitylimits,includingcityoutskirtsandcommutertowns,usingsatellitedata.These616urbanareasarehometoabout1.7billionpeople,roughly25%oftheworld’stotalpopulation,andcoverUSD34000billionorabout50%oftheglobalGDP.3Ofthesemetropolitanregions334arelocatedinAsia/Oceania,90inEurope,83inNorthAmerica,60inAfricaand49inSouthAmerica.

BasedonhazarddatafromSwissRe’sCatNet®wedevisedariskscenarioperperilforeachmetropolitanarea.Wefocusedonrarecatastrophes:ahurricanewithwindssubstantiallystrongerthanSandyoratsunamisimilartotheonetrig-geredbytheTohokuearthquakeinJapan.Statistically,acitywouldbehitbysuchaneventonceeveryfewhundredyearsorless.Atthislevelofintensity,protectionmeasurestypicallyfailbecausetheforceofthedisasterexceedstheimpactanticipatedbylocalbuildingcodesandprotectionmeasures.

Thehumanandeconomictollofaneventlikethiscanbeenormous.Toshowtheeffectsanaturaldisastercanhaveonametropolitanareaandtheeconomy,weconsideredtwoindicators:thesizeoftheurbanpopulationthatcouldbehitbyoneormorenaturalperils(indexofpeoplepotentiallyaffected)andtheimpactthiscanhaveonthelocalandnationaleconomy(indexofthevalueofworkingdayslost).

Citiesarecentresofeconomicactivityandgrowth.Asmorepeoplemovetothecitiesandbusinessesinvestlocally,morelivesandassetsconcentrateindisaster-proneareas.

3UnitedNationsDepartmentofEconomicandSocialAffairs/PopulationDivision,WorldUrbanizationProspects:The2011Revision


Forthepopulationindex,wecalculatedtheeffectsoncityresidentsusingdetaileddataonpopulationdistributionandhazardvulnerabilityestimatesforallrelevantperils.Ourdefinitionof“peoplepotentiallyaffected”comprisesfatalities,injuriesandevacuations.Italsoincludespeoplewhosehomesweredamagedandwhowereunabletoaccesstheirwork-place.

Fortheeconomicindex,weassessedthecostsoflargenaturalcatastrophesintermsoflosteconomicproductionorthevalueofworkingdayslost.Thisesti-mateapproximatesthetimeduringwhich

affectedresidentswouldbeunabletogotoworkintheeventofadisasterandthecostsresultingfromlostoutput.4Thedefi-nitiondoesnotincludesecondaryeffects,suchaspoweroutagesorinterruptionoftrafficlines.OurassessmentofthePearlRiverDeltainChinaprovidesapracticalexplanationofhowweusedthismethod-ology(seepages8–9).

Asetofriskparametersguidedouranalysis:thegeographicareaaffectedbyastorm,flood,earthquakeortsunamiandtheintensityusedtoassesstheimpactofeachperil(table1).

Table 1: Assumptions used to calculate exposed metropolitan area by city and peril

ScenarioAssumedaffectedareapercity

Intensityparameterforimpactassessment

Storm(Winterstorm,tropicalcyclone)

Fullarea Peakgustwindspeed

Stormsurge

Reducedarea(lowlyingcoastalareas)

Coastalfloodriskzones,incombinationwithsimplifiedfactorsforbathymetry,coastalmorphology,estuarineconditions,peakgustwindspeedandangleoflandfall

Riverflood Reducedarea Variableintensityperfloodriskzone

Earthquake

Fullarea

Peakgroundaccelerationandpotentialforseismicwaveamplification

Tsunami

Reducedarea(lowlyingcoastalareas)

Coastalfloodriskzones,incombinationwithsimplifiedfactorsforbathymetry,coastalmorphology,estuarineconditionsandregionalseaquakerisk

4WorkingdayslosthererevealafractionoftheGDP/capitawhichisnotbeingproducedintheshorttermduetotheevent.Weaccountfortheeconomicimportanceofthemetropolitanareasandbuildworkingassumptionsbasedonvariouspubliclyavailablesources;countryGDP-dataisbasedonOxfordEconomics.ForareaswithoutinformationonarespectivecityGDP/capita,weusemultipliersonthecountryGDP/capita.ThesemultipliersaretailoredtotheWordBankcountryclassifications.


Ourapproachinfocus:ExamplePearlRiverDelta,China

ThePearlRiverDeltaisadenselypop-ulatedmetropolitanareathatishometomorethan42millioninhabitants.Coveringaterritoryofsome20600squarekilometres,itcomprisestheur-bandistrictsofHongKong,Shenzhen,Dongguan,MacauandGuangzhou.TheregionisoneofChina’smaineco-nomiccentres,withanestimatedGDPofUSD690billion.ItsaverageGDPpercapitaismuchhigherthanthenationalaverage.

Perils affecting Pearl River DeltaThemapsonpage9(fig.1.1to1.4)showthemetropolitanareaofthePearlRiverDelta,localpopulationden-sityandfourperils:typhoon-relatedstormhazard,riverandcoastalfloodzones,andearthquakeintensity.

Population potentially affectedInafirststep,weoverlaidpopulationdatawithourhazardandvulnerabilityinformationpresentedinCatNet®andidentifiedthenumberofpeopleatriskfromeachperil.Weusedtheresulttogloballyrankall616cities.Duetoitshighexposureandthegreatnumberofresidents,thePearlRiverDeltaranksnumberoneamongallmetropolitanareaswhenlookingattheabsolutenumberofpeoplepotentiallyaffected

bystorm,stormsurgeandriverflood(seetable2).Theareadoesnotfeatureintheearthquakerankingsbecausetheearthquakeriskisalmostinexistent.DuetoanactivesubductionzonealongthePhilippinestrenchseveralhundredkilometresaway,thereissomeprobabilityofatsunamihittingthearea,butitisrelativelylow.Sincetheareaisverylarge,thepicturechangeswhenlookingatthepercent-ageofpeoplepotentiallyaffectedratherthanabsolutenumbers.

Index of working days lostInasecondstep,wecalculatedthepotentialeconomicvalueofworkingdayslost–orthetotalGDPvalueforalldaysduringwhichacertainper-centageofthepopulationcannotgotowork.Again,wecomparedittotheother615metropolitanareas.Inthisrespect,thePearlRiverareaisrankedhighestforstormsurge,thirdforwindbehindTokyo-YokohamaandOsaka-Kobe,andfifthforriverfloodafterTo-kyo-Yokohama,Nagoya,Osaka-KobeandParis.Thevalueofworkingdayslostcouldreachuptoalowtwo-dig-itbillionUSDfigureforastrongty-phoon–andisthereforeintherangeof1–2percentoftheregion’sannualGDP.Duetoourgeneralapproach,however,wedecidednottoprovidespecificGDPvaluesandinsteaddevelopedarankingofall616cities.

Table 2: Results and global rankings for the Pearl River Delta with a population of approximately 42 million

Perilscenario

Populationpotentiallyaffectedinmn(absolutenumbers)

Rankpopula-tionpotentiallyaffected(absolutenumbers)

Populationpotentiallyaffectedin%ofmetroareapopulation

Rankvalueofworkingdayslost(globalindex)

Storm 17.2 1 41 3Stormsurge 5.3 1 12 1Riverflood 12.0 1 28 5Earthquake – – – –Tsunami – – – –

ThePearlRiverDeltaisadenselypopulatedmetropolitanareacomprisingHongKongandGuangzhou.Situatedinoneoftheworld’smostdisaster-proneregions,floodsandtyphoonsputmorepeopleatriskthaninanyothermetropolitanareaintheworld.


