Future scenarios for earthquake and flood risk in Eastern Europe and Central Asia

We report on a regional flood and earthquake risk assessment for 33 countries in Eastern Europe and Central Asia. Flood and earthquake risk were defined in terms of affected population and affected gross domestic product (GDP). Earthquake risk was also quantified in terms of fatalities and capital loss. Estimates of future population and GDP affected by earthquakes vary significantly among five shared socioeconomic pathways that are used to represent population and GDP in 2030 and 2080. There is a linear relationship between the future relative change in a nation's exposure (population or GDP) and its future relative change in annual average population or GDP affected by earthquakes. The evolution of flood hazard was quantified using a flood model with boundary conditions derived from five different general circulation models and two representative concentration pathways, and changes in population and GDP were quantified using two shared socioeconomic pathways. There is a nonlinear relationship between the future relative change in a nation's exposure (population or GDP) and its future relative change in its annual average population or GDP affected by floods. Six regions can be defined for positive and negative relative change in population that designate whether climate change can temper, counter, or reinforce relative changes in flood risk produced by changes in population or exposure. The departure from the one‐to‐one relationship between a relative change in a nation's population or GDP and its relative change in flood risk could be used to inform further efforts at flood mitigation and adaptation.

[1]  Wolfgang Lutz,et al.  The human core of the shared socioeconomic pathways: Population scenarios by age, sex and level of education for all countries to 2100 , 2017, Global environmental change : human and policy dimensions.

[2]  Alanna Leigh Simpson,et al.  Understanding risk: what makes a risk assessment successful? , 2016 .

[3]  F. Wenzel,et al.  The economic costs of natural disasters globally from 1900-2015: historical and normalised floods, storms, earthquakes, volcanoes, bushfires, drought and other disasters , 2016 .

[4]  D. Guha-Sapir,et al.  EM-DAT: The CRED/OFDA International Disaster Database , 2016 .

[5]  P. Albini The Great 1667 Dalmatia Earthquake: An In-Depth Case Study , 2015 .

[6]  Brenden Jongman,et al.  Assessing flood risk at the global scale: model setup, results, and sensitivity , 2013 .

[7]  Richard P. Allan,et al.  Observed and simulated precipitation responses in wet and dry regions 1850–2100 , 2013 .

[8]  F. Piontek,et al.  A trend-preserving bias correction – the ISI-MIP approach , 2013 .

[9]  H. Winsemius,et al.  A framework for global river flood risk assessments , 2012 .

[10]  P. Bubeck,et al.  How reliable are projections of future flood damage , 2011 .

[11]  A. Sanghi,et al.  Natural hazards, unnatural disasters : the economics of effective prevention , 2011 .

[12]  James E. Daniell,et al.  The CATDAT damaging earthquakes database , 2011 .

[13]  A. Thomson,et al.  The representative concentration pathways: an overview , 2011 .

[14]  M. Bierkens,et al.  Global monthly water stress: 1. Water balance and water availability , 2011 .

[15]  H. Moel,et al.  Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates , 2011 .

[16]  K. Trenberth Changes in precipitation with climate change , 2011 .

[17]  Roberto Buizza,et al.  TIGGE: Preliminary results on comparing and combining ensembles , 2008 .

[18]  B. Merz,et al.  Quantification of uncertainties in flood risk assessments , 2008 .

[19]  Bruno Merz,et al.  Flood risk analysis: uncertainties and validation , 2008 .

[20]  P. Lucas,et al.  Downscaling drivers of global environmental change Enabling use of global SRES scenarios at the national and grid levels , 2007 .

[21]  S. Stiros The AD 365 Crete earthquake and possible seismic clustering during the fourth to sixth centuries AD in the Eastern Mediterranean: a review of historical and archaeological data , 2001 .

[22]  T. Rikitake,et al.  Global tectonics and earthquake risk , 1974 .

[23]  Jean Chateau,et al.  Long-term economic growth projections in the Shared Socioeconomic Pathways , 2017 .

[24]  James E. Daniell,et al.  Development of socio-economic fragility functions for use in worldwide rapid earthquake loss estimation procedures , 2014 .

[25]  J. Edmonds,et al.  A new scenario framework for climate change research: background, process, and future directions , 2013, Climatic Change.

[26]  Brian C. O'Neill,et al.  Meeting Report of the Workshop on The Nature and Use of New Socioeconomic Pathways for Climate Change Research , 2012 .

[27]  A. Constantin,et al.  VRANCEA ( ROMANIA ) SUBCRUSTAL EARTHQUAKES : HISTORICAL SOURCES AND MACROSEISMIC INTENSITY ASSESSMENT , 2011 .

[28]  N. Ambraseys Earthquakes in the Mediterranean and Middle East: Preface , 2009 .

[29]  M. R. Sbeinati,et al.  The historical earthquakes of Syria: an analysis of large and moderate earthquakes from 1365 B.C. to 1900 A.D. , 2009 .

[30]  D. Wald,et al.  Topographic Slope as a Proxy for Seismic Site-Conditions (VS30) and Amplification Around the Globe , 2007 .

[31]  Isdr,et al.  Global Facility for Disaster Reduction and Recovery , 2007 .

[32]  S. Solomon The Physical Science Basis : Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change , 2007 .

[33]  Tom Kram,et al.  Intergrated modelling of global environmenthal change : An overview of IMAGE 2.4 , 2006 .