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A case study describes the impact on a collection of the extreme floods in eastern Australia in February 2022, and the salvaging of the Lismore Regional Art Gallery art collection. Despite predetermined protocols and preparedness efforts, the gallery suffered unprecedented flooding, requiring coordinated solutions to support emergency recovery. The project included relocating and stabilising around 1400 artworks, divided between the permanent collection and temporary exhibitions. Coordinated collaboration with stakeholders was needed to determine which artworks were salvageable; initial assessments indicated 60%. However, after further assessment this was reduced to 40% of all artworks able to be returned to a condition suitable for storage and display. The paper focuses on the assessment criteria used to prioritise artworks for salvage and conservation: insurance value, condition post-flooding, the views of living artists on display of treated works, and sentimental and community importance. It also outlines the conservation processes for flood-damaged paintings on canvas, works on paper, and photographgraphs, highlighting challenges and outcomes. [ABSTRACT FROM AUTHOR]

Background: Iran is a disaster-prone country, which in recent years has been affected by heavy rainfall and consequent flooding. In March 26, 2019, heavy rainfall in northern parts of Iran resulted in flooding. The situation became more critical when central and western provinces were affected, finally causing significant damages in 25 provinces. The most affected areas were Golestan, and Khuzestan provinces with significant damages to their infrastructure, killing 76 people. Materials and Methods: This qualitative study aims to describe the findings and results of field visits in flood-hit provinces of Lorestan, Khuzestan and Golestan. All interviews were held with experts in late April 2019. Results: Golestan province was in recovery phase and Lorestan and Khuzestan provinces were in response phase. Due to the acute conditions of these two mentioned areas, it was not possible to visit all areas. In Lorestan Province Treatment and Emergency Situations; In Golestan Province Health Status and in Khuzestan Province Pre-hospital Care and Rescue Support were visited and evaluated. The field visited results indicate the presence of government forces and people in the field and provide comprehensive assistance to the flood-affected areas. Conclusion: There are numerous hazards each year, but few documented lessons are available for researchers. Due to the importance of applying lessons for community development it is imperative that special attention be paid to the discussion of emergency and disaster research and the presence of specialized researchers to record lessons learned. Although organizations make significant efforts during disasters, the specialized research force for recording these achievements in disasters remains neglected. Therefore, it is valuable to document and apply appropriate documentation to promote interventions and responses to possible future events. [ABSTRACT FROM AUTHOR]

Flooding is Aotearoa-New Zealand's most frequent natural hazard, and there is high confidence that climate change is making extreme rainfall events more frequent and intense. Additionally, there are significant development pressures which could both increase the number of people and assets at risk and the flood hazard. To date, there is no publicly available consistent approach to accurately determine flood risk on a national scale, nor for how this may be changing; although there is a growing legislative requirement to provide quality information over multiple spatial scales. This paper draws on empirical data to gain insights on how to best manage changing flood risks in Aotearoa-New Zealand from the perspective of centrally organised entities. Findings confirm the need for a nationally consistent approach to flood risk management, better understanding of Aotearoa's communities and their vulnerability to floods, equitable access to quality information and decision-support tools, and better understanding of the economic impacts on differing communities, regions and places. The paper concludes that to achieve a flood-resilient Aotearoa, flood governance needs to be reconfigured to achieve national consistency in flood risk management whilst enabling targeted variability at the local scale. [ABSTRACT FROM AUTHOR]

Lacustrine environments are considered favorable locations for Neolithic settlements, constituting a reliable year‐round water resource, which contributes to fertile arable land, rich biodiversity, and natural protection. Living by the wetlands, however, is characterized by intensive ecological vulnerabilities, that is, floods and fire events. These recurrent episodes are difficult to trace in the occupation layers since natural processes combined with human activities can form variable mixed microenvironments. Consequently, the direct impact of these events on the biography of the settlement and the decision‐making of its inhabitants is understudied. This paper presents a high‐resolution, microstratigraphic analysis at the Neolithic pile‐dwelling settlement of Dispilio (Kastoria, northern Greece) to trace past ecological threats and unravel the resilience strategies of the lake‐dwellers against the continuously altered microenvironments. By correlating the results with regional environmental and cultural events, this paper questions the role of environmental changes as triggers for cultural modifications and considers a wide range of strategies for coping with wetland hazards. [ABSTRACT FROM AUTHOR]

Losses from catastrophic floods are driving intense efforts to increase preparedness and improve response to disastrous flood events by providing early warnings. Yet accurate flood forecasting remains a challenge due to uncertainty in modeling, calibrating, and validating a useful early warning system. This paper presents the Requisitely Simple (ReqSim) flood forecasting system that includes key variables and processes of basin hydrology and atmospheric forcing in a data-driven modeling framework. The simplicity of the modeling structure and data requirements of the system allows for customization and implementation in any medium to large rain-fed river basin globally, provided there are water level or discharge measurements at the forecast locations. The proposed system's efficacy is demonstrated in this paper through providing useful forecasts for various river basins around the world. This include 3–10-day forecasts for the Ganges and Brahmaputra rivers in South Asia, 2–3-day forecast for the Amur and Yangtze rivers in East Asia, 5–10-day forecasts for the Niger, Congo and Zambezi rivers in West and Central Africa, 6–8-day forecasts for the Danube River in Europe, 2–5-day forecasts for the Parana River in South America, and 2–7-day forecasts for the Mississippi, Missouri, Ohio, and Arkansas rivers in the USA. The study also quantifies the effect of basin size, topography, hydrometeorology, and river flow controls on forecast accuracy and lead times. Results indicate that ReqSim's forecasts perform better in river systems with moderate slopes, high flow persistence, and less flow controls. The simple structure, minimal data requirements, ease of operation, and useful operational accuracy make ReqSim an attractive option for effective real-time flood forecasting in medium and large river basins worldwide. [ABSTRACT FROM AUTHOR]

This paper presents a building‐level post‐hazard functionality model for communities exposed to flood hazards including the interdependencies between the population, buildings, and infrastructure. An existing portfolio of building archetypes is used to model the post‐hazard physical flood functionality of different building typologies within the community with the goal of supporting resilience‐informed decision‐making. Specific fragility‐based flood functionality curves were developed for this portfolio to quantify the exceedance probability of a prescribed set of functionality states. While the physical functionality of buildings is significant to the total functionality of a building and community resilience assessment, the functionality of utilities such as power and water along with the accessibility of the household to essential services such as schools and hospitals is crucial to measure their total functionality. Therefore, functionality models for essential infrastructure were developed to assess housing unit‐ and building‐level functionality following flood hazards. This model also accounts for the functionality of the road network following a flood hazard to identify the level of accessibility of households to different services (e.g., schools, hospitals, gas stations, shopping centers, etc.). The main novelty of this paper is the ability to quantify the total functionality of buildings based on a socio‐physical formulation after including the interdependencies between the functionality of the physical systems and the subsequent functionality of the socio‐economic systems, which is key to measuring resilience at the community level. This was evident from the analysis results using a testbed community of Lumberton, NC, showing that the physical functionality is not sufficient to quantify the total post‐hazard functionality of buildings and that the functionality of other subsystems such as utilities and accessibility to essential services are also needed to quantify the total functionality of buildings and the livability of households. [ABSTRACT FROM AUTHOR]

