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 0.0049

0.068

0.250.13

0.22

GDP (billions of $)

FLOOD

EARTHQUAKE

10

5

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 (%)

Bijelo PoljeDanilovgradBeraneAndrijevicaPodgoricaPlavUlcinjBarPluzineCetinje

11765310000

BudvaUlcinjDanilovgradKotorBarPodgoricaTivatCetinjeNiksicHerceg Novi

4322222221

Montenegro’s population and economy 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 60 percent of Montenegro’s population lives in urban environments. The country’s GDP was approximately US$4.0 billion in 2015, with close to 90 percent derived from services, most of the remainder generated by industry,

MontenegroEUROPE AND CENTRAL ASIA (ECA) RISK PROFILES

GDP $4.0 billion*

Population 623,000*

AFFECTED BY 100-YEAR FLOOD

AFFECTED BY 250-YEAR EARTHQUAKE

CAPITAL LOSS FROM 250-YEAR EARTHQUAKE

$400 million (10%)

60,000 (10%)

$3 billion (64%)

300,000 (50%)

$400 million (10%)

50 (<1%)

*2015 estimates

and agriculture making a small contribution. Montenegro’s per capita GDP was $6,470.

This map displays GDP by prov-ince in Montenegro, with great-er color saturation 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 normalized risk. The risk is estimated using flood and earthquake risk models.

The table displays the provinces at greatest normalized risk for each peril. In relative terms, as shown in the table, the province at greatest risk of floods is Bijelo Polje, and the one at greatest risk of earthquakes is Budva. In absolute terms, the province at greatest risk of both floods and earthquakes is Podgorica.

81

A L B A N I A

S E R B I A

K O S O V O

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

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 AA 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

Cetinje Danilovgrad

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

Floods in 2010, declared by the country’s government as the “worst floods ever recorded,”1

affected over 5,000 people in Mon-tenegro. In 2014, a devastating flood in the Balkans also affected Monte-negro, although at the time of this publication its impact had not been quantified.

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 affected by flooding in Montenegro is about 10,000 and the annual average affected GDP about $90 million. With-in 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 PROFILESFLOODMontenegro

0 1 2 4 8

Annual Average of Affected GDP (%)

6

40

20

10

Affected GDP (%) for

10 and 100-year return periods

Annual average

10-year 100-year

One block = 5%

82

A L B A N I A

S E R B I A

K O S O V O

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

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

Montenegro’s worst earth-quake since 1900 took place in 1979. The earth-

quake caused over 120 fatalities and close to $13 billion in damage. Other earthquakes affecting Mon-tenegro during the twentieth cen-tury occurred in 1905 and 1968.

This map depicts the impact of earthquakes on provinces’ GDPs, represented as percentages of their annual average GDPs affect-ed, with greater color saturation indicating higher percentages. The bar graphs represent GDP affected by earthquakes with return peri-ods 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 probability of occurrence of an earthquake of that magnitude or greater is 10 percent per year. A 100-year earthquake has a prob-ability of occurrence of 1 percent per year. This means that over a long period of time, an earthquake of that magnitude 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 average of affected GDP is dominated by events that happen relatively frequently. If the impact of a 100-year event is much great-er 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 frequent and more intense events can still have large impacts.

The annual average population af-fected by earthquakes in Montene-gro is about 9,000 and the annual average affected GDP about $70 million. The annual averages of fatalities and capital losses caused by earthquakes are about eight and about $10 million, respec-tively. The fatalities and capital losses caused by more intense, less frequent events can be substantial-ly 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 $400 million in capital loss (about 10 percent of GDP).

EUROPE AND CENTRAL ASIA (ECA) RISK PROFILESEARTHQUAKEMontenegro

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%

83

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

Cetinje Danilovgrad

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

B E L A R U S

C Z E C H R E P U B L I C

G E R M A N Y

L I T H U A N I A

R U S S I A N F E D E R A T I O N

U K R A I N E

Dolnoslaskie

Kujawsko-Pomorskie

Lodzkie

Lubeiskie

Lubuskie

Malopolske

Mazowieckie

Opolskie

Podkarpackie

Podlaskie

Pomorskie

Slaskie

Swietokrzyskie

Warminsko-Mazurskie

Wielkopolskie

Zachodnio-Pomorskie

Warsaw

B A LT 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 Podgorica, which is not surprising, given the economic importance of the province.

EUROPE AND CENTRAL ASIA (ECA) RISK PROFILESMontenegro

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 Montenegro had experienced a 100-year return period flood event in 2015, the affected GDP would have been an estimated $400 million. In 2080, however, the affected GDP from the same type of event would range from about $1 billion to about $2 billion. If Montenegro had experienced a 250-year earthquake event in 2015, the affected GDP would have been about $3 billion. In 2080, the affected GDP from the same type of event would range from about $7 billion to about $15 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. Government quote on floods is from Government of Montenegro, “Montenegro Suffers Worst Floods Ever Recorded,” press release, December 3, 2012, http://www.gov.me/en/News/101512/Montenegro-suffers-worst-floods-ever-recorded.html. 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

4

6

2

8

10

16

12

14

2080

2015

Return period (years)

Probability (%)

10

10

250

0.4

50

2

100

1

2.0

0.5

1.0

1.52080

2015

Danilovgrad800,000

Kotor 500,000

Bar 900,000

Cetinje 500,000

Podg

oric

a7,

00

0,0

00

Ulc

inj 5

00

,00

0

Budva 700,000

Herceg Novi400,000

Niksic 50

0,0

00

Tivat 300

,00

0

Danilovgrad 0Tivat 0

Budva 1

Kotor 0

Podg

oric

a 7

Her

ceg

Nov

i 0

Bar 0

Cetinje 0

Niksic 0

Ulcinj 0

84