Declining vulnerability to river floods and the global benefits of adaptation

Exploring the fidelity of satellite precipitation products in capturing flood risks: A novel framework incorporating hazard and vulnerability dimensions over a sensitive coastal multi-hazard catchment

Complexities involved in flood risks over global coastal multi-hazard catchments are a severe concern for vulnerable communities, infrastructure, and the environment. Data scarcity in these regions often hinders our holistic understanding of flood risks, especially when socio-economic and physical vulnerabilities are involved. The extent to which Satellite Precipitation Products (SPPs), which are looked upon as alternatives to ground-based observations, can influence flood risk dynamics remains unexplored. In an attempt to answer the most riveted questions in flood management literature, this study, for the first time, explores the suitability of two competent SPPs, i.e., CHIRPS v2.0 and PERSIANN-CDR, in multi-hazard flood risk mapping. The proposed framework is demonstrated over the sensitive flood-prone deltaic stretches of the Lower Mahanadi River Basin (India). A computationally efficient MIKE+ 1D2D hydrodynamic model is developed to account for the wave propagation of concurrent flood drivers and generate high-resolution flood hazard maps for three disastrous historical flood events (July 2019, September 2020, and August 2022). To understand the hidden characteristics of vulnerability, a comprehensive set of 24 physical and socio-economic indicators is considered in a Shannon-entropy and TOPSIS framework. The variations in flood risk from both SPPs at the finest administrative scale are represented using the novel concept of Bivariate Choropleth, which portrays the marginal and compound contributions of hazard and vulnerability. A superlative performance of CHIRPS v2.0 over PERSIANN-CDR was observed in capturing hydro-climatological behaviors. CHIRPS v2.0-derived flood hazards were found analogous to the SAR-derived maps for all the three events. >70 % of villages display large disparities in flood risk, thereby affirming the role of appropriate SPPs towards efficient flood management. The observations from the study add vital information to the existing flood management policies, especially over resource-constrained regions in low and middle-income nations.

Current and projected flood exposure for Alaska coastal communities

Globally, coastal communities experience flood hazards that are projected to worsen from climate change and sea level rise. The 100-year floodplain or record flood are commonly used to identify risk areas for planning purposes. Remote communities often lack measured flood elevations and require innovative approaches to estimate flood elevations. This study employs observation-based methods to estimate the record flood elevation in Alaska communities and compares results to elevation models, infrastructure locations, and sea level rise projections. In 46 analyzed communities, 22% of structures are located within the record floodplain. With sea level rise projections, this estimate increases to 30-37% of structures by 2100 if structures remain in the same location. Flood exposure is highest in western Alaska. Sea level rise projections suggest northern Alaska will see similar flood exposure levels by 2100 as currently experienced in western Alaska. This evaluation of record flood height, category, and history can be incorporated into hazard planning documents, providing more context for coastal flood exposure than previously existed for Alaska. This basic flood exposure method is transferable to other areas with similar mapping challenges. Identifying current and projected hazardous zones is essential to avoid unintentional development in floodplains and improve long-term safety.

Citizen scientists' engagement in flood risk-related data collection: a case study in Bui River Basin, Vietnam

Time constraints, financial limitations, and inadequate tools restrict the flood data collection in undeveloped countries, especially in the Asian and African regions. Engaging citizens in data collection and contribution has the potential to overcome these challenges. This research demonstrates the applicability of citizen science for gathering flood risk-related data on residential flooding, land use information, and flood damage to paddy fields for the Bui River Basin in Vietnam. Locals living in or around flood-affected areas participated in data collection campaigns as citizen scientists using self-investigation or investigation with a data collection app, a web form, and paper forms. We developed a community-based rainfall monitoring network in the study area using low-cost rain gauges to draw locals' attention to the citizen science program. Fifty-nine participants contributed 594 completed questionnaires and measurements for four investigated subjects in the first year of implementation. Five citizen scientists were active participants and contributed more than 50 completed questionnaires or measurements, while nearly 50% of citizen scientists participated only one time. We compared the flood risk-related data obtained from citizen scientists with other independent data sources and found that the agreement between the two datasets on flooding points, land use classification, and the flood damage rate to paddy fields was acceptable (overall agreement above 73%). Rainfall monitoring activities encouraged the participants to proactively update data on flood events and land use situations during the data collection campaign. The study's outcomes demonstrate that citizen science can help to fill the gap in flood data in data-scarce areas.

Economic assessment of nature-based solutions to reduce flood risk and enhance co-benefits

Flooding is expected to increase due to climate change, urbanisation, and land use change. To address this issue, Nature-Based Solutions (NBSs) are often adopted as innovative and sustainable flood risk management methods. Besides the flood risk reduction benefits, NBSs offer co-benefits for the environment and society. However, these co-benefits are rarely considered in flood risk management due to the inherent complexities of incorporating them into economic assessments. This research addresses this gap by developing a comprehensive methodology that integrates the monetary analysis of co-benefits with flood risk reduction in economic assessments. In doing so, it aspires to provide a more holistic view of the impact of NBS in flood risk management. The assessment employs a framework based on life-cycle cost-benefit analysis, offering a systematic and transparent assessment of both costs and benefits over time supported by key indicators like net present value and benefit cost ratio. The methodology has been applied to the Tamnava basin in Serbia, where significant flooding occurred in 2014 and 2020. The methodology offers valuable insights for practitioners, researchers, and planners seeking to assess the co-benefits of NBS and integrate them into economic assessments. The results show that when considering flood risk reduction alone, all considered measures have higher costs than the benefits derived from avoiding flood damage. However, when incorporating co-benefits, several NBS have a net positive economic impact, including afforestation/reforestation and retention ponds with cost-benefit ratios of 3.5 and 5.6 respectively. This suggests that incorporating co-benefits into economic assessments can significantly increase the overall economic efficiency and viability of NBS.

Societal determinants of flood-induced displacement

What explains human consequences of weather-related disaster? Here, we explore how core socioeconomic, political, and security conditions shape flood-induced displacement worldwide since 2000. In-sample regression analysis shows that extreme displacement levels are more likely in contexts marked by low national income levels, nondemocratic political systems, high local economic activity, and prevalence of armed conflict. The analysis also reveals large residual differences across continents, where flood-induced displacement in the Global South often is much more widespread than direct human exposure measures would suggest. However, these factors have limited influence on our ability to accurately predict flood displacement on new data, pointing to important, hard-to-operationalize heterogeneity in flood impacts across contexts and critical data limitations. Although results are consistent with an interpretation that the sustainable development agenda is beneficial for disaster risk reduction, better data on societal consequences of natural hazards are critically needed to support evidence-based decision-making.