The increasing availability of hydrological and physiographic spatiotemporal data has boosted machine learning's role in rapid flood mapping. Yet, data scarcity, especially high-resolution DEMs, challenges regions with limited access. This paper examines how DEM type and resolution affect flood prediction accuracy, utilizing a cutting-edge deep learning (DL) method called 1D convolutional neural network (CNN). It utilizes synthetic hydrographs as training input and water depth data obtained from LISFLOOD-FP, a 2D hydrodynamic model, as target data. This study investigates digital surface models (DSMs) and digital terrain models (DTMs) derived from a 1 m LIDAR-based DTM, with resolutions from 15 to 30 m. The methodology is applied and assessed in a established benchmark, city of Carlisle, UK. The models' performance is then evaluated and compared against an observed flood event using RMSE, Bias, and Fit indices. Leveraging the insights gained from this region, the paper discusses the applicability of the methodology to address the challenges encountered in a data-scarce flood-prone region, exemplified by Pakistan. Results indicated that utilizing a 30 m DTM outperformed a 30 m DSM in terms of flood depth prediction accuracy by about 21% during the flood peak stage, highlighting the superior performance of DTM at lower resolutions. Increasing the resolution of DTM to 15 m resulted in a minimum 50% increase in RMSE and a 20% increase in fit index across all flood stages. The findings emphasize that while a coarser resolution DEM may impact the accuracy of machine learning models, it remains a viable option for rapid flood prediction. However, even a slight improvement in data resolution in data-scarce regions would provide significant added value, ultimately enhancing flood risk management. [ABSTRACT FROM AUTHOR]

Disaster is often seen as a "leveller" that affects everyone equally but the impact of disasters varies due to structural inequalities, access to resources, gender roles, and power relations, leading to a disproportionate effect on certain populations. This paper is based on a case study of three flood-affected districts of Assam and explores how gender is often used in a restrictive manner, confining it to a binary and neglecting non-binary gender identities, their vulnerabilities, and capacities in disaster risk reduction. These case studies illustrate that communities are vulnerable not only because of their physical nature but also due to their social positioning. [ABSTRACT FROM AUTHOR]

The significant rainfall in October 2018 in northern Iran caused devastating flooding that caused considerable economic losses and claimed at least nine lives. Following the flooding, several bridges have suffered different levels of damage. Immediately after the event, the authors conducted a field investigation to study the performance of RC bridges during the flood. This paper presents the failure modes of flood-affected bridges and provides reasons for every failure case. The results revealed that scour around foundations, pier tilting, flexural failure of piers, and superstructure unseating were the most significant failure modes observed. Pile-supported bridges performed notably better than those with shallow foundations. In addition, observations have revealed that structural integrity plays a crucial role in the general stability of bridges during flooding. Pier ductility is another significant parameter that affects the performance of bridges during flood events. Finally, fragility curves were developed based on the empirical data set provided from the post-flood status of the bridges in the affected region. The river flow velocity (Vs), maximum flow discharge (Qp), and Qp normalized to the 10-year average river discharge (Qm) were considered intensity measures of the fragility analysis. The correlation analyses revealed that despite Vs and Qp/Qm , the flow discharge was not an appropriate intensity measure for generating fragility curves. [ABSTRACT FROM AUTHOR]

The intensities and frequencies of extreme rainstorms are increasing, which may result in severe inundation of urban metro systems. Although there is some risk assessment research on regional metro systems based on spatiotemporal data, the characteristics of specific metro stations and shortcomings in the emergency response process need more consideration. In this paper, a risk analysis model for rainstorm inundation in metro systems based on a Bayesian network and a practical case study are proposed. First, the risk factors are obtained by integrating general mechanism analysis and the case study. Second, an event evolution diagram is established to represent the comprehensive evolution process of a potential event. Third, the risk analysis model is established using a Bayesian network model considering the quantitative causal relationships between risk factors. This model is used to analyze the risk of supporting emergency management, including emergency preparation based on critical risk factor sensitivity identification, prewarning response strategy development based on risk analysis as rainstorms occur, and rescue strategy development based on risk analysis as rainstorm water flows into metro tunnels. Furthermore, this model can be flexibly improved as natural hazards and metro systems change and as new problems are exposed in practical cases. [ABSTRACT FROM AUTHOR]

Increasing resilience to flooding is a complex process that requires horizontal and vertical coordination between institutions in policy making and implementation. This paper explores the effect of institutional coordination on managing flood risk in two cities plagued by flooding. Our results show that efforts on building urban flood resilience can be undermined by lack of proper coordination between urban development, water management and land use planning. We find that this complexity is magnified by the emergence of the concept of resilience as an urban development goal that is increasingly pursued by various authorities, but that is inherently contested in practice. [ABSTRACT FROM AUTHOR]

Global hydrological reanalyses are modelled datasets providing information on river discharge evolution everywhere in the world. With multi‐decadal daily timeseries, they provide long‐term context to identify extreme hydrological events such as floods and droughts. By covering the majority of the world's land masses, they can fill the many gaps in river discharge in‐situ observational data, especially in the global South. These gaps impede knowledge of both hydrological status and future evolution and hamper the development of reliable early warning systems for hydrological‐related disaster reduction. River discharge is a natural integrator of the water cycle over land. Global hydrological reanalysis datasets offer an understanding of its spatio‐temporal variability and are therefore critical for addressing the water–energy–food–environment nexus. This paper describes how global hydrological reanalyses can fill the lack of ground measurements by using earth system or hydrological models to provide river discharge time series. Following an inventory of alternative sources of river discharge datasets, reviewing their advantages and limitations, the paper introduces the Copernicus Emergency Management Service (CEMS) Global Flood Awareness System (GloFAS) modelling chain and its reanalysis dataset as an example of a global hydrological reanalysis dataset. It then reviews examples of downstream applications for global hydrological reanalyses, including monitoring of land water resources and ocean dynamics, understanding large‐scale hydrological extreme fluctuations, early warning systems, earth system model diagnostics and the calibration and training of models, with examples from three Copernicus Services (Emergency Management, Marine and Climate Change). [ABSTRACT FROM AUTHOR]

