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Southwest Indian Ocean Risk Assessment and Financing Initiative

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(12016 The World BankThe International Bank for Reconstruction and DevelopmentTheWorld Bank Group1818 HStreet, NWWashington, D.C. 20433, USANovember 2016

Africa Disaster Risk Profiles are co-financed by the EU-funded ACP­EU NaturalDisaster Risk Reduction Program and the ACP-EUAfricaDisaster Risk Financing Program, managed by the Global Facilityfor Disaster Reductionand Recovery.

DISCLAIMERThis document is the product of work performed by GFDRR staff,based on information provided by GFDRR's partners. Thefindings ,analysis and conclusions expressed in this document do not nec­essarily reflect the views of any individual partner organizationof GFDRR, including, for example, the World Bank, the ExecutiveDirectorsof the World Bank, UNOP, the European Union, or thegovernments they represent. Although GFDRR makes reasonableefforts to ensure all the information presented in this documentis correct, its accuracy and integrity cannot be guaranteed. Useofany data or information from this document is at the user's ownrisk and under no circumstances shall GFDRR or any of its partnersbe liable for any loss, damage, liability or expense incurred orsuffered which is claimed to result from reliance on the data con­tained in this document. The World Bank does not guarantee theaccuracyof the data included in this work. The boundaries, colors,denomination, and other information shown in any map in thiswork do not imply any judgment on the part of TheWorld Bankconcerning the legal stat us of any territory or the endorsement oracceptance of such boundaries.

RIGHTS AND PERMISSIONSThe material in this work is subject to copyright. Because TheWorld Bank encourages dissemination of its knowledge. thiswork may be reproduced, in whole or in part, for noncommercialpurposes as long as full attribution to this workis given. Anyqueries on rights and licenses. including subsidiary rights. shouldbe addressed to the Office of the Publisher, TheWorld Bank, 1818HStreet NW, Washi ngton, DC20433, USA; fax: 202-522-2422;e-mail: pubrights@worldbank.org.

The SWIO RAFI Project

The Sout hwest Indian Ocean Risk Assessmentand Financing Init iative (SWIG RAFI)seeks to provide a solid bas is for the futu re

imp lemen ta tion ofdisaster risk financi ng th rou ghthe improved unders tanding of disaster risksto participa ting isla nd nations. This initia tive isin pa rtne rsh ip wi th th e Ministries of Finan ce,National Disaster Risk Management Offices andInsurance secto r representatives from The Comoros,Madagasca r, Mauritius, Seyche lles, and Zanzibar, andcarr ied out in coordina tion with the Indian OceanCommissio n (lOC) ISLANDS Project. the UnitedNations Office for Disaster Risk Reduction (UNISDR),and the French Development Agency (AFD). TheSWID RA FI supports the ISLANDS project's Islan dsFina ncial Protection Program (IFPP), which is alsosupported by the European Union (EU), UN ISDR,andAFD. Africa Disaster Risk Profiles are co-financedby the Elf-funded ACP-EU Natural Disaster RiskReduction Program and the ACP-EU Africa DisasterRisk Financing Program, managed by the GlobalFacility for Disaster Reduction and Recovery.

SWIO RA FI complemented the ongoing wo rk ofthe IOCto reduce vulnerability to natural disastersin accordance wi th the Mauriti us Stra tegy for theFurther Implementation of the Progra m of Actionfor th e Susta ina ble Development of Small Is landDeveloping States (SIDS) 2005-2015. More broadly,this init iative offers support to lon g-term, coreeconomic, and socia l developmen t objectives.

The risk mo deling under taken through SWIO RAFIfocused on th ree perils: t ropical cyclones, floodsprod uced by eve nts other than tropical cyclones, andearthquakes. Three hazards associated with tropicalcyclones, wind, flooding and storm surge wereconsidered in the risk assessment. In addition, aspart of the earthquake risk assessment, tsunami riskzones were identified for each country.