A hydrologic similarity-based parameters dynamic matching framework: Application to enhance the real-time flood forecasting

Conventional hydrological modeling is usually based on the assumption that parameters are statically time-invariant. However, recent studies suggest that the influences of climate change and human interventions have made this hypothesis questionable. Meanwhile, machine learning techniques are increasingly used to extract patterns and insights from the ever-increasing hydrometeorological data. Here, we proposed a hybrid framework (HSPDM) to improve the precision of real-time flood forecasting in response to nonstationary conditions. It utilizes multiple machine learning techniques to dynamically retrieve calibrated hydrological model parameters from historical similar floods, thus continuously obtaining hourly time-variant parameters in real-time flood forecasting operations. Using the Quzhou Basin in China as a case study, the effectiveness and advancement of HSPDM framework was examined. Three schemes, including traditional time-invariant parameters (scheme 1), hourly time-variant parameters (scheme 2), and probabilistic forecasting scheme (scheme 3), were built for comparison purpose. The results were summarized as follows: (1) The proposed framework can successfully identify continuous flood subsequence with a high retrieval accuracy (1.74) and acceptable time consumption (175.05 s) by adopting k-means, K-Nearest Neighbor (KNN), and embedding-based subsequence matching (EBSM) method. (2) Compared to scheme 1, scheme 2 provided more reliable forecasting results with higher accuracies, in terms of the general goodness-of-fit (higher NSE value) and reproducing flood peak and flood process. (3) The streamflow hydrographs forecasted by scheme 2 fell exactly in the predictive uncertainty bounds of scheme 3 and even showed superiority compared to a preferred deterministic forecast (Q50) of scheme 3. The major scientific contribution of this study lies in advancing the technique of real-time flood forecasting based on the hourly time-variant model parameters, thereby strengthening our understanding of model behaviors under changing conditions. The proposed framework can also act as a new alternative for flood control and ultimately contribute to the mitigation of flooding disasters.

Adaptation constraints in scenarios of socio-economic development

Climate change adaptation is paramount, but increasing evidence suggests that adaptation action is subject to a range of constraints. For a realistic assessment of future adaptation prospects, it is crucial to understand the timescales needed to overcome these constraints. Here, we combine data on documented adaptation from the Global Adaptation Mapping Initiative with national macro indicators and assess future changes in adaptation constraints alongside the Shared Socioeconomic Pathways, spanning a wide range of future socio-economic development scenarios. We find that even in the most optimistic scenario, it will take until well after 2050 to overcome key constraints, which will limit adaptation for decades to come particularly in vulnerable countries. The persistence of adaptation constraints calls for stringent mitigation, improved adaptation along with dedicated finance and increasing efforts to address loss and damage. Our approach allows to ground truth indicators that can be further used in climate modelling efforts, improving the representation of adaptation and its risk reduction potential.

Exploring the spatial pattern of house collapse rates caused by extreme rainfall in central China: The role of natural and social factors

The collapse of houses represents a prominent hazard associated with floods, mudslides, and other disastrous events resulting from extreme rainfall. Nevertheless, previous research in this area has been insufficiently dedicated to comprehending the factors that specifically contribute to house collapse triggered by extreme rainfall. This study endeavors to address this knowledge gap by proposing a hypothesis that the occurrence of house collapse, induced by extreme rainfall, demonstrates spatial heterogeneity and is subject to the interactive impacts of various factors. In the study, we investigate the relationship between house collapse rates and natural and social factors in the provinces of Henan, Shanxi, and Shaanxi provinces in 2021. These provinces are representative of flood-prone areas in central China. Spatial scan statistics and GeoDetector model were used to analyze spatial hotspot areas of house collapse rates and determinant power of natural and social factors on the spatial heterogeneity of house collapse rates, respectively. Our analysis reveals that the spatial hotspot areas predominantly concentrated in regions characterized by high rainfall, including areas along riverbanks and low-lying regions. Multiple factors contribute to the variations in house collapse rates. Among these factors, precipitation (q = 0.32) is the most significant, followed by the ratio of brick-concrete houses (q = 0.24), per capita GDP (q = 0.13), elevation (q = 0.13) and other factors. Notably, the interaction of precipitation and slope explains 63 % of the damage pattern, making it the strongest causal factor. The results substantiate our initial hypothesis and underscore the fact that the pattern of damage does not solely rely on a singular factor but rather on the interaction of multiple factors. These findings hold significance in advancing the formulation of more precise strategies aimed at bolstering safety measures and safeguarding properties within regions susceptible to flooding.

Characterizing the level of urban Flood vulnerability using the social-ecological-technological systems framework, the case of Adama city, Ethiopia

This study characterizes the flood vulnerability of Adama City, Ethiopia, where the city faces high flood vulnerability due to its unplanned urbanization in low-lying floodplain areas surrounding deforested mountains and ridges. The study applied an interlinked Social-Ecological-Technological-Systems (SETS) vulnerability framework using a GIS-based Multi-Criteria Decision-Making and Analytical Hierarchy Process (MCDM-AHP). The framework analyzed exposure, sensitivity, and adaptive capacity to flooding for each of the three SETS domains. The study analyzed 18 variables at the city level within each SETS domain. The result revealed that clusters of flood-vulnerable areas were identified by each SETS domain showing the concentration of flood vulnerability in the study area and the need to consider prompt adaptive mechanisms to severe and recurring flooding. The finding has significant implications for holistic approaches to sustainable cities. Moreover, the reduction of complex urban flood vulnerabilities according to their priority as individual or combined solutions for decision-makers and professionals in early warning and flood management systems is the other contribution of the study.

Human displacements, fatalities, and economic damages linked to remotely observed floods

We present a new open source dataset FLODIS that links estimates of flood-induced human displacements, fatalities, and economic damages to flooded areas observed through remote sensing. The dataset connects displacement data from the Internal Displacement Monitoring Centre (IDMC), as well as data on fatalities and damages from the Emergency Events Database (EM-DAT), with the Global Flood Database (GFD), a satellite-based inventory of historic flood footprints. It thereby provides a spatially explicit estimate of the flood hazard underlying each individual disaster event. FLODIS contains two datasets with event-specific information for 335 human displacement events and 695 mortality/damage events that occurred around the world between 2000 and 2018. Additionally, we provide estimates of affected population, GDP, and critical infrastructure, as well as socio-economic indicators; and we provide geocoding for displacement events ascribed to other types of disasters, such as tropical cyclones, so that they may be linked to corresponding hazard estimates in future work. FLODIS facilitates integrated flood risk analysis, allowing, for example, for detailed assessments of local flood-damage and displacement vulnerability.

Satellites reveal hotspots of global river extent change

Rivers are among the most diverse, dynamic, and productive ecosystems on Earth. River flow regimes are constantly changing, but characterizing and understanding such changes have been challenging from a long-term and global perspective. By analyzing water extent variations observed from four-decade Landsat imagery, we here provide a global attribution of the recent changes in river regime to morphological dynamics (e.g., channel shifting and anabranching), expansion induced by new dams, and hydrological signals of widening and narrowing. Morphological dynamics prevailed in ~20% of the global river area. Booming reservoir constructions, mostly skewed in Asia and South America, contributed to ~32% of the river widening. The remaining hydrological signals were characterized by contrasting hotspots, including prominent river widening in alpine and pan-Arctic regions and narrowing in the arid/semi-arid continental interiors, driven by varying trends in climate forcing, cryospheric response to warming, and human water management. Our findings suggest that the recent river extent dynamics diverge based on hydroclimate and socio-economic conditions, and besides reflecting ongoing morphodynamical processes, river extent changes show close connections with external forcings, including climate change and anthropogenic interference.

