WORLDBANKGROUP GROPE Q GFDRR EI ANDCENTRALA5IA (ECA) RI5K PROFILES AFFECTED BY 100-YEAR AFFECTED BY 250-YEAR CAPITAL LOSS FROM 250-YEAR FLOOD EARTHQUAKE EARTHQUAKE GDP $126 billion* Hunga ry 0.Population 9.8 million* SLOVAK REPUBLIC ungary's population and to 70 percent derived from services, table, the province at greatest risk is Csongrad, and the one at greatest economy are eposed to most of the remainder generated by of floods is Csongrad, and the one at risk of earthquakes is Budapest. earthquakes and floods, with industry and agriculture making a greatest risk of earthquakes is Koma- R floods posing the greater risk. The small contribution. Hungary's per rom-esztergom. In absolute terms, model results for present-day risk capita GDP was $12,800. the province at greatest risk of floods shown in this risk profile are based on population and gross domestic This map displays GDP by provnce in A Borsodabauj-7emlen product (GDP) estimates for 2015. Hungary, with greater color satura- Buap & The estimated damage caused by Szabolci-s7atmar-bereg historical events is inflated to 2015 a province. The blue circles indicate US dollars. the riskofexperieningfloods and Heves the orange circles the risk of earth- 6yo -io n-5 n on s About 70 percent of Hungary's pop- quakes in terms of normalized annual Hdi ulation lives in urban environments. average of affected GDP. The largest The country's GDP was approximate- circles represent the greatest normal- -nagykun-szolnok ly US$126 billion in 2015, with close ized risk. The risk is estimated using Vas Veszpreme N do a r flood and earthquake risk models. TOP AFFECTED PROVINCES The table displays the provinces at greatest normalized risk for each per- Zalar i. In relative terms, as shown in the nagkunison Sonogy onac sk n EARTHQUAKE ANNUAL AVERAGE OF ANNUAL AVERAGE OF AFFECTED GDP (%) AFFECTED GDP (%)ROMA Baranya Csongrad 1 Komarom-esztergom 2 CR0ATIA lasz-nagykun-szolnok 13 Budapest I SERB A Gyor-moson-sopron Pest I Bekes Zala I Szabocs- Veszprem i Annual Average of Affected GOP (%) GDP (billions of $) szatmar-bereg Heves I Teves 2 No rad 1 20 There is a high correlation Borsod-abauj- lasz-nagykun-szolnok 1 EARTHQUAKE I (r=95) betwee the zemoplen Vas 1ATQAEl 1 d I d population anid GOP of a province. Bacs-kiskun Hajdu-bihar o Negligible DR Hun aryWORLDBANKGROUP ROPE" ANDEENTRAL A51A(ECA) E|G POLAND T he most deadly flood in Hun- gary since 1900 took place in flood will occur exactly once every 100 years. In fact, it is possible for a 1970 and caused about 300 flood ofany return period to occur CZELH REPUBLIC fatalities and over $500 million in more than once in the same year, or damage. More recently, in 1999, two to appear in consecutive years, or not floods occurred that together caused to happen at all over a long period of at least eight fatalities, affected over time. 100,000 people, and brought over E $400 million in damage. A single If the 10- and 100-year bars are the flood in 2010 caused no fatalities same height, then the impact of a 10- but almost $500 million in damage. year event is as large as that of a 100- These statistics highlight the lives year event, and the annual avenge of being saved by disaster risk manage- affected GDP is dominated by events Budapest ment efforts but also the possibility that happen relatively frequently. that the damage associated with Ifthe impact ofa 100-year event is flooding will rise. much greater than that of a 10-year S Hee This map depicts the impact of flood-fevent,tthennlessaf This map ep astheimpacto fflod - a larger contribution to the annual ing on provinces' GDPs, represented average of affected GDP. Thus, even as percentages of their annual aver- if a province's annual affected GDP age GDPs affected, with greater color seems small, less frequent and more Vai Veszprem Fejer saturation indicating higher percent- intense events can still have large ages. The bar graphs represent GDP impacts. affected by floods with return periods of 10 years (white) and 100 years The annual avenge population affect- Zaa (black). The horizontal line across the ed by flooding in Hungary is about bars also shows the annual average of 200,000 and the annual average somogy GDP affected by floods. affected GDP about $2 billion. Within the variou s provinces, th e 10 - an d ROMA When a flood has a 10-year return 100-year impacts do not differ much, Baranya period, it means the probability of so relatively frequent floods have occurrence of a flood of that magni- large impacts on these averages. CR0ATIA SERB tude or greater is 10 percent per year. A 100-year flood has a probability Affected GDP for Annual Average of Affected GDP of occurrence of 1 percent per year. 10 and 100year return periods One h[ock = 5% This means that over a long period of 50 time, a flood of that magnitude will, 30 0 F 6 & on average, occur once every 100 Annual averageA 10 years. It does