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Among the most prevalent natural hazards, flooding has been threatening human lives and properties. Robust flood simulation is required for effective response and prevention. Machine learning is widely used in flood modeling due to its high performance and scalability. Nonetheless, data pre-processing of heterogeneous sources can be cumbersome, and traditional data processing and modeling have been limited to a single resolution. This study employed an Icosahedral Snyder Equal Area Aperture 3 Hexagonal Discrete Global Grid System (ISEA3H DGGS) as a scalable, standard spatial framework for computation, integration, and analysis of multi-source geospatial data. We managed to incorporate external machine learning algorithms with a DGGS-based data framework, and project future flood risks under multiple climate change scenarios for southern New Brunswick, Canada. A total of 32 explanatory factors including topographical, hydrological, geomorphic, meteorological, and anthropogenic were investigated. Results showed that low elevation and proximity to permanent waterbodies were primary factors of flooding events, and rising spring temperatures can increase flood risk. Flooding extent was predicted to occupy 135–203% of the 2019 flood area, one of the most recent major flooding events, by the year 2100. Our results assisted in understanding the potential impact of climate change on flood risk, and indicated the feasibility of DGGS as the standard data fabric for heterogeneous data integration and incorporated in multi-scale data mining.

Abstract Risk management has reduced vulnerability to floods and droughts globally 1,2 , yet their impacts are still increasing 3 . 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 change 3 .

Abstract Recent policy changes highlight the need for citizens to take adaptive actions to reduce flood‐related impacts. Here, we argue that these changes represent a wider behavioral turn in flood risk management (FRM). The behavioral turn is based on three fundamental assumptions: first, that the motivations of citizens to take adaptive actions can be well understood so that these motivations can be targeted in the practice of FRM; second, that private adaptive measures and actions are effective in reducing flood risk; and third, that individuals have the capacities to implement such measures. We assess the extent to which the assumptions can be supported by empirical evidence. We do this by engaging with three intellectual catchments. We turn to research by psychologists and other behavioral scientists which focus on the sociopsychological factors which influence individual motivations (Assumption 1). We engage with economists, engineers, and quantitative risk analysts who explore the extent to which individuals can reduce flood related impacts by quantifying the effectiveness and efficiency of household‐level adaptive measures (Assumption 2). We converse with human geographers and sociologists who explore the types of capacities households require to adapt to and cope with threatening events (Assumption 3). We believe that an investigation of the behavioral turn is important because if the outlined assumptions do not hold, there is a risk of creating and strengthening inequalities in FRM. Therefore, we outline the current intellectual and empirical knowledge as well as future research needs. Generally, we argue that more collaboration across intellectual catchments is needed, that future research should be more theoretically grounded and become methodologically more rigorous and at the same time focus more explicitly on the normative underpinnings of the behavioral turn. This article is categorized under: Engineering Water > Planning Water Human Water > Water Governance Science of Water > Water Extremes

Abstract Floods are amongst the most frequent disasters in terms of human and economic impacts. This study provides new insights into the frequency of loss of life at the global scale, mortality fractions of the population exposed to floods, and underlying trends. A dataset is compiled based on the EM-DAT disaster database covering the period 1975 until 2022, extending previous studies on this topic. Flood impact data are analysed over spatial, temporal and economic scales, decomposed in various flood types and compared with other natural disasters. Floods are the most frequent natural disasters up to 1000 fatalities, and flash floods lead to the highest mortality fractions per event, i.e. the number of deaths in an event relative to the exposed population. Despite population growth and increasing flood hazards, the average number of fatalities per event has declined over time. Mortality fractions per event have decreased over time for middle- and high-middle-income countries, but increased for low-income countries. This highlights the importance of continuing and expanding risk reduction and adaptation efforts.

Abstract The frequency of floods is predicted to increase in south-east Asia, and this may exacerbate the living conditions of poor people in flood-prone areas. Though much work has been conducted on the effects of poverty, there is a pressing need for more analysis on the local effects of floods. The work that does exist usually is based on qualitative analysis. This paper investigates the relationship between floods and poverty at a household level. It is based on a questionnaire survey conducted in Bago city, Myanmar. Using multi-regression analysis and spatial analysis, we found that poor people tend to live in flood-prone areas, and that floods can cause and exacerbate poverty. Spatial distribution results show that the people who suffer most from floods are those who live in the worst conditions. We discuss the resettlement of communities as an option for countering the effects of floods and alleviating poverty.

Purpose This study investigates why Turkmen women’s traditional handicraft skills have declined and explains how the local, traditional craft skills accelerated the post-flood recovery of Turkmen women in the aftermath of the 2019 Northeast floods in Iran. Design/methodology/approach The research adopts a case study approach, employing reflective thematic analysis. Findings Post-disaster recovery spurred a shift from traditional to modern lifestyles through new housing designs, enhanced female literacy and greater economic participation. However, this transition devalued traditional crafts due to heightened household chores, material scarcity and reduced market demand. Nonetheless, women with craft skills played a pivotal role in household recovery by repairing damaged items and crafting dowries for their daughters, illustrating their contribution to social and economic resilience. Social implications These research findings shed light on the importance of traditional craft skills in enabling the female household member, in particular, to recover from disasters and contribute to the recovery of their households and communities. Originality/value The originality of this study lies in its focus on the specific context of Turkmen women’s traditional craft skills and their role in post-disaster recovery, particularly after the 2019 Northeast floods in Iran. While there is existing research on post-disaster recovery mechanisms, this study uniquely examines the under-researched impact of traditional craft skills on the recovery process, specifically for female household members.