Natural hazard insurance outcomes at national, regional and local scales: A comparison between Sweden and Portugal

This study addresses the role of natural hazard insurance in two European countries with different insurance markets and socioeconomic conditions: Sweden and Portugal. The analyses were conducted at the national, regional (Southern Sweden and Lisbon Metropolitan Area - LMA), and local (Malmö and Lisbon cities) scales. Most damage caused by weather and climate-related (WCR) hazards during the 1980-2019 period was not covered by insurance companies in Sweden (71%) and Portugal (91%). An insurance affordability analysis was performed using income for the national and regional scales. Unaffordability is higher in Southern Sweden than in LMA, implying that better socioeconomic conditions do not necessarily mean a higher average capacity to pay for insurance. At the local scale, urban flooding was analysed for Malmö (1996-2019) and Lisbon (2000-2011) using insurance databases, in which the most relevant 21st century rainfall events for each city are included (2014 and 2008, respectively). The influence of terrain features on flooding claims and payouts was determined using Geographic Information Systems (GIS) spatial analyses. The flat Malmö favours ponding and extensive flooding, while the distance to the drainage network and flow accumulation are key factors to promote flooding along valley bottoms in the hilly Lisbon. Flooding hotspots tend to result from a combination of higher depths/lower velocities (accumulation of floodwaters and ponding) and not from a pattern of lower depths/higher velocities (shallow overland flow). More detailed data on insurance, flooding, and socioeconomic conditions, at regional and mainly local scales, is needed to improve affordability and urban flooding risk assessments.

The impact of flooding on food security across Africa

Recent record rainfall and flood events have prompted increased attention to flood impacts on human systems. Information regarding flood effects on food security is of particular importance for humanitarian organizations and is especially valuable across Africa's rural areas that contribute to regional food supplies. We quantitatively evaluate where and to what extent flooding impacts food security across Africa, using a Granger causality analysis and panel modeling approaches. Within our modeled areas, we find that ∼12% of the people that experienced food insecurity from 2009 to 2020 had their food security status affected by flooding. Furthermore, flooding and its associated meteorological conditions can simultaneously degrade food security locally while enhancing it at regional spatial scales, leading to large variations in overall food security outcomes. Dedicated data collection at the intersection of flood events and associated food security measures across different spatial and temporal scales are required to better characterize the extent of flood impact and inform preparedness, response, and recovery needs.

Potential impact of diversion canals and retention areas as climate change adaptation measures on flood risk reduction: A hydrological modelling case study from the Chao Phraya River Basin, Thailand

The countries of Southeast Asia are projected to experience severe flood damage and economic impacts from climate change, compared with the global average. Hence adaptation by incorporating infrastructures is essential, but it has been seldom explicitly included in the simulations projecting climate change impacts on flood risk in these countries. Quantifying the effects of infrastructure is the key to climate change impact and adaptation assessment. Therefore, this study was conducted in the Chao Phraya River Basin (CPRB) in Thailand to examine the adaptation potential of (i) existing structural and non-structural measures that include reservoir and diversion dams, diversion canals, and water retention areas, and (ii) the combined adaptation measures, a combination of alterations made to the existing diversion canals and retention areas, on reducing future floods using the H08 global hydrological model (GHM). The results revealed that the impact of existing measures on the future flood reduction was smaller than the increase caused by warming in the CPRB. Conversely, the combined adaptation measures successfully mitigated the effect of warming by redirecting nearly 50 % of the diverted river flow to the ocean and storing 30 % of the diverted flow in the retention areas. Although a remarkable reduction was noted in the basin-wide flood risk, the effect of adaptation measures greatly varied across the basin. The combined adaptation measures largely reduced the number of flooding days by close to 100 at many of the considered stations within the basin, except for extreme flood events (historical 1-percentile flood events). This further reveals that the feasibility of adaptation measures in alleviating the extreme future floods will be limited in flood-vulnerable basins and thus require area-based prioritization for flood management. The modelling framework implemented in this study can be easily adapted to different GHMs and regions and should be examined for their applicability.

Vulnerability to typhoons: A comparison of consequence and driving factors between Typhoon Hato (2017) and Typhoon Mangkhut (2018)

Typhoon disasters have caused casualties, property loss, and other negative impacts to social and economic development. Vulnerability is an important component of typhoon risk. However, little is known about the contributions of vulnerability factors and their interaction effects on typhoon-induced losses at a fine scale. Focusing on the vulnerability measures of Typhoon Hato in 2017 and Typhoon Mangkhut in 2018, this study aims to quantify the contribution and interactive effects of physical and socioeconomic factors on vulnerability based on the GeoDetector method and determine the factors that account for most of the change in vulnerability. The results show that from Typhoon Hato in 2017 to Typhoon Mangkhut in 2018, the vulnerability of the economy and houses decrease on average. Rain intensity and wind intensity are the dominant factors of disaster loss for Typhoon Hato and Typhoon Mangkhut, respectively. Vegetation cover and landform explain vulnerability better than average slope in most instances. For different loss types, the dominant socioeconomic vulnerability factor is different. For both typhoons, emergency transfer has a higher determining power (q) ranking for the population vulnerability, while the percentage of the GDP made up of primary industry have higher q ranking for economic vulnerability. The dominant interaction effects between two vulnerability factors differ depending on the typhoon and loss type but show a nonlinear enhancement effect in most cases. Moreover, changes in the maximum 4-hour accumulated rainfall account for most of the change in vulnerability between Hato and Mangkhut. Overall, the results can be conducive to understanding the complexity of vulnerability to typhoons and provide a reference for possible indicators for vulnerability assessment models, and determining the reasons for changes in vulnerability can be constructive to the formulation of specific policies for disaster prevention and mitigation.

The challenge of unprecedented floods and droughts in risk management

Risk management has reduced vulnerability to floods and droughts globally^1,2, yet their impacts are still increasing³. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data^4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change³.

Modelling and quantifying tomorrow's risks from natural hazards

Understanding and modelling future risks from natural hazards is becoming increasingly crucial as the climate changes, human population grows, asset wealth accumulates, and societies become more urbanised and interconnected. This need is recognised by the 2015-2030 Sendai Framework for Disaster Risk Reduction, which emphasises the importance of preparing for the disasters that our world may face tomorrow through strategies/policies that aim to minimise uncontrolled development in hazardous areas. While the vast majority of natural-hazard risk-assessment frameworks have so far focused on static impacts associated with current conditions and/or are influenced by historical context, some authors have sought to provide decision makers with risk-quantification approaches that can be used to cultivate a sustainable future. This Review documents these latter efforts, explicitly examining work that has modelled and quantified the individual components that comprise tomorrow's risk, i.e., future natural hazards affected by climate change, future exposure (e.g., in terms of population, land use, and the built environment), and the evolving physical vulnerabilities of the world's infrastructure. We end with a discussion on the challenges faced by modellers in determining the risks that tomorrow's world may face from natural hazards, and the constraints these place on the decision-making abilities of relevant stakeholders.