DISASTER RISK PROFILE I INTROOU CTION

The SWIO RAFI included the collection of existinghazard and exposure data, and the creation of newhazard and exposure data, that were used in thedeve lopmen t ofa risk assessment and risk profilesfor The Comoros, Madagascar, Mauritius, Seychelles,and Zanziba r.

The exposure data includes deta iled informati onon build ing cons truction for a var iety of occupancyclasses including: resid enti al; commercial;indu strial; public facilities such as educationalfacilit ies and emergency facilit ies; and infrast ructuresuch as roads, airports, ports, and utilities. Finally,risk information that is determi ned through acombi nati on of data on hazard, exposure, andvu lnera bility is provided at the nat ional level andat several administration levels for each peril andfor all pe rils combined, and broke n down int ooccupancy classes.

In add ition to the information provided in the riskprofiles, the hazard and exposure data and theresults of the risk analysis will be collated and storedon ope n data geospatial risk information platforms,or GeoNodes, in each country and will be availableto a wide ra nge of end-users. The results will beava ilable in the form of geospati al files. text files,and de ta iled fina l rep orts and can be used for sectorspeci fic development pla nning and im plementation.

1

-

on Mauritius's Main Isla nd, whichexperiences nea rly 90 pe rcent of theaverage annual losses from the threeperils combined, with the remaininglosses occurring on Rodrigues. In additionto the direct losses, an annual averageof nearly $26 million is estimated foremergency costs .

I

The 2S0-yea r re turn period loss from all perils cou ld benearly $3.6 billion, or over 30% of Mauritius's 2015 GOP.

The 1DO-year return peri od loss from all perils is over $1.9billion, or over 16% of Mauritius's 2015 GOP.

The average ann ual di rect losse s from earth quakes, floods,and tropical cyclones are over $110 million .

In thi s analysis th e residential sectorexperiences over SOpercent of th ecombined losses, the comme rcial sectorover 25 percent, and industry over 10percent. The high est loss t.~a~k,~,~p~l~a~"o... _

This analysis suggests th at:

Tropical cyclones are by fa r the mo stsignificant risk in the study, causingapproxtmate jy80 percent oftheaverage lo ss pe r year fro m all th reeperils. Flooding is the next la rges t r isk ,accounting for nearly 20 percent.

Key Facts

0%2345

Average Annual Loss (%)

••T

his anal ysis suggests that, onavera ge, Mauritius experi enc esover US$110 million in combined

direct losses from earthquakes. floods.and tropical cyclones each yea r.However,a specific event such as a severe tropicalcyclone can produce si gnificantly largerlosses. For example. resul ts suggest thata tun-year return period tropical cycloneevent could produce direct losses of $1.9billion and require approximately $430million in emergency costs. ~

Direct losses from All PerilsI

Direcllosses by Hazard

Average Annual Loss (%)

o 0 .090.180.270.36%

Earthquake-----

RP250RP10

Tropical cyclone

AAL

'9Flood

..•

RP10AALRP250RPIOO

No direct losse s from earthquakes

Ml

$3.68$1.8 B

$900 M

$450 M

2 DISASTER RISK PROFILE I RISK SUMMARY

Average Annual Loss roo-veer Return Period Loss

Peril TotalOirect Emergency TotalOirect EmergencyLosses Costs Losses Costs

Earthquakes $54,000 $8,700 \ 0 \ 0

Floods $22 million $5.2 million $150 million $34 million

Tropical Cyclones $91 million $21 million $1.9 billion $430 million

The populati on of Maur itius in 20 15was approximately 1.3 million.The mos t populous regions are Por t

Louis and Plaines Wilhems on the MainIsland. Nearly 70 percent of Mauritius'spopulation lives in metropolitan orurban areas (that is, areas with morethan 2,000 people per square kilometer)and slightly more than 25 percent inrural areas (fewer than 1,600 people persquare kilometer) . In 20 15, Mauritius'sgross domestic p roduct (GOP) wasapproximately $11.5 billion ($24.3billion in purchasing power panty), andthe per-capita GOP $9,6 10.