A typhoon passing through or making landfall in a coastal city may result in seawater intrusion and continuous rainfall, which may cause urban flooding. The urban flood disaster caused by a typhoon is a dynamic process that changes over time, and a dynamic Gaussian Bayesian network (DGBN) is used to model the time series events in this paper. The scene data generated by each typhoon are different, which means that each typhoon has different characteristics. This paper establishes multiple DGBNs based on the historical data of Macau flooding caused by multiple typhoons, and similar analysis is made between the scene data related to the current flooding to be predicted and the scene data of historical flooding. The DGBN most similar to the scene characteristics of the current flooding is selected as the predicting network of the current flooding. According to the topography, the influence of the surface confluence is considered, and the Manning formula analysis method is proposed. The Manning formula is combined with the DGBN to obtain the final prediction model, DGBN-m, which takes into account the effects of time series and non-time-series factors. The flooding data provided by the Macau Meteorological Bureau are used to carry out experiments, and it is proved that the proposed model can predict the flooding depth well in a specific area of Macau under the condition of a small amount of data and that the best predicting accuracy can reach 84%. Finally, generalization analysis is performed to further confirm the validity of the proposed model. [ABSTRACT FROM AUTHOR]

The cornerstone assumption of all Flood Geology models is that rocks can form quickly (i.e., within the timeframe of months to years). However, to date, only isolated examples from the field have been used to support the hypothesis without any quantitative justification. This paper therefore presents the theoretical basis (originally set out by Terzaghi, 1922) for determining the timescales for the first phase of lithification, the mechanical compaction of the sediment under its self-weight (otherwise known as consolidation). The paper demonstrates that when basic soil mechanics theory is applied to the consolidation of thick clay layers of the order of 1,000 m such as those found in the North Sea, Gulf of Mexico, and the Caspian Sea, the timescales predicted for compaction are orders of magnitude greater than is currently assumed. Additionally, it is shown that there is a physical limit to the rate at which sediment can accumulate without creating excessive pore pressure and inducing geotechnical failures. For clay, this limit is approximately 0.1 m/yr, and, for silt, approximately 10 m/yr. [ABSTRACT FROM AUTHOR]

This paper develops a tsunami inundation model, filling the current void between industry applied simplified methods (bathtub and attenuation) and comprehensive numerical modeling. The proposed model utilizes two‐dimensional equations established on hydraulic principles (energy conservation and friction loss) to produce the finite‐difference, two‐dimensional model. While the sophistication of depth‐averaged numerical modeling has not been entirely replicated, the incorporation of hydraulic roughness and gravitational effects (slope) through the Bernoulli energy equation, accompanied by suitable assumptions, significantly improves performance over simplified bathtub and attenuation methods. This improvement not only retains excellent efficiency (completing case studies in under 100 s) but also yields inundation results comparable to traditional numerical modeling, which typically takes multiple hours to days. This is the first application of such equations to a two‐dimensional tsunami inundation model, leading to simulations at Gisborne and Christchurch, New Zealand, for validation against the numerical model, COMCOT. F1 scores produced from inundation extent comparisons were upwards of 84%. Inundation depth discrepancies recorded 77% within a ±$\pm$1 m range, while over 93% within a ±$\pm$2 m range. [ABSTRACT FROM AUTHOR]

Sea-level rise was a key factor changing environments during the Early Holocene in Northwest Europe. It affected Mesolithic hunter-gatherer communities by inundating large areas in the current North Sea, commonly referred to as Doggerland. In this paper we present novel inundation models for the southern North Sea providing visualisations of lateral inundation driven by sea-level rise and relate it to frequency analysis of radiocarbon dates from archaeological sites. These improve on previous studies that relied on bathymetric data, which includes post-inundation overprints of Holocene sedimentation and erosion, and thus significantly underestimates the timing of inundation in some areas. We constructed a paleoDEM (a composite elevation grid of the top of the Pleistocene) for the eastern part of the southern North Sea; and sea level surfaces that combine relative sea-level curves from glacio-isostatic adjustment models optimised for Britain and southern Scandinavia respectively. We corrected our paleoDEMs for tectonic background basin subsidence, and in the inundation modelling account for pre-compaction elevation of peat in coastal areas. We evaluated the impact of these model components on our results and describe the possible inundation history of Doggerland. We suggest earlier inundation than predicted by previous models, showing significant area loss around 10.5–10 ka cal BP. Palaeogeographic changes are compared with archaeological radiocarbon data using a dates-as-data approach. Composite Kernel Density Estimate and permutation tested Summed Probability Distributions are used as a proxy for the visibility, nature and intensity of human activity. Results indicate key periods of growth and decline recorded in the dataset, as well as regional differences in growth rate, some correlating with inundation phases. Chiefly, we find elevated growth rates around 10.5–10 ka in northwest Germany and the Netherlands, contemporaneous with the abovementioned phase of extensive area loss, and moreover, with changes in culture and practices on Early Mesolithic sites. However, the spatiotemporal distribution of archaeological data is significantly influenced by accessibility and preservation of sediments of a certain age. We discuss the importance of inundation modelling and sediment data in understanding how landscape taphonomy affects archaeological patterning, especially in dates-as-data approaches. [ABSTRACT FROM AUTHOR]

Open-channel junctions pose a risk associated with flooding and erosion. However, despite the numerous studies concerning the channel junctions, the bed and flow field evolutions at junctions for flood conditions have yet to be investigated. To address this research gap, this paper investigates the evolutions of the bed and flow field during a flood event at a right-angled open-channel junction utilizing three-dimensional (3D) computational fluid dynamics (CFD) modeling. The transient Reynolds-averaged Navier–Stokes (RANS) equations with the renormalized group (RNG) k–ϵ as the turbulence closure for the flow field, the Meyer-Peter and Muller equation for bed-load sediment transport rate, the convection–diffusion equation for the sediment concentration distribution, and the sediment continuity equation for the bed evolution are used in the numerical model. The model simulates the characteristics bed morphology at the junction with reasonable accuracy compared with the available laboratory data. Three scenarios (Scenarios 1, 2, and 3) were considered by applying the triangular flood wave at the inlet of the tributary channel, main channel, and both channels, respectively. The quasi-equilibrium deformed bed channel junction with steady inflow conditions of the validation case was considered as the initial condition for the flood flow simulations. The simulated results show that the junction bed is deformed considerably due to the significant increase in bed shear stress during a flood event. The deepest scour area gradually grows wider during the passage of the flood wave. The maximum value of the scour increased by 24.4%, 14.6%, and 31.2% in Scenarios 1, 2, and 3, respectively. The findings of the study improve the understanding of the junction hydrodynamics and bed morphological features for flood conditions. [ABSTRACT FROM AUTHOR]