Abstract Floods are among the most devastating natural hazards worldwide. While rainfall is the primary trigger of floods, human activities and climate change can exacerbate the impacts of floods and lead to more significant economic and social consequences. In this research, fluvial flood fatalities in the 1951–2020 period have been studied, analyzing the information reported in the Emergency Database (EM‐DAT). The EM‐DAT data were classified into five categories in terms of the number of events and fatalities connected with riverine floods, considering only events that caused more than 10 fatalities. The results show that the severity of flood‐related fatalities is not equally distributed worldwide, but presents specific geographical patterns. The flood fatality coefficient, which represents the ratio between the total number of fatalities and the number of flood events, calculated for different countries, identified that the Southern, Eastern, and South‐Eastern regions of Asia have the deadliest floods in the world. The number of flood events has been increasing since 1951 and peaked in 2007, following a relative decline since then. Though, the resulting fatalities do not follow a statistically significant trend. An analysis of the number of flood events in different decades shows that the 2001–2010 decade saw the highest number of events, which corresponds to the largest precipitation anomaly in the world. The lethality of riverine floods decreased over time, from 412 per flood in 1951–1960 to 67 in the 2011–2020 decade. This declining trend is probably a consequence of a more resilient environment and better risk reduction strategies. Based on the presented data and using regression analysis, relationships between flood fatalities and the number of flood events with population density and gross domestic product are developed and discussed.

Prenatal stress alters fetal programming, potentially predisposing the ensuing offspring to long-term adverse health outcomes. To gain insight into environmental influences on fetal development, this QF2011 study evaluated the urinary metabolomes of 4-year-old children (n = 89) who were exposed to the 2011 Queensland flood in utero. Proton nuclear magnetic resonance spectroscopy was used to analyze urinary metabolic fingerprints based on maternal levels of objective hardship and subjective distress resulting from the natural disaster. In both males and females, differences were observed between high and low levels of maternal objective hardship and maternal subjective distress groups. Greater prenatal stress exposure was associated with alterations in metabolites associated with protein synthesis, energy metabolism, and carbohydrate metabolism. These alterations suggest profound changes in oxidative and antioxidative pathways that may indicate a higher risk for chronic non-communicable diseases such obesity, insulin resistance, and diabetes, as well as mental illnesses, including depression and schizophrenia. Thus, prenatal stress-associated metabolic biomarkers may provide early predictors of lifetime health trajectories, and potentially serve as prognostic markers for therapeutic strategies in mitigating adverse health outcomes.

Risk management, justice (i.e. equity, fairness), and sustainability are tightly interconnected. This literature review investigates how and why justice is considered in flood risk management. 20 scientific documents published between 2015 and 2020 are analyzed in depth. The results show a distinction between distributive and procedural justice and a complicated judgment of fairness based on different philosophies that vary depending on the country, the type of flood, and the type of strategy studied. Equity is found to be an under-discussed topic compared to its importance. Justice in flood risk management matters because (i) the impacts of floods affect different people unevenly, (ii) the interest in equity evinced by public authorities influences societal transformation, and (iii) the perception of fairness matters at both individual and collective levels. This paper analyzes the link between justice considerations and sustainability in relation to four dimensions: social, ecological, spatial, and temporal. Social and spatial issues are the most commonly studied in the literature, while ecological and temporal ones have generally been overlooked, creating a research gap. The results are discussed in terms of their diversities of justice concepts, places of investigation, and types of strategies. Various justice frameworks are used, but since none of them focus specifically on the contribution of flood risk management to sustainability through justice considerations, a flood risk justice framework is developed, which translates into theoretical and practical tools. It is based on the considerations of both humans and non-humans into different spatio-temporal scales. • Justice issues are under-discussed while they matter for flood risk management. • Diverse case studies in various places show procedural and distributive (in)justice. • There is no agreement in the literature on how to judge the fairness of a strategy. • The literature is mostly limited to social and spatial justice aspects. • Flood risk justice includes social, ecological, spatial, and temporal issues.

Abstract Topo‐bathymetric LiDAR (TBL) can provide a continuous digital elevation model (DEM) for terrestrial and submerged portions of rivers. This very high horizontal spatial resolution and high vertical accuracy data can be promising for flood plain mapping using hydrodynamic models. Despite the increasing number of papers regarding the use of TBL in fluvial environments, its usefulness for flood mapping remains to be demonstrated. This review of real‐world experiments focusses on three research questions related to the relevance of TBL in hydrodynamic modelling for flood mapping at local and regional scales: (i) Is the accuracy of TBL sufficient? (ii) What environmental and technical conditions can optimise the quality of acquisition? (iii) Is it possible to predict which rivers would be good candidates for TBL acquisition? With a root mean square error (RMSE) of 0.16 m, results from real‐world experiments confirm that TBL provides the required vertical accuracy for hydrodynamic modelling. Our review highlighted that environmental conditions, such as turbidity, overhanging vegetation or riverbed morphology, may prove to be limiting factors in the signal's capacity to reach the riverbed. A few avenues have been identified for considering whether TBL acquisition would be appropriate for a specific river. Thresholds should be determined using geometric or morphological criteria, such as rivers with steep slopes, steep riverbanks, and rivers too narrow or with complex morphologies, to avoid compromising the quality or the extent of the coverage. Based on this review, it appears that TBL acquisition conditions for hydrodynamic modelling for flood mapping should optimise the signal's ability to reach the riverbed. However, further research is needed to determine the percentage of coverage required for the use of TBL as a source of bathymetry in a hydrodynamic model, and whether specific river sections must be covered to ensure model performance for flood mapping.