For 20 15, the es timated totalrep lacement value for all residential,

commercial, industrial, and publicbuild ings and other infrast ru cture isestimated to be nearly $33. 5 billion. Thela rgest concentration of rep laceme ntva lue is in the Pla ines Wilhems region.

To assess r isk be tter, replacement valuesand loss are often categorized accordingto occupancy and con struction types. Interms of occupancy type, the residenti a l

sector accounts for nearly 40 percent ofthe total rep laceme nt value. In termsof construction type, build ings withm asonry and concrete wall constructionaccount for the nearly 8 0 p ercent of thetotal rep laceme nt va lue .

_ Direct Losses by Building Type for All Perils

Residential

Average Annual Loss (%)

Com mercial/Industrial

Average Annual Loss (%)

•

_ 0 .8%

_ 0 .6

0 .40 .2

o

Infrastructure

Average Annual Loss (%)

. 0 .8%__ 0 .6

0 .40 .2

o

•

_ 0 .8%

_ 0 .6

0 .40 .2

o

Public*

Average Annual Loss (%)

•

0 .8%_ 0 .6

0 .40 .2

o

DISASTER RISK PROFILE I RIS K SUIollol ARY

-toucanon. Heetthcare. Religion, Emergency

3

Tro pical cyclones a re commo n inthe Southwest Ind ian Ocean region,and Maurit ius experiences their

effects almost yearly, alt houg h directhits are less freq uent. The wind. rain,and storm surge associated with tropicalcyclones all contr ibute to losses. Tropicalcyclone season run s from November 1th rough May 15, al though storms canoccur outside th is time frame.

A recent exam ple of a tropical cycloneaffecting Mauritius is Fantala. in April2016. All residents ofthe South Islandof Agalega, one of the Outer Islands ofMauri t ius, were forced to evacuate to theNorth Island.'

This analysis suggests that. on average.Mauritius will experience around $91million in d irect losses a nnuallyfrom wi nds, flooding. and sto rm surgeass octared with tropical cyclones. This is80 percent of the country's to tal an nualdirect losses from earthquakes, flood s,and tro pical cyclones . The res ults suggestthat SOpercent of th e loss fro m tropicalcyclones originate s from th e reside ntialsector an d nea rly 30 percent from thecomm erdal sector. Losse s to indu strycontribu te approximately 12 pe rce ntto th e total of direct losses. Annualemerge ncy costs for tropi cal cyclonesare estimated at near ly $2 1 mill ion . onavera ge.I Modeled Direct Losses

Tropical cyclones generate wind , flood,and storm surge hazards. On averagein this analysis. winds cause over 80percent of the lo ss from the threehazards, while st orm su rge and floodingeach produce around 10 pe rce nt of theremaining damage.

Return Period Total Modeled LossesAA.l I $90 million

RPm . $100 millionRP100 $2billionRP250 $3.6 billion

AYerageAnnual Losses ($) Exposure ($)

.10M . 0 .665-10,", 0 0 3.5-66

<5,", 0 0 <3.56

Public

Residential

Infrastructure

Ayerage Annual Loss

AAL _ $45 millionRPI0:- $SS million

RP 100:::::::::::';$~9~O~o~m:;::::llionRP250' $1.5 billion

j ..AAl - $2S million

Commerciall RPI0 ,~ $2S million

___ ~ ~ _. __ ~~~-~~~~:~ -- - - - - - -;:~~~i:'.:.:..::::::~ $~5~O~o~m:iil~i~~iIl iOnAAl _ $4.Smillion

RPI0 - $SmillionRP100 ' $90 millionRP2S0 ' $200 million

1AAl - $S.5 million

RPI0 - $4 millionRPl00 $100 millionRP2S0 $250 million

I

4

Key FactsThis analysis suggests th at:

• The average annual direct loss fromtrop ical cyclones is $91million.

• Plaines Wilhems has the greatest riskof direct loss fro m tropical cycloneswith a n ave rage annual lossof$ 16million.

