Assessing dike safety is of key interest to societies in low-lying areas, but results can be implausible when, for example, they contradict the observed performance of the dike. To improve credibility, load monitoring data can be incorporated using reliability updating techniques. This paper investigated the role of load variations in reliability updating and assessing credible failure probabilities. It was found that the impact of reliability updating increases when load variations are small, as a large contribution to failure probabilities comes from relatively frequent load levels, of which the conditional failure probabilities are reduced most through reliability updating. Moreover, a credibility check was introduced for dikes that have been stable for decades, where load levels with return periods of up to 10 years are not expected to contribute more than 50% to the failure probability, indicating an imbalance between load variation and strength uncertainty. This imbalance occurs when the inverse gradient of the fragility curve exceeds 1.5 times the decimate height of the load. Many Dutch dikes, including canal dikes and dikes along the large lakes and delta regions, have small decimate heights. For these dikes, strength uncertainties must be sufficiently small to obtain credible failure probability estimates.

Flood hazard maps are essential for protection and emergency plans, yet their probabilistic application is constrained by the computational cost of numerical models. Deep learning surrogates can provide orders of magnitude faster predictions, but their use for uncertainty quantification in realistic settings and their ability to incorporate hydraulic structures remain largely unexplored. Studying deep learning surrogates for probabilistic flood maps is non-trivial because of the lack of reference ground-truth data that might lead to misleading confidence in predictions. Moreover, hydraulic structures are challenging to include due to their generally unidimensional nature. In this work, we investigate the use of deep learning surrogates for realistic, large-scale flood simulations in case studies with hydraulic structures under diverse boundary conditions. To this end, we employ the multi-scale shallow-water-equations graph neural network (mSWE-GNN) that enjoys transferability to different boundary conditions and locations and whose graph-based architecture allows to represent structures such as canals, underpasses, and elevated elements as inputs. To address the lack of reference ground-truth data, we further introduce the average relative mass error (ARME), a mass-conservation-based criterion that helps identify physically plausible simulations. We applied the model on dike ring 41 in the Netherlands, generating probabilistic flood maps that account for uncertainties in breach location and breach outflow hydrographs. The model was trained on 30 simulations, generated with Delft3D, and evaluated against unseen benchmark simulations from the Dutch national flood catalogue, achieving a critical success index (CSI) of 73.6 % while running 10 000 times faster than the numerical simulator. The proposed ARME is negatively correlated with the CSI, with a Spearman correlation coefficient of -0.7, making it a useful indicator of simulation plausibility when evaluating unseen case studies. We obtained probabilistic flood maps by running 10 000 different flooding scenarios on a computational mesh of 180 000 cells in approximately 10 h, with about half of the simulations classified as plausible based on the mass-conservation check. This framework offers a practical tool for rapid probabilistic flood hazard assessment and a way to prioritize detailed physical simulations, supporting more efficient and robust flood risk management.

Hydro meteorological hazards, especially floods and cyclones, present considerable risks to public health, leading to fatalities, physical damage to healthcare facilities (HCFs), and major disruptions in health care delivery. This study undertook a systematic review of academic literature to explore both the direct and indirect effects of flooding on HCFs, along with the risk management approaches employed to mitigate these impacts. We conducted searches across four major databases (MEDLINE, Embase, Web of Science, and Scopus) for English-language publications, using keywords related to floods, cyclones, healthcare facility types, and disaster risk reduction. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We screened 7500 records, ultimately selecting 74 studies that met the inclusion criteria. Roughly 76% of the selected studies focused on cyclone-induced flooding and were mostly based in the United States. Hospitals emerged as the most frequently studied HCF type (n = 54), followed by long-term care facilities (n = 11). A prevalent issue reported was basement flooding, which affected critical systems such as equipment storage, medical supplies, and backup power. Disruptions to electricity and water services also posed severe operational challenges. While more than two-thirds of the studies referenced patient evacuation procedures, relatively few reported the use of structural mitigation strategies. Over one-third mentioned the presence of emergency preparedness plans. However, the review uncovered a lack of consistency in the preparedness levels among HCFs. To improve resilience, the main policy recommendation is to develop standardized guidelines and strengthen oversight of preparedness planning.