Flood resilience in paired US-Mexico border cities: a study of binational risk perceptions

Disastrous floods in the twin cities of Nogales, Arizona, USA, and Nogales, Sonora, Mexico (collectively referred to as Ambos Nogales) occur annually in response to monsoonal summer rains. Flood-related hazards include property damage, impairment to sewage systems, sewage discharge, water contamination, erosion, and loss of life. Flood risk, particularly in Nogales, Sonora, is amplified by informal, "squatter" settlements in the watershed floodplain and associated development and infrastructure. The expected increase in precipitation intensity, resulting from climate change, poses further risk to flooding therein. We explore binational community perceptions of flooding, preferences for watershed management, and potential actions to address flooding and increase socio-ecological resilience in Ambos Nogales using standardized questionnaires and interviews to collect data about people and their preferences. We conducted 25 semi-structured interviews with local subject matter experts and gathered survey responses from community members in Ambos Nogales. Though survey response was limited, expected frequencies were high enough to conduct Chi-squared tests of independence to test for statistically significant relationships between survey variables. Results showed that respondents with previous experience with flooding corresponded with their level of concern about future floods. Additionally, respondents perceived greater flood-related risks from traveling across town and damage to vehicles than from inundation or damages to their homes or neighborhoods. Binationally, women respondents felt less prepared for future floods than men. On both sides of the border, community members and local experts agreed that Ambos Nogales lacks adequate preparation for future floods. To increase preparedness, they recommended flood risk education and awareness campaigns, implementation of green infrastructure, additional stormwater infrastructure (such as drainage systems), enhanced flood early warning systems, and reduction of flood flows through regulations to reduce the expansion of hard surfaces. This study contributes systematic collection of information about flood risk perceptions across an international border, including novel data regarding risks related to climate change and gender-based assessments of flood risk. Our finding of commonalities across both border communities, in perceptions of flood risk and in the types of risk reduction solutions recommended by community members, provides clear directions for flood risk education, outreach, and preparedness, as well as measures to enhance cross-border cooperation.

Behavioral, health- related and demographic risk factors of death in floods: A case-control study

During the first half of 2019, many provinces of Iran were affected by floods, which claimed the lives of 82 people. The present study aimed to investigate the behavioral, health related and demographic risk factors associated with deaths due to floods. We measured the odds ratio and investigated the contribution and significance of the factors in relation to mortality. This case-control study was conducted in the cities affected by flood in Iran. Data were collected on the flood victims using a questionnaire. Survivors, a member of the flood victim's family, were interviewed. In total, 77 subjects completed the survey in the case group, and 310 subjects completed the survey in the control group. The findings indicated that factors such as the age of less than 18 years, low literacy, being trapped in buildings/cars, and risky behaviors increased the risk of flood deaths. Regarding the behavioral factors, perceived/real swimming skills increased the risk of flood deaths although it may seem paradoxical. This increment is due to increased self confidence in time of flood. On the other hand, skills and abilities such as evacuation, requesting help, and escape decreased the risk of flood deaths. According to the results, the adoption of support strategies, protecting vulnerable groups, and improving the socioeconomic status of flood-prone areas could prevent and reduce the risk of flood deaths.

Climate change, social vulnerability and child nutrition in South Asia

Despite recent advancements in global population well-being and food security, climate change threatens to undermine child nutritional health, particularly for marginalized populations in tropical low- and middle-income countries. South Asia is at particular risk for climate-driven undernutrition due to a combination of historical weather exposures, existing nutritional deficits, and a lack of sanitation access. Previous studies have established that precipitation extremes increase rates of undernutrition in this region, but the existing literature lacks adequate consideration of temperature anomalies, mediating social factors, and the developmentally-relevant timing of exposure. We combine high-resolution temperature and precipitation data with large-sample survey data on household demographics and child anthropometry, using an approach that incorporates three key developmental periods and a rigorous fixed effects design. We find that precipitation extremes in the first year of life significantly decrease children's height-for-age (HAZ) in South Asia. The detrimental effects of extreme precipitation are especially concentrated in under-resourced households, such as those lacking access to proper sanitation and education for women, while anomalous heat is particularly harmful for children in Pakistan, though it tends to benefit children in some demographic groups. These results indicate that nutritional status in South Asia is highly responsive to climate exposures, and that addressing sanitation infrastructure and other development priorities is a pathway towards reducing this vulnerability.

Satellite imaging reveals increased proportion of population exposed to floods

Flooding affects more people than any other environmental hazard and hinders sustainable development^1,2. Investing in flood adaptation strategies may reduce the loss of life and livelihood caused by floods³. Where and how floods occur and who is exposed are changing as a result of rapid urbanization⁴, flood mitigation infrastructure⁵ and increasing settlements in floodplains⁶. Previous estimates of the global flood-exposed population have been limited by a lack of observational data, relying instead on models, which have high uncertainty^3,7-11. Here we use daily satellite imagery at 250-metre resolution to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018. We determine a total inundation area of 2.23 million square kilometres, with 255-290 million people directly affected by floods. We estimate that the total population in locations with satellite-observed inundation grew by 58-86 million from 2000 to 2015. This represents an increase of 20 to 24 per cent in the proportion of the global population exposed to floods, ten times higher than previous estimates⁷. Climate change projections for 2030 indicate that the proportion of the population exposed to floods will increase further. The high spatial and temporal resolution of the satellite observations will improve our understanding of where floods are changing and how best to adapt. The global flood database generated from these observations will help to improve vulnerability assessments, the accuracy of global and local flood models, the efficacy of adaptation interventions and our understanding of the interactions between landcover change, climate and floods.

Uncertainty and Bias in Global to Regional Scale Assessments of Current and Future Coastal Flood Risk

This study provides a literature-based comparative assessment of uncertainties and biases in global to world-regional scale assessments of current and future coastal flood risks, considering mean and extreme sea-level hazards, the propagation of these into the floodplain, people and coastal assets exposed, and their vulnerability. Globally, by far the largest bias is introduced by not considering human adaptation, which can lead to an overestimation of coastal flood risk in 2100 by up to factor 1300. But even when considering adaptation, uncertainties in how coastal societies will adapt to sea-level rise dominate with a factor of up to 27 all other uncertainties. Other large uncertainties that have been quantified globally are associated with socio-economic development (factors 2.3-5.8), digital elevation data (factors 1.2-3.8), ice sheet models (factor 1.6-3.8) and greenhouse gas emissions (factors 1.6-2.1). Local uncertainties that stand out but have not been quantified globally, relate to depth-damage functions, defense failure mechanisms, surge and wave heights in areas affected by tropical cyclones (in particular for large return periods), as well as nearshore interactions between mean sea-levels, storm surges, tides and waves. Advancing the state-of-the-art requires analyzing and reporting more comprehensively on underlying uncertainties, including those in data, methods and adaptation scenarios. Epistemic uncertainties in digital elevation, coastal protection levels and depth-damage functions would be best reduced through open community-based efforts, in which many scholars work together in collecting and validating these data.

