Global flood risk under climate change

Flooding is one of the most destructive natural hazards worldwide, with risks expected to rise sharply under climate change, sea-level rise, population growth in vulnerable areas, and unsustainable resource extraction. Global flood risk assessments have become essential tools for guiding international investments, policymaking, and disaster risk reduction (DRR) strategies. Yet, these models often privilege financial performance and engineered defences, while neglecting alternative solutions, social inclusivity, and the lived realities of marginalised groups. This thesis investigates how global flood risk assessments can evolve to incorporate a wider range of measures, decision-making metrics, and equity considerations, ultimately contributing to more effective and inclusive strategies for reducing flood risk. The study first evaluates global coastal flood risk, revealing that without intervention, annual damages could exceed USD 1 trillion by 2080. While traditional dykes and levees achieve the greatest risk reduction in monetary terms, alternative measures such as zoning restrictions, dry-proofing, and foreshore vegetation offer significant benefits when assessed through benefit-cost ratios. Importantly, all four measures studied return positive investment outcomes at the global scale, highlighting the economic viability of diverse DRR strategies. Riverine flood risk is then examined, with damages projected to increase nearly 50-fold by the end of the century in the absence of adaptation. Analysis across 180 sub-national regions shows striking differences in the cost-effectiveness of dykes, zoning restrictions, and dry-proofing depending on the metric applied. Notably, benefit-cost analysis and efficacy analysis often point to different “best” solutions, with three-quarters of regions arriving at different recommendations depending on the chosen metric. This finding underscores the importance of incorporating multiple approaches to decision-making rather than relying on a single evaluative lens. The role of Nature-based Solutions (NbS) is further explored through a global review of rural coastal contexts, which are typically overlooked in flood modelling despite being home to highly vulnerable populations. Evidence from 28 peer-reviewed cases illustrates that while NbS face significant barriers—including resource constraints and governance challenges—they can deliver co-benefits such as agricultural support, aquaculture opportunities, and ecotourism. Many successful examples emphasise the importance of local knowledge and community participation in implementation, suggesting that future global assessments should integrate these perspectives alongside economic metrics. Beyond technical measures, the thesis also addresses social vulnerability in global flood risk assessments. Current frameworks often ignore or inadequately capture the experiences of sexual and gender minorities, treating gender as a binary and excluding sexual orientation altogether. By combining global flood risk data with indicators of legal and social protections, this research highlights that tens of millions of people exposed to flood risk currently live without recognition or legal safeguards. These numbers are expected to rise significantly by 2050 if social and legal conditions remain static. This omission represents a major blind spot in international DRR frameworks and demonstrates the need for more inclusive, human rights-based approaches to flood resilience. The synthesis chapter argues for a redefinition of global flood risk assessments. Future models must account for a broader spectrum of adaptation measures evaluated with multiple decision-making metrics that move beyond financial efficiency alone. They must also reflect the diversity of exposure and vulnerability across societies, incorporating marginalised groups and overlooked regions. By embedding inclusivity, pluralism, and hybridised strategies into global frameworks, flood risk assessments can better inform equitable and sustainable pathways for reducing disaster impacts worldwide. In sum, this thesis demonstrates that global flood risk assessments are powerful tools, but only if they evolve to reflect the complex realities of climate change, societal vulnerability, and adaptation potential. Expanding their scope to include multiple strategies, diverse decision metrics, and equity considerations can enable more effective, just, and forward-looking disaster risk reduction in the decades ahead.

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5 × 0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km2 of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km2 of cropland, and the change in risk varies between −9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.

Editorial: steps towards global flood risk modelling

<p>The South Asian summer monsoon (SASM) system is one of the most energetic regional monsoon systems. Its onset and demise timings determine the propagation, duration, and magnitude of precipitation through thermodynamic and dynamic processes in the SASM-prevailing areas. Particularly, anomalous onsets and demises of the SASM could generate a large anomaly in precipitation and serious water-related disasters over the SASM-prevailing areas.</p><p>The South-Central Tibetan Plateau (SCTP), known as the “Asian water tower”, is the origin of several major Asian rivers, including the Yellow River, Yangtze River, Brahmaputra River, Mekong River, and the Indus River, providing a huge amount of freshwater for ecosystems and billions of people in Asia. It is widely known that the SCTP is controlled by the SASM system in summer, accounting for approximately 60% of annual precipitation, but with significant spatiotemporal heterogeneity due to the complex topographic and geographic conditions. Presently, most studies have focused on the effects and physical causes of the linear trend of SASM onset over the SCTP. However, little attention has been paid to the question as to how both anomalous onset and anomalous demise of the SASM influence the interannual precipitation variation in this region. In particular, the spatial manifestation of thermodynamic and dynamic mechanisms for the interannual precipitation variation is largely unknown. Adequate knowledge about these mechanisms is critical for sustainable freshwater management and water disasters control in this region and surrounding areas.</p><p>These call a detailed study to investigate the influences of the early and late onset (demise) of the SASM system on the interannual variations in precipitation and their underlying mechanisms over the SCTP. In this study, we mainly clarify the following key questions: (1) How do the onset and demise of the SASM control the interannual variations in precipitation over the SCTP? (2) Is there an asymmetric effect of the SASM on SCTP precipitation between its onset and demise, and between its early and late onset (demise)? and (3) What are the underlying mechanisms that are responsible for the variations in interannual precipitation? The results would help improve our understanding of the SASM-precipitation relationship over the SCTP and alleviation of water-related disasters in the region.</p>