The tnu-year direct loss to Mauriti usfrom tropical cyclones could be $1.9billion.

DISAS TER RISK PR OFILE I TROPICAl CYClONE

Tropical cyclones generate wind,flood. a nd stor m surge hazards.

Th is analys is suggests thatRodrigues Island te nds to be most likelyto expe rie nce the strongest winds anddeepest storm surge. On RodriguesIsland a t un-year event can generatewi nds exceed ing 200 kph and. on thesouthern side of the isla nd. stor m surgeof nea rly 2m. In contrast. flooding fromtro pical cyclones is greater on the mainisland, Mauritius.

Tropical cyclone hazardsWmdspeed~ exceedmg6Jkph. storm surge inundation exc~ing 1m,and /looding exceeding lCkm

r.

-

Wind Intensity

Residen tial Commercial/Industrial Public Infrastructure

•.a•>..• 'Q ;/" ' ]

~

DISASTER RISK PROFI LE I TROPICAL CYClONE 5

Plaines Wilhems also has the greatesttotal rep lacement value for exposedassets ($8.8 billion).

AverageAnnual Losses ($) Exposure ($)

,3 · . 0,"t .5 - 3M 0 0 3.5- 6 6

<t.5 M0 0 <3.56

Return Period Total Modeled LossesAAt. . $20 million

RPIO _ $60 millionRP100 $150 millionRP250 $180 million

o

o

•

o

•I,

o

Significant flood losses can occurfrequently. For Mauritius as a wh ole,direct losses from a l O-ye a r returnperiod flood are estimated to be $63million, and direct losses from the -.100­year flood event are estimated to h e$150 mill ion.

This analysis suggests that , on average.Mauritius will experience around $22mill ion each year in dire ct lossesfrom flood ing. amounting to nearly 20percent of the country's tota l ann ualdir ect losses from earthquakes. flood s,and tropical cyclones .

It is es timated th at nearly 60 percentof the direct losses from flood ing arefrom th e residential sector and 20percent from the commercial sector.Losses to indu stry an d public assetscontribute ap proxi mately 10 perce ntand 7 percent, res pectively. to the total.Annua l emergency co sts for floodsare es timated at ove r $5.2 million , onaverage.

These re sul ts sugges t tha t the m ainIsland of Mauritiu s has the greatestrisk for flood loss, expe riencing 98% ofMaurit ius 's average loss per year fromnon-tropical cyclone flooding events.On the main island, the regi on with thehighest r isk is Plaines Wllh ems withaverage annual losses of $4 ,9 mlllion.

Floa d ing in Mauri t ius mainly resultsfrom pe riods of Intense ra infall.One of the most sig nificant flood

events for th e country occurred in Ma rch20 13, wh en more tha n 150 m ill imetersof rai n fell in less than two hours. Theflooding caused 11 fatalities.

I Modeled Direct Losses

Average Annual Loss

RP100RP250

jAAt - $4.5 million

RPI0 $12.5 millionRP100 $30 millionRP250 $35 million

i-AAt_ $IS million

RPtO $5 millklnRP100 ' ItOmillionRP250 $1S million

1·AAt- $650,000

RPtO- $2.5 millionRPl00 $7.Smillion

Residential

Commercial/Indust rial

Public

Infrastructure

Ml,RPI0,

$15million$35million

$85 million$100 million

Key FactsThis anal ysis suggests th at:

• The average annual d irect loss fromflooding is $22 million.

• Plaines Wilhems, Pamplemousses,and Port Louis account for 58% of theaverage annual d irect losses.

The tnu-year direct loss to Mauritiusfrom flooding is $150 million.

RP250 $9 millionI

6 DISASTER RISK PROFILE I FLOOD

Flood extentlOO-yroT RPdo/a using 11lOCm thrtshold

In this analysis. the a nnua l averagerainfall from non-trop ical cycloneevents is 577 mm with a minimum of

209 mm and a maximum of 1.078 mm.