The impact of humanitarian assistance on post-disaster social vulnerabilities: some early reflections on the Nepal earthquake in 2015

Every year, thousands of people around the world who face unequal access to political and social power and resources lose their lives and/or livelihoods in natural hazard events. As a result, the reduction of vulnerability has become a central concern of humanitarian actors. This paper analyses the impact of humanitarian assistance on vulnerabilities in Nepal following the Gorkha earthquake on 25 April 2015. The causes and manifestations of vulnerability before and after the disaster are determined through the application of the Pressure and Release model and the adoption of a mixed-methods research approach. The findings of the study reveal that 20 months after the earthquake, humanitarian assistance had not had any long-term positive influences on the root causes of the phenomenon, and that vulnerabilities at the micro level could be resolved in part. To diminish the extent of disasters in the future, however, the fundamental reasons for the vulnerability have to be addressed better.

Climate signals in river flood damages emerge under sound regional disaggregation

Climate change affects precipitation patterns. Here, we investigate whether its signals are already detectable in reported river flood damages. We develop an empirical model to reconstruct observed damages and quantify the contributions of climate and socio-economic drivers to observed trends. We show that, on the level of nine world regions, trends in damages are dominated by increasing exposure and modulated by changes in vulnerability, while climate-induced trends are comparably small and mostly statistically insignificant, with the exception of South & Sub-Saharan Africa and Eastern Asia. However, when disaggregating the world regions into subregions based on river-basins with homogenous historical discharge trends, climate contributions to damages become statistically significant globally, in Asia and Latin America. In most regions, we find monotonous climate-induced damage trends but more years of observations would be needed to distinguish between the impacts of anthropogenic climate forcing and multidecadal oscillations.

Simulating flash flood hydrographs and behavior metrics across China: Implications for flash flood management

China frequently suffers from considerable and disastrous flash floods with wide areal coverage and high frequency. Obtaining useful information to support flash flood management and decision-making is challenging for massive flash flood events that vary greatly in spatio-temporal characteristics. In this study, hydrological modelling approach (CNFF) and cluster analysis were integrated to assess simulation reliability of entire flash flood processes including both hydrographs and behavior characteristics in a manner of similarity classification, rather than at event scale. A total of 207 hourly events from 13 mountainous catchments with diverse physiographic and meteorological characteristics across China were selected for study. Representative flash flood types were classified using normalized hydrographs with diverse spatio-temporal patterns by k-means clustering algorithm. For individual flash flood types, simulation reliability of CNFF was assessed in capturing corresponding hydrographs, seven behavior metrics measuring flash flood magnitude, intensity, occurrence time, flood timescale, rates of change and variability, and their uncertainties. Results showed that three (fast, intermediate and slow) flash flood types were identified from all the flash flood events with overall average silhouette index of 0.45. Hourly hydrographs of three flash flood types were well reproduced by CNFF, with absolute average relative error of runoff within 15% and Nash-Sutcliffe Efficiency above 0.55. All the behavior metrics were the most accurately reproduced for slow flash flood type with the least average relative root-mean-square error (0.30), followed by intermediate (0.52) and fast (0.58) types. Moreover, the slow flash flood type had the most reliable but greatest uncertainty interval of both hydrograph and behavior metrics, with average relative interval length being 1.24 and 71.96%, and 93.10% and 100% of observations contained in 95% confidence interval, respectively. This study provided efficient and detailed information for flash flood management, and extended application scope of hydrological models to encompass flash flood types and behavior metrics.

Understanding dynamics of population flood exposure in Canada with multiple high-resolution population datasets

In recent years, geospatial data (e.g. remote sensing imagery), and other relevant ancillary datasets (e.g. land use land cover, climate conditions) have been utilized through sophisticated algorithms to produce global population datasets. With a handful of such datasets, their performances and skill in flood exposure assessment have not been explored. This study proposes a comprehensive framework to understand the dynamics and differences in population flood exposure over Canada by employing four global population datasets alongside the census data from Statistics Canada as the reference. The flood exposure is quantified based on a set of floodplain maps (for 2015, 1 in 100-yr and 1 in 200-yr event) for Canada derived from the CaMa-Flood global flood model. To obtain further insights at the regional level, the methodology is implemented over six flood-prone River Basins in Canada. We find that about 9% (3.31 million) and 11% (3.90 million) of the Canadian population resides within 1 in 100-yr and 1 in 200-yr floodplains. We notice an excellent performance of WorldPop, and LandScan in most of the cases, which is unaffected by the representation of flood hazard, while Global Human Settlement and Gridded Population of the World showed large deviations. At last, we determined the long-term dynamics of population flood exposure and vulnerability from 2006 to 2019. Through this analysis, we also identify the regions that contain a significantly larger population exposed to floods. The relevant conclusions derived from the study highlight the need for careful selection of population datasets for preventing further amplification of uncertainties in flood risk. We recommend a detailed assessment of the severely exposed regions by including precise ground-level information. The results derived from this study may be useful not only for flood risk management but also contribute to understanding other disaster impacts on human-environment interrelationships.

Quantifying the inundation impacts of earthquake-induced surface elevation change by hydrological and hydraulic modeling

Current estimates of flood hazards are often based on the assumption that topography is static. When tectonic and/or anthropogenic processes change the land surface elevation, the spatial patterns of floods might also change. Here, we employ the hydrological and hydraulic modeling to simulate floods in the Kujukuri Plain, Japan, in the years 2004 and 2013, when two severe floods occurred. In between the two floods, land surface elevations were changed by the 2011 Tohoku-Oki earthquake. The effects of land surface elevation changes on inundation areas were quantified by changing input topographies. Our results showed that, without taking into account land surface elevation changes, around 10% of inundation areas were underestimated at the time of flood events in the year 2013. The spatial distribution of inundation locations varied with local topographical features, for example, the areas with backmarsh and valley fill deposits were sensitive to the extent of inundation by land surface elevation changes. The sub-watershed near the coastal shoreline having below-zero meter elevation areas showed that the earthquake-induced land surface elevation changes exacerbated an additional 22% inundation area. This study suggests that the inundation areas will increase in catchments suffering severe settlements, which highlights the necessity of taking into account the spatio-temporal changes of land surface elevations on the assessment of flood hazards.

Role of dams in reducing global flood exposure under climate change

Globally, flood risk is projected to increase in the future due to climate change and population growth. Here, we quantify the role of dams in flood mitigation, previously unaccounted for in global flood studies, by simulating the floodplain dynamics and flow regulation by dams. We show that, ignoring flow regulation by dams, the average number of people exposed to flooding below dams amount to 9.1 and 15.3 million per year, by the end of the 21^st century (holding population constant), for the representative concentration pathway (RCP) 2.6 and 6.0, respectively. Accounting for dams reduces the number of people exposed to floods by 20.6 and 12.9% (for RCP2.6 and RCP6.0, respectively). While environmental problems caused by dams warrant further investigations, our results indicate that consideration of dams significantly affect the estimation of future population exposure to flood, emphasizing the need to integrate them in model-based impact analysis of climate change.

Exposure to natural hazard events unassociated with policy change for improved disaster risk reduction

Natural hazard events provide opportunities for policy change to enhance disaster risk reduction (DRR), yet it remains unclear whether these events actually fulfill this transformative role around the world. Here, we investigate relationships between the frequency (number of events) and severity (fatalities, economic losses, and affected people) of natural hazards and DRR policy change in 85 countries over eight years. Our results show that frequency and severity factors are generally unassociated with improved DRR policy when controlling for income-levels, differences in starting policy values, and hazard event types. This is a robust result that accounts for event frequency and different hazard severity indicators, four baseline periods estimating hazard impacts, and multiple policy indicators. Although we show that natural hazards are unassociated with improved DRR policy globally, the study unveils variability in policy progress between countries experiencing similar levels of hazard frequency and severity.