Figure 1.1:Populationdensity,PearlRiverDelta,AsiaSource:EastviewLandScan2011™

Figure 1.3:Riverfloodriskzones,PearlRiverDelta,AsiaSource:SwissReGlobalFloodZones™

All figures based on:©GfkGeoMarketingMapEditionWorld/Imagery:©2013ESRI,i-cubed,GeoEye

Figure 1.2: Tropicalcyclonetracksandcoastalfloodzones,PearlRiverDelta,AsiaSource:Unisys/trackset,SwissRe

Figure 1.4:Earthquakerisk,PearlRiverArea,AsiaSource:GSHAP

Pearl River Delta: population at risk from multiple perils


Roads in the North Bangkok Business District are submerged in floodwaters in November 2011 after heavy rainfall during the annual monsoon season. The Thailand flood of 2011 cost the insurance industry USD 15 billion, the largest insured fresh water flood loss ever.


PartII–Globalfindings

Peoplepotentiallyaffected–aglobalranking

Someoftheworld’sfastest-growingmet-ropolitanareasaresituatedalongChina’scoastlines,suchasthePearlRiverDeltaandShanghai.Besidesbeingexposedtofrequenttropicalcyclonesandstormsurges,manycitiesintheregionarealsolocatedinzonesofhighseismicactivity,includingTokyo,TaipeiandManila.

Whenlookingattheirexposuretonaturaldisasters,mostoftheworld’sriskiestcitiesarethereforesituatedinEastAsia,notablyChina,Taiwan,thePhilippinesandJapan.Buttherearedifferentwaysoflookingatriskexposure.Nodoubt,humanlifecomesfirst.Inthatrespect,Tokyo-Yokohama,thePearlRiverDeltaandOsaka-Kobearetheriskiestmetro-politanareasintheworld(table3).

LikeEastAsia’ssprawlingconurbations,mostothermajorcitiesdevelopedalongtheseaandnaturalwaterwayssuchaslakesandrivers.Soitishardlysurprisingthatfloodriskthreatensmorepeoplethananyothernaturalcatastrophe.Acrossthe616metropolitanareasincludedinthisstudy,riverfloodingposesathreattoover379millionresidents.Thatismorethanthe283millioninhabitantspotentiallyaffectedbyearthquakesandthe157mil-lionpeopleatriskfromstrongwinds.

Incontrast,coastalstormsurgepotentiallyaffectsonlyabout33millionurbandwellers,andtsunamisposearisktojustover12millionpeople.Thisisbecauseonlyabout220million–or13%–ofthemetropolitanareas’residentsactuallyliveincoastalplains.Themapsonthefollow-ingpagesillustratehowdifferentregionsarepotentiallyaffectedbyeachoftheseperils,withdetailedresultslistedintheappendix.

The vast majority of cities are prone to river floodingSituatedonriverfloodplainsoralongriverdeltas,almostalllargemetropolitanareasareindangeroffloodingtosomedegree.IndiaandChina,inparticular,faceasignificantthreatfromriverflooding.With12millionresidentspotentiallyaffected,thePearlRiverDeltaisthemostflood-exposedurbanareaintheworld.Shanghai(11.7million)andKolkata(10.5million)followinsecondandthird

place.WedonotfindasingleEuropeanmetropolitanareaamongthetwentymostpotentiallyaffectedurbanpopula-tions.This,however,changeswhenlookingattheeconomiclosspotentialfromriverfloodinginthenextchapter.

Earthquakes are prevalent in many locationsMostpeoplepotentiallyaffectedbyearthquakeslivealongtheso-calledRingofFire,anareaofhighseismicandvol-canicactivityalongthePacificOcean.Besidestheirproximitytothesea,manyofthesesettlementssitinflatbasinsoftencharacterisedbysoftsoilconditions,whichmakeshakingintensitiesevenstronger.Earthquakesintheseareascanalsoresultinsoilliquefaction,aphenom-enonwherebythesaturatedsoilsubstan-tiallylosesitsstrengthandreactslikealiquid.

Withcloseto30millionpeoplepotentiallyaffected,themetropolitanareaofTokyo-YokohamainJapanisbyfarthemostearthquake-exposedcommunityinourrankings.OtherpopulationsthreatenedbyearthquakesareJakarta(17.7million)andManila(16.8million),followedbyLosAngeles(14.7million)andOsaka-Ko-be(14.6million).

ThedangerfacedbycitiesneartheSanAndreasFault,suchasSanFranciscoandLosAngeles,iswidelyknown.ButthetremendouslosspotentialinregionsofCentralAsiaandalongtheNorthernAnatolianfaultintheMiddleEastisoftenoverlookedandnotimmediatelyappar-ent.Forexample,thepopulationsoftheIraniancapitalofTehran(13.6million)orTashkent(2.9million),thecapitalofUzbekistan,arehighlyexposedtoearth-quakeriskandfeatureprominentlyinourearthquakerankings.UnlikecitiesinNewZealand,metropolitanareasinAustraliaarerelativelysafe,asarecitiesintheeasternpartsofSouthAmericaandmostregionsofAfrica.

Table 4: Cumulative number of people potentially affected in all metropolitan areas – by peril

Peril Peoplepotentiallyaffected globally,inmillionRiverflood 379Earthquake 283Windstorm 157Stormsurge 33Tsunami 12

Table 3: Most people potentially affected, aggregated for all five perils (in million)

Tokyo-Yokohama(JPN) 57.1Manila(PHL) 34.6Pearl-RiverDelta(CHN) 34.5Osaka-Kobe(JPN) 32.1Jakarta(IND) 27.7Nagoya(JPN) 22.9Kolkata(IND) 17.9Shanghai(CHN) 16.7LosAngeles(USA) 16.4Tehran(IRN) 15.6


Storms endanger mostly urban areas on the coastThedangerofwindstormsismostacuteinthemetropolitanareasofeasternAsia.Tropicalcyclonesinthispartoftheworld,alsoknownastyphoons,aremostactiveinthebasinoftheWestPacific.Inaddition,morepeopleliveinlargerandmorecondensedmetropolitanareaslocatedalongthecoastthantheydoanywhereelseintheworld.

EightoutofthetenmostheavilyexposedurbancommunitiesarethereforeallinEastAsia,withthePearlRiverDelta(17.2millionpeoplepotentiallyaffected),Tokyo-Yokohama(14.1million)andManila(12.6million)toppingtherankings.TheIndiancitiesofMumbai(4.3million)andChennai(4.0million)areranked8th

and9th.Thehighestnon-Asianmetro-politanareaisLondon(2.2million,winterstorms)ranked18th.Miami(1.4million,tropicalcyclons)isranked23rd.

Incontrasttowinterstorms,tropicalcycloneslosetheirdestructionpotentialrelativelyquicklyoncetheymakelandfall,andtheirgeographicexpanseislimited.InwesternandcentralEurope,metropoli-tanareasarethreatenedbywinterstormswhichmaintaintheirstrengthevenwhentheymovefarinland.However,theirwindspeedsarelowerthanthoseoftropicalcyclones.WhenlookingatwinterstormsinEurope,London(2.2million),Paris(1.1million),theRhine-RuhrareainGer-many(1.0million)andAmsterdam-Rotterdam(0.9million)assumethetopfourspots.

Sincemostmajorcitiesdevelopedalongtheseaorwaterways,floodriskthreatensmorepeoplethananyothernaturalcatastrophe.Acrossthe616citiesassessed,riverfloodingposesathreattoover379millionresidents.Over283millioninhabitantscouldpotentiallybeaffectedbyearthquakes,and157millionpeopleareatriskfromstrongwinds.Inmanycases,urbanpopulationsmustbepreparedtocopewithmorethanonehazard.


CatNet®Mostresultsofthisstudy,includinghazarddataused,areavailableinCatNet®,SwissRe’sonlinenaturalhazardinformationandmappingsystem.Thistoolallowsyoutozoominonindividualregionsandproducetailor-mademapsliketheonesbelow.Userscanimporttheirowncoordi-natesandinformationintothetooltogeneratecustomiseddatasets.

CatNet®isfreeofchargetoSwissReclientsandisavailableonrequesttothirdparties.

Forfurtherinformationortoregister:www.swissre.com/catnet [email protected]

Figure2.1:CatNet®mapshowingthenumberofpeoplepotentiallyaffectedbyriverfloodsinblueandstormsurgesinlightblue.