Modeled flood depths are highest inPamplemousses. Port Louis and GrandPort and can exceed 1m based on thisanalys is. On Rodrigues Island. modeledflood depths are less than 0.5 m except forreturn periods greater than 100 years.

Ii.

- ....-:-. •• I~....

•Residen tial Commercial/Industrial Public Infrastructure

•.a•>..• 'Q ;/" ' ]

~

;Q

'/\~

DISASTER RISK PROFI LE I FL OOD 7

Eart hquakes are common in theSouthwest Indian Ocean reg ion,but the ma jor seismic sources in

the region are far from Ma uritius . Thetwo majo r sources of seismic activityare the Mid-India n Ridge in the Ind ianOcean and the East-African Rift system.Earthquakes in these regions are frequentbut usually oflaw to moderate magnitude.Consequently, Mauritius has no hi storyof economic losses or casualties fromearthquakes.

Significant losses from earthquakesare expected to occur infr eq uently. Forexample, this analysis suggests that directlosses are not expected for earthquakeswith a SaO-year return period.

Average an nual losses from earthquakesin Mauritius are driven by extremely rareearthquakes with return periods greaterthan once every 500 years.

I Modeled Direct Losses

Return PeriodAAl

RPIO $0RPIOO $0RP250 So

Total Modeled Lones~54.000

AverageAnnual Lones ($) Exposure ($)

.20K . 0 >68

9.S-20K 0 0 3.5-68

<9.SK 0 0 <H8

Public

Residential

Infrastructure

Average Annual Loss

AAl

RP10 1 ~O

:;~~~ l :~.................... [.

AAl:..- - - - - - - - - $15,000Commercial/ RPI01~OIndustrial RPlool so

RP2S01 so... . . . . . . . . . . . . . . . . . . . . . . . . j:.,........

AAL $2,000RPIO I so

RPlOOI soRP2S01so

1,_·__

AAL - ~4,OOO

RPIO' soRPl00 ' soRP2S0' se

I

8

$30,000

DISASTER RISK PROFILE I EARTHQUAKE

This analys is sugges ts thatea rth qua ke ha za rd Is minimalthrou ghout Mauritiu s. and is

consis tent wit h the lack of any reportedhistorical da mage . Fort una tely, modelres ults suggest only a rem ote poss ibilityof an ea rthq uake that would prod ucesignificant damage to structures.

Tsu namis us ually result from high­magni tude. subd ucuon-aone earthquakes.The Sout hwest India n Ocean region doesnot experience many high -magnitu deearthquakes. nor does it contain majorsubduction zones . The entire region is a trisk, however.of tsunamis generated bysubduct ion zones elsewhere in the Ind ianOcean.

A recent tsunami event that affected th eSouthwest Indian Ocean reg ion was the2004 India n Ocean ts u na mi. Mau rit iusexpe rienced only m inor inundatio n, withgreater impacts on Rod rigues.

Tsunami zone and earthquake hazardGround mol/Of! from a l 50 ·yeor RP eorlhquuke andtsunomu,sk/Ones

c,

• EarthquakeHazardfof 2SQRP

Residen tial Commercial/I ndust rial Public Infrast ructure

;/" ,]~

No losseson RP250

.Q

No losseson RP250

..•

•

No losses on RP250

• .Q • ;~.. ;Q

~~, ,6\ "

~~ j

, , ,~ , .~ > ~<c

No losseson RP250

I

•.a•>

DI5A5TER RI 5K PROFI LE I EARTHQUAKE 9

These risk profiles have been developed from a multi­hazard risk ass ess ment using a variety of exposure dataand vulnerability funct ions. Modeled perils includeearthquake, flood , and tropical cyclone. The results forindividual and agg regated pe rils ar e available in severalformats, includin g geos patial data and text files. The riskprofil e results are presented in terms of average lossper year and for select ed retu rn pe riods. For details onthe development of the risk pro files, see th e final report"Southwest Indian Ocean Risk Assess me nt FinancingInitiative (SWIO RAFI): Compon ent 4 - Risk Proffles'; Briefexplanatio ns of the exposure and hazard data and th evuln erability functions are given below.

