R O M A N I A

U K R A I N E

Balti

Cahul

Chisinau

Dubasari

Edinet

Gagauzia

Lapusna

Orhei

Soroca

Tighina

Ungheni

Chisinau

B L A C K S E A

0.150.28

0.420.74

0.722.2

GDP (billions of $)

FLOOD

EARTHQUAKE

3

1

Negligible

Annual Average of Affected GDP (%)

There is a high correlation(r=0.95) between the

population and GDP of a province.

TOP AFFECTED PROVINCES

FLOOD EARTHQUAKEANNUAL AVERAGE OF AFFECTED GDP (%)

ANNUAL AVERAGE OF AFFECTED GDP (%)

DubasariSorocaEdinetTighinaBaltiChisinauOrheiCahulUngheniLapusna

3332222100

CahulGagauziaLapusnaUngheniChisinauBaltiTighinaDubasariOrheiSoroca

2111000000

Moldova’s population and econ-omy are exposed to earth-quakes and floods, with floods

posing the greater risk. The model results for present-day risk shown in this risk profile are based on population and gross domestic product (GDP) esti-mates for 2015. The estimated damage caused by historical events is inflated to 2015 US dollars.

Just over half of Moldova’s popula-tion lives in rural environments. The country’s GDP was approximately US$6.3 billion in 2015, with over 60 percent derived from services, and with industry and agriculture generating the

MoldovaEUROPE AND CENTRAL ASIA (ECA) RISK PROFILES

GDP $6.3 billion*

Population 3.6 million*

AFFECTED BY 100-YEAR FLOOD

AFFECTED BY 250-YEAR EARTHQUAKE

CAPITAL LOSS FROM 250-YEAR EARTHQUAKE

$500 million (7%)

300,000 (7%)

$4 billion (62%)

2 million (59%)

$4 billion (59%)

200 (<1%)

*2015 estimates

remainder. Moldova’s per capita GDP was $1,760.

This map displays GDP by province in Moldova, with greater color satura-tion indicating greater GDP within a province. The blue circles indicate the risk of experiencing floods and the orange circles the risk of earth-quakes in terms of normalized annual average of affected GDP. The largest circles represent the greatest normal-ized risk. The risk is estimated using flood and earthquake risk models.

The table displays the provinces at greatest normalized risk for each per-il. In relative terms, as shown in the table, the province at greatest risk of floods is Dubasari, and the one at greatest risk of earthquakes is Cahul. In absolute terms, the province at greatest risk of floods and earth-quakes is Chisinau.

77

R O M A N I A

U K R A I N E

Balti

Cahul

Chisinau

Dubasari

Edinet

Gagauzia

Lapusna

Orhei

Soroca

Tighina

Ungheni

Chisinau

B L A C K S E A

R O M A N I A

U K R A I N E

Balti

Cahul

Chisinau

Dubasari

Edinet

Gagauzia

Lapusna

Orhei

Soroca

Tighina

Ungheni

Chisinau

B L A C K S E A

The worst flood in Moldova since the country gained its in-dependence in 1991 occurred

in 1994. It killed close to 50 people and caused almost $500 million in damage. In 1997, 28 of Moldova’s 40 provinces experienced floods, causing nine deaths and about $70 million in damage. Further flooding occurred in 1999, 2002, and 2005 with smaller impacts, ranging from $1 million to nearly $10 million in damage. This record highlights Mol-dova’s vulnerability to floods. While not always devastating, they have a relatively large cumulative effect on the country when they follow one another quickly.

This map depicts the impact of flood-ing on provinces’ GDPs, represented as percentages of their annual aver-age GDPs affected, with greater color saturation indicating higher percent-ages. The bar graphs represent GDP affected by floods with return periods of 10 years (white) and 100 years (black). The horizontal line across the bars also shows the annual average of GDP affected by floods.

When a flood has a 10-year return period, it means the probability of occurrence of a flood of that magni-tude or greater is 10 percent per year. A 100-year flood has a probability of occurrence of 1 percent per year. This means that over a long period of time, a flood of that magnitude will,

on average, occur once every 100 years. It does not mean a 100-year flood will occur exactly once every 100 years. In fact, it is possible for a flood of any return period to occur more than once in the same year, or to appear in consecutive years, or not to happen at all over a long period of time.

If the 10- and 100-year bars are the same height, then the impact of a 10-year event is as large as that of a 100-year event, and the annual average of affected GDP is dominated by events that happen relatively frequently. If the impact of a 100-year event is much greater than that of a 10-year event, then less frequent events make a larger contribution to the annual average of affected GDP. Thus, even if a province’s annual affected GDP seems small, less frequent and more intense events can still have large impacts.

The annual average population affect-ed by flooding in Moldova is about 70,000 and the annual average affect-ed GDP about $100 million. Within the various provinces, the 10- and 100-year impacts do not differ much, so relatively frequent floods have large impacts on these averages.

EUROPE AND CENTRAL ASIA (ECA) RISK PROFILESFLOODMoldova

0 1 2 4 8

Annual Average of Affected GDP (%)

6

10

5

2

Affected GDP (%) for

10 and 100-year return periods

Annual average

10-year 100-year

One block = 1%

78

R O M A N I A

U K R A I N E

Balti

Cahul

Chisinau

Dubasari

Edinet

Gagauzia

Lapusna

Orhei

Soroca

Tighina

Ungheni

Chisinau

B L A C K S E A

The worst earthquake af-fecting Moldova since 1900 occurred in 1986 in Vrancea,

Romania, with a magnitude of 7.2. It killed at least four people in Moldo-va and caused over $200 million in damage. Other major earthquakes affecting Moldova occurred in 1802, 1838, 1940, 1977, and 1990, and all were centered in Vrancea. The 1802 event was one of the largest earthquakes on record to occur in Europe.

This map depicts the impact of earthquakes on provinces’ GDPs, represented as percentages of their annual average GDPs affected, with greater color saturation indicating higher percentages. The bar graphs represent GDP affected by earth-quakes with return periods of 10 years (white) and 100 years (black). The horizontal line across the bars also shows the annual average of GDP affected by earthquakes.

When an earthquake has a 10-year return period, it means the prob-ability of occurrence of an earth-quake of that magnitude or greater is 10 percent per year. A 100-year earthquake has a probability of occurrence of 1 percent per year. This means that over a long period of time, an earthquake of that mag-nitude will, on average, occur once every 100 years. It does not mean a 100-year earthquake will occur exactly once every 100 years. In

fact, it is possible for an earthquake of any return period to occur more than once in the same year, or to appear in consecutive years, or not to happen at all over a long period of time.

If the 10- and 100-year bars are the same height, then the impact of a 10-year event is as large as that of a 100-year event, and the annual av-erage of affected GDP is dominated by events that happen relatively fre-quently. If the impact of a 100-year event is much greater than that of a 10-year event, then less frequent events make larger contributions to the annual average of affected GDP. Thus, even if a province’s annual affected GDP seems small, less fre-quent and more intense events can still have large impacts.

The annual average population affected by earthquakes in Moldo-va is about 20,000 and the annual average affected GDP about $40 million. The annual averages of fa-talities and capital losses caused by earthquakes are about 20 and about $50 million, respectively. The fatal-ities and capital losses caused by more intense, less frequent events can be substantially larger than the annual averages. For example, an earthquake with a 0.4 percent annual probability of occurrence (a 250-year return period event) could cause about $4 billion in capital loss (about 60 percent of GDP).

EUROPE AND CENTRAL ASIA (ECA) RISK PROFILESEARTHQUAKEMoldova

0 1 2 4 8

Annual Average of Affected GDP (%)

6

100

50

20

Affected GDP (%) for

10 and 100-year return periods

Annual average

10-year 100-year

One block = 10%

79

R O M A N I A

U K R A I N E

Balti

Cahul

Chisinau

Dubasari

Edinet

Gagauzia

Lapusna

Orhei

Soroca

Tighina

Ungheni

Chisinau

B L A C K S E A

A L B A N I A

B O S N I A A N D H E R Z E G O V I N A

S E R B I A

K O S O V O

Andrijevica

Bar

Berane

Bijelo Polje

Budva

CetinjeDanilovgrad

Herceg Novi

Kolasin

Kotor

Mojkovac

Niksic

Plav

Pljevlja

Pluzine

Podgorica

Rozaj

Savnik

Tivat

Ulcinj

Zabljak

Podgorica

A D R I A T I C S E A

The rose diagrams show the provinces with the potential for greatest annual average capital losses and highest

annual average numbers of fatalities, as determined using an earthquake risk model. The potential for greatest capital loss occurs in Chisinau, which is not surprising, given the economic importance of the province.

EUROPE AND CENTRAL ASIA (ECA) RISK PROFILESMoldova

EARTHQUAKEEXCEEDANCE PROBABILITY CURVE, 2015 AND 2080

FLOODEXCEEDANCE PROBABILITY CURVE, 2015 AND 2080 The exceedance probability curves display the GDP

affected by, respectively, floods and earthquakes for varying probabilities of occurrence. Values for two different time periods are shown. A solid line depicts the affected GDP for 2015 conditions. A diagonally striped band depicts the range of affected GDP based on a selection of climate and socioeconomic scenarios for 2080. For example, if Mol-dova had experienced a 100-year return period flood event in 2015, the affected GDP would have been an estimated $500 million. In 2080, however, the affected GDP from the same type of event would range from about $2 billion to about $3 billion. If Moldova had experienced a 250-year earthquake event in 2015, the affected GDP would have been about $4 billion. In 2080, the affected GDP from the same type of event would range from about $20 billion to about $30 billion, due to population growth, urbanization, and the increase in exposed assets.

All historical data on floods and earthquakes are from D. Guha-Sapir, R. Below, and Ph. Hoyois, EM-DAT: International Disaster Database (Université Catholique de Louvain, Brussels, Belgium), www.emdat.be, and J. Daniell and A. Schaefer, “Eastern Europe and Central Asia Region Earthquake Risk Assessment Country and Province Profiling,” final report to GFDRR, 2014. Damage estimates for all historical events have been inflated to 2013 US$. More information on the data and context can be found in the full publication, Europe and Central Asia Country Risk Profiles for Floods and Earthquakes, at www.gfdrr.org/publications, or by contacting Joaquin Toro (jtoro@worldbank.org) or Dr. Alanna Simpson (asimpson1@worldbank.org). Please see the full publication for the complete disclaimer and limitations on methodology. Although GFDRR makes reasonable efforts to ensure all the information presented in this document is correct, its accuracy and integrity cannot be guaranteed.

Aff

ecte

d G

DP

(b

illi

on

s o

f $

)

EARTHQUAKEANNUAL AVERAGE FATALITIES

EARTHQUAKEANNUAL AVERAGE CAPITAL LOSS ($)

Return period (years)

Probability (%)

10

10

250

0.4

50

2

100

1

15

10

5

20

25

30

2080

2015

Return period (years)

Probability (%)

10

10

250

0.4

50

2

100

1

1.5

1.0

0.5

2.0

2.5

3.5

3.0

2080

2015

Balti 5Gagauzia 3

Cahul 10

Tighina 3

Chis

inau

10

Duba

sari

4

Ungheni 5

Orhei 1

Lapusna 5

Soroca 1

Gagauzia 1Tighina 0

Lapusna 2

Dubasari 0

Cahu

l 10

Balt

i 0

Ungheni 1

Orhei 0

Chisinau 1

Soroca 0

80