WORLDBANKGROUP GR QRI5KPROFILES EROPE ANDCENTRALA5IA (ECA) AFFECTED BY 100-YEAR AFFECTED CAPITAL LOSS BY 250-YEAR FROM 250-YEAR FLOOD EARTHQUAKE EARTHQUAKE GDP $43.0 billion* Lithuamia o Lithuania's population and econ- and agriculture making a small omy are exposed to earthquakes contribution. Lithuania's per and floods, with floods posing capita GDP was $15,100. the greater risk. The model results for LA7,VIA present-day risk shown in this risk pro- This map displays GDP by prov- file are based on population and gross ince in Lithuania, with greater Teau o domestic product (GDP) estimates for color saturation indicating Siauli 'Panevezia 2015. The estimated damage caused by greater GDP within a province. historical events is inflated to 2015 US The blue circles indicate the risk dollars. of experiencing floods and the Kalpedes orange circles the risk of earth- Close to 70 percent of Lithuania's quakes in terms of normalized population lives in urban environments. annual average of affected GDR The country's GDP was approximately The largest circles represent the Ta rages US$43.0 billion in 2015, with nearly 70 greatest normalized risk. The percent derived from services, most of risk is estimated using flood and the remainder generated by industry, earthquake risk models. auno The table displays the provinces at greatest normalized risk for RUSS AN FEDERATION ilnia TOP AFFECTED PROVINCES each peril. In relative terms, as shown in the table, the prov- ince at greatest risk of floods is EARTHQUAKE Alythaus, and the one at greatest ANNUAL AVERAGE OF ANNUAL AVERAGE OF risk of earthquakes is Siauliu. In AFFECTED GDP (%) AFFECTED GDP (%) absolute terms, the province at greatest risk of floods is Vilniaus, Parevezio KlSipedos 0 and the one at greatest risk of 0 earthquakes is Siauliu. Annual Average of Affected GOP (%) BELARUS Kauno 2 Telsiu Vilniaus 2 Panevezio 0 5 Taurages 2 Marijampoles 0 5ODP (billions of$ Marijampoles 2 Utenos 0 There is a high correlation Klaipedos I Kauno 0 POLAvD 1 ATQAE(r=O.95) EARTHQUAKE between the Utenos Taurages 0 Siaulio Alytaus 0 population and GDP of a Teliu ViAniaus 0 0 Negligible province. Telsiui u VilniaUS 0 Lith aniaWORLDBANKGROUP DR ROPE ANDEENTRAL A51A(ECA) E|G F looding in 2010 caused four much greater than that of a 10-year LATVIA fatalities in Lithuania. event, then less frequent events make a larger contribution to the annual This map depicts the impact average of affected GDP. Thus, even of flooding on provinces' GDPs, repre- if a province's annual affected GDP sented as percentages of their annual seems small, less frequent and more average GDPs affected, with greater intense events can still have large color saturation indicating higher impacts. percentages. The bar graphs repre- sent GDP affected by floods with re- The annual average population turn periods of 10 years (white) and affected by flooding in Lithuania is 100 years (black). The horizontal line about 60,000 and the annual average Te Siaul i across the bars also shows the annual affected GDP about $800 million. For average of GDP affected by floods. most provinces, in which the impacts _ from 10- and 100-year floods do not Klaipedos When a flood has a 10-year return differ much, relatively frequent floods period, it means the probability of have large impacts on these averages. occurrence of a flood of that magni- For the few in which the 100-year teno tude or greater is 10 percent per year. impacts are much greater than the A 100-year flood has a probability 10-year impacts, less frequent events Taurage of occurrence of 1 percent per year. make a significant contribution to the This means that over a long period of annual average of affected GDKa time, a flood of that magnitude will, on average, occur once every 100 years. It does not mean a 100-year v flood will occur exactly once every 100 years. In fact, it is possible for a nius 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. Aftected GDP ()for If the 10- and 100-year bars are the and 100-year return periods same height, then the impact of a 10- One block =2% 20 year event is as large as that of a 100- year event, and the annual average of 10 Annual Average of Affected GDP (%) affected GDP is dominated by events P 0 LAN D Annual average -L that happen relatively frequently. If the impact of a 100-year event is 10-year 100-year o 1 s C & 66ya 0-ea 6 : Lith aniaWORLDBANKGROUP GF RROP EL ECENTRAL A5IA(ECA) AND Lihua ia h RS[ PRO T he worst earthquake to affect Lithuania since 1900 oc- If the 10- and 100-year bars are the same height, then the impact of LATVIA