HazardThis stu dy encompasses three pe rils: earthquake, flood,and tropical cyclone. One or more hazards are ass ociatedwith each peri l. For example, the hazards associated withtropical cyclones indude strong wind s. storm surge, andflood ing. A cata log representing 10.000 years of simulatedevents was constructed using empirical and theoreticalprinciples and information derived from hist oricalobservations. A varie ty of sta tistical characteris ticsderived from the even ts in the cata logs are consistent withthe histori cal record for ea ch peril. The cata log (which isproprietary) includes inform ati on such as the intensity­for exampl e, central pre ssure for a tropical cyclone an dmom ent magnitude for an eart hquake- and location ofeach peril event. This information is then coup led wit hperil-specific empirical and theoretical considerationsto describe the spatial distribution of hazard intensityfor each simulated peril even t in the cata log. at a gridspacing of abo ut one kilome ter. The information is used todetermine the hazard Inten si ties expected at each returnperiod.

EARTHQUAKE

This analysis suggests tha t there is a low likelihood ofearthquakes in the SWIDregion. The catalog ofsyntheticearthquake events is devel oped using characteristicsbased on th e historical record of 1.228 earthquakes wit hmoment magnitudes 5.0 or greater that occurred in theSWIObasin between 1901 and 2014 and the slip rates andgeometries of known fault s in the region. Ground motionpr ediction equations are used to determine the spatialdistribution of ground moti on (su ch as peak groundacceleration. or PGA)produced by ea ch earthquake event.

FLOOD

The ris k assessme nt indicates th at flood s from rainfall notassociated with tropi cal cyclones are a significant hazard

10

in th e SWIO region, particu larly for the areas close r tothe equator. Flood hazard sta tis tics in this analysis ar eult imately based on satellite-derived ra infall estimatesfrom the years 1998-2013. The satellite-derived data areused with a ra infall model to develop a cata log of da ilyrainfall produced by events other than tropical cyclones.A flood model then dynamically distributes the rainfallthroughout the affected region and calculates flood depths.

TROPICAL CYClONE

This analysis suggest that the most costly catastrophichazard in th e SWIObasin is tropical cyclone. The historicalrecord of tropical cyclones in the region includes 847events that took place between the 1950 and 2014.The event catalog is developed using characteristics ofthe historical catalog. such as annual tropical cyclonefrequency, landfall frequency, seasonality. genesis location,forward speed, central pressure. and radius of maximumwinds. Three tropical cyclone hazards are considered:wind, flooding from rainfall. and storm surge.

Tropical cyclone wind speeds are calculated using anequation that includes parameters such as the differencebetween the tropical cyclon e's central pressure and thesurrounding environment, a storm's forward motion andits asymmetry, and account for surface features such asland use .

Rainfall produced by modeled tropical cyclones iscalibrated using satellite-derived rainfall estimates an dused as a boundary condition to force a flood model thataccounts for factors such as hou rly rainfa ll. elevation. andsoils.

Stonn surge is derived from a variety of tro pical cyclonecharacteristics that include central pressure. forwardmotion of the storm , maxim um wind speed, and radius ofmaximum winds. For a tropical cyclone in the Southe rnHemisphere, the highes t storm surge generally occursnear th e radius of maximum winds on the left side of the

storm track.

ExposureThe methodol ogy used to develop the exposure datais illustrated in figure At. The exact process varies bycountry because of differences in available da ta. Theexposure database for each island nation is constructedfrom various data sources. including governmentcensuses, local agencie s. satellite imagery. publiclyavailable spatial sta tist ics. and previous regionalinvestigations . The end result is datasets that representthe built environment of each island nation and includenationally appropriate replacement values (that is. theestimated cost to rebuild a structure as new). constructioncharacteristics, and occupancy classes.