This study presents a comprehensive numerical investigation into the use of displacement piles as a reinforcement measure for river dikes founded on soft soil, with a particular focus on geotechnical performance, macro stability, and impacts on nearby buildings. A finite element model is developed using parameters derived from a representative Dutch dike case (Bergambacht), incorporating the Hardening Soil, Soft Soil Creep and NGI-ADP-SHANSEP models to capture soil behaviour. Pile installation is simulated through the application of lateral volumetric strain, with varying pile diameters, spacings, and locations within the dike profile. The equivalent diameters used in the analysis range from 10 to 40 cm, corresponding to pile walls with diameters between 25.5 and 100 cm when the spacing equals the diameter. The pile wall location varies from the dike toe up to 21 m away, which is at the outer crest, with a varied length reaching -12 m NAP. A two-storey building on deep pile foundations is included to assess the effect of installation-induced displacements, with its location ranging from 5 to 20 m from the dike toe. Results show that positioning the pile wall within the inner slope offers the best balance between increased factor of safety, reduced required pile length, and acceptable levels of deformation. However, the installation process can generate significant horizontal displacements, particularly near the dike toe, which may compromise adjacent structures. The study finds that displacement piles are unsuitable within 10–15 m of existing buildings unless smaller pile diameters or alternative installation methods are used. Soil stiffness and installation-induced stresses also play a key role, highlighting the importance of site-specific assessments and careful design calibration using field data.

Backward erosion piping is a failure mechanism of dikes. Numerical modelling is crucial for design and assessment against BEP. Over 30 models have been developed, each with a different purpose and approach. This paper provides a comprehensive overview of the available numerical BEP models, highlighting their limitations, capabilities, and associated challenges. It discusses the different assumptions and their implications on the representation of BEP. Key challenges in the numerical modelling of BEP are (1) the flow (regime) inside the pipe, which is often simplified, even though the impact of this is relatively unknown. (2) The type of erosion (primary or secondary) differs per model, and even within a given type of erosion, approaches vary. (3) Overcoming the difference in scale is a trade-off between the computational effort and simplification. (4) Furthermore, validation of the physics in BEP modelling is difficult due to a of lack micro-scale experimental data.

Hydrometeorological hazards, particularly floods and cyclones, pose significant threats to human health, including fatalities, damage to healthcare facilities (HCFs), and disruptions to health services. This study systematically reviewed scientific articles to identify the direct and indirect impacts of floods on HCFs and the risk management strategies implemented to address these challenges. To that end, we searched four databases (MEDLINE, Embase, Web of Science and Scopus) for articles written in English. Our search query included terms related to flood and cyclone hazards, HCF types and disaster risk management strategies. We followed the PRISMA guidelines to conduct the study. The search resulted in 7500 records, which were finally filtered down to 74 studies after removing duplicates, screening records and full article eligibility checks. Approximately 76 % of the included studies addressed cyclone-related flood impacts and were conducted in the United States. Hospitals were the most studied HCFs (n = 54) followed by long-term care facilities (n = 11). The main impact of floods on hospitals was due to flooded basements as they house important services including equipment, supplies and backup generators. Interruptions of electricity and water supplies were reported to cause serious challenges. Regarding flood risk management, patient evacuation was mentioned by more than 66 % of the studies while few studies reported the implementation of structural measures. More than a third of the studies reported the availability of preparedness plans. The review revealed inconsistencies in the flood preparedness of HCFs. The main policy recommendations are the availability of guidelines to standardize preparedness plans and oversight.