Whether disasters spur policy change remains contested. Here, the authors utilize a dataset of 10,976 natural hazard events and multiple disaster risk reduction (DRR) policy indicators across 85 countries over eight years to show that frequency and severity factors are unassociated with improved DRR policy.

Risk factors of death from flood: Findings of a systematic review

PURPOSE

The number of flood disaster deaths has been on the rise in recent years. The current review investigated and categorized the risk factors of deaths from floods in parallel with preventive and control measures designed to minimize deaths from floods.

METHODS

In a systematic review, International electronic databases including PubMed, Scopus, Web of Science, and Google Scholar were investigated for articles published in English language. In addition, Iranian databases including IranMedex, Irandoc, Magiran, and Scientific Information Database (SID) were investigated for studies published in Persian. ProQuest database was also searched for related theses. The studies were selected regardless their methods but based on the inclusion and exclusion criteria. The data were extracted, coded and prepared for further analysis. Finally, descriptive and thematic analyses were conducted.

RESULTS

A total of 114 factors were identified and categorized into the following five category that can influence on flood death.: hazard related factors, and individual, environmental, socio-economic, and managerial categories.

CONCLUSIONS

The study identified many factors that affect flood deaths. The variety and the diverse nature of the factors necessitate appropriate interventions for removing or reducing the effects of the identified factors. More quantitative analytical studies are needed to confirm causal relationship between extracted factors and floods death.

The Role of Experience and Different Sources of Knowledge in Shaping Flood Risk Awareness

Understanding what makes people vulnerable to flooding is key in informing the risk management process. Non-structural measures, such as risk communication, can reduce vulnerability by improving flood risk awareness, but they require a deep understanding of which factors influence risk awareness, and how. We analysed and untangled the role of experience with, and knowledge of, floods by conducting a survey in a municipality in North-eastern Italy that was hit by a flash flood in 2018. The results show that previous experience with floods influences risk awareness not only directly, but also indirectly through the knowledge that was gained from that experience. In addition, specific (as opposed to generic) definitions of experience have been found to be better suited for exploring their effects on risk awareness. Based on the literature and on our results, we propose an experience-knowledge typology to help unravel the complex role that these two variables play in shaping flood risk awareness.

Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA

Social vulnerability indicators seek to identify populations susceptible to hazards based on aggregated sociodemographic data. Vulnerability indices are rarely validated with disaster outcome data at broad spatial scales, making it difficult to develop effective national scale strategies to mitigate loss for vulnerable populations. This paper validates social vulnerability indicators using two flood outcomes: death and damage. Regression models identify sociodemographic factors associated with variation in outcomes from 11,629 non-coastal flood events in the USA (2008–2012), controlling for flood intensity using stream gauge data. We compare models with (i) socioeconomic variables, (ii) the composite social vulnerability index (SoVI), and (iii) flood intensity variables only. The SoVI explains a larger portion of the variance in death (AIC = 2829) and damage (R2 = 0.125) than flood intensity alone (death—AIC = 2894; damage—R2 = 0.089), and models with individual sociodemographic factors perform best (death—AIC = 2696; damage—R2 = 0.229). Socioeconomic variables correlated with death (rural counties with a high proportion of elderly and young) differ from those related to property damage (rural counties with high percentage of Black, Hispanic and Native American populations below the poverty line). Results confirm that social vulnerability influences death and damage from floods in the USA. Model results indicate that social vulnerability models related to specific hazards and outcomes perform better than generic social vulnerability indices (e.g., SoVI) in predicting non-coastal flood death and damage. Hazard- and outcome-specific indices could be used to better direct efforts to ameliorate flood death and damage towards the people and places that need it most. Future validation studies should examine other flood outcomes, such as evacuation, migration and health, across scales.

Evaluation of LoRa Technology in Flooding Prevention Scenarios

Global climate change originates frequent floods that may cause severe damage, justifying the need for real-time remote monitoring and alerting systems. Several works deal with LoRa (Long Range) communications over land and in the presence of obstacles, but little is known about LoRa communication reliability over water, as it may happen in real flooding scenarios. One aspect that is known to influence the communication quality is the height at which nodes are placed. However, its impact in water environments is unknown. This is an important aspect that may influence the location of sensor nodes and the network topology. To fill this gap, we conducted several experiments using a real LoRa deployment to evaluate several features related to data communication. We considered two deployment scenarios corresponding to countryside and estuary environments. The nodes were placed at low heights, communicating, respectively, over the ground and over the water. Measurements for packet loss, received signal strength indicator (RSSI), signal-to-noise ratio (SNR) and round-trip time (RTT) were collected during a period of several weeks. Results for both scenarios are presented and compared in this paper. One important conclusion is that the communication distance and reliability are significantly affected by tides when the communication is done over the water and nodes are placed at low heights. Based on the RTT measurements and on the characteristics of the hardware, we also derive a battery lifetime estimation model that may be helpful for the definition of an adequate maintenance plan.

Satellite-based data driven quantification of pluvial floods over Europe under future climatic and socioeconomic changes

Flooding is one of the major threats jeopardizing lives and properties of the people, and its risk is expected to increase remarkably under changing climatic and socioeconomic conditions. Yet, future flood risk has not been well studied due primarily to a limited availability of detailed and consistent data on future vulnerability components and the computationally expensive continental flood modeling. Here we perform a top-down data driven flood risk assessment for 20-, 30-, 50- and 100-year return periods over Europe at the continental, regional and national levels for the late 21st century. To account for the impact of changes in both climatic and socioeconomic conditions on floods, the Shared Socioeconomic Pathways (SSPs) are merged with Representative Concentration Pathways (RCPs), integrating hazard and several social, economic and agricultural exposure-vulnerability proxy indicators. Our results show a ubiquitous drastic increase up to 87% in future flood risks of different return periods over Europe, with eastern and southern regions experiencing the highest risk increase. A fossil-fuel based development in the future would lead to 14-15% higher flood risk compared to a sustainable development, which goes up to 23% in north Europe. The amplified future flood risk is predominantly driven by climate change, although with a large uncertainty, rather than socioeconomic drivers.

Social Capital and Disaster Resilience Nexus: A Study of Flash Flood Recovery in Jeddah City

Governments, researchers, and humanitarian agencies have increasingly focused on reducing disaster impacts and enhancing the resilience of individuals, households, and communities, as the human and economic costs of natural disaster events have dramatically increased over the past century. Achieving resilience in a disaster context means the ability to survive future natural disasters with minimum loss of life and property as well as the ability to create a greater sense of place among residents, a stronger, more diverse economy, and a more economically integrated and diverse population. However, less attention has been paid to the significance of social capital in a post-disaster context and its contribution in building community resilience. It is very obvious that the contribution of social capital to post-disaster resilience in a Middle Eastern/Saudi Arabian context is virtually unknown. With a focus on the Saudi Arabian context, this research paper develops a social capital framework centered on resilience and post-disaster recovery. To conduct this study, a holistic approach to data collection is followed through questionnaire surveys, structured and non-structured interviews with citizens, and informal discussions with government and major stakeholders related to flash flood disaster management in the City of Jeddah. It is interesting to note that several religious institutions have played important roles in evacuating people and providing help for a quick recovery. In addition, government organizations are taking the recovery process seriously by providing necessary help in the flood-stricken areas. Within the scope of the given framework, the research explores and evaluates the role of social capital in post-disaster recovery efforts through a case study of the 2009 and 2011 Jeddah flash floods.