DISASTER RISK PROFILE I METHODOLOGY

The exposure data are divided into eighteen differentoccupancy classes spanning different types of residential,commercial, industrial. public facility, and infrastructureassets. The residential occupancy class includes single andmultifamily residences. The commercial class includesgeneral commercial buildings and accommodation. Theexposure groups in the publi c occupancy class are healthcare services. religion, emergency services, primaryeducational, university educational. and general publicfacilities . The infrastructure occupancy classes are road/highway, bus/rail , airport. maritime port, electrical utility,and water utility. An ' unknown" occupancy class is alsoassigned.

In addition to their categorization by occupancy class,the exposure data are categorized according to thirteenconstruction classes. Seven of these are specific toinfrastructure occupancies and include structures suchas roads, railroads, and bridges. Five represent commonconstruction classes, such as single-story traditionalbamboo and earthen buildings and single and multistorytraditional wood, wood frame, masonry/concrete,and steel frame buildings. As with occupancy class, an"unknown" construction class is assigned.

The exposure data for residential, commercial, and generalindustrial assets are provided on a grid of 30 arc-seconds(approximately one kilometer). when high-resolutiongovernment and infrastructure data are available,these assets are captured at their individual exposurelocat ions. When location- level information is not available,government and infrastructure assets are distributed tothe one-ki lometer grid.

VulnerabilityVulnerability functions appropriate to the constructionand occupancy classes most commonly found in theSWIO region are used to estimate loss from a hazard. Thefunctions calculate the average level of damage to thestructures using the hazard intensity and informationon their occupancy and construction. The damage levelrepresents the fraction of the total building replacementvalue that has been damaged Vulnerability functionsused in this study have been developed specifically for theSWIOregion based on research on local building practices,applicable building codes, engineering analysis, historicaldamage reports, and expert judgment.

Vulnerability functions for earthquake ground shaking.non-tropical cyclone flooding. tropical cyclone flooding.and tropical cyclone storm surge are assumed to beuniform throughout the SWIO region for all occupanciesother than infrastructure. Except for infrastructure, thetropical cyclone wind damage functions for Mauritiusand Seychelles are modified to be less vulnerable thanthe SWIObase functions used for the other island nationsbecause of their history of more stringent constructionpractices relative to the other three nations. Alldamagefunctions for infrastructure occupancy classes areassumed to be uniform for all perils throughout the SWIOregion.

- All dollar amounrs ore US. dollors unless otherwiseindicated.

Grldded population(3Darc-second)

...Spanal costadjustment

..

..

..

Averagenumber ofbuildings per person

Exposure database ofbUildings

..

Percentage ofbuildings by

occupancy type

...Average building

floor area byoccupancy type

Figurt Al. S<htmOtic diagram illlIStratingtnt methodologyustd to dtw/op tht SWID-RAf/ exposurtdata

DISASTER RISK PROFILE I METHODOLOGY 11

Average Annual LossThe modeled average ann ual loss (AAL) is equ alto the total of all impacts produ ced by a hazard(e.g. earthq uake) in a specified time period (e.g.10,000 years) divided by the number of yea rs in th atspecified tim e period (e.g. 10,000 years).

Building Construction ClassBuilding Construction Class is used to classify anasset's construction, wh ich determines an ass et'svu lnerability to a certain hazard. contributing toa risk estimate . For example. a traditiona l woodbuilding is more vulnerable (le.likely to be damagedor dest royed) by a tropical cyclone than a buildingmade of steel-re inforced concrete. Th us an area withtra ditio nal wood bu ildings is likely to experiencemore damage and larger losses fro m a trop icalcyclone th an an area with steel-re info rced concretebuildings. Building Const ruction Class is on e of thefactors used to determ ine vu lne rability (see below) .

Building TypeBuilding Type, or Occupancy Class , specifies theusage of a given building. which cont r ibutes to abuilding's vuln erability.The bu ildin g types usedin these profi les are: resi dent ia l, commercial,industrial, infrastructu re, and public.