Rock groins in the Elbe Estuary are constructed to maintain proper water levels for navigation and for embankment erosion protection. At certain localities, significant damages to rock groins have been observed due to the primary ship-generated waves. Primary waves are generated along the ship's hull and then propagate toward the river banks and groin fields, appearing in the interaction with the structures as a turbulent overflow phenomenon. Eventually, this overflowing may cause damages mainly to the crest and leeward side of the groins. Since this overflowing is the most pronounced with large primary waves at certain water levels, the estimation of the probabilities of extreme primary waves is a key element for a safe and reliable design of groins. For this goal, nonparametric Bayesian networks (NPBNs) are used here to infer the probability distribution function of the extreme primary wave heights at the tip of a groin in the Elbe Estuary. Results demonstrate the suitability of the NPBN in their prediction. The model framework allows the designer to predict the probabilities of primary ship-generated waves at groins when the information of ship dimensions, nautical parameters, and waterway geometry is available. These probabilities can later be used for design purposes for current and future conditions.

Land subsidence is a significant issue in many coastal megacities, including Shanghai, where it poses risks to infrastructure and economic stability. Although numerous studies have used SAR datasets to monitor land subsidence in Shanghai, multi-decadal displacement measurements obtained from multi-sensor SAR data remain unavailable. Moreover, the contributions and variations of driving factors behind the evolution of land subsidence remain poorly understood. This study employs multi-sensor SAR fusion method and a Random Forest model, along with Shapley Additive exPlanations (SHAP), to examine subsidence evolution and assess the influence of key drivers over the past 30 years. The results show that severe subsidence has spread from central urban areas to surrounding suburban regions, particularly in the eastern coastal and southern industrial zones in Shanghai. SHAP analysis identified that evapotranspiration, sediment thickness, and groundwater extraction were the dominant factors in the early stage of subsidence, while recent groundwater management and recharge practices have significantly mitigated the subsidence rate. These findings demonstrate the shifting importance of different subsidence factors over time and provide valuable insights for long-term prevention and control measures.

The structural response of masonry walls during flood events is a critical concern for the flood resilience of (Dutch) buildings, as they typically constitute part of the load-bearing structure. This study investigates the out-of-plane behaviour of a full-scale single-wythe fired-clay-brick masonry wall under out-of-plane hydrostatic pressure and debris impact loads. Experimental tests were conducted on a 2.7 × 2.7 m masonry wall subjected to a vertical pre-compression and simultaneously varying water levels and debris impacts at the Flood Proof Holland facility in Delft, the Netherlands. Results demonstrated that the wall remained within the linear-elastic regime up to a water depth of approximately 90 cm when the interior side was dry. Beyond this threshold, crack initiation and stress redistribution occurred, leading to significant deformation. On the basis of calibrated models, failure was predicted at approximately 150 cm water depth for a fully restrained wall. Debris impact tests showed that soft debris, represented by a floating log, caused negligible additional damage, whereas repeated impacts with a steel cube (hard debris) resulted in progressive cracking and local failure, particularly at higher water levels. Numerical models, including analytical, linear-elastic finite element method (FEM), and non-linear FE approaches, were calibrated using the experimental data. While one-way bending models predicted conservative failure thresholds, two-way, non-linear models accurately captured the wall’s deformation and cracking behaviour, demonstrating the importance of lateral boundary constraints in determining wall capacity and stability. The findings emphasise that traditional masonry walls in Dutch buildings can safely withstand water depths up to 90 cm without significant damage. However, higher water levels or hard debris impacts pose substantial risks, highlighting the need for improved flood resilience strategies. Future work should focus on cavity wall systems, leakage effects, and the behaviour of walls with openings.