Floods are one of the most prevalent natural disasters globally, causing huge annual losses to the population and economies of the world. Identifying the distribution and evolution of global flood risk is essential in context of the growing trend of extreme natural hazards under climate change. This study presents predictions of global flood risk based on Global Climate Models (GCMs) under four Shared Socioeconomic Pathways (SSPs). Here our results demonstrate that a slow increase trend in global flood risk under different scenarios. Currently, about 23% of the global area is at very high risk of floods, which are concentrated in regions with high rainfall, flat terrain, and dense population and economic densities, such as eastern China, Japan and the eastern US. By the end of the 21st century (2081-2100), according to the SSP5-8.5 scenario, the global flood risk increases by up to about 2% overall compared to the baseline period (2001-2020), with an increase in the area at medium, high, and very high flood risk of about 780,316 km2. Over global countries with different income levels, high-income countries typically have a higher risk of floods than low-income countries, with 8 of the 10 most at-risk countries in the world being high-income countries. Singapore, Japan, Luxembourg, and South Korea are among the group of countries with the highest flood risk in the world. This study constructs a framework for global flood risk prediction from disaster-inducing factor, disaster-breeding environment, and disaster-bearing body, rather than just meteorological factors. These results indicate an increasing trend in global flood risk as predicted by a combination of factors, and we need to take mitigation measures to prevent the acceleration of these risks.

Global river flood risk is expected to increase substantially over coming decades due to both climate change and socioeconomic development. Model-based projections suggest that southeast Asia and Africa are at particular risk, highlighting the need to invest in adaptation measures. Understanding global future river flood risk is a prerequisite for the quantification of climate change impacts and planning effective adaptation strategies1. Existing global flood risk projections fail to integrate the combined dynamics of expected socio-economic development and climate change. We present the first global future river flood risk projections that separate the impacts of climate change and socio-economic development. The projections are based on an ensemble of climate model outputs2, socio-economic scenarios3, and a state-of-the-art hydrologic river flood model combined with socio-economic impact models4,5. 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 Asia6, we show that it is dwarfed by the effect of socio-economic growth, even after normalization for gross domestic product (GDP) growth. African countries face a strong increase in risk mainly due to socio-economic change. However, when normalized to GDP, climate change becomes by far the strongest driver. Both high- and low-income countries may benefit greatly from investing in adaptation measures, for which our analysis provides a basis.

Precipitation variability in space and time has been a focus of research over the past decades. The largest body of literature was essentially focused on long-term changes in average climates and in climate extremes. Analyses of the changes in the inter-annual climate variability (the year-to-year variability), which represent an index of climatic risk, received instead very less attention, but it represents an important issue in order to quantitatively measure the socioeconomic impact of climate change impact over water resources. In order to depict a general characterization of the long-term climate variability for the Campania region, located in Southern Italy within the Mediterranean basin, an analysis of the precipitation coefficient of variation, assumed as an index of inter-annual climate variability, was performed over the period 1918–2015 and compared with the annual precipitation regime and the intra-annual precipitation variability of the same region. The Mann–Kendall and the modified Mann–Kendall tests were applied to detect the sign and significance of the temporal changes and Sen’s test was applied to quantify the temporal changes in inter-annual variability. The results illustrated a generalized condition (73% of total stations) of statistically significant increase of inter-annual variability distributed almost over the whole analyzed area, even though the detected change appeared rather moderate in magnitude. The relationship between annual precipitation, intra-annual precipitation variability, and inter-annual precipitation variability was not clearly identified for the studied region, likely because of the characteristics of climatic homogeneity for the area under investigation. However, the comparative analyzes clearly showed how, if the variations in the annual precipitation regime and in the intra-annual precipitation variability are poorly significant (respectively for 9% and 11% of total station), changes in inter-annual precipitation variability are strongly marked over the studied region.

