Floods are a natural hazard that affect communities worldwide, but to date the vast majority of flood hazard research and mapping has been undertaken by wealthy developed nations. As populations and economies have grown across the developing world, so too has demand from governments, businesses, and NGOs for modeled flood hazard data in these data‐scarce regions. We identify six key challenges faced when developing a flood hazard model that can be applied globally and present a framework methodology that leverages recent cross‐disciplinary advances to tackle each challenge. The model produces return period flood hazard maps at ∼90 m resolution for the whole terrestrial land surface between 56°S and 60°N, and results are validated against high‐resolution government flood hazard data sets from the UK and Canada. The global model is shown to capture between two thirds and three quarters of the area determined to be at risk in the benchmark data without generating excessive false positive predictions. When aggregated to ∼1 km, mean absolute error in flooded fraction falls to ∼5%. The full complexity global model contains an automatically parameterized subgrid channel network, and comparison to both a simplified 2‐D only variant and an independently developed pan‐European model shows the explicit inclusion of channels to be a critical contributor to improved model performance. While careful processing of existing global terrain data sets enables reasonable model performance in urban areas, adoption of forthcoming next‐generation global terrain data sets will offer the best prospect for a step‐change improvement in model performance.

Rising global temperature has put increasing pressure on understanding the linkage between atmospheric warming and the occurrence of natural hazards. While the Paris Agreement has set the ambitious target to limiting global warming to 1.5 ∘ C compared to preindustrial levels, scientists are urged to explore scenarios for different warming thresholds and quantify ranges of socioeconomic impact. In this work, we present a framework to estimate the economic damage and population affected by river floods at global scale. It is based on a modeling cascade involving hydrological, hydraulic and socioeconomic impact simulations, and makes use of state-of-the-art global layers of hazard, exposure and vulnerability at 1-km grid resolution. An ensemble of seven high-resolution global climate projections based on Representative Concentration Pathways 8.5 is used to derive streamflow simulations in the present and in the future climate. Those were analyzed to assess the frequency and magnitude of river floods and their impacts under scenarios corresponding to 1.5 ∘ C, 2 ∘ C, and 4 ∘ C global warming. Results indicate a clear positive correlation between atmospheric warming and future flood risk at global scale. At 4 ∘ C global warming, countries representing more than 70% of the global population and global gross domestic product will face increases in flood risk in excess of 500%. Changes in flood risk are unevenly distributed, with the largest increases in Asia, U.S., and Europe. In contrast, changes are statistically not significant in most countries in Africa and Oceania for all considered warming levels.

Abstract. EURO-CORDEX (Coordinated Downscaling Experiment over Europe), a new generation of downscaled climate projections, has become available for climate change impact studies in Europe. New opportunities arise in the investigation of potential effects of a warmer world on meteorological and hydrological extremes at regional scales. In this work, an ensemble of EURO-CORDEX RCP8.5 scenarios is used to drive a distributed hydrological model and assess the projected changes in flood hazard in Europe through the current century. Changes in magnitude and frequency of extreme streamflow events are investigated by statistical distribution fitting and peak over threshold analysis. A consistent method is proposed to evaluate the agreement of ensemble projections. Results indicate that the change in frequency of discharge extremes is likely to have a larger impact on the overall flood hazard as compared to the change in their magnitude. On average, in Europe, flood peaks with return periods above 100 years are projected to double in frequency within 3 decades.

Higher evaporative demands and more frequent and persistent dry spells associated with rising temperatures suggest that drought conditions could worsen in many regions of the world. In this study, we assess how drought conditions may develop across the globe for 1.5, 2, and 3°C warming compared to preindustrial temperatures. Results show that two thirds of global population will experience a progressive increase in drought conditions with warming. For drying areas, drought durations are projected to rise at rapidly increasing rates with warming, averaged globally from 2.0 month/°C below 1.5°C to 4.2 month/°C when approaching 3°C. Drought magnitudes could double for 30% of global landmass under stringent mitigation. If contemporary warming rates continue, water supply‐demand deficits could become fivefold in size for most of Africa, Australia, southern Europe, southern and central states of the United States, Central America, the Caribbean, north‐west China, and parts of Southern America. In approximately 20% of the global land surface, drought magnitude will halve with warming of 1.5°C and higher levels, mainly most land areas north of latitude 55°N, but also parts of South America and Eastern and South‐eastern Asia. A progressive and significant increase in frequency of droughts is projected with warming in the Mediterranean basin, most of Africa, West and Southern Asia, Central America, and Oceania, where droughts are projected to happen 5 to 10 times more frequent even under ambitious mitigation targets and current 100‐year events could occur every two to five years under 3°C of warming.

Abstract. Anticipation and preparedness for large-scale flood events have a key role in mitigating their impact and optimizing the strategic planning of water resources. Although several developed countries have well-established systems for river monitoring and flood early warning, figures of populations affected every year by floods in developing countries are unsettling. This paper presents the Global Flood Awareness System (GloFAS), which has been set up to provide an overview on upcoming floods in large world river basins. GloFAS is based on distributed hydrological simulation of numerical ensemble weather predictions with global coverage. Streamflow forecasts are compared statistically to climatological simulations to detect probabilistic exceedance of warning thresholds. In this article, the system setup is described, together with an evaluation of its performance over a two-year test period and a qualitative analysis of a case study for the Pakistan flood, in summer 2010. It is shown that hazardous events in large river basins can be skilfully detected with a forecast horizon of up to 1 month. In addition, results suggest that an accurate simulation of initial model conditions and an improved parameterization of the hydrological model are key components to reproduce accurately the streamflow variability in the many different runoff regimes of the earth.