Social-media and newspaper reports reveal large-scale meteorological drivers of floods on Sumatra

Floods are a major contributor to natural disasters in Sumatra. However, atmospheric conditions leading to floods are not well understood due, among other factors, to the lack of a complete record of floods. Here, the 5 year flood record for Sumatra derived from governmental reports, as well as from crowd-sourcing data, based on Twitter messages and local newspapers' reports, is created and used to analyze atmospheric phenomena responsible for floods. It is shown, that for the majority of analyzed floods, convectively coupled Kelvin waves, large scale precipitation systems propagating at ∼12 m/s along the equator, play the critical role. While seasonal and intraseasonal variability can also create conditions favorable for flooding, the enhanced precipitation related to Kelvin waves was found in over 90% of flood events. In 30% of these events precipitation anomalies were attributed to Kelvin waves only. These results indicate the potential for increased predictability of flood risk.

The interplay between structural flood protection, population density, and flood mortality along the Jamuna River, Bangladesh

Levees protect floodplain areas from frequent flooding, but they can paradoxically contribute to more severe flood losses. The construction or reinforcement of levees can attract more assets and people in flood-prone area, thereby increasing the potential flood damage when levees eventually fail. Moreover, structural protection measures can generate a sense of complacency, which can reduce preparedness, thereby increasing flood mortality rates. We explore these phenomena in the Jamuna River floodplain in Bangladesh. In this study area, different levels of flood protection have co-existed alongside each other since the 1960s, with a levee being constructed only on the right bank and its maintenance being assured only in certain places. Primary and secondary data on population density, human settlements, and flood fatalities were collected to carry out a comparative analysis of two urban areas and two rural areas with different flood protection levels. We found that the higher the level of flood protection, the higher the increase of population density over the past decades as well as the number of assets exposed to flooding. Our results also show that flood mortality rates associated with the 2017 flooding in Bangladesh were lower in the areas with lower protection level. This empirical analysis of the unintended consequences of structural flood protection is relevant for the making of sustainable policies of disaster risk reduction and adaptation to climate change in rapidly changing environments.

Disaster Risk Science: A Geographical Perspective and a Research Framework

In this article, we recall the United Nations’ 30-year journey in disaster risk reduction strategy and framework, review the latest progress and key scientific and technological questions related to the United Nations disaster risk reduction initiatives, and summarize the framework and contents of disaster risk science research. The object of disaster risk science research is the “disaster system” consisting of hazard, the geographical environment, and exposed units, with features of regionality, interconnectedness, coupling, and complexity. Environmental stability, hazard threat, and socioeconomic vulnerability together determine the way that disasters are formed, establish the spatial extent of disaster impact, and generate the scale of losses. In the formation of a disaster, a conducive environment is the prerequisite, a hazard is the necessary condition, and socioeconomic exposure is the sufficient condition. The geographical environment affects local hazard intensity and therefore can change the pattern of loss distribution. Regional multi-hazard, disaster chain, and disaster compound could induce complex impacts, amplifying or attenuating hazard intensity and changing the scope of affected areas. In the light of research progress, particularly in the context of China, we propose a three-layer disaster risk science disciplinary structure, which contains three pillars (disaster science, disaster technology, and disaster governance), nine core areas, and 27 research fields. Based on these elements, we discuss the frontiers in disaster risk science research.

A global database of historic and real-time flood events based on social media

Early event detection and response can significantly reduce the societal impact of floods. Currently, early warning systems rely on gauges, radar data, models and informal local sources. However, the scope and reliability of these systems are limited. Recently, the use of social media for detecting disasters has shown promising results, especially for earthquakes. Here, we present a new database for detecting floods in real-time on a global scale using Twitter. The method was developed using 88 million tweets, from which we derived over 10,000 flood events (i.e., flooding occurring in a country or first order administrative subdivision) across 176 countries in 11 languages in just over four years. Using strict parameters, validation shows that approximately 90% of the events were correctly detected. In countries where the first official language is included, our algorithm detected 63% of events in NatCatSERVICE disaster database at admin 1 level. Moreover, a large number of flood events not included in NatCatSERVICE were detected. All results are publicly available on www.globalfloodmonitor.org.

Assessment of future flash flood inundations in coastal regions under climate change scenarios-A case study of Hadahe River basin in northeastern China

Climate change may considerably influence flash floods by increasing extreme precipitation. Coastal regions in eastern and southern China may experience especially negative effects because of the frequent occurrence of tropical cyclones (TCs). This study presented a hazard assessment framework for TCs-induced flash floods under climate change scenarios and assessed future inundations in Hadahe River basin, which is in northeastern China. From 1965 to 2014, there were twenty-four TCs ranging from severe tropical storm to super typhoon over Hadahe River basin in twenty years. General Circulation Models (GCMs) are too coarse to depict the impact of TCs on extreme precipitation; therefore, hourly precipitation data from two gauges and the tracks of TCs were used to assess the impact of TCs. An extreme precipitation event on 3-4 August 2012 and the same 600-year future probabilistic extreme rainfall were utilized to investigate the impact of climate change. Daily precipitation data from eight climate models from the NEX-GDDP dataset during 1965-2005 and 2050-2099 represented historical and future simulation conditions, respectively. The hydrologic model HEC-HMS was integrated with the hydraulic model FLO-2D to simulate discharges and inundations of past and future TCs episodes. The results showed that flooded area is projected to increase by 6.6% and 7.8% for inundation depth between 1.0 and 3.0 m under RCP 4.5 and RCP 8.5 scenarios, respectively. For inundation depth over 3.0 m, flooded area is projected to increase by 17.6% and 22.0%. Relative change of flash flood extent increases as inundation depth increases, indicating that climate change is likely to increase the risk of flash floods. Additional adaptation measures are needed to make the Hadahe River basin and other similar coastal basins more resilient. The results also indicated that considering the impact of TCs produces a more reliable assessment of future flash floods in coastal regions.

River flooding risk prevention: A cooperative game theory approach

Socio-economic development combined with changing hydrological factors represents a challenge for extending flood protection. In particular, land owners should be encouraged to use their land in a way that improves its water retention capacity. However, problems of fairness may arise because a landowner can benefit or lose out depending on the use of other lands. This paper sets out to study the possibility of applying game theory through a cooperative game to solve this problem. Specifically, we look for a sharing rule function to help the planners to distribute the total benefit among landowners, taking into account a principle of stability. We concentrate on enhancing upstream water retention and focus on the role played by forests as natural water retention features. This is a methodological contribution that analyzes land use management for flood retention. Land planners, governments and landowners could use cooperative games as a flood risk management tool. With this method, compensations and benefits could be established to raise awareness and encourage land owners to cooperate.