Figure2.2:CatNet®mapshowingtheaggregatednumberofpeoplepotentiallyaffectedandtheshareperperil.ThebubblesareexemplarilydisplayedontopofSIGMAworldinsuranceinformationforthedensityofnon-lifepremiums.

I

MosturbanpopulationspotentiallyaffectedbyearthquakeslivealongtheRingofFire,anareaofhighseis-micactivityinthePacificOcean.WhilethedangerfacedbyAmericanandJapanesecitiesiswellknown,thelosspotentialfromearthquakesinCentralAsiaandtheNorthernAnatolianFaultintheMiddleEastissignificantandoftenoverlooked.

People potentially affected by earthquakes and tsunamis

People at risk per metropolitan area and peril scenario

Earthquakes: 10 million people potentially affected

Tsunamis: 2.5 million people potentially affected

Source: GSHAP, www.swissre.com/catnet

II

Most of the world’s major cities developed along the sea and natural waterways such as lakes and rivers. Many are situated on river flood plains or near river deltas. Almost all large metropolitan areas are therefore exposed to some risk of flooding. The threat from river flooding is particularly high for cities in India and China.

III

IV

People potentially affected by river floods


River floods: 10 million people potentially affected

Source: www.swissre.com/catnet

The danger posed by storms is most acute in eastern Asia. Tropical cyclones in this region, known as typhoons, are most active in the basin of the West Pacific. In Europe, cities are threatened by winter storms. While they have lower wind speeds than tropical cyclones, winter storms can keep their force even when far inland.

V

VI

People potentially affected by storms and storm surges

Source: http://weather.unisys.com/hurricane and data processing by Swiss Re, www.swissre.com/catnet


Storms: 10 million people potentially affected

Storm surges: 2.5 million people potentially affected

14 Swiss Re Mind the risk

Storm surge risk is linked to heavy windsPeople living in coastal areas exposed to heavy winds are also endangered by storm surge. Eastern Asia is most at risk because typhoons, which have the high-est wind speeds, regularly hit the region. Pearl River Delta (some 5.3 million peo-ple), Osaka-Kobe (3.0 million people) and Mumbai (2.6 million people) are ranked highest for storm surge risk, since these metropolitan areas developed on large coastal plains.

The Amsterdam-Rotterdam conurbation in the Netherlands is entirely located within a zone of highest risk and holds a top spot in the storm surge rankings, with 1.8 million people potentially affected. Most sections of these cities are even situated below sea level. However, it is important to point out that these areas are protected extremely well by massive storm surge defences, so the chance of catastrophic damage is substantially lower than in other lesser protected areas. New York City is the most exposed urban area in the United States, with more than 1 million people directly at risk from storm surge. Following Hurricane Sandy, city authorities are taking measures to strengthen local defences.

Tsunami risk dominates in the PacificThe cities most exposed to tsunami risk are in Japan, since they are located along the active faults of the Western Pacific. Tokyo-Yokohama and Nagoya, each with around 2.4 million people who are poten-tially affected, top our tsunami rankings. Osaka-Kobe (1.8 million), Shantou (0.7 million) and Kolkata (0.6 million) complete the list of the five most tsunami-exposed metropolitan areas.

Subduction zones, whereby oceanic plates dive underneath the continental crust, are expected to create much larger tsunamis than so-called strike-slip faults such as the San Andreas Fault. For this reason, the Californian coastline is only classified as a medium risk zone. A tsunami can, however, travel over very large distances and affect coastal areas far away from the triggering seaquake. Metropolitan areas within the medium and low risk zones can therefore also experience devastating tsunamis.

Working days lost – a global ranking

Natural catastrophes do not only affect people. They can also significantly disrupt the economy of an affected metropolitan area and, in some cases, the economy of an entire country. We estimated the eco-nomic effects of earthquakes, storms and floods using average assumptions of working days lost for each hazard and developed an index for cross-city com-parisons.5

We can look at the results from a global and a local perspective. In our global rankings, standardised absolute values of working days lost apply. By this measure, the metropolitan areas of high-income countries top the list. This is because ab-solute losses are generally higher in plac-es like Tokyo-Yokohama or Los Angeles than in Jakarta or Istanbul, even though similar numbers of people are potentially affected by a natural disaster.

However, when we take a local view and put the productivity losses of a city in relation to the GDP of an entire country, the picture changes. In this case, a small-er country with only one or a handful of urban centres can end up in the first ranks because these cities play an essential role to their home country’s national econo-my. Examples include the Latin American capitals of San Jose, Costa Rica and Lima, Peru. These local rankings give an indi-cation of how a disaster can impact the resilience of a whole nation.

Natural catastrophes not only endanger human lives, but they can also significantly disrupt the local economy of a city and, in some cases, the economy of an entire country.

5 In our rankings, an index value of “1” denotes the city with the highest potential impact from one particular peril. To index the impact of all five perils combined (earthquake, wind speed, river flood, storm surge and tsunami), the individual peril indices are added up.


How to read the chartsEachchartshowstheeconomicimpactranking(workingdayslost)foreachcityfrombothaglobalandanationalperspective,alongwiththesizeoftheurbanpopulationpotentiallyaffectedbyoneormoreperils.Thesketchbelowillustratesthefourvaluespre-sentedineachchart(figure3):

1)Thesizeofeachbubblerepresentsthenumberofinhabitantslivinginagivenmetropolitanarea.

2)Thecolouredwedgeinthepiechartistheshareofinhabitantspotential-lyaffectedbyagivenperil.

3)Thex-axismarksthevalueofworkingdayslostpercityusingalogarithmicscale(globalindex).

4)They-axismarksthevalueofwork-ingdayslostpercityinrelationtothecountry’snationaleconomy

usingalogarithmicscale(globalindex,relativetothenationaleconomyofhomecountry).

Asthefourquadrantsillustrate,wecandrawdifferentconclusionsfromthepositionofeachcityonthechart.Sincewecannotfitall616citiesinonechartwehavelimitedthechoicetothetoptenranksusingalogarithmicscale.Theycombinethetop10ranksfortheanalyses‘peoplepotentiallyaffected,’‘globalindexofworkingdayslost’,‘globalindexofworkingdayslostrelativetothenationaleconomy’.

Forillustrativepurposes,figure4showsthedistributionofcitiesonalinearscaleforearthquakerisk.Ithighlightsthewidedivergencesinnumericalvaluesbetweencities,suchasthegapbetweenthefirstandsecondranks.

Manila (PHL)

San Francisco (USA)

Taipei (TWN)

San Jose (CRI)

Lima (PER)

Los Angeles (USA)Nagoya (JPN) Osaka-Kobe (JPN)

Tokyo-Yokohama (JPN)

1.0

0.5

00.5 1.00

Value of working days lost, global view

Valu

e of

wor

king

day

s lo

st, n

atio

nal v

iew

Severe impact per country, low global ranking

Severe impact per country, top global ranking

Limited impact per country, top global ranking

Limited impact per country, low global ranking

Value of working days lost, global view

Valu

e of

wor

king

day

s lo

st, n

atio

nal v

iew

KeyUnaffected population

Share of population potentially affected by peril

Figure 4: Illustrativechartusingalinearscaleforearthquakeriskinsteadofalogarithmicscale(seefigure7forcomparison).Thisshowstheactualdistributionofcitiesandtheunequalgapsinriskexposurebetweenthem.

Figure 3: Visualisationofglobalrankings.Citiesintheupperright-handcornerofeachchartfacethehighestpotentialimpactinabsolutetermsandinrelationtotheircountry’snationaleconomy.


EarthquakesAmajorearthquakecanaffectalmostallresidentsofacity.Givencountries’differentlevelsofeconomicdevelopment,theabsoluteimpactonproductioncanbemagnitudeshigherindevelopedcoun-triesthaninemergingmarkets.TheTokyo-Yokohamaregionhas37millioninhabitants,ofwhich80%or29millioncouldbepotentiallyaffectedbyaverylargeearthquake.Ofall616metropolitanareasstudied,ithasthehighestvalueofworkingdayslostandsocarriesanindexvalueof1onthex-axis(figure5).