curred in 1908 near the Be- 10-year event is as large as that of a larus border. A more recent, widely 100-year event, and the annual av- felt earthquake occurred in 1988; erage of affected GDP is dominated damage was minimal, however. by events that happen relatively fre- quently. If the impact of a 100-year This map depicts the impact of event is much greater than that of earthquakes on provinces'GDPs, a 10-year event, then less frequent represented as percentages of their events make larger contributions to annual average GDPs affected, with the annual average of affected GDP. greater color saturation indicating Thus, even if a province's annual TelsiuSauli Pan io higher percentages. The bar graphs affected GDP seems small, less fre- represent GDP affected by earth- quent and more intense events can quakes with return periods of 10 still have large impacts. KLaipedos years (white) and 100 years (black). The horizontal line across the bars The annual average population af- also shows the annual average of fected by earthquakes in Lithuania GDP affected by earthquakes. is about 100 and the annual average Taues affected GDP about $2 million. The K When an earthquake has a 10-year annual averages of fatalities and return period, it means the prob- capital losses caused by earth- Kauno ability of occurrence of an earth- quakes are less than one and about quake of that magnitude or greater $500,000, respectively. The fatal- is 10 percent per year. A 100-year ities and capital losses caused by RUSS AN FEDERATION J VilniaUS earthquake has a probability of more intense, less frequent events Marijampoles VIFiu occurrence of t percent per year. can he substantiall larger than This means that over a long period the annual averages. For example, of time, an earthquake of that mag- an earthquake with a 0.4 percent nitude will, on average, occur once annual probability of occurrence (a every 100 years. It does not mean 250-year return period event) could a 100-year earthquake will occur cause about $20 million in capital Alvtaus exactly once every 100 years. In loss (less than 1 percent of GDP). fact, it is possible for an earthquake BE LAR us of any return period to occur more than once in the same year, or to appear in consecutive years, or not GOP (%) not affected for 10 and Annual Average of Affected GDP (%) i-U LALi-10O-year return periods to happen at all over a long period Annual average = 0 of time. Lit ua iaWORLDBANKGROUP EL|GFDRR "AND CENTRAL A51A(ECA) EARTHQUAKE 7 EARTHQUAKE ANNUAL AVERAGE CAPITAL LOSS ($) ANNUAL AVERAGE FATALITIES 7 6 he rose diagrams show the provinces with the potential 0o1S T for greatest annual average capital losses and highest annual average numbers of fatalities, as determined using Utenos 8,000 Tj u 40,000 T s 0an earthquake risk model. The province with the potential for greatest capital loss is Siauliu. . ......----- . 0 EARTHQUAKE EXCEEDANCE PROBABILITY CURVE, 2015 AND 2080 EXCEEDANCE PROBABILITY CURVE, 2015 AND 2080 he exceedance probability curves display the GDP 1 affected by, respectively, floods and earthquakes for 12 0.18 varying probabilities of occurrence. Values for two different 0.16 time periods are shown. A solid line depicts the affected 10 0.14 GDP for 2015 conditions. A diagonally striped hand depicts 2080 8 0.12 the range of affected GDP based on a selection of climate and socioeconomic scenarios for 2080. For example, if Lith- 6 ania had experienced a 100-year return period flood event u0.10 0.08 in 2015, the affected GDP would have been an estimated $4 2015 2080 4 0.06 billion. In 2080, however, the affected GDP from the same .0 type of event would range fmm about $7 billion to about 0.02 2015 $10 billion. If Lithuania had experienced a 250-year earth- I I I 2015quake _____ event in 2015, the affected GDP would have been 10 50 100 250 10 50 100 250 about $60 million. In 2080, the affected GDP from the same Return period (years) Return period (years) type of event would range from about $100 million to about 10 2 1 0.4 10 2 1 074 $200 million, due to population growth, urbanization, and Probability (%) Probability (%) the increase in exposed assets. All historical data on floods and earthquakes are from D. Guha-Sapir, R. Below, and Ph. Hoyois, EM-DAT: International Disaster Database (Universit Catholique de Louvain, Brussels, Belgium), www.emdat.be, and 1. Daniell and A. Schae- fer, "Eastern Europe and Central Asia Region Earthquake Risk Assessment Country and Province Profiling," final report to GFDRR, 2014. Damage estimates for all historical events have been inflated to 2015 US$.