Each building type has subty pes:

• Residential : single, mul ti-family (e.g. apartment)

• Commercial: accommodation [e.g. hotel) .comme rcial (e.g. shop)

• Indust r ial: general industrial (e.g. factory)

• Infra st ructure: bus terminals, ra il termina ls,a irports, maritime ports, utilities, roads,highways

• Public: healt bcare, educati on, religious,emergency services, general public facilities

Building Type is one o f th e facto rs used to determinevulnerability (see below) .

Exposure I Exposed AssetsExposure refers to ass ets such as bu ildings, criticalfacilities and t ransport a tion ne tworks, which couldbe damaged by a hazard. A variety ofattributesassociated with the exposure, such as locationand occupancy and structural characteris tics , helpdetermine the vu lnerabi lity of the exposure to ahazard .

12

HazardHazard refers to the damaging forces produced by aperil, such as inun dat ion associated with flood ing. orwin ds produced by a trop ical cyclone. A single perilca n have multiple hazards associated with it. Thoseassociated with a tropical cyclone, for example,include strong winds, sto rm surge and flooding.

ImpactImpact refers to th e consequences of a hazardaffecting th e exposure, give n the exposure'svulnerability. The impact on st ructu res is usuallyqua ntified in te rms of di rect monetary loss.

Replacement ValueReplacement value re fers to the estimated amount itwo uld cos t to replace physical assets.

Return Period (RP)Th rou ghout th is profile to-year (RP10), 100-yea r (RP100), and 2S0-yea r (RP2S0) events arereferenced. These eve nts have intensi t ies that (onaverage) are expected to occur once du ri ng a "returnperiod'; A re turn period is based on the probabilitythat an event could happen in a given year. Thelarger the return per iod for an event, the less likelyits occurrence, and the greater its intensity. Theprobability of an eve nt occurring in any given yeareq uals 1 divided by th e number of years named inthe "x-year event'; e.g. for a 10-yea revent (an even twit h a t u-year return period), the p robabili ty is1/1 0 or 10%; for a 100-year eve nt, the proba bility is1/1 00 0r1 %.

RiskRisk is a combination of hazard, exposure. andvu lnerability. It is qu an tified in probabilistic terms(for example, average a nnua l loss) using the impactsof all events produced by models.

VulnerabilityVulnerability accounts for the susceptibility of theexposure to th e forces associated with a hazard.Vulnerability accounts for factors such as thematerials used to build the asset (as specified by theBuilding Construct ion Class) and the asset's use (asspeci fied by th e Building Typ e).

DISASTER RISK PROFILE I GLOSSARY

1 Vel Moonien, ~Agalega; I'lle du Sud evacuee en previsiondu cyclone Fanrala," La Defi Media Group (audio), April 16,2016, http:/ /defirnediainfo/agalega-Iile-du-sud-evacuee­en-prevision-du-cyd one· fantala.

DISASTER RISK PROFILE I AC ltNOWUO GMENT5

ACKNOWlEDGNENTSThese risk profiles were prepared by a team comprising AlannaSimpson, Emma Phillips, Simone Balog, Richard Murnane, VivienDeparday, Stuart fraser, Brenden jcngman. and Lisa FerraroParmelee. The core teem wishes to acknowledge those that wereinvolved in the production of these risk profiles. First, we wouldlike to thank the financial support from the European Union (EU)in the framework of the African, Caribbean and Pacific (ACP)-EUAfrica Disaster Risk financing Initiative, managed by GFDRR.In the GfDRR secretariat we would like to particularly thankfrancis Ghesquiere, Vivien Deparday, Isabelle Forge, RossellaDella Monica, and Hugo Wesley. We would also like to extend ourappreciation to the World Bank Africa Disaster Risk ManagementTeam: Christoph Pusch and Doekle Wielinga. Thank you 10theDisaster Risk Financing and Insurance Team: Julie Dana, SamanthaCook, Barry Maher, Richard Poulter. Benedikt Signer, and EmilyWhite. Our thanks to AIR Worldwide for their risk assessmentanalysis. finally, we are grateful to Axis Maps and Dave Heymanfor creating the data visualizations and these well-designedprofiles .

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