Japan,however,hasseveralotherurbancentreswhichsustainthecountry’seconomy.Bycontrast,anearthquakeofasimilarmagnitudewouldhaveamuchmoresevereimpactonthenationalecon-omyofacountrylikeCostaRica.Some2.2millioninhabitantsliveinthecapitalofSanJose,whichmakesupahighpro-portionofthecountry’stotalpopulation.Almostallofthemareexposedtosignifi-cantearthquakerisk.SanJoseistheeco-nomichubofCostaRica.ThepotentialcostsofanearthquakemakesSanJosethecitywiththehighestpotentialfalloutforacountry’snationaleconomy,indi-catedbyanindexvalueof1onthey-axis.

Wecandrawsomeinterestingconclusionsfromthis.Smallerurbanareasaremorebroadlyaffectedthanlargerareas(egLimarankshigherthanJakarta).Butahighnumberofpeoplepotentiallyaffecteddoesnotautomaticallymeanahighglobalrankwhenmeasuredintermsofproductionlost(egJakartais25timeslessaffectedthanLosAngeles).LessobviousperhapsisthatalthoughLosAngelesandSanFranciscoarewidelyconsideredathighriskofearthquakes,theyarefromanationalperspectivelowerrankedthancitieslikeManilaorLima.Finally,thedif-ferenceinproductionlossescanbehuge.Forexample,thenationalimpactofanearthquakeinYerevan(Armenia)andTo-kyo-Yokohamaissimilar,buttheabsoluteimpactinTokyoismorethan300timeshigher.

0.010

0.100

1.000

0.001 0.010 0.100 1.000

Value of working days lost (global index, relative to national economy of home country)

Value of working days lost (global index)

Jakarta (IDN)33.1 mn

Santiago (CHL)6.2 mn

Taichung (TWN)5.8 mn

Tehran (IRN)15.1 mn

Shizuoka (JPN)1.6 mn

Almaty (KAZ)1.7 mn

Manila (PHL)21.0 mn

San Jose (CRI)2.2 mn

Bishkek (KGZ)1 mn

Osaka-Kobe (JPN)18.6 mn

Los Angeles (USA)15.4 mn

San Francisco (USA)5.0 mn

Taipei (TWN)8.1 mn

Santo Domingo (DOM)3.3 mn

Istanbul (TUR)11.5 mn

Nagoya (JPN)11.6 mn

Tokyo-Yokohama (JPN)37.1 mn

Lima (PER)8.9 mn

Yerevan (ARM)1.4mn

Figure 5: Metropolitan areas at risk from earthquakes


River floodsThefloodrankingsofmetropolitanareasinfigure6showasomewhatdifferentpicturecomparedtoearthquakes.Metro-politancentreswithmorethan50%ofthepopulationpotentiallyaffectedareex-ceptionsandaremainlylocatedineast-ernChina.Yet,anumberofcitiesappearintherankingswhicharenotknowntobeparticularlyexposedtoflooding,suchasMexicoCity,Baghdad,ParisorDoha.

TheanalysisshowsthatBangkokishighlyexposedtoriverfloodingwithpotentiallymassiveimpactstothenationaleconomy.Thiswastragicallyconfirmedbythe2011ChaoPhrayaRiverflood,thelargestin-suredfreshwaterfloodeventeverrecord-ed.Thetotallossamountedtoaround10%ofnationalGDP,whichhighlightsthecriticalimportanceoffloodprotectionmeasuresfortheThaigovernment.

Storms Fewermetropolitanareasareexposedtoheavydamagefromstormsthanbyearthquakesorfloods.Thecitiespoten-tiallymostaffectedbyhighwindspeedsarelocatedalongthecoastlinesofAsia,suchasTokyo-Yokohama,Manila,TaipeiandthePearlRiverDelta.

AsFigure7shows,onlythreeofthemostexposedmetropolitanareasareoutsideAsia:Havana(Cuba),Port-au-Prince(Haiti)andSantoDomingo(DominicanRepublic).AllthreeCaribbeancitiesplayanessen-tialroleinthefunctioningoftheirsmallislandeconomies.Perhapssurprisingly,bigUScitiesknowntobeexposedtostormandhurricanerisk–suchasMiamiorNewYork–donotfeatureintheworldtop10forthisperil,ranking23rdand45threspectively.

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0.001 0.010 0.100 1.000



Cairo (EGY)17.7 mn

Jakarta (IDN)33.1 mn

Pearl River Delta (CHN)42.4 mn


Nagoya (JPN)11.6 mn

Doha (Qat)1.4 mn

Dehli (IND)21.9 mn

Khartoum (SDN)5.6 mn

Bagdad (IRQ)8.0 mn

Kolkata (IND)19.1 mn

Ndjamena (TCL)1.2 mn

Phnom Peng (KHM)1.6 mn

Ulaanbaatar (MNG)0.9 mn

Paris (FRA)11.2 mn

Amsterdam-Rotterdam (NLD)5.4 mn

Mexico City (MEX)19.6 mn

Milan (ITA)7.3 mn

Bangkok (THA)9.5 mn

Yerevan (ARM)1.4 mn

Shanghai (CHN)17.6 mn

Tianjin (CHN)5.8 mn


Manila (PHL)20.9 mn

0.001

0.010

0.100

1.000

0.001 0.010 0.100 1.000



Pearl River Delta (CHN)42.4 mn

Busan (KOR)5.0 mn

Shantou (CHN)10.0 mn

Fukuoka (JPN)3.9 mnChennai (IND)

8.5 mn

Port-au-Prince (HTI)2.0 mn

Santo Domingo (DOM)3.3 mn

Tainan-Kaohsiung (TWN)5.1 mn Taipei (TWN)

8.1 mn

Mumbai (IND)20.6 mn

Taichung (TWN)5.8 mn

Nagoya (JPN)11.6 mn



Manila (PHL)20.9 mn

Figure 6: Metropolitan areas at risk from river flooding

Figure 7: Metropolitan areas at risk from storms


Multipleperils–aglobalranking

Manyoftheworld’smetropolitanareasarethreatenedbymorethanjustonenat-uralperil,andsomeevenfacetheriskofbeinghitbyseveralperilsatonce.The2011Tohokuearthquake,forexample,triggeredamassivetsunamiwavewhichledtoextensivefloodingacrossthenorth-easternseaboardofJapan.FloodingwasalsobroughtonbyHurricaneSandyin2012andsubmergedvastpartsofNewYorkCitywhilewinddamagewasminorinthiscase.

Naturalperilshavedifferentphysicalcharacteristicsandprobabilities.Forex-ample,thechanceofamajorearthquakeandatyphoonhappeningatthesametimeisextremelylow.Nevertheless,tocreateagloballyconsistentriskindexitmakessensetolookattheaggregatedriskthatalltheperilsposetoanurbancommunity.Todoso,weaddeduptheresultsforallfiveperilsforeachcity.Accordingly,theindexvalueofworkingdayslostcanadduptoamaximumof5.

Urbanresidentswhoarethreatenedbymultipleperilsaremorelikelytobehitbyanaturalcatastropheintheirlifetimethanthoseconfrontedwithonlyoneperil.Inourstatistics,theseresidentsarecountedmorethanonce.Theaggregatenumberofpeoplepotentiallyaffectedbymultipleperilscanthereforeexceedtheactualsizeofacity’spopulation.Themoreitdoes,themoreprobableitisthatlocalresidentswillatsomepointhavetocopewithanaturaldisaster.

Table5showsaggregatedrankingsforallfiveperils.Theylisttheabsolutenumberofpeoplepotentiallyaffected;thevalueofworkingdayslostinrelationtothelocalandnationaleconomy.Insmaller,denselypopulatedmetropolitanareas,earth-quakesandstormscouldaffectvirtuallytheentirepopulation.Althoughmorecommonthananyothernaturaldisaster,riverfloodstypicallyonlyaffectalimitedpartofametropolitanarea.Stormsurgesandtsunamisonlyaffectpeoplelivingnearthecoast.