Based on the Lagrangian particle dispersion model, HYSPLIT 4.9, this study analyzed the summertime atmospheric moisture sources and transportation pathways affecting six subregions across China. The sources were: Midlatitude Westerly (MLW), Siberian-Arctic regions (SibArc), Okhotsk Sea (OKS), Indian Ocean (IO), South China Sea (SCS), Pacific Ocean (PO), and China Mainland (CN). Furthermore, the relative contributions of these seven moisture sources to summertime precipitation in China were quantitatively assessed. Results showed that the CN precipitation source dominates the interannual and interdecadal variation of precipitation in most subregions, except Southwest and South China. The Northeast China vortex and Pacific–Japan (PJ) teleconnection, which transport water vapor from the MLW, OKS and PO sources, are crucial atmospheric systems and patterns for the variation of precipitation in Northeast China. The interannual variation of precipitation in Northwest and North China is mainly dominated by mid–high-latitude Eurasian wave trains, which provide the necessary dynamical conditions and associated moisture transport from the MLW and SibArc sources. In addition, an enhanced western North Pacific subtropical high (WNPSH) accompanied by the East Asian–western North Pacific summer monsoon and PJ teleconnection, transports extra moisture to North China from the SCS and PO sources, as well to the Yangtze River Valley and South China. The Indian summer monsoon (ISM) is also critically important for the interdecadal change in precipitation over the Yangtze River Valley and South China, via the southwesterly branch of moisture transport from the IO source. The interdecadal changes in precipitation over Southwest China are determined by the IO and SCS sources, via enhanced WNPSH coupling with a weakened ISM. These results suggest that the interdecadal and interannual variations of moisture sources contribute to the attendant variation of summertime precipitation in China via large-scale circulation regimes in both the mid–high and lower latitudes.

This article presents the first results of a three-year study that aimed at studying, understanding, and characterizing the evolution of flood risk in Quebec. In this study, flood risk is defined as the product of the return period of an event and the damages caused by this event. It is therefore important that both these components of the flood risk be assessed historically. The two components have been evaluated for a 32 km reach of the Châteauguay River located between the Canadian-American border and Ormstown, Quebec. A flood frequency analysis was undertaken on historical flow data for two gauging stations on the river and the data fitted with a log-Pearson type III distribution. The flood risk was then established using a three-step methodology. The first step was to establish flood levels over a range of discharges using a hydraulic model. Then the computed water levels were processed to define the flooded area and determine the property damage. The last step established the global flood risk, taking into account the complete flood distribution function. The results show that over the last 60 years, the global flood risk has increased for all of the study sites along the reach of interest. When the global flood risk is standardized based on population, the evolution of the risk differs greatly between study sites. For one site, the standardized global flood risk has increased by one order of magnitude over the period studied. The results also demonstrate that 75% of the global flood risk is due to floods having a return period of 4 years or less.Key words: flood, risk, damages, numerical modelling, flood forecasting.[Journal translation]

Projected change in the relationship between East Asian summer rainfall and upper-tropospheric westerly jet

Abstract. This paper describes an assessment of the implications of future climate change for river runoff across the entire world, using six climate models which have been driven by the SRES emissions scenarios. Streamflow is simulated at a spatial resolution of 0.5°x0.5&#176 using a macro-scale hydrological model, and summed to produce total runoff for almost 1200 catchments. The effects of climate change have been compared with the effects of natural multi-decadal climatic variability, as determined from a long unforced climate simulation using HadCM3. By the 2020s, change in runoff due to climate change in approximately a third of the catchments is less than that due to natural variability but, by the 2080s, this falls to between 10 and 30%. The climate models produce broadly similar changes in runoff, with increases in high latitudes, east Africa and south and east Asia, and decreases in southern and eastern Europe, western Russia, north Africa and the Middle East, central and southern Africa, much of North America, most of South America, and south and east Asia. The pattern of change in runoff is largely determined by simulated change in precipitation, offset by a general increase in evaporation. There is little difference in the pattern of change between different emissions scenarios (for a given model), and only by the 2080s is there evidence that the magnitudes of change in runoff vary, with emissions scenario A1FI producing the greatest change and B1 the smallest. The inter-annual variability in runoff increases in most catchments due to climate change — even though the inter-annual variability in precipitation is not changed — and the frequency of flow below the current 10-year return period minimum annual runoff increases by a factor of three in Europe and southern Africa and of two across North America. Across most of the world climate change does not alter the timing of flows through the year but, in the marginal zone between cool and mild climates, higher temperatures mean that peak streamflow moves from spring to winter as less winter precipitation falls as snow. The spatial pattern of changes in the 10-year return period maximum monthly runoff follows changes in annual runoff. Keywords: SRES emissions scenarios, climate change impacts on runoff, multi-decadal variability, macro-scale hydrological model, drought frequency, flood frequency