not mean a 100-year itN possibe f iNs a 10-year 100-year HWORLDBANKGROUP GROPE EL ANDEENTRALA5A (ECA) POLAND H ungary's worst earthquake to happen at all over a long period since 1900 took place in of time. 1911 in Kecskemet, causing CZECH REPUBLIC 10 fatalities. Others occurred in If the 10- and 100-year bars are 1599, 1763, 1783, and 1879, and, the same height, then the impact most recently, in 2011. of a 10-year event is as large as that of a 100-year event, and the This map depicts the impact of annual average of affected GDP is I AN F earthquakes on provinces' GDPs, dominated by events that happen represented as percentages of their relatively frequently. If the impact annual avenage GDPs affected, with of a 100-year event is much greater greater color saturation indicat- than that of a 10-year event, then ing higher percentages. The bar less frequent events make largera graphs represent GP affected by contributions to the annual aver- zabocs-szatmar-bereg earthquakes with return periods age of affected GDP. Thus, even if of 10 years (white) and 100 years a province's annual affected GP (black). The horizontal line across seems small, less frequent and Gyor-rnowon-sopron .ca Bdpt the bars also shows the annual more intense events can still have average of GDP affected by earth- large impacts. quakes. The annual average population When an earthquake has a 10-year affected by earthquakes in HungaryYO7PI Foj return period, it means the prob- is about 80,000 and the annual ability of occurrence of an earth- average affected GP about $1 quake of that magnitude or greater billion. The annual averages of is 10 percent per year. A 100-year fatalities and capital losses caused earthquake has a w aongrad probability of by earthquakes are about one and ccurrence of p ercent per year. about $200 million, respectively. This mean s th at over a loIng p erio d The fatalities and capital losses ROMA of time, an earthquake of that mag- is caused by more intense, less fre- 100percent0perayear.uAn100-year nitude will, on average, occur once quent events can be substantially every 100 years. It does not mean Ilarge rtha n the an nu al averages. CROATI A SERB A a 100-year earthquake will occur For example, an earthquake with exactly once every 100 years. In greae a . percent annual probability Af fectd () f rra f d fact, it is possible for an earthquake of occurrence (a 250-year return One block = 10% of any return period to occur more period event) could cause about than ne in the same year, or to $6 billion in capital loss (about S appear in consecutive years, or not percent of GP). Ariua[ average 20 BOSNI AND NAZCSO A 10-year 100-year ROPE AND CENTRAL HunaryWORLDBANKGROUP E|GDR A51A(ECA) EARTHQUAKE EARTHQUAKE ANNUAL AVERAGE CAPITAL LOSS (MILLIONS $) ANNUAL AVERAGE FATALITIES 00 6 0he rose diagrams show the provinces with the potential &6 T for greatest annual average capital losses and highest o annual average numbers of fatalities, as determined using an earthquake risk model. The potential for greatest capital Komarom-esztergiom Komaram. Fejer 4 oBekes 0 loss occurs in Budapest, which is not surprising, given the economic importance of the province. 4, 0 EARTHQUAKE he exceedance probability curves display the GDP EXCEEDANCE PROBABILITY CURVE, 2015 AND 2080 EXCEEDANCE PROBABILITY CURVE, 2015 AND 2080 he ecedancepectily floods dieathe for T affected by, respectively, floods and earthquakes for 45 350 varying probabilities of occurrence. Values for two different 40 time periods are shown. A solid line depicts the affected 300 GDP for 2015 conditions. A diagonally striped hand depicts 2 250 the range of affected GDP based on a selection of climate 2080 -2 and socioeconomic scenarios for 2080. For example, if Hun- 25 I 200 gary had experienced a 100-year return period flood event 150 2in 2015, the affected GDP would have been an estimated $9 15 billion. In 2080, however, the affected GDP from the same 2015 100 2 10dtype of event would range from about $10 billion to about 50 $40 billion. If Hungary had experienced a 2 50-year earth- 2015 quake event in 2015, the affected GDP would have been 10 50 10 50 100 250 about $50 billion. In 2080, the affected GDP from the same Return period (years) Return period (years) type of event would range from about $80 billion to about 10 10 2 1 o4 $300 billion, due to population growth, urbanization, and Probability (%) Probability (%) the increase in exposed assets. All historical data on floods and earthquakes are from, respectively, D.Guha-Sapir, R.Below, arid Pih. Hoyois, EMDAT: International Disaster Database (Universite Catholique de Louvain, Brussels, Belgium), www.emdat.be, and I. Daniel[ and A.Schaefer, "Eastern Europe and Central Asia Region Earthquake Risk Assessment Country and Province Profiling,' final reportto GFDRR, 2014. Damage estimates for all historical events have been inflated to 2015 US$.