Table 5: Top ten city rankings by analysis for all aggregated perils

Metroarea

Ranking:peoplepotentiallyaffected(aggregateforall5perils)

Metroarea

Ranking:valueofworkingdayslost(globalindex,aggregatedforall5perils)

Metroarea

Ranking:valueofworkingdayslostrelativetonationaleconomy(globalindex,aggregatedforall5perils)

Tokyo-Yokohama(JPN) 57.1mn Tokyo-Yokohama(JPN) 4.50 Manila(PHL) 1.95Manila(PHL) 34.6mn Osaka-Kobe(JPN) 2.71 Amsterdam-Rotterdam

(NLD)1.31

PearlRiverDelta(CHN) 34.5mn Nagoya(JPN) 2.69 Tokyo-Yokohama(JPN) 1.29Osaka-Kobe(JPN) 32.1mn PearlRiverDelta(CHN) 1.78 SanJose(CRI) 1.26Jakarta(IND) 27.7mn Amsterdam-Rotterdam

(NLD)0.96 Guayaquil(ECU) 1.20

Nagoya(JPN) 22.9mn LosAngeles(USA) 0.93 Taipei(TWN) 1.02Kolkata(IND) 17.9mn NewYork-Newark

(USA)0.62 Ndjamena(TCL) 1.00

Shanghai(CHN) 16.7mn SanFrancisco(USA) 0.47 Nagoya(JPN) 0.97

LosAngeles(USA) 16.4mn Paris(FRA) 0.46Tainan-Kaohsiung(TWN)

0.90

Tehran(IRN) 15.6mn Taipei(TWN) 0.39 Lima(PER) 0.90


Withsomeexceptions,theworld’sriski-estmetropolitanareasarelocatedinAsia,especiallyinChina,Taiwan,thePhilip-pinesandJapan.Hostingseveralmillionpeopleindenselypopulatedconurbations,Asia’scitiesarelikelytobethehardesthitbynaturalcatastrophes,bothintermsofabsolutenumbersofpotentiallyaffectedpeopleandeconomicimpact.

Figure8showsanoverviewofthemostexposedcitiesworldwide.Becauseearth-quakescanaffectthemajorityofthepopulation,theirsharedominatesthepiechartinseismicallyactiveorexposedregions.Inlocationswithamulti-hazardrisk,theprobabilityofaneventincreasessubstantially.Tokyo-Yokohama,Osaka-KobeandNagoyainJapanaswellasthePearlRiverDeltainChina,Taichung,TaipeiandTainan-KaohsiunginTaiwanandManilainthePhilippinesfaceahighlikelihoodofbeingimpactedbydifferentperils.Thisamplifiesthethreattotheirin-habitantsandeconomies.

Figure 8: Impact of all perils by metropolitan area – Top 10Thechartincludestheaggregatenumberofpeoplepotentiallyaffectedbyallrelevantperils(bubblesize)andglobalrankingsbythevalueofworkingdayslost,inabsoluteterms(x-axis)andinrelationtothecountry’snationaleconomy(y-axis).Residentsarecountedmultipletimeswhenaffectedbymorethanoneperilbecauseeachperilisaccountedforindividually.

0.010

0.100

1.000

0.010 0.100 1.000 5.000



5.000

Shanghai (CHN)

Tehran (IRN)Taipei (TWN)

Los Angeles (USA)

Lima (PER)

Manila (PHL)

San Jose (CRI)

Guayaquil (ECU)

Osaka-Kobe (JPN)

Nagoya (JPN)

Jakarta (IDN)

San Francisco (USA)

Pearl River Delta (CHN)

Paris (FRA)

Tokyo-Yokohama (JPN)

Amsterdam-Rotterdam (NLD)

Tainan-Kachsiung (TWN)

Kolkata (IND)

New York-Newark (USA)

Whenconsideringtherelativeimportanceofametropolitanareatothenationaleconomyofacountry,othercitiesmoveuptherankings:Amsterdam-Rotterdam(Netherlands),SanJose(CostaRica),Lima(Peru)andGuayaquil(Ecuador).

Thefollowingchapterpresentstheglobalresultsbycontinent.Wechosetoonlydisplaythetoptenpercontinent.Locationsshowninthischapterreappearalongwithcitiesnotrepresentedintheglobalrankings.

EarthquakeWindspeedRiverfloodStormsurgeTsunami

Peoplepotentiallyaffected(cumulativenumberinmn)

15


Two men stand among the debris from the March 2011 earthquake and tsunami in the Japanese city of Kesennuma. The magnitude 9.0 quake off the coast of Japan is considered the costliest natural disaster in history, causing an estimated USD 235 billion in total losses.


PartIII–Regionalfindings

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5.000 Manila (PHL) Tokyo-Yokohama (JPN)

Osaka-Kobe (JPN)Jakarta (IDN)

Kolkata (IND)

Yerevan (ARM)

Phnom Penh (KHM)

Fukuoka (JPN)

Shizuoka (JPN)

Shanghai (CHN)

Tainan-Kaohsiung (TWN)

Bangkok (THA)

Taichung (TWN) Taipei (TWN)

Pearl River Delta (CHN)

Nagoya (JPN)

Teheran (IRN)

Figure 9: Impact of all perils by metropolitan area – Top 10Thechartincludestheaggregatenumberofpeoplepotentiallyaffectedbyallrelevantperils(bubblesize)andglobalrankingsbythevalueofworkingdayslost,inabsoluteterms(x-axis)andinrelationtothecountry’snationaleconomy(y-axis).

AsiaandOceaniahostmanylarge,eco-nomicallyvibrantmetropolitanareas.Comparedtoallothercontinents,citiesinAsiaandOceaniastandoutasbeingmostexposedtonaturaldisasters.Manyofthemalsoappearinthetop10globalrankings.Ingeneral,Asia’smetropolitanareasarethreatenedbythewidestmixofallperilswithmanyofthemendangered

Table 6: Asia and Oceania at a glanceMetropolitanareasanalysed 334–totalpopulation 989.0mn–totalcombinedGDP USD12.6trnMostpeopleendangeredbysinglescenario

29.4mnearthquakeTokyo-Yokohama,17.7mnearthquakeJakarta,17.2mnwindPearlRiverDelta

Top3allperils:peoplepotentiallyaffected Tokyo-Yokohama,Manila,PearlRiverDeltaTop3allperils:absolutevalueofworkingdayslost(globalindex)

Tokyo-Yokohama(4.50),Osaka-Kobe(2.71),Nagoya(2.69)

Top3allperils:relativevalueofworkingdayslost(globalindexrelativetonationaleconomy)

Manila(1.95),Tokyo-Yokohama(1.29),Taipei(1.02)

AsiaandOceania

byallfiveperilsincludedinthisstudy.Therisksofearthquakes,typhoonsandriverfloodingdominateinthenorthernhemisphere.Thisisillustratedinthechartsbythelargebubblesizesandtheclustersintheupperright-handcorneraswellasthecolourscheme.

AustraliaandNewZealandarealsoexposedtonaturalcatastrophes,buttheyhavesmallercitiesandthereforedonotfeatureinthetoptenriskiestcities.

Othercountriesmayplayalesserroleintheworldeconomy,buttheireconomiesdependheavilyonahandfulofcitiesthatfunctionascentresofeconomicpro-duction.HerewefindmetropolitanareassuchasBishkek(Kyrgyzstan),Almaty(Kazakhstan)orYerevan(Armenia),wherealargerearthquakeorriverfloodcouldbedisastrousfortheentirecountry’seco-nomicproduction.