This study investigates the interannual variability of winter precipitation over the Three River Source (TRS) region in China based on precipitation observations collected at stations in the TRS region and reanalysis datasets for the period of 1980–2015. The results suggest that the TRS winter precipitation has distinct interannual variability with discordant trends in different months, that is, an increasing trend is found in November and February, a decreasing trend is found in other winter months, and interannual variations in precipitation are different in different months. The mechanisms for the interannual variation in monthly precipitation over the TRS region are significantly different in different winter months. The interannual variability of TRS precipitation in November is modulated by an anomalous westerly water vapour transport (WVT) branch. This anomalous WVT branch is related to a North Atlantic‐Europe‐Tibetan Plateau (NA‐E‐TP) wave‐train that originates in the North Atlantic due to the ocean–atmosphere interaction. In December, a circum‐global teleconnection (CGT) wave‐train can induce anomalous westerly WVT in the TRS region, resulting in increased precipitation there. This CGT wave‐train is triggered by warm SST anomalies in the central‐eastern tropical Pacific associated with the El Niño‐Southern Oscillation (ENSO). The interannual variability of TRS precipitation in January and February is affected by southwesterly WVT anomalies over the TRS region, which are associated with a southeastward propagating wave‐train over Eurasia caused by the North Atlantic Oscillation (NAO). In March, the interannual variability of TRS precipitation is modulated by the leading mode of the Eurasian circulation that resembles the Scandinavian (EU1) pattern, which can cause anomalous southwesterly WVT in the TRS region. In winter, the characteristics of sea surface temperature anomalies, weather systems, and atmospheric circulations associated with interannual variations of monthly precipitation in the TRS region are different for individual winter months.

Effect of species-independent conspecific and heterospecific density dependence is contingent on seedling growth stage, season, and climate conditions

In the context of global climate change, floods have become one of the major natural disasters affecting the safety of human life, economic construction, and sustainable development. Despite significant improvements in flood risk and exposure modeling in some studies, there is still a lack of evidence on the spatiotemporal distribution patterns associated with flood risk across the globe. Meanwhile, numerous studies mostly explore flood risk distribution patterns based on specific spatial scales, ignoring to some extent the fact that flood risk has different distribution patterns on different scales. Here, on the basis of hazard–vulnerability components quantified using game theory (GT), we proposed a framework for analyzing the spatiotemporal distribution patterns of global flood risk and the influencing factors behind them on multiple scales. The results revealed that global flood risk increased during 2005–2020, with the percentages of high-risk areas being 4.3%, 4.48%, 4.6%, and 5.02%, respectively. There were 11 global risk hotspots, mainly located in areas with high population concentration, high economic density, abundant precipitation, and low elevation. On the national scale, high-risk countries were mainly concentrated in East Asia, South Asia, Central Europe, and Western Europe. In our experiment, developed countries accounted for the majority of the 20 highest risk countries in the world, with Singapore being the highest risk country and El Salvador having the highest positive risk growth rate (growing by 19.05% during 2015–2020). The findings of this study offer much-needed information and reference for academics researching flood risk under climate change.

This study investigated the long-term trends and interannual variations (IAVs) of seasonal precipitation during two different periods in India and their relation to atmospheric circulation. To focus on the relation between the regional characteristics of precipitation and the large-scale circulation system, we defined homogeneous regions based on pentad rainfall seasonality using hierarchical cluster analysis. Seven obtained clusters (regions) were used to analyze the long-term trends, IAVs, and their relation to atmospheric circulation. Seasonal precipitation showed no remarkable trend in most regions and seasons, which implies the effect of IAV in seasonal precipitation is greater than the long-term trend. Based on regression analysis, the IAV of seasonal precipitation and its relation to atmospheric circulation over the ocean surrounding India were detected for each season. Enhancement of the southwesterly monsoon flow over the Indian Ocean and the strength of the southeasterly wind related to the activity of the monsoon trough around the Gangetic Plain both affected the increase of summer monsoon precipitation in regions CL3 (central and eastern India) and CL6 (western coast of the Arabian Sea in southern India). In contrast, neither region CL5 (eastern coastal region of southern India) nor CL7 (northeastern India and part of the western coastal region of southern India) showed a relationship between IAV of summer monsoon precipitation and the southwesterly flow or the southeasterly flow over the Indian Ocean or the Gangetic Plain, respectively. Region CL5 showed strong correlation with the northeasterly monsoon flow (strength of the southeasterly flow over the Bay of Bengal) during the post-monsoon season. Other regions showed no relation with the northeasterly flow during the post-monsoon season. Furthermore, IAV of precipitation in region CL7 showed no correlation with either the southwesterly monsoon during the summer monsoon season or the northeasterly monsoon during the post-monsoon season.