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

Abstract

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.Plain Language Summary Floods and earthquakes affect the economy and population of countries in Eastern Europe and Central Asia. Future changes in these countries' economies and population will change the impacts of floods and earthquakes. In addition, future changes in climate will change how often flooding occurs. We assume that earthquake occurrence won't change with climate changes. We show how much the economies and populations of these countries are affected by floods and earthquakes in 2015, 2030 and 2080. However, as we don't know for certain how the economies, population and climate will change in the future, we show result for a variety of scenarios for future economies, population and climate. We assess how future changes in the economy and population affect future flood risk using changes in earthquake risk, and assume the remaining change is caused by changes in climate. We suggest that for some countries the population affected by floods can increase even with a decrease in population, or the population affected by floods and decrease even with an increase in population, if the future change in flood hazard is sufficiently large.

The Asynergies of Structural Disaster Risk Reduction Measures: Comparing Floods and Earthquakes

“…In this article, we assess the asynergies of structural, residential building-level DRR measures that are aimed at reducing the impacts of two independent hazards that threaten the same country. A case study of Afghanistan is used to quantify changing risk, expressed in terms of AAL (similar to Murnane et al (2017)), due to asynergies between flood and earthquake building-level DRR measures. The asynergies are assessed by creating two DRR scenarios: in the first scenario, the structural, residential building-level DRR measures are designed to decrease the impacts of fluvial flooding and in the second scenario they are designed to decrease the impacts of earthquakes.…”

“…This is expected to continue in the future, with projections estimating that the world's population will have doubled between 1950 and 2050, which requires the construction of an additional 1 billion housing units (Bilham, 2009). Moreover, social inequalities cause developing countries and the poor to suffer disproportionally from the impacts of natural hazards (Bacigalupe, 2019; Di Baldassarre et al., 2010; Hallegatte et al., 2018; Murnane et al., 2017; Winsemius et al., 2018) and their built environment is especially vulnerable to the impacts of natural hazards (Alexander, 2017; Balica et al., 2015). For these countries it is especially important to improve our understanding of the potential of disaster risk reduction (DRR) measures to reduce risk (Kreibich et al., 2015).…”

“…A commonly used metric in multirisk studies is the average annual losses (AALs; Delmonaco et al., 2006). This has, for example, been applied in the EU Directive on multirisk mapping (Delmonaco et al., 2006) and in other studies comparing flood and earthquake risk (e.g., Murnane et al., 2017).…”

Data-Driven Community Flood Resilience Prediction

“…Over the years, numerous researchers have embarked on flood categorization and prediction studies [20][21][22][23]. However, most such studies focused on the hazard's features and, to a lesser extent, on the direct impact and losses due to the flood hazard or long-term recovery cost and time [24][25][26][27][28][29]. In this respect, this study aims at developing a prediction framework that classifies the long-term potential impacts, recovery, and resilience of the exposed community, a categorization that captures the resilience of the exposed communities rather than simply the hazard's characteristics.…”

Improving flood damage assessments in data-scarce areas by retrieval of building characteristics through UAV image segmentation and machine learning – a case study of the 2019 floods in southern Malawi

“…A priori flood damage assessments are generally modeled and require extensive datasets on flood hazard characteristics, the exposed elements at risk and the vulnerability of these elements (Budiyono et al, 2015;Alam, L. Wouters et al: Improving flood damage assessments in data-scarce areas UNDRR, 2019). Much work has focused on improving these damage estimates, quantifying the effect of different flood scenarios and the consequences (Murnane et al, 2017;Jongman et al, 2012;. Unfortunately, sufficient information on the exposure and vulnerability is often lacking or less accessible in developing countries (van den Homberg and Susha, 2018).…”