Peoplepotentiallyaffected(cumulativeinmn)

15


0.001

0.010

0.100

1.000

0.001 0.010 0.100 1.000 5.000



5.000

San Salvador (SLV)

Tegucigalpa (HDN)

Guadalajara (MEX)

Port-au-Prince (HTI)

Havana (CUB)

Managua (NIC)

Panama City (PAN)

Boston (USA)

Washington-Baltimore (USA)

San Francisco (USA)

Miami (USA)

New Orleans (USA)

Houston (USA)

Tampa (USA)

Guatemala (GTM)

Mexico City (MEX)

New York-Newark (USA)

Los Angeles (USA)

San Jose (CRI)

Santo Domingo (DOM)

Table 7: North and Central America at a glanceMetropolitanareasanalysed 83–totalpopulation 222.7mn–totalcombinedGDP USD10.5trnMostpeopleendangeredbysinglescenario

14.7mnearthquakeLosAngeles,6.1mnriverfloodMexicoCity,5.0mnearthquakeSanFranciso

Top3allperils:peoplepotentiallyaffected LosAngeles,MexicoCity,SanFrancisoTop3allperils:absolutevalueofworkingdayslost(globalindex)

LosAngeles(0.93),NewYork-Newark(0.62),SanFrancisco(0.47)

Top3allperils:relativevalueofworkingdayslost(globalindex)

SanJose(1.26),SantoDomingo(0.69),Port-au-Prince(0.49)

NorthandCentralAmericacomprisearegionthreatenedbyearthquakesalongthePacificcoastaswellasbyhurricanesandstormsurgesfromtheAtlantic.Riverfloodingcanhappenpracticallyany-where.AkeydifferencebetweenNorthandCentralAmerica,however,isintheirdistributionofeconomicproductionsites.

WhiletheeconomiesofthesmallercountriesofCentralAmericaarehighlydependentonjustafewmetropolitanareas,theUS,CanadaandMexicohave

moreurbancentres.ThedifferenceineconomicgeographyisreflectedonthechartbythefactthatNorthAmerica’scitiesarelocatedinthelowerright-handcornerwhileCentralAmericancitiesarefoundintheupperleft-handcorner.

Fromtheperspectiveofthenationaleconomy,theCentralAmericancapitalsofSanJose(CostaRica)andSantoDomingo(DominicanRepublic)rankhighest.Aca-tastropheineitherofthesetwolocationswouldheavilyaffecttheentirecountry.ThedeadlyearthquakethatravagedHaitiinJanuary2010isrememberedasoneoftheworstdisasterstohittheimpoverishedislandnation.ButitisworthnotingthatSantoDomingohasanevenhigherearth-quakeriskthanPort-au-Prince(Haiti).

IncontrasttoCentralAmerica,metropol-itanareasoftheUnitedStatesarenu-merousandhighlydeveloped.Theyarerankedhigherintermsoftheabsolutevalueofworkingdayslostwhencomparedtoallothercitiesintheworld.

Figure 10: Impact from all perils per metropolitan area – Top 10Thechartincludestheaggregatenumberofpeoplepotentiallyaffectedbyallrelevantperils(bubblesize)andglobalrankingsbythevalueofworkingdayslost,inabsoluteterms(x-axis)andinrelationtothecountry’snationaleconomy(y-axis).

NorthandCentralAmerica



15


ThevulnerabilityofEurope’scitiestonatu-raldisastersvariesfromregiontoregion.CountriesineasternandsouthernEuropefacerisksfromearthquakes.Windbe-comesmoreimportantasanaturalperilwhenmovingtowardscentralEurope,whilethehazardfromriverfloodingispre-sentalmosteverywhere.Metropolitanare-asofcentralEuropearenotwidelyspreadonthechart.However,althoughmanyeasternEuropeanmetropolitanareasstillhaveaGDPpercapitabelowtheEurope-anaverage,theycanbeevenmoreimpor-tantfortheircountry’snationaleconomy.

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1.000

0.001 0.010 0.100 1.000 5.000



5.000

Liverpool (GBR)

Budapest (HUN)

Zagreb (HRV)

Lille (FRA)

Hamburg (DEU)

Rhine-Ruhr (DEU)

Milan (ITA)

Berlin (DEU)

Frankfurt (DEU)

Sofia (BGR)

Istanbul (TUR)

Brussels-Antwerp (BEL)

Zurich (CHE)

Athens (GRC)

Dublin (IRL)

Amsterdam-Rotterdam (NLD)

Paris (FRA)

London (GBR)

Onelikelyscenariocouldbeastrongwin-terstormintheNorthSeathatpushesastormsurgetowardsAmsterdam-Rotter-damandcauseswindstormdamageatthesametime.WhilefloodprotectionmeasuresaregenerallywelldevelopedinEurope,mostdefencesaredesignedtoprotectagainstlocalriverfloodsexpectedonceevery50to100years.Asaresult,onlylargefloodeventsshouldtriggerma-jordamage,atleastifthedamsdonotfailatlowerwaterlevels.

Amajorwinterstorm,whichhasthelarg-estexpanseofallperilscoveredinthisstudy,orafloodcanaffectseveralcitiesheavily.ThisisparticularlytrueinEuropewherecitiesarelocatedclosertogetherthanelsewhere.ThishastobetakenintoaccountwhenEuropeiscomparedtootherregions.Istanbul,ahugeurbansprawlhighlyendangeredbyearthquakes,isalsocoveredintheregionaloverviewofAsia,butdoesnotfeatureinthetop10.

Table 8: Europe at a glanceMetropolitanareas 91(incl.Istanbul)–totalpopulation 206.4mn–totalcombinedGDP USD8.2trnMostpeopleendangeredbysinglescenario 6.4mnearthquakeIstanbul,2.7mnriverflood

Paris,2.2mnwinterstormLondonTop3allperils:peoplepotentiallyaffected Istanbul,Amsterdam-Rotterdam,LondonTop3allperils:absolutevalueofworkingdayslost(globalindex)

Amsterdam-Rotterdam(0.96),Paris(0.46),London(0.32)


Amsterdam-Rotterdam(1.31),Istanbul(0.27),Zagreb(0.26)


Europe



15


0.001

0.010

0.100

1.000

0.001 0.010 0.100 1.000 5.000



5.000

5

Valencia (VEN)

Valparaiso (CHL)

Quito (ECU)

Rio de Janeiro (BRA)Maracay (VEN)

Caracas (VEN)

Sao Paulo (BRA)

Buenos Aires (ARG)

Santiago (CHL)Bogota (COL)

Guayaquil (ECU)

Cali (COL)

Lima (PER)

SouthAmericafaceslittleriskofextendedandhighwindspeeds,apartfromafewexceptionsclosetotheCaribbeanandEastBraziliancoastline.Butotherhazardsareclearlypresent.Wecanseeearth-quakesincombinationwithsomeriverfloodinginthewest,whereaseasternmetropolitanareasofBrazilandArgentinafaceriverfloodasthedominantperil.Tsunamihazardsaccompanyseismicallyendangeredmetropolitanareasalongthewesterncoastlineattimes.

Table 9: South America at a glanceMetropolitanareas 49–totalpopulation 148.5mn–totalcombinedGDP USD2.1trnMostpeopleendangeredbysinglescenario 8.9mnearthquakeLima,5.3mnearthquake

Santiago,3.9mnearthquakeBogotaTop3allperils:peoplepotentiallyaffected Lima,Santiago,BogotaTop3allperils:absolutevalueofworkingdayslost(globalindex)

SaoPaulo(0.12),Lima(0.12),SantiagodeChile(0.07)


Guayaquil(1.20),Lima(0.90),SantiagodeChile(0.47)

Onaglobalscale,theeconomicproduc-tioninSouthAmericaisrelativelyevenlydistributedamongthecountriesranginginthemid-scale.Thisresultsinaverydenseclusterforthetop10ranks.

Adequatebuildingstandardstoimproveearthquakedamageresistanceaswellasfloodriskmapswithconsecutiveplanningmeasureswouldimprovetheresilienceofmanymetropolitanareasintheregion.

SouthAmerica




15


Africa’scitiesarealmostexclusivelythreatenedbyriverfloodingalone.Africaisrelativelysafewhenitcomestonaturalhazardsanalysedhere.TheonlyareasthreatenedbyearthquakesaresituatedalongtheMediterraneanSeaandalongtheAfricanriftsystem,fromCairodowntoTanzania.Tropicalcyclonesonlyposearisktocommunitiesalongthesoutheasterncoastline.