Flood maps are a crucial component of integrated flood risk management. While their key role is commonly acknowledged by experts and scholars, however, literature and findings on the practical utilization of flood maps (including the user' experiences) within the processes of governance are scarce. Our study aims to contribute to closing this gap; by focusing on the Czech local government bodies, data collected through a questionnaire survey allowed us to examine (a) how, or whether at all, the officials employ flood maps in their agendas; (b) how do they experience and assess working with the maps; and (c) which data would they supplement the extant flood maps by. Our findings show that the praxis of local flood-related governance in the Czech Republic still largely neglects the up-to-date approaches and practices of flood risk management. The officials addressed mostly continue to rely on the earliest type of floodplain maps and purely technical aspects of floods, while largely omitting the newer flood danger and risk maps; thus, they are also missing the opportunities of applying multi-criteria assessment of the flood risk and more effective communication with the public. The paper concludes with a set of suggestions for relevant praxis and future research. [ABSTRACT FROM AUTHOR]

It has become common to attribute the growing frequency and severity of floods to climate change. But the factors behind flooding are many, and climate change often disappears from the equation at the local level. This study draws on interviews with key informants and community members and focus group discussions to explore the increasing incidence of flooding in two sub-districts in Eastern Thailand. To our surprise, there was little sense of community anger: flood risk had increased; the causes rooted in maladaptation linked to land conversion were recognised and uncontested; and injustice was palpable. But anger and resistance were muted. The paper seeks to make sense of this situation. Villagers accepted their complicity in creating the conditions for heightened flood risk through their willingness to sell their land for conversion. The disconnection between the identification of causality and the allocation of blame raises questions about how notions of environmental justice play out in places like Ban Thapma and Ban Nhonglalok, where justice and injustice do not fall equally across space and society. [ABSTRACT FROM AUTHOR]

This paper moves across the ecological assemblages of the Periyar basin in Kerala. It argues that the connectivities and unintentional designs that emerge bespeak the Anthropocene in its regional and political peculiarities. The river has never been a conduit of water alone. The narrative builds broadly on ecological relations entrenched in history, most visibly as hydrological regimes. Such regimes are significant because of the riparian densities that articulate the geo‐morphology. The different entanglements in ecology, as well as the successive productions of natures, gain significance as 'recognitions' during rupture events like the large floods. In contemporary contexts, the versatile flows of capital dissolve markers and boundaries and reconfigure regions in terms of capital. Vikasanam or new urban reforms, apart from political policies, are also ecological designs that normalise exceptions, otherwise reserved for special economic zones. The frictions with new materiality, post dam floods and hydrological controls, during developmental and neoliberal post developmental phases, become moments of recognition, making and unmaking sense of place. [ABSTRACT FROM AUTHOR]

Flood detection from synthetic aperture radar (SAR) imagery plays an important role in crisis and disaster management. Based on pre- and post-flood SAR images, flooded areas can be extracted by detecting changes of water bodies. Existing state-of-the-art change detection methods primarily target optical image pairs. The nature of SAR images, such as scarce visual information, similar backscatter signals, and ubiquitous speckle noise, pose great challenges to identifying water bodies and mining change features, thus resulting in unsatisfactory performance. Besides, the lack of large-scale annotated datasets hinders the development of accurate flood detection methods. In this paper, we focus on the difference between SAR image pairs and present a differential attention metric-based network (DAM-Net), to achieve flood detection. By introducing feature interaction during temporal-wise feature representation, we guide the model to focus on changes of interest rather than fully understanding the scene of the image. On the other hand, we devise a class token to capture high-level semantic information about water body changes, increasing the ability to distinguish water body changes and pseudo changes caused by similar signals or speckle noise. To better train and evaluate DAM-Net, we create a large-scale flood detection dataset using Sentinel-1 SAR imagery, namely S1GFloods. This dataset consists of 5,360 image pairs, covering 46 flood events during 2015–2022, and spanning 6 continents of the world. The experimental results on this dataset demonstrate that our method outperforms several advanced change detection methods. DAM-Net achieves 97.8% overall accuracy, 96.5% F1, and 93.2% IoU on the test set. Our dataset and code are available at https://github.com/Tamer-Saleh/S1GFlood-Detection. [ABSTRACT FROM AUTHOR]

The paper presents an experience of using artificial intelligence techniques, in particular, neural networks to solve relevant problems of hydrometeorology. The results of the investigations at the Planeta State Research Center on Space Hydrometeorology in detecting clouds and snow cover from the Himawari, Electro-L, and Meteor-M satellite data, as well as on classifying cloud types according to the AHI instrument data (Himawari-8) are reported. The findings of the work on retrieving values of total ozone and water vapor according to the infrared sensing devices are demonstrated. The work on detecting the boundaries of the ice cover and river floods from medium- and high-resolution satellite instruments, as well as the technologies for temperature and humidity sensing in the microwave spectrum are considered. The studies have shown that the use of neural network technologies provides the required accuracy of the received hydrometeorological information and high speed of processing incoming data. [ABSTRACT FROM AUTHOR]

Serving as a crucial part of the Yangtze River Basin (YRB)'s flood control system, Flood Detention Areas (FDAs) are vital in mitigating large-scale floods. Urbanization has led to the development of urban FDAs, but significant losses could ensue if these FDAs are activated. With improved reservoirs and embankments, flood pressure in the middle reaches has lessened, posing challenges in balancing flood control and economic benefits. This paper presents a comparative analysis of land use, GDP, and population in FDAs and adjacent cities, enhancing our understanding of their disparities and interrelations. Using the Analytic Hierarchy Process (AHP)–Entropy Weight Method (EW)–Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) comprehensive evaluation method, we assess changes in flood control and economic values in FDAs. The results show a conflict between flood control and economic policies in FDAs, highlighting their underestimated economic potential, especially in urban areas. This study identifies differences in economic development across FDAs and a strong correlation between flood control value and inundation rates. Based on evaluations and simulations of the 1954 flood, we provide recommendations for the FDAs' construction plan, which serves the development and flood management of the YRB and offer insights for similar assessments elsewhere. [ABSTRACT FROM AUTHOR]