Introduction: The 2021 European floods in Germany, Belgium, and the Netherlands significantly impacted healthcare. With climate change increasing flood risks, healthcare preparedness is essential. Floods affect healthcare directly and indirectly by disrupting patient access, damaging infrastructure and impeding care continuity. Our interdisciplinary research in the Netherlands systematically assesses flood impacts on healthcare, optimises disaster preparedness, patient logistics, and continuity and explores crisis governance, incorporating lessons from coronavirus disease-2019 (COVID-19). Methods: Our multi-sited, interdisciplinary project titled “Pandemic lessons for flood disaster preparedness” includes literature reviews on: (i) the (in) direct impacts of floods on healthcare, (ii) disaster decision-making strategies and (iii) patient logistics during crises. Empirically, ethnographic methods (interviews, focus groups, document analyses, and observations) will: (a) assess hospital flood preparedness, (b) explore decision-making and crisis management strategies and (c) analyse the dynamics of health system governance during floods. Data from these sources and flood scenarios will inform models on healthcare impacts and decision-making, culminating in a simulation game for research and training. Discussion: This study offers a comprehensive, interdisciplinary approach to understanding and improving healthcare system preparedness for floods. By integrating diverse fields such as healthcare governance, disaster risk management, logistics and hydraulic engineering, we provide a unique lens on resilience. A key strength is the incorporation of lessons from the COVID-19 pandemic, allowing us to draw parallels between pandemic response and flood preparedness. In addition, our simulation game serves as a robust tool for translating knowledge into practice. However, the study’s reliance on collaboration with busy healthcare and disaster response professionals may limit engagement. Moreover, the absence of direct public and patient involvement in the research design, though partially mitigated by engaging representative organizations, presents a potential limitation. Lastly, the challenge of obtaining real-time data from flood events could introduce recall bias, but triangulation of various data sources aims to address this issue. Despite these challenges, the study’s integration of long-term data from recent floods and focus on healthcare-specific crisis governance provides valuable insights for improving disaster preparedness.

Dam-break waves are highly unsteady long-wave phenomena, characterized by a breaking front with a strong recirculating air–water mixture. While the air–water flow properties of steady flows have often been investigated, the understanding of dynamic processes in unsteady multiphase flows remains limited. In this experimental study, a new approach was implemented to analyze the air–water flow properties of highly unsteady flows in the form of dam-break waves using ensemble-averaging techniques to account for short-duration measurements. The new dataset includes four different flow conditions, providing novel insights into the relation between various hydrodynamic characteristics and key air–water flow properties, including bubble characteristics and void fraction. The void fraction profiles indicated the presence of a turbulent shear layer along with a recirculation zone close to the free surface, showing analogies with similar steady and unsteady flow phenomena. Variations in the Froude number were shown to strongly affect the number and size of air bubbles, particularly in the shear layer. Higher depth-averaged air concentrations were found with increasing Froude numbers, reaching up to 40% for Fr = 5.14. Overall, the results confirm the importance of considering the presence of air in dam-break waves and demonstrate the suitability of this new methodology for investigating air–water flow properties in highly turbulent flows. They offer a deeper understanding of the multiphase nature of dam-break waves, which is relevant for a wide range of processes in coastal and hydraulic engineering.

Mangrove forests reduce wave attack along tropical and sub-tropical coastlines, decreasing the wave loads acting on coastal protection structures. Mangrove belts seaward of embankments can therefore lower their required height and decrease their slope protection thickness. Wave reduction by mangroves depends on tree frontal surface area and stability against storms, but both aspects are often oversimplified or neglected in coastal protection designs. Here we present a framework to evaluate how mangrove belts influence embankment designs, including mangrove growth over time and failure by overturning and trunk breakage. This methodology is applied to Sonneratia apetala mangroves seaward of embankments in Bangladesh, considering forest widths between 10 and 1000 m (cross-shore). For water depths of 5 m, wave reduction by mangrove forests narrower than 1 km mostly affects the slope protection and the bank erodibility, whereas the required embankment height is less influenced by mangroves. Sonneratia apetala trees experience a relative maximum in wave attenuation capacity at 10 years age, due to their large submerged canopy area. Once trees are more than 20 years old, their canopy is emergent, and most wave attenuation is caused by trunk and roots. Canopy emergence exposes mangroves to wind loads, which are much larger than wave loads, and can cause tree failure during cyclones. These results stress the importance of including tree surface area and stability models when predicting coastal protection by mangroves.

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.

Floods are consistently ranked as the most financially devastating natural disasters worldwide. Recent flood events in the Netherlands, Caribbean, and US have drawn attention to flood risks resulting from pluvial and fluvial sources. Despite shared experiences with flooding, these regions employ distinct approaches and flood management strategies due to differences in governance and scale—offering a three-site case study comparison. A key, yet often lacking, factor for flