The impacts of flooding are expected to rise due to population increases, economic growth and climate change. Hence, understanding the physical and spatiotemporal characteristics of risk drivers (hazard, exposure and vulnerability) is required to develop effective flood mitigation measures. Here, the long-term trend in flood vulnerability was analysed globally, calculated from the ratio of the reported flood loss or damage to the modelled flood exposure using a global river and inundation model. A previous study showed decreasing global flood vulnerability over a shorter period using different disaster data. The long-term analysis demonstrated for the first time that flood vulnerability to economic losses in upper-middle, lower-middle and low-income countries shows an inverted U-shape, as a result of the balance between economic growth and various historical socioeconomic efforts to reduce damage, leading to non-significant upward or downward trends. We also show that the flood-exposed population is affected by historical changes in population distribution, with changes in flood vulnerability of up to 48.9%. Both increasing and decreasing trends in flood vulnerability were observed in different countries, implying that population growth scenarios considering spatial distribution changes could affect flood risk projections.

Water‐related disasters, such as fluvial floods and cyclonic storm surges, are a major concern in the world's mega‐delta regions. Furthermore, the simultaneous occurrence of extreme discharges from rivers and storm surges could exacerbate flood risk, compared to when they occur separately. Hence, it is of great importance to assess the compound risks of fluvial and coastal floods at a large scale, including mega‐deltas. However, most studies on compound fluvial and coastal flooding have been limited to relatively small scales, and global‐scale or large‐scale studies have not yet addressed both of them. The objectives of this study are twofold: to develop a global coupled river‐coast flood model; and to conduct a simulation of compound fluvial flooding and storm surges in Asian mega‐delta regions. A state‐of‐the‐art global river routing model was modified to represent the influence of dynamic sea surface levels on river discharges and water levels. We conducted the experiments by coupling a river model with a global tide and surge reanalysis data set. Results show that water levels in deltas and estuaries are greatly affected by the interaction between river discharge, ocean tides and storm surges. The effects of storm surges on fluvial flooding are further examined from a regional perspective, focusing on the case of Cyclone Sidr in the Ganges‐Brahmaputra‐Meghna Delta in 2007. Modeled results demonstrate that a >3 m storm surge propagated more than 200 km inland along rivers. We show that the performance of global river routing models can be improved by including sea level dynamics.

Current global riverine flood risk studies assume a constant mean sea level boundary. In reality high sea levels can propagate up a river, impede high river discharge, thus leading to elevated water levels. Riverine flood risk in deltas may therefore be underestimated. This paper presents the first global scale assessment of the joint influence of riverine and coastal drivers of flooding in deltas. We show that if storm surge is ignored, flood depths are significantly underestimated for 9.3% of the expected annual population exposed to riverine flooding. The assessment is based on extreme water levels at 3433 river mouth locations as modeled by a state-of-the-art global river routing model, forced with a multi-model runoff ensemble and bounded by dynamic sea level conditions derived from a global tide and surge reanalysis. We first classified the drivers of riverine flooding at each location into four classes: surge-dominant, discharge-dominant, compound-dominant or insignificant. We then developed a model experiment to quantify the effect of surge on flood hazard and impacts. Drivers of riverine flooding are compound-dominant at 19.7% of the locations analyzed, discharge-dominant at 69.2%, and surge-dominant at 7.8%. Compared to locations with either surge- or discharge-dominant flood drivers, locations with compound-dominant flood drivers generally have larger surge extremes and are located in basins with faster discharge response and/or flat topography. Globally, surge exacerbates 1-in-10 years flood levels at 64.0% of the locations analyzed, with a mean increase of 11 cm. While this increase is generally larger at locations with compound- or surge-dominant flood drivers, flood levels also increase at locations with discharge-dominant flood drivers. This study underlines the importance of including dynamic downstream sea level boundaries in (global) riverine flood risk studies.

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<p>Current global riverine flood risk studies assume a constant mean sea level boundary. In reality, high sea levels can propagate up a river leading to elevated water levels, and/or the drainage of high river discharge can be impeded by elevated sea levels. Riverine flood risk in deltas might therefore be underestimated if dynamic sea levels are ignored. This contribution presents the first global scale assessment of drivers of riverine flooding in deltas and underlines the importance of including dynamic downstream sea level boundaries in global riverine flood risk studies.</p><p>The assessment is based on extreme water levels at 3433 river mouth locations as modeled by the state-of-the-art global river routing model CaMa-Flood, forced with a multi-model runoff ensemble from the EartH2Observe project and bounded by dynamic sea level conditions from the global tide and surge model GTSM. Using this framework, we classified the drivers of riverine flooding at each location into four classes: surge dominant, discharge dominant, compound or insignificant. The classification is based on rank correlations between annual maximum riverine water levels and surge levels, and annual maximum riverine water levels and discharge. We developed a model experiment to quantify the effect of surge on flood levels and impacts.</p><p>We find that drivers of riverine flooding are compound at 19.7 % of the locations analyzed, discharge dominant at 69.2 % and surge dominant at 7.8 %. Compared to locations with either surge or discharge dominant flood drivers, locations with compound flood drivers generally have larger surge extremes, are located in basins with faster discharge response and/or flat topography. Globally, surge exacerbates 1-in-10 years flood levels at 64.0 % of the locations analyzed, with a mean increase of 13.5 cm. While this increase is the largest at locations with compound or surge dominant flood drivers, surge also affects flood levels at locations with discharge dominant flood drivers. A small decrease in 1-in-10 years flood levels is observed at 12.2 % of locations analyzed due to negative seasonal component of surge associated with dominant seasonal gyre circulations. Finally, we show that if surge is ignored, flood depths are underestimated for 38.2 million out of a total of 332.0 million (11.6 %) expected annual mean people exposed to riverine flooding.</p>

Fluvial flood events are a major threat to people and infrastructure. Typically, flood hazard is driven by hydrologic or river routing and floodplain flow processes. Since they are often simulated by different models, coupling these models may be a viable way to increase the integration of different physical drivers of simulated inundation estimates. To facilitate coupling different models and integrating across flood hazard processes, we here present GLOFRIM 2.0, a globally applicable framework for integrated hydrologichydrodynamic modelling. We then tested the hypothesis that smart model coupling can advance inundation modelling in the Amazon and Ganges basins. By means of GLOFRIM, we coupled the global hydrologic model PCR-GLOBWB with the hydrodynamic models CaMa-Flood and LISFLOOD-FP. Results show that replacing the kinematic wave approximation of the hydrologic model with the local inertia equation of CaMa-Flood greatly enhances accuracy of peak discharge simulations as expressed by an increase in the Nash-Sutcliffe efficiency (NSE) from 0.48 to 0.71. Flood maps obtained with LISFLOOD-FP improved representation of observed flood extent (critical success index C = 0.46), compared to downscaled products of PCR-GLOBWB and CaMa-Flood (C = 0.30 and C = 0.25, respectively). Results confirm that model coupling can indeed be a viable way forward towards more integrated flood simulations. However, results also sug-gest that the accuracy of coupled models still largely depends on the model forcing. Hence, further efforts must be undertaken to improve the magnitude and timing of simulated runoff. In addition, flood risk is, particularly in delta areas, driven by coastal processes. A more holistic representation of flood processes in delta areas, for example by incorporating a tide and surge model, must therefore be a next development step of GLOFRIM, making even more physically robust estimates possible for adequate flood risk management practices.

Fine particulate matter (aerodynamic diameter<2.5 μm; PM2.5) poses risks to human health. While precipitation is the main process for decreasing ambient pollutant concentrations, scavenging of PM2.5 by precipitation remains to be investigated. Here we formulated the processes of PM2.5 scavenging by precipitation from observed PM2.5 concentrations ([PM2.5]) and precipitation intensities. Then we analyzed how changes in precipitation patterns would affect health risks related to PM2.5 on the basis of a Monte Carlo simulation. Tokyo, the capital of Japan, was selected as the target for this study because of its social significance. We found that [PM2.5] decreased significantly through scavenging of PM2.5 from the atmosphere by precipitation. In contrast, we found no significant correlation between reduction of [PM2.5] and precipitation intensity. Our model for estimating the reduction of PM2.5 and the Monte Carlo simulation showed good agreement with observations. Among various changes in potential precipitation patterns, changes in the arithmetic mean of the number of events and/or in precipitation duration were more influential on reduction of [PM2.5] than changes in their standard deviations. Health risks due to PM2.5 will increase with decreases in precipitation duration and occurrence.

We investigate hydrology during a past climate slightly warmer than the present: the last interglacial (LIG). With daily output of preindustrial and LIG simulations from eight new climate models we force hydrological model PCR-GLOBWB and in turn hydrodynamic model CaMa-Flood. Compared to preindustrial, annual mean LIG runoff, discharge, and 100-yr flood volume are considerably larger in the Northern Hemisphere, by 14%, 25%, and 82%, respectively. Anomalies are negative in the Southern Hemisphere. In some boreal regions, LIG runoff and discharge are lower despite higher precipitation, due to the higher temperatures and evaporation. LIG discharge is much higher for the Niger, Congo, Nile, Ganges, Irrawaddy, and Pearl and lower for the Mississippi, Saint Lawrence, Amazon, Paraná, Orange, Zambesi, Danube, and Ob. Discharge is seasonally postponed in tropical rivers affected by monsoon changes. Results agree with published proxies on the sign of discharge anomaly in 15 of 23 sites where comparison is possible. Plain Language Summary It is still uncertain how the water cycle will respond to a warmer climate in the coming decades. To increase our understanding of the relationships between climate and hydrology, we study the past climate of the last interglacial, which was slightly warmer than the present. We present the results of a modeling approach, showing that while Northern Hemisphere precipitation was higher during the last interglacial, discharge of rivers was even higher, and floods were even larger. On the contrary, in the Southern Hemisphere precipitation, discharge and floods were lower. We show that, for some regions, precipitation, discharge, and floods do not have the same direction of change. The seasonal timing of discharge also changes for some large basins of the Northern Hemisphere. Finally, for 23 sites, we compare our results to geological evidence. These results form a useful term of comparison to both projections of the future and geological studies of past hydrology.