Flood Fatalities in Europe, 1980–2018: Variability, Features, and Lessons to Learn

Floods are still a significant threat to people, despite of the considerable developments in forecasting, management, defensive, and rescue works. In the near future, climate and societal changes as both urbanization of flood prone areas and individual dangerous behaviors could increase flood fatalities. This paper analyzes flood mortality in eight countries using a 39-year database (1980–2018) named EUFF (EUropean Flood Fatalities), which was built using documentary sources. The narratives of fatalities were investigated and standardized in the database reporting the details of the events. The entire dataset shows a stable trend on flood fatalities, despite the existence of individual increasing (Greece, Italy, and South France) and decreasing (Turkey and Catalonia) trends. The 2466 fatalities were mainly males, aged between 30–49 years and the majority of them happened outdoor. Most often people were dragged by water/mud when travelling by motor vehicles. Some cases of hazardous behaviors, such as fording rivers, were also detected. The primary cause of death was drowning, followed by heart attack. This work contributes to understand the human–flood interaction that caused fatalities. The changes in society’s vulnerability highlighted throughout this study contribute to manage future risks, to improve people protection actions, and to reduce risk behaviors.

The Role of Hazard and Vulnerability in Modulating Economic Damages of Inland Floods in the United States Using a Survey-Based Dataset

This study investigates the trends in economic damages caused by three types of inland floods (flash flood, flood, and heavy rain) in the United States and the variations in related hazard and vulnerability indicators between 1996 and 2016. We explore the underlying mechanisms based on a survey-based dataset maintained by the National Oceanic and Atmospheric Administration (NOAA) National Weather Service. An annual average of 6518 flood occurrences was reported, which caused economic damages of 3351 million USD per year. Flash flood and flood contributed to 53% and 32% of total occurrences and was associated with a larger share of damaging events (SDE). Results show that the higher impacts by flood and flash flood on property and crop are partly attributed to the greater intensity of rainfall. In addition, flood has the highest unit cost of damages. Notably, despite an upward tendency in economic damages by flash floods, no evident change trend is observed for inland floods as a whole. Further analysis shows changes in economic damages by heavy rain and flash flood are mainly governed by the increased annual frequency and hazard intensity, but the change of trend in their vulnerability indicators (i.e., SDE and Damage Per Event (DPE)) is not obvious. Regarding floods, it was not possible to attribute the variations in economic losses to hazard and vulnerability, as no significant tendency is found except for an increasing SDE. Despite limitations of length of records, data collection, and methodology, the difference in economic impacts and the related hazard and vulnerability revealed in this study can help better target future adaptation and mitigation measures.

Empirical evidence of declining global vulnerability to climate-related hazards

Death tolls and economic losses from natural hazards continue to rise in many parts of the world. With the aim to reduce future impacts from natural disasters it is crucial to understand the variability in space and time of the vulnerability of people and economic assets. In this paper we quantified the temporal dynamics of socio-economic vulnerability, expressed as fatalities over exposed population and losses over exposed GDP, to climate-related hazards between 1980 and 2016. Using a global, spatially explicit framework that integrates population and economic dynamics with one of the most complete natural disaster loss databases we quantified mortality and loss rates across income levels and analyzed their relationship with wealth. Results show a clear decreasing trend in both human and economic vulnerability, with global average mortality and economic loss rates that have dropped by 6.5 and nearly 5 times, respectively, from 1980-1989 to 2007-2016. We further show a clear negative relation between vulnerability and wealth, which is strongest at the lowest income levels. This has led to a convergence in vulnerability between higher and lower income countries. Yet, there is still a considerable climate hazard vulnerability gap between poorer and richer countries.

Are We Adapting to Floods? Evidence from Global Flooding Fatalities

There has been a growing interest in understanding whether and how people adapt to extreme weather events in a changing climate. This article presents one of the first empirical analyses of adaptation to flooding on a global scale. Using a sample of 97 countries between 1985 and 2010, we investigate the extent and pattern of flood adaptation by estimating the effects of a country's climatological risk, recent flood experiences, and socioeconomic characteristics on its flood-related fatalities. Our results provide mixed evidence on adaptation: countries facing greater long-term climatological flooding risks do not necessarily adapt better and suffer fewer fatalities; however, after controlling for the cross-country heterogeneity, we find that more recent flooding shocks have a significant and negative effect on fatalities from subsequent floods. These findings may suggest the short-term learning dynamics of adaptation and potential inefficacy of earlier flood control measures, particularly those that promote increased exposure in floodplains. Our findings provide important implications for climate adaptation policy making and climate modeling.

Global mapping of eco-environmental vulnerability from human and nature disturbances

Global environments are threatened by intensively natural variation and continuously increased human-made disturbances. Assessment of the global eco-environment vulnerability (global EV or GEV) caused by both natural and human-induced disturbances plays a key role in providing valuable information about ecological and environmental background for designing suitable policy measures to improve and restore environment. We present the first global-scale map of quantified eco-environmental vulnerability by integrating remote sensing, GIS modelling, and global census datasets, employing 16 influential factors across five domains: socioeconomics, land resources, natural hazards, hydrometeorology, and topography. The GEV is classified into six levels, namely very low vulnerability, low vulnerability, medium vulnerability, medium high vulnerability, high vulnerability, and very high vulnerability. At global scale, a small fraction of the globe (10.1%) is strongly (high and very high vulnerability) affected by influential factors. Among continents, the largest fraction of very high vulnerability level is attributed to Asia (74.6%) followed by Africa (19.6%). National-scale analysis shows that China and India are the most vulnerable in Asia and in the world. Our study provides accumulative impacts of manmade and natural disturbances, which are vital for decision makers to set improvement targets on specific areas over local, regional, and global scales, and design and adopt new practices to lessen natural and manmade disturbances on environment, while keeping track of evolution of the other environmental aspects.

Global exposure to rainstorms and the contribution rates of climate change and population change

Quantifying global population exposure to rainstorms is a key component of population risk assessments for rainstorms and induced floods. Based on daily precipitation data from the NEX-GDDP dataset, rainfall from rainstorms is first calculated by a multi-model ensemble method for four periods from 1986 to 2100. Combined with population data from the SSP2 scenario, the global population exposure to rainstorms is then calculated and analyzed. Finally, the contribution rates of climate change effect, population change effect, and joint change effect on exposure change are quantitatively assessed. The results showed that (1) Population exposure to rainstorms shows a linear upward trend from base period to the late 21st century period in most regions, and the mid-21st century period compared with base period has the fastest rate of increase. (2) The spatial patterns of population exposure to rainstorms are very similar for the four periods and the areas with high exposure are mainly distributed in Asia, population exposure of Africa is gradually increasing. The countries with high exposure show little volatility, especially the top eight countries. (3) The change in total exposure is mainly due to population change. Based on the composition of the total exposure change for each country, the number of countries whose climate change effect is greater than that of population change is gradually increasing, and this number reaches more than a quarter of the total when the late 21st century period is compared with the mid-21st century period.