The January 2011 flood event that impacted southeast Queensland is amongst the most extensive and severe floods in terms of loss of life and property damage that the region has experienced, despite it being only the eighth highest flood on record at the Brisbane City Gauge. The spring of 2010 was the wettest on record for Queensland, New South Wales, and the Murray-Darling Basin (Bureau of Meteorology 2011a) at that time. The flood mitigation dams in the region, Somerset Dam and Wivenhoe Dam, had to be operated for flood mitigation purposes during October 2010, which was the first occasion since February 2001 that Wivenhoe Dam had been called into action due to the Millennium Drought. The wet October was followed by a very dry November which, in turn, was followed by the wettest December on record for Brisbane. Somerset Dam and Wivenhoe Dam were again pressed into action on three separate occasions during December 2010. The resultant releases ensured that only minor flooding resulted in the Lower Brisbane River during these events. However, on the 5th of January 2011, another rainfall event started to unfold across the catchments of the dams. By the 10th of January 2011, an upper-level low combined with a humid easterly flow to bring very heavy rainfall and flash flooding to southeast Queensland and northeast New South Wales. The heaviest falls were in the areas north and west of Brisbane, with three-day totals exceeding 200 mm over most of the Brisbane River catchment. This rainfall event resulted in a flood of record in the Upper Brisbane River and Upper Lockyer Creek catchments that sadly resulted in a substantial loss of life in Toowoomba and the Lockyer Valley, and which required record releases from Wivenhoe Dam. The resultant downstream flooding saw some 14,000 properties impacted, principally in the Lockyer Valley Regional Council, Somerset Regional Council, Brisbane City Council, and Ipswich City Council local government regions. Flood damage was estimated to be around $2.53 billion. This paper discusses the event as it unfolded and the subsequent judicial inquiries, engineering reviews, and legal proceedings that resulted from the consequences of the operation of Somerset Dam and Wivenhoe Dam. [ABSTRACT FROM AUTHOR]

The Qinghai-Tibet Plateau is a climate-sensitive region. The characteristics of drought and flood events in this region are significantly different as compared to other areas in the country, which could potentially induce a series of water security, ecological and environmental problems. It is urgent that innovative theories and methods for estimation of drought and flood disasters as well as their adaptive regulations are required. Based on extensive literature review, this paper identifies new situations of the evolution of drought and flood events on the Qinghai-Tibet Plateau, and analyzes the research progress in terms of monitoring and simulation, forecasting and early warning, risk prevention and emergency response. The study found that there were problems such as insufficient integration of multi-source data, low accuracy of forecasting and early warning, unclear driving mechanisms of drought and flood disaster chains, and lack of targeted risk prevention and regulation measures. On this basis, future research priorities are proposed, and the possible research and development paths are elaborated, including the evolution law of drought and flood on the Qinghai-Tibet Plateau, the coincidence characteristics of drought and flood from the perspective of a water resources system, prediction and early warning of drought and flood coupled with numerical simulation and knowledge mining, identification of risk blocking points of drought and flood disaster chain and the adaptive regulations. Hopefully, the paper will provide technical support for preventing flood and drought disasters, water resources protection, ecological restoration and climate change adaptation on the Qinghai-Tibet Plateau. [ABSTRACT FROM AUTHOR]

Few publications may claim to have transcended the original field in which they were written, by shaping a wide range of research areas and philosophies. In this short paper we reflect on the manner in which Gilbert F. White’s 1945 publication ‘Human adjustment to floods’ has not only shaped how we study and perceive flooding, but has also had a significance beyond its original aims, revolutionizing the ways in which hazard and risk are conceptualized more generally. Before considering the impact of ‘Human adjustment to floods’, we briefly review academic understanding of floods in the decades leading up to the 1940s and later place the 1945 paper in the context of White’s subsequent contributions to research which both developed and built on his ideas. [ABSTRACT FROM AUTHOR]

The runoff change in a large river is significant for hydrological event monitoring, such as floods and droughts. In this paper, we attempt to invert the river flow change based on the surface displacements observed by the continuous global navigation satellite system (GNSS) stations in the Wuhan section of the Yangtze River (WYR). We establish a two‐dimensional model accounting for deformation from a line load in an elastic half‐space to estimate the annual water load change from the GNSS data. The results show that the inverted line load from the annual maximum displacement change observed by the GNSS is Ne=2.30×108N·m−1 ${N}_{e}=2.30\times {10}^{8}\mathrm{N}\cdot {\mathrm{m}}^{-1}$, which is in good agreement with the river load from the hydrological station. This paper demonstrates a low‐cost and practical method to river flow research in local areas, which is also a creative application for the GNSS. Plain Language Summary: The runoff change in large rivers is an important element for flood and drought monitoring. Hydrological stations are used to monitor the water load change. Because of the high cost of construction and maintenance, there are few hydrological stations in most areas, and the unpredictable noise of hydrological stations influences the stability and precision of the results. We use the vertical displacements observed by the global navigation satellite system (GNSS) to estimate the river load and find that the results agree with the calculated water load change from hydrological stations. Thus, the GNSS can be an alternative for runoff change research, with low cost and high efficiency. In this study, we find a new application for the GNSS to water runoff change in local areas. Key Points: We propose a new method for estimate the river load change using the continuous global navigation satellite system (GNSS) dataA simple two‐dimensional line load on Elastic half‐space can invert the river load with considerable accuracy in local areasThe forward modeling prove that the modeled displacement agrees with the observed displacement from the GNSS [ABSTRACT FROM AUTHOR]

Flood events are becoming more severe, causing significant problems to human communities, including physical, psychological, and material damage. For both flood forecasting in emergency response situations and flood mapping, georeferencing and data curation are paramount in the context of prevention or preparedness. Hence, data display, data management, and articulation with numerical simulation results must occur on GIS platforms. Our research is motivated by recent advances in Web and GIS technologies, social sensing and high-performance computing, and an envisaged wider availability of remote sensing data. This paper presents and discusses an innovative Web GIS platform named "RiverCure Portal" or "RCP" for short. This platform combines observations and hydrodynamic modelling tools to support various stages of the flood risk management cycle, including operational response, emergency preparedness, and risk assessment. RCP is a multi-organization, multi-context digital platform with flexible configuration features to define and support multiple sensor types and modelling options, satisfying the various needs of different organizations and stakeholders. In addition, this paper discusses the RiverCure Approach, which encompasses the following tasks directly supported by the RCP platform: defining the context and involved geometries, associating sensors to the context, pre-processing and generating the context mesh, defining the simulation event, running the simulation event, and analyzing the results from the simulation event. Thus, the RCP streamlines and simplifies data analysis and simulation procedures to meet decision-makers' needs. The novelties discussed in this paper include the design and discussion of a Web GIS platform that allows (i) to manage flood data and results of simulations at several contextual levels by different stakeholders such as domain experts, decision-makers, researchers, or students; (ii) to process and curate sensed data obtained from physical and social sensors; and (iii) update the state and values of the parameters of simulation tools through continuous data assimilation techniques for forecasting purposes. Finally, this paper supports the explanation and discussion with a running example, "Águeda 2016 flood" event, which dataset is publicly available for further study and experimentation. [ABSTRACT FROM AUTHOR]

Uniformitarian scientists were surprised to discover channels on Mars like the Channeled Scablands of eastern Washington. Climate models indicate that large-scale Martian floods are impossible. This paper will describe what appear to be flood features on Mars. Three types of channels on Mars are described in this paper: valley networks, outflow channels, and gullies. Like the Solar System's other solid bodies that have not been resurfaced by debris and volcanism, Mars possesses numerous impact craters, some very large, which provide a framework for the planet's history. Secular uniformitarian scientists divide the geologic history of Mars into four main periods which span 4.5 billion years. [ABSTRACT FROM AUTHOR]

