A F G H A N I S T A N
C H I N A
I N D I A
K A Z A K H S T A N
K Y R G Y Z R E P U B L I C
P A K I S T A N
T A J I K I S T A N
T U R K M E N I S T A N
I S L A M I C R E P U B L I C O F I R A N
Andijan
BukharaFergana
Karakalpakstan
Kashkadarya
Khorezm
Namangan
Samarkand
Surkhandarya
Sirdarya
Tashkent
Jizzakh
Navoiy Tashkent City
Tashkent
1.1 2.9 7.44.8 6.9
GDP (billions of $)
FLOOD
EARTHQUAKE
75
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 (%)
AndijanFerganaKarakalpakstanNamanganSirdaryaBukharaTashkentJizzakhSamarkandKashkadarya
3221111111
NamanganAndijanFerganaTashkent citySamarkandTashkentSurkhandaryaSirdaryaJizzakhKashkadarya
7763333222
Uzbekistan’s population and econ-omy are exposed to earthquakes and floods, with earthquakes
posing the greater risk of a high impact, lower probability event. 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.
More than 60 percent of Uzbekistan’s population lives in rural environments. The country’s GDP was approximately US$66.0 billion in 2015, with most derived from services and industries
UzbekistanEUROPE AND CENTRAL ASIA (ECA) RISK PROFILES
GDP $66.0 billion*
Population 30.2 million*
AFFECTED BY 100-YEAR FLOOD
AFFECTED BY 250-YEAR EARTHQUAKE
CAPITAL LOSS FROM 250-YEAR EARTHQUAKE
$4 billion (5%)
2 million (6%)
$20 billion (30%)
10 million (32%)
$10 billion (19%)
10,000 (<1%)
*2015 estimates
(together about 80 percent) and agriculture generating the remain-der. Uzbekistan’s per capita GDP was $2,190.
This map displays GDP by prov-ince in Uzbekistan, with greater color saturation indicating greater GDP within a province. The blue circles indicate the risk of expe-riencing floods and the orange circles the risk of earthquakes in terms of normalized annual av-erage of affected GDP. The largest circles represent the greatest nor-malized 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 great-est risk of floods is Andijan, and the one at greatest risk of earth-quakes is Namangan. In absolute terms, the province at greatest risk of floods is Fergana, and the one at greatest risk of earthquakes is Namangan.
5.5
127
A F G H A N I S T A N
C H I N A
I N D I A
I S L A M I C R E P U B L I C O F I R A N
K A Z A K H S T A N
K Y R G Y Z
R E P U B L I C
P A K I S T A N
T A J I K I S T A N
T U R K M E N I S T A N
Andijan
BukharaFergana
Karakalpakstan
Kashkadarya
KhorezmNamangan
Samarkand
Surkhandarya
Sirdarya
Tashkent
Jizzakh
NavoiyTashkent City
Tashkent
A F G H A N I S T A N
C H I N A
I N D I A
K A Z A K H S T A N
K Y R G Y Z
R E P U B L I C
P A K I S T A N
T A J I K I S T A N
T U R K M E N I S T A N
I S L A M I C R E P U B L I C O F I R A N
Andijan
Bukhara
Fergana
Karakalpakstan
Kashkadarya
KhorezmNamangan
Samarkand
Surkhandarya
Sirdarya
Tashkent
Jizzakh
Navoiy
Tashkent City
Tashkent
C A S P I A N S E A
A flood that occurred in Uzbeki-stan in 2005 affected around 1,500 people.
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 Uzbekistan is about 400,000 and the annual average affected GDP about $800 million. For most provinces, the 10- and 100-year impacts do not differ much, so relatively frequent floods have large impacts on these averages. For the few in which the 100-year impacts are much greater than the 10-year impacts, less frequent events make a significant contribution to the annual average of affected GDP.
EUROPE AND CENTRAL ASIA (ECA) RISK PROFILESFLOODUzbekistan
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%
128
A F G H A N I S T A N
C H I N A
I N D I A
I S L A M I C R E P U B L I C O F I R A N
K A Z A K H S T A N
K Y R G Y Z
R E P U B L I C
P A K I S T A N
T A J I K I S T A N
T U R K M E N I S T A N
Andijan
BukharaFergana
Karakalpakstan
Kashkadarya
KhorezmNamangan
Samarkand
Surkhandarya
Sirdarya
Tashkent
Jizzakh
NavoiyTashkent City
Tashkent
Uzbekistan’s worst earthquake since 1900 took place in 1902 in Andizhan, with a
magnitude of 6.4, and caused nearly 5,000 fatalities. More recently, earthquakes in 1992 and 2011 caused approximately 10 fatalities per event. Other major earthquakes affecting Uzbekistan occurred in circa 838, 1966, and 1984.
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 aver-age 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 af-fected by earthquakes in Uzbekistan is about 1 million and the annual average affected GDP $2 billion. The annual averages of fatalities and capital losses caused by earthquakes are about 200 and about $900 million, respectively. The fatalities 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 10,000 fatalities and $10 billion in capital loss (about 20 percent of GDP).
EUROPE AND CENTRAL ASIA (ECA) RISK PROFILESEARTHQUAKEUzbekistan
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%
129
A F G H A N I S T A N
C H I N A
I N D I A
K A Z A K H S T A N
K Y R G Y Z
R E P U B L I C
P A K I S T A N
T A J I K I S T A N
T U R K M E N I S T A N
I S L A M I C R E P U B L I C O F I R A N
Andijan
Bukhara
Fergana
Karakalpakstan
Kashkadarya
KhorezmNamangan
Samarkand
Surkhandarya
Sirdarya
Tashkent
Jizzakh
Navoiy
Tashkent City
Tashkent
C A S P I A N 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 Namangan, which is not surprising, given the economic importance of the province.
EUROPE AND CENTRAL ASIA (ECA) RISK PROFILESUzbekistan
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 Uzbekistan had experienced a 100-year return period flood event in 2015, the affected GDP would have been an estimated $4 billion. In 2080, however, the affected GDP from the same type of event would range from about $20 billion to about $30 billion. If Uzbekistan had experienced a 250-year earthquake event in 2015, the affected GDP would have been about $20 billion. In 2080, the affected GDP from the same type of event would range from about $100 billion to about $200 billion, due to population growth, urbaniza-tion, and the increase in exposed assets.
All historical data on floods and earthquakes are from D. Guha-Sapir, R. Below, and Ph. Hoyois, EM-DAT: International Disaster Database (Université Catholique de Louvain, Brussels, Belgium), www.emdat.be; the National Geophysical Data Center/World Data Service (NGDC/WDS), Significant Earthquake Database (National Geophysical Data Center, NOAA), doi:10.7289/V5TD9V7K; and J. Daniell and A. Schaefer, “Eastern Europe and Central Asia Region Earthquake Risk Assessment Country and Province Profiling,” final report to GFDRR, 2014. Damage estimates for all historical events have been inflated to 2013 US$. More in-formation 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 ([email protected]) or Dr. Alanna Simpson ([email protected]). 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
50
100
150
250
200
2080
2015
Return period (years)
Probability (%)
10
10
250
0.4
50
2
100
1
10
15
5
20
25
30
35
40
2080
2015
Andijan 100Navoiy 50
Fergana 200
Tashkent 60
Nam
anga
n 20
0
Jizza
kh 7
0
Tashkent city
80
Kashkadarya 40
Surkhandarya
80
Samarkand40
Namangan 20Tashkent city 10
Samarkand 30
Kashkadarya 20
Ferg
ana
40
Nav
oiy
20
Surkhandarya 20
Tashkent 10
Andijan 20
Bukhara 9
130