0.001

0.010

0.100

1.000

0.001 0.010 0.100 1.000 5.000



5.000

Durban (ZAF)

Kinshasa (COD)Algiers (DZA)

Antananarivo (MDG)Tripoli (LBY)

Nairobi (KEN)

Tunis (TUN)

Lusaka (ZMB)

Casablanca (MAR)

Lagos (NGA)

Cairo (EGY)

Ndjamena (TCL)

Khartoum (SDN)

Cape Town (ZAF)

Table 10: Africa at a glanceMetropolitanareas 60–totalpopulation 155.7mn–totalcombinedGDP USD0.7trnMostpeopleendangeredbysinglescenario 5.5mnriverfloodCairo,2.5mnriverflood

Khartoum,1.8mnriverfloodKinshasaTop3allperils:peoplepotentiallyaffected Cairo,Khartoum,KinshasaTop3allperils:absolutevalueofworkingdayslost(globalindex)

Cairo(0.05),Khartoum(0.02),Kinshasa(0.01)


Ndjamena(1.00),Khartoum(0.45),Cairo(0.30)

Onaglobalscale,theeconomicoutputofAfrica’scitiesiscomparativelylow.Thisisillustratedbythepositionsofthemetropolitanareasontheleft-handsideoffigure13.Ontheotherhand,theindividualimpactonacountrycanbeenormousinAfrica.

Forexample,amajorriverfloodinNdja-mena(Chad)orKhartoum(Sudan)wouldaffectvirtuallytheentirepopulationandsignificantlydisrupttheircountries’nationaleconomies.Inabsoluteterms,Cairo–whichfacesrisksfromearthquakesandriverfloods–rankshighestamongAfrica’scities,bothbyworkingdayslostandpeoplepotentiallyaffected.

Africa




15


Conclusion

Buildingcityresilienceiscritical

Millionsofpeopleliveintheworld’sbigmetropolitancentres,andtheyarebeingjoinedbymanymorepeoplewhoflocktothecitiesforeconomicpursuits.Amajornaturalcatastrophecancausetremen-doussufferinganddisruption.Thethreattocityresidentsandlocaleconomiesisreal,anditismountingrelentlesslyasmegacitiescontinuetoexpandandriskmanagementpracticesfailtokeepupwiththepaceofchange.

Asthefindingsofthisstudyshow,therearesubstantialdifferencesinriskexposureacrossregions.Asia’scitiesaremostatriskfromnaturalhazards,followedbycitiesinNorthAmerica.Theyalsoshow

Making cities more resilient

Risk transfer solutions – the example of Mexico’s MultiCatMexico’sMultiCatcatastrophebondprogramme,whichwasdesignedbytheWorldBankandtheMexicangovernmentwithsupportfromSwissRe,formsakeypartofMexico’ssovereigndisasterrisktransferstrategy.Theprogrammecombinesriskmitiga-tion,riskmodeling,andtraditionalandparametricinsurancetoallowthegovernmenttofinanciallypreparefordisasters.Itcoversearthquakeandhurricanerisk.

ThetransactionhighlightsSwissRe’slong-standingcommitmenttohelpingcountriesandlocalcommunitiesbuildresiliencethroughinnovativeinsur-ancesolutionsandthepublic-privatepartnershipmodel.SwissRewasthefirstglobalreinsurancecompanytodedicateateamofexpertstoworkwithnationalandmunicipalgovern-mentsontheirriskmanagement

needs.ThesuccessofMultiCathigh-lightsthegrowingdemandwithinthepublicsectorforthesesolutions.

Economics of Climate Adaptation – tackling climate risk locallyClimateadaptationisanurgentpriorityfornationalandcityauthorities.Whilemanyadaptationmeasuresareavailabletomakecitiesmoreresilienttotheimpactofclimatechange,decision-makersneedtoidentifythemostcost-effectiveinvestments.TheEconomicsofClimateAdaptation(ECA)method-ologygivesthemthefactstodosoinasystematicway.Ithelpsthemassessthelocalimpactofclimatechangeandtakeactionstominimisethatimpactatthelowestcosttosociety.Withitspartners,SwissRehascarriedoutECAstudiesinover20locations,includingseveralcities.Theyallpresentastrongcaseforimmediateaction:itischeapertostartadaptingnowthantobearthecostsoffuturedisasterstomorrow.Source:http://www.swissre.com/rethinking

thatmanyofthesmallerandoftenlesserknownmetropolitanareasdeservemoreofourattention.Notonlyarethesecen-tresdevelopingrapidly,butinourrankingstheyalreadyappearalongsidecitiestypicallymentionedasnaturalcatastrophehotspots,suchasTokyo,SanFrancisco,Miamior,morerecently,NewYork.

Savinglivesisandshouldbethehighestpriorityinriskmitigationefforts.However,higherlivingstandardsinmanycitiesmeanthatdemandforbetterprotectionmeas-uresisalsosettoincrease,especiallyintheworld’shighgrowthmarkets.Com-biningsuchmeasureswithinsurancecoversforresidualriskisthemostcost-effectiveandrecommendedapproach.


6SeeSwissRePrivateEquityPartners(2010):Anintroductiontoinfrastructureinvesting,SwissReCentreforGlobalDialogue(2012):IntegrativeRiskManagement:FosteringInfrastructureResilience.

7UNISDR(2013):MakingCitiesResilient:SummaryforPolicymakersAglobalsnapshotofhowlocalgovernmentsreducedisasterrisk.8OECD(2012):DisasterRiskAssessmentandRiskFinancing–AG20/OECDMethodologicalFramework.

Yetthemajorityofurbanassetsinhighgrowthmarketsiscurrentlynotinsured.Asaconsequence,insureddisasterloss-esintheUnitedStates,CanadaandEu-ropearestillsignificantlybigger.AsChinaandothereconomiescatchup,Asiaissettoemergeastheregionwiththehighesteconomiclosspotentialandthebiggestgapbetweeneconomicandinsuredloss-eswithinthenextdecades.

Investmentsininfrastructurearevitaltostrengthentheresilienceofmetropolitanareas.Thepotentialdamagethatalargenaturaldisastercancausetoroads,bridg-es,telecommunicationsandotheressen-tialinfrastructureisperhapsnowheremoreapparentthanintheworld’sbigcities.Thisiswhystrengtheningurbanresilienceisalsoaprimeconcernfortheinsuranceindustry.Asanultimaterisktaker,theinsuranceindustryhasavestedinterestinnewinfrastructureinvest-ments,upgradestoageinginfrastructureandadaptationmeasures.6

Investmentsininfrastructurewouldalsohelpcitiestocopebetterwithnaturaldisastersandothershockssuchashumanpandemicsandactsofterrorism.Asmanyoftheserisksarelikelytomaterial-iseinurbanlocations,buildingresilienceintheworld’scitiesisanurgentpriority.Butresourcelimitationsandbudgetcon-straintsmakethisachallengingtaskformayors,cityplannersandlocaldisaster

riskmanagers.Thisstudyaimstosupporttheirworkbyprovidingnewinsightsintothepotentialimpactofnaturaldisastersonurbancommunities.

Sincepeopleandeconomiesareinter-connected,comparisonsacrosscitiesandregionsarerelevanttocityauthorities.However,morespecificassessmentsoflocalconditionshavetobemadetogivethemanaccuratebasisfordecision-mak-ing.Initspublication‘MakingCitiesResil-ient,’theUnitedNationsOfficeforDisas-terRiskReduction(UNISDR)providesguidelinesandbestcaseexamplesforsuchplanning.7TheOECDalsoprovidesadetailedG20/OECDframeworkontheintegrationofriskfinanceandinsuranceintodisasterriskmanagement.8

Theimpactofalargenaturalcatastrophecanonlyeverbeavoidedtoacertainex-tent.Therewillalwaysbecostsforrelief,recoveryandreconstructionefforts,andtheywillconstituteafinancialburdenfortheaffectedregion.However,insurancecanhelpsoftentheimpactbyofferingrisktransferproductsthathelpnarrowthewidegapbetweeneconomicandinsuredlosses.

SwissReworkswithlocalandnationalgovernments,businessesandmanyotherstakeholderstostrengthenriskmanage-mentanddisasterpreparedness.Itdoessobyassessing,takingandsharingrisks,providingcapitaltotherealeconomyandpayingoutclaimswhendisastershap-pen.Furtherstrengtheningthesepartner-shipscangoalongwaytowardsmakingurbancommunitiesmoreresilientandsupportingthemtorecoverfasterwhendisasterstrikes.

Naturaldisasters,alongwithothershockssuchashumanpandemicsandactsofterrorism,arelikelytomaterialiseinurbanlocationsandaffectmillionsofresidents.Strengtheningtheresilienceoftheworld’scitiesisthereforeanurgentpriority.


Appendix

Tables 11–15: Top 10 ranks per peril for the three analyses: (1) people potentially affected; (2) value of working days lost, global index; (3) Value of working days lost, relativ to national economy, global index

Earthquake ranking (see figure 5)

Metroarea

Area(km2);population(mn)

Peoplepotentiallyaffected(mn)

Metroarea


Valueofworkingdayslost(globalindex0–1)

Metroarea


Valueofworkingdayslost,relativtonationaleconomy(globalin-dex0–1)

1 Tokyo-Yokohama(JPN)

1630037.1

29.4 Tokyo-Yokohama(JPN)

1630037.1

1.00 SanJose(CRI) 10002.2

1.00

2 Jakarta(IDN) 1160033.1

17.7 LosAngeles(USA) 1440015.4

0.79 Lima(PER) 26008.9

0.73

3 Manila(PHL) 290020.9

16.8 SanFrancisco(USA)

53005.0

0.40 Taipei(TWN) 21008.1

0.41

4 LosAngeles(USA) 1440015.4

14.7 Osaka-Kobe(JPN) 1360018.6

0.32 Bishkek(KGZ) 16001.0

0.36

5 Osaka-Kobe(JPN) 1360018.6

14.6 Nagoya(JPN) 1560011.6

0.24 Manila(PHL) 290020.9

0.36

6 Tehran(IRN) 1100015.1

13.6 Taipei(TWN) 21008.1

0.15 Yerevan(ARM) 18001.4

0.34

7 Nagoya(JPN) 1560011.6

9.4 Lima(PER) 26008.9

0.10 Almaty(KAZ) 22001.7

0.32

8 Lima(PER) 26008.9

8.9 Shizuoka(JPN) 21001.6

0.10 SantoDomingo(DOM)

8003.3

0.28

9 Taipei(TWN) 21008.1

8.0 Taichung(TWN) 57005.8

0.09 Santiago(CHL) 38006.2

0.26

10 Istanbul(TUR) 410011.5

6.4 Istanbul(TUR) 410011.5


0.24

Storm ranking (see figure 7)

Metroarea



Metroarea



Metroarea



1 PearlRiverDelta(CHN)

2060042.4


1630037.1

1.00 Manila(PHL) 290020.9

1.00


1630037.1


0.49 Taipei(TWN) 21008.1

0.46

3 Manila(PHL) 290020.9

12.6 PearlRiverDelta(CHN)

2060042.4

0.39 Tainan-Kaohsiung(TWN)

31005.1

0.38


7.8 Nagoya(JPN) 1560011.6

0.30 Port-au-Prince(HTI) 3002.0

0.38

5 Taipei(TWN) 21008.1

5.4 Taipei(TWN) 21008.1

0.18 Havana(CUB) 5002.0

0.34

6 Shantou(CHN) 520010.0

5.1 Manila(PHL) 290020.9

0.17 SantoDomingo(DOM)

8003.3

0.32

7 Nagoya(JPN) 1560011.6


31005.1


0.31

8 Mumbai(IND) 260020.6

4.3 Fukuoka(JPN) 29003.9


1630037.1

0.19

9 Chennai(IND) 16008.5


0.12 Busan(KOR) 25005.0

0.12

10 Tainan-Kaohsiung(TWN)

31005.1

4.0 Busan(KOR) 25005.0

0.11 Osaka-Kobe(JPN) 13600 0.10


River flood ranking (see figure 6)

Metroarea



Metroarea



Metroarea




2060042.4


1630037.1

1.00 Ndjamena(TCL) 8001.2

1.00

2 Shanghai(CHN) 800017.6

11.7 Nagoya(JPN) 1560011.6

0.64 PhnomPenh(KHM) 5001.6

0.81

3 Kolkata(IND) 320019.1


0.48 Bangkok(THL) 45009.5

0.80

4 Jakarta(IDN) 1060033.1

10.0 Paris(FRA) 1360011.2

0.42 Doha(QAT) 10001.4

0.52

5 Delhi(IND) 570021.9


2060042.4

0.40 Manila(PHL) 290020.9

0.46


1630037.1

8.9 Shanghai(CHN) 800017.6

0.28 Khartoum(SDN) 26005.6

0.45

7 Bangkok(THL) 35009.5

7.1 MexicoCity(MEX) 450019.6

0.20 Yerevan(ARM) 18001.4

0.43

8 MexicoCity(MEX) 450019.6


0.20 Baghdad(IRK) 45008.0

0.41

9 Cairo(EGY) 350017.7

5.5 Amsterdam-Rotterdam(NDL)

108005.4

0.20 Ulaanbaatar(MNG) 10000.9

0.35

10 Tianjin(CHN) 26005.8

5.5 Milan(ITA) 149007.3

0.20 Cairo(EGY) 350017.7

0.29

Storm surge ranking

Metroarea



Metroarea



Metroarea




2060042.4


2060042.4


108005.4

1.00



108005.4

0.73 HoChiMinh(VNM) 2’0009.1

0.32

3 Mumbai(IND) 260020.6

2.6Osaka-Kobe(JPN)

1350018.6


2060042.4

0.20


1630037.1


1630037.1


0.15

5 Amsterdam-Rotterdam(NDL)

108005.4

1.8Nagoya(JPN)

1560011.6


1630037.1

0.13

6 Nagoya(JPN) 1560011.6

1.7 NewYork-Newark(USA)

1190016.5

0.46 Manila(PHL) 290020.9

0.13

7 Shanghai(CHN) 800017.6

1.4 NewOrleans(USA) 27001.0

0.18 Nagoya(JPN) 1560011.6

0.11


1.4 Hamburg(DEU) 60002.3

0.09 Rangoon(MMR) 11004.2

0.10

9 HoChiMinh(VNM) 20009.1

1.3 Shanghai(CHN) 800017.6


0.09

10 NewYork-Newark(USA)

1190016.5

1.1 Fukuoka(JPN) 30003.9

0.06 Havana(CUB) 5002.0

0.08


Tsunami ranking

Metroarea



Metroarea



Metroarea




1630037.1

2.4 Nagoya(JPN) 1560011.6

1.00 Guayaquil(ECU) 9002.4

1.00

2 Nagoya(JPN) 1560011.6


1630037.1

0.88 Nagoya(JPN) 1560011.6

0.63




1630037.1

0.55

4 Shantou(CHN) 520010.0

0.7 Busan(KOR) 25005.0


0.43


0.6 Izmir(TUR) 14002.7

0.06 PanamaCity(PAN) 6001.1

0.33

6 Dhaka(BGD) 180012.9

0.4 Kagoshima(JPN) 5000.6

0.04 Izmir(TUR) 14002.7

0.28

7 Izmir(TUR) 14002.7

0.4 Shizuoka(JPN) 21001.6

0.04 Busan(KOR) 25005.0

0.21

8 Jiaojing(CHN) 27003.1

0.3 Shantou(CHN) 520010.0


31005.1

0.21

9 Guayaquil(ECU) 9002.4


31005.1

0.03 Jaffna(LKA) 8000.7

0.15

10 Chennai(IND) 16008.5

0.2 Istanbul(TUR) 410011.5

0.02 Dhaka(BGD) 180012.9

0.13

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