This paper examines the ripple effects of flooding on the roles and economic activities of women in Isoko-Nation, flood-prone areas that exhibit low-lying plain that resides on the coaster region of Delta State. The region attracts high population due to flooding fluvial deposits on the flood plains that serve as fertilizer to boost agricultural activities of the people. Consequent upon this, the socioeconomic development of the region is facing reversing years of progress, socially and economically in response to the rippling effects thus crippling effective and sustainable role of the women. The situation is worsened by lack of infrastructural facilities to encourage alternative income earning activities. And the dearth of the women socio-economic status means the dearth of socioeconomic development of the region therefore the need to severe the women from the rippling flood effects is vital to the sustainable development of the region. Therefore the paper discussed the implications of the downgrading and reversed economic activities of the women on the sustainable development in the region and noted that though the annual flooding occurrence in the region cannot be completely eliminated however the associated disasters can be mitigated and the rippling effects reduced. The paper recommends that a proper understanding of the season and dynamic climatic trends of the region will create conscious knowledge on the mitigation strategies to reduce the unprecedented effect of incessant flooding and ginger the effort of the government to fulfill its commitment of improving the quality of lives and standard of living in Isoko-nation. The study substantiate that provision of infrastructure would energize the women whose socio-economic status is on the decline to embrace alternative source of income that would revive their hope and faith in the economy of the region. [ABSTRACT FROM AUTHOR]

Here we present FOCA (Italian FlOod and Catchment Atlas), the first systematic collection of data on Italian river catchments for which historical discharge time series are available. Hydrometric information, including the annual maximum peak discharge and average daily annual maximum discharge, is complemented by several geomorphological, climatological, extreme rainfall, land-cover and soil-related catchment attributes. All hydrological information derives from the most recently released datasets of discharge and rainfall measurements. To enhance the reproducibility and transferability of the analysis, this paper provides a description of all the raw data and the algorithms used to build the basin attribute dataset. We also describe the approaches adopted to solve problems encountered during the digital elevation model elaboration in areas characterized by a complex morphology. Details about the data quality-control procedure developed to detect and correct errors are also reported. One of the main novelties of FOCA with respect to other national-scale datasets is the inclusion of a rich set of geomorphological attributes and extreme rainfall features for a large set of basins covering a wide range of elevations and areas. Using this first nationwide data collection (available at 10.5281/zenodo.10446258, Claps et al., 2023), a wide range of environmental applications, with a particular focus on flood studies, can be undertaken within the Italian territory. [ABSTRACT FROM AUTHOR]

Heavy rainfall in eastern Africa between late 2019 and mid 2020 caused devastating floods and landslides throughout the region. These rains drove the levels of Lake Victoria to a record-breaking maximum in the second half of May 2020. The combination of high lake levels, consequent shoreline flooding, and flooding of tributary rivers caused hundreds of casualties and damage to housing, agriculture, and infrastructure in the riparian countries of Uganda, Kenya, and Tanzania. Media and government reports linked the heavy precipitation and floods to anthropogenic climate change, but a formal scientific attribution study has not been carried out so far. In this study, we characterize the spatial extent and impacts of the floods in the Lake Victoria basin and then investigate to what extent human-induced climate change influenced the probability and magnitude of the record-breaking lake levels and associated flooding by applying a multi-model extreme event attribution methodology. Using remote-sensing-based flood mapping tools, we find that more than 29 000 people living within a 50 km radius of the lake shorelines were affected by floods between April and July 2020. Precipitation in the basin was the highest recorded in at least 3 decades, causing lake levels to rise by 1.21 m between late 2019 and mid 2020. The flood, defined as a 6-month rise in lake levels as extreme as that observed in the lead-up to May 2020, is estimated to be a 63-year event in the current climate. Based on observations and climate model simulations, the best estimate is that the event has become more likely by a factor of 1.8 in the current climate compared to a pre-industrial climate and that in the absence of anthropogenic climate change an event with the same return period would have led lake levels to rise by 7 cm less than observed. Nonetheless, uncertainties in the attribution statement are relatively large due to large natural variability and include the possibility of no observed attributable change in the probability of the event (probability ratio, 95 % confidence interval 0.8–15.8) or in the magnitude of lake level rise during an event with the same return period (magnitude change, 95 % confidence interval 0–14 cm). In addition to anthropogenic climate change, other possible drivers of the floods and their impacts include human land and water management, the exposure and vulnerability of settlements and economic activities located in flood-prone areas, and modes of climate variability that modulate seasonal precipitation. The attribution statement could be strengthened by using a larger number of climate model simulations, as well as by quantitatively accounting for non-meteorological drivers of the flood and potential unforced modes of climate variability. By disentangling the role of anthropogenic climate change and natural variability in the high-impact 2020 floods in the Lake Victoria basin, this paper contributes to a better understanding of changing hydrometeorological extremes in eastern Africa and the African Great Lakes region. [ABSTRACT FROM AUTHOR]

Mismanaged plastic waste (MPW) and urban flooding are typically considered distinct environmental challenges. However, there are notable links between growing quantities of MPW and the rising incidence of floods in cities. A majority of people now live in cities, especially along coastlines and in estuaries where residents are both vulnerable to flooding and significant sources of plastic waste. Predicted increases in the frequency and severity of heavy rainfall associated with anthropogenic climate change coincide with rising global quantities of MPW, much of which is discharged into water bodies and the sea. Given the urgent and expanding nature of these issues, understanding impacts of urban floods on solid waste management and vice versa is crucial. Social-ecological systems (SES) thinking calls for a holistic approach to the relationships and interactions between human actors and environmental systems which can result in dynamic and emergent outcomes. In this review paper, we make a first step towards better understanding of the interactions between urban flooding and MPW by synthesizing emerging quantitative and qualitative research on particular aspects of such interactions. More research is needed which explicitly focuses on and elaborates the nature of these interactions, and also to consider potential relations across scales (from global to local) and over both long and short timeframes. We conclude that an SES approach can make visible novel possibilities for interventions which are context specific and sensitive to the interactions between urban floods and MPW. This article is categorized under: Science of Water > Water and Environmental Change Human Water > Water Governance Engineering Water > Planning Water [ABSTRACT FROM AUTHOR]

Every few years, Karachi floods during the summer monsoon. The flooding brings latent manoeuvrings by political actors looking to establish their hold over the city to the surface. Politicians, urban administrators, and relevant state and non‐state institutions blame historical planning failures, informal and illegal constructions, institutional conflict, incapable municipal governance, and widespread corruption for the flooding. They move quickly to establish authority and consolidate power while offering 'fixes'. Eviction drives against 'illegal settlements' built along storm‐water drains, heavy taxes, fines, and demolitions of non‐conforming constructions, institutional reforms, budget allocations, and project approvals for new infrastructure all happen at once. Once the emergency ceases, key players in urban politics – resident groups, community associations, political parties, municipal authorities, land developers, planners, international non‐governmental organisations, and military institutions – start working on projects of accumulation and entrenchment, in preparation for the next crisis. In this paper, we look at the space–time of Karachi's certain and yet uncertain flooding crisis as a moment to study the politics of the maybe in the Pakistani megacity. Outlining marginal and affluent residents' lived experiences in a flooding city and relating their politics with governmental responses to immediate and possible future floods, we study the conditions of inhabitation, citizenship claims, and governmental relations in Karachi. We argue that the monsoon's expectant arrival becomes a locus for articulating and modulating different kinds of popular vernaculars, governmental practices, and political manoeuvrings for institutional and individual actors seeking profit and power in and through Karachi. The politics of the maybe hinges on actors entrenching their political positions without care, taking away any possibility for a shared, coherent worldview for all Karachiites. In conclusion, we argue that distant interests and logics of this politics of governance and inhabitation are inherently exploitative, threatening to pull apart the very city they thrive on. [ABSTRACT FROM AUTHOR]

Background: Despite the high occurrence of floods in Iran, its psychological consequences have been less discussed. The present paper addresses the prevalence of Post-traumatic Stress Disorder (PTSD) and its determinants among the affected adults by the huge flood of 2019. Methods: An analytical cross-sectional study was conducted through household face-to-face surveys in August and September 2019. Individuals who were affected by floods and were at least 16 years old were randomly selected from three provinces in Iran: Lorestan and Khuzestan in the west and southwest, and Golestan in the northeast. The questionnaire of demographic and flood related variables in addition to the Impact of Event Scale-Revised (IES-R) were utilized to collect the data. We applied a complex sample analysis to describe the prevalence of PTSD and logistic regression analyses to find its determinants. Results: Out of the 2,305 individuals approached for surveys, 1,671 (72.5%) adults affected by the floods participated in the study. The majority of participants were housewives, married, had either no formal education or primary education, and resided in rural areas. The prevalence of PTSD in the participants was 24.8% (CI 95%: 20.7–28.8%) and was significantly higher in Lorestan province (39.7%, P < 0.001). Determinants of PTSD, were unemployment (adjusted odds ratio [AOR] = 3.53, CI 95%: 1.38-9.00), primary (AOR = 2.44, CI 95%: 1.10–5.41) or high school (AOR = 2.35, CI 95%: 1.25–4.40) education (vs. university), a history of mental disorders (AOR = 2.36, CI 95%: 1.22–4.58), high damage to assets (AOR = 2.29, CI 95%: 1.40–3.75), limited access to health care services after the flood (AOR = 1.95, CI 95%: 1.20–3.19), not receiving compensation for flood damage (AOR = 1.94, CI 95%: 1.01–3.83), high wealth index (AOR = 1.90, CI 95%: 1.23–2.93), and flooded house with a height of more than one meter (AOR = 1.66, CI 95%: 1.02–2.76). Conclusion: Results show a notable prevalence of PTSD, especially in Lorestan province, among adults affected by floods. Determinants of PTSD include unemployment, lower education, psychiatric history, extensive property damage, limited post-flood healthcare access, lack of compensation, and increased flood exposure. We recommend adopting an inclusive screening approach for high-risk groups and developing appropriate therapeutic and supportive interventions. [ABSTRACT FROM AUTHOR]

Trend of bridge collapses as reporting increases In recent weeks and months, there has been increased coverage of bridge collapses in the daily media. These concerned both collapses of bridges under construction and collapses caused by accidental events, such as floods, flash floods, impacts or fires, or under traffic loads. This clustered reporting suggests the question of whether the frequency of bridge collapses has increased this year and last. This paper will attempt to answer this question. To do so, both previous studies and current forecasts are summarized. In addition, a comparison of data from the IABSE collapse database with our own data collection was made. As a result, it cannot be said in principle that the collapse frequency of bridges has increased, but presumably the downward trend in collapse frequencies that has been observed for decades may have come to a halt. [ABSTRACT FROM AUTHOR]

X-band radar observations with a transmitting frequency of 9.4 GHz were conducted for over 10 h at the mouth of Tenryu River, Japan, to estimate surface velocity distributions during floods in 2010 and 2020 and analyse changes in the flow field caused by dredging in 2014. X-band radar is an imaging radar that can collect backscatter of floating objects flowing downstream with the flood flow every 2 s. The observation area extends approximately 1000 m × 1000 m. Particle image velocimetry is applied to the image sequences to guess the surface flow pattern. Flow direction in the main river channel changed smoothly, while surface flow speeds ranged from 1 to 3 m s–1 depending on the discharge. Water levels were computed using the estimated surface flow velocities, river cross-section from survey data, and observed discharge for indirect validation: it agreed within an error of 0.3 m with the observed water level. This paper highlights radar's potential for estimating surface velocity distribution during floods and harsh weather conditions. [ABSTRACT FROM AUTHOR]

Coastal regions, increasingly threatened by floods due to climate-change-driven extreme weather, lack a comprehensive study that integrates coastal and riverine flood dynamics. In response to this research gap, we conducted a comprehensive bibliometric analysis and thorough visualization and mapping of studies of compound flooding risk in coastal cities over the period 2014–2022, using VOSviewer and CiteSpace to analyze 407 publications in the Web of Science Core Collection database. The analytical results reveal two persistent research topics: the way to explore the return periods or joint probabilities of flood drivers using statistical modeling, and the quantification of flood risk with different return periods through numerical simulation. This article examines critical causes of compound coastal flooding, outlines the principal methodologies, details each method's features, and compares their strengths, limitations, and uncertainties. This paper advocates for an integrated approach encompassing climate change, ocean–land systems, topography, human activity, land use, and hazard chains to enhance our understanding of flood risk mechanisms. This includes adopting an Earth system modeling framework with holistic coupling of Earth system components, merging process-based and data-driven models, enhancing model grid resolution, refining dynamical frameworks, comparing complex physical models with more straightforward methods, and exploring advanced data assimilation, machine learning, and quasi-real-time forecasting for researchers and emergency responders. [ABSTRACT FROM AUTHOR]

Due to the complex interaction of urban and mountainous floods, assessing flood susceptibility in mountainous urban areas presents a challenging task in environmental research and risk analysis. Data-driven machine learning methods can evaluate flood susceptibility in mountainous urban areas lacking essential hydrological data, utilizing remote sensing data and limited historical inundation records. In this study, two ensemble learning algorithms, Random Forest (RF) and XGBoost, were adopted to assess the flood susceptibility of Kunming, a typical mountainous urban area prone to severe flood disasters. A flood inventory was created using flood observations from 2018 to 2022. The spatial database included 10 explanatory factors, encompassing climatic, geomorphic, and anthropogenic factors. Artificial Neural Network (ANN) and Support Vector Machine (SVM) were selected for model comparison. To minimize the influence of expert opinions on model training, this study employed a strategy of uniformly random sampling in historically non-flooded areas for negative sample selection. The results demonstrated that (1) ensemble learning algorithms offer higher accuracy than other machine learning methods, with RF achieving the highest accuracy, evidenced by an area under the curve (AUC) of 0.87, followed by XGBoost at 0.84, surpassing both ANN (0.83) and SVM (0.82); (2) the interpretability of ensemble learning highlighted the differences in the potential distribution of the training data's positive and negative samples. Feature importance in ensemble learning can be utilized to minimize human bias in the collection of flooded-site samples, more targeted flood susceptibility maps of the study area's road network were obtained; and (3) ensemble learning algorithms exhibited greater stability and robustness in datasets with varied negative samples, as evidenced by their performance in F1-Score, Kappa, and AUC metrics. This paper further substantiates the superiority of ensemble learning in flood susceptibility assessment tasks from the perspectives of accuracy, interpretability, and robustness, enhances the understanding of the impact of negative samples on such assessments, and optimizes the specific process for urban flood susceptibility assessment using data-driven methods. [ABSTRACT FROM AUTHOR]

Due to its geophysical characteristics and location in a tropical zone, Colombia is prone to flooding phenomena, which, in addition to the vulnerability of the road network and the permanent presence of the population residing close to the roads, increase the social and economic fragility of the road corridors. This situation is evident when traffic collapses due to flooding, as the country mobilizes most of its goods by land. The knowledge and systematization of the social and economic conditions of the national road layout, and the incorporation of these data into a replicable spatial model, could be an alternative for making decisions aimed at risk prevention. This paper presents the conceptual and methodological design of a proposal of the socioeconomic factors required in a road flood risk assessment using spatial analysis tools in the pilot section Route 6008 Chiquinquirá-Sáchica (36 km). A global index of socioeconomic aspects related to vulnerability is quantified at three levels: local, zonal and regional. The main result is that the road corridor presents a medium-high level of vulnerability, due to the aspects of exposure and fragility in housing and livelihood conditions. [ABSTRACT FROM AUTHOR]

One of the main problems faced by authorities when delimiting flood areas is derived from the fact that hydraulic-hydrological models and their flood maps do not accurately correspond to the actual extent of the floods and hazards, often underestimating them. In order to assess this hypothesis, this paper analyses the recent flood in Campanillas (Málaga, Spain). The study compares the differences between the official flood maps and the real flood. The results of this study clearly confirm the aforementioned underestimation. Beyond a simple comparison, a series of potential causes of this underestimation are proposed. Some of them are related to the hydraulic-hydrological model used to create the official maps (e.g., it represents a closed area, it omits indirect anthropogenic activities, it omits flood flux alterations caused by roads, bridges, etc.). Additionally, other causes are related to the characteristics of the flood hazard in Mediterranean areas (e.g., simultaneous and synergic associated hazards and the omission of rhexistasy in Mediterranean areas when modelling water infrastructures). To conclude, based on the causes of the highlighted inaccuracy of the official maps, several measures aimed at improving the forecasts in flood areas in these official maps are proposed. [ABSTRACT FROM AUTHOR]

Floods are among the most common natural disasters responsible for severe damages and human losses. Numerically produced data, managed by user-friendly tools for geographically referenced data, have been adopted to increase preparedness and reduce vulnerabilities. This paper describes the locally sensed and numerically produced data that characterize a flood event that occurred in February 2016 in the Portuguese Águeda River, referred to as Agueda.2016Flood for short. The data were managed through the RiverCure portal, a collaborative web platform connected to a validated shallow-water model featuring modelled dynamic bed geometries and sediment transport. The dataset provides a synthesis of topo-bathymetric, hydrometric and numerically produced data from a calibrated hydrodynamic model. Due to the lack of measured hydrometric data near the city, the numerically produced data are crucial for a complete description of the flood event. The Agueda.2016Flood dataset constitutes a complete validation test for flood forecasting models and a tool to better mitigate floods in this river and in similar rivers. Thus, Agueda.2016Flood is a relevant dataset for Águeda River stakeholders as well as for the community of flood modellers, as it provides a well-documented validation event for forecasting tools. The dataset can be accessed at 10.4211/hs.937927473a3a4e66a07a2e2fdd9d581e (Ricardo et al., 2024). [ABSTRACT FROM AUTHOR]

The process of a damaged ship flooding is a complicated free surface flow problem. There is a complex coupling effect between the ship cabin and the flow inside and outside of the cabin. In this paper, a GPU (graphic processing unit)- δ + -SPH (smoothed particle hydrodynamics) numerical model for the cabin flooding in deep-water environments is developed based on GPU parallel acceleration technology and Nvidia's CUDA (compute unified device architecture). First, the computational accuracy and efficiency of this numerical model are verified by experiments results on the water flooding of a simple damaged cabin model. Furthermore, the flooding characteristics of a submarine cabin are analyzed, considering different numbers of damaged cabins, depths, and opening positions. Finally, the progressive flooding and the dynamic response characteristics of a full-scale submarine model are investigated. The results show that the process of progressive flooding in a submarine cabin is characterized by its rapidity and intensity. Different factors, for example, damaged cabin numbers, cabin depths, and opening positions, have great influences on the process of flooding and the motion of the submarine cabin. This study can offer valuable technical assistance in the post-damage remediation process. [ABSTRACT FROM AUTHOR]

Located in the hyper-arid regions of Algeria, the M'zab Wadi basin has historically experienced severe flash flooding, causing severe economic damage and loss of life. Identifying potential flood hazard areas in such an arid environment, challenged by data scarcity, is necessary to forecast flood and to create early warning strategies. The paper aims to map and highlight potential flood hazard areas in the M'zab Wadi basin using geographic information system coupled with the Analytical Hierarchy Process method based on seven related flood hazard factors. The accuracy of the flood hazard map was validated using the Receiver Operating Characteristic based Area Under Curves method. The results show that 3.04% (50.35 km2) and 0.53% (8.74 km2) of the basin area are under high and very high flood vulnerability levels, respectively. The obtained results can offer significant insights to policymakers and decision-makers to make well-informed judgments regarding the effectiveness of flood protective infrastructure/measures. Furthermore, the approach adopted can be advantageous for other regions under similar conditions. [ABSTRACT FROM AUTHOR]