Understanding global future river flood risk is a prerequisite for the quantification of climate change impacts and planning e ective adaptation strategies 1. Existing global flood risk projections fail to integrate the combined dynamics of expected socioeconomic development and climate change. We present the first global future river flood risk projections that separate the impacts of climate change and socioeconomic development. The projections are based on an ensemble of climate model outputs 2 , socioeconomic scenarios 3 , and a state-of-the-art hydrologic river flood model combined with socioeconomic impact models 4,5. Globally, absolute damage may increase by up to a factor of 20 by the end of the century without action. Countries in Southeast Asia face a severe increase in flood risk. Although climate change contributes significantly to the increase in risk in Southeast Asia 6 , we show that it is dwarfed by the e ect of socioeconomic growth, even after normalization for gross domestic product (GDP) growth. African countries face a strong increase in risk mainly due to socioeconomic change. However, when normalized to GDP, climate change becomes by far the strongest driver. Both highand low-income countries may benefit greatly from investing in adaptation measures, for which our analysis provides a basis. Between 1980 and 2013, the global direct economic losses due to floods exceeded $1 trillion (2013 values), and more than 220,000 people lost their lives 7. Global flood damages have been increasing steeply over the past decades, so far mainly driven by steady growth in population and economic activities in flood-prone areas 8,9. Future increases in flood frequency and severity due to changes in extreme weather are expected 1,9. Such increasing trends in flood risk may have severe direct humanitarian and economic impacts and lasting long-term negative effects on economic growth 10,11. In 2015, several major international policies are being initiated or renewed that may catalyse flood risk adaptation and hence risk reduction, such as the Sustainable Development Goals, Conference of the Parties (COP) 21, and the Sendai Framework for Disaster Risk Reduction. Such efforts require global understanding of the drivers of flood risk change in the future. Past efforts to enhance this understanding have focused on the global-scale mapping of present-day flood hazard 12,13 and risk 4,5 and future changes in global flood exposure and risk 14 due to either climate change 6,15,16 or socioeconomic development 8,17. One recent study 18 combined global socioeconomic and climate change into future global flood risk projections for the first time, however, this work did not reveal regional patterns nor quantify the drivers of risk change. Furthermore, no study has so far accounted for installed and maintained flood protection standards (FPS; ref. 10).

Globally, economic losses from flooding exceeded $19 billion in 2012, and are rising rapidly. Hence, there is an increasing need for global-scale flood risk assessments, also within the context of integrated global assessments. We have developed and validated a model cascade for producing global flood risk maps, based on numerous flood return-periods. Validation results indicate that the model simulates interannual fluctuations in flood impacts well. The cascade involves: hydrological and hydraulic modelling; extreme value statistics; inundation modelling; flood impact modelling; and estimating annual expected impacts. The initial results estimate global impacts for several indicators, for example annual expected exposed population (169 million); and annual expected exposed GDP ($1383 billion). These results are relatively insensitive to the extreme value distribution employed to estimate low frequency flood volumes. However, they are extremely sensitive to the assumed flood protection standard; developing a database of such standards should be a research priority. Also, results are sensitive to the use of two different climate forcing datasets. The impact model can easily accommodate new, user-defined, impact indicators. We envisage several applications, for example: identifying risk hotspots; calculating macro-scale risk for the insurance industry and large companies; and assessing potential benefits (and costs) of adaptation measures.

Abstract. Coastal flood hazard and exposure are expected to increase over the course of the 21st century, leading to increased coastal flood risk. In order to limit the increase in future risk, or even reduce coastal flood risk, adaptation is necessary. Here, we present a framework to evaluate the future benefits and costs of structural protection measures at the global scale, which accounts for the influence of different flood risk drivers (namely sea-level rise, subsidence, and socioeconomic change). Globally, we find that the estimated expected annual damage (EAD) increases by a factor of 150 between 2010 and 2080 if we assume that no adaptation takes place. We find that 15 countries account for approximately 90 % of this increase. We then explore four different adaptation objectives and find that they all show high potential in cost-effectively reducing (future) coastal flood risk at the global scale. Attributing the total costs for optimal protection standards, we find that sea-level rise contributes the most to the total costs of adaptation. However, the other drivers also play an important role. The results of this study can be used to highlight potential savings through adaptation at the global scale.

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Disasters such as floods, storms, heatwaves and droughts can have enormous implications for health, the environment and economic development. In this article, we address the question of how climate change might have influenced the impact of weather-related disasters. This relation is not straightforward, since disaster burden is not influenced by weather and climate events alone-other drivers are growth in population and wealth, and changes in vulnerability. We normalized disaster impacts, analyzed trends in the data and compared them with trends in extreme weather and climate events and vulnerability, following a 3 by 4 by 3 set-up, with three disaster burden categories, four regions and three extreme weather event categories. The trends in normalized disaster impacts show large differences between regions and weather event categories. Despite these variations, our overall conclusion is that the increasing exposure of people and economic assets is the major cause of increasing trends in disaster impacts. This holds for long-term trends in economic losses as well as the number of people affected. We also found similar, though more qualitative, results for the number of people killed; in all three cases, the role played by climate change cannot be excluded. Furthermore, we found that trends in historic vulnerability tend to be stable over time, despite adaptation measures taken by countries. Based on these findings, we derived disaster impact projections for the coming decades. We argue that projections beyond 2030 are too uncertain, not only due to unknown changes in vulnerability, but also due to increasing non-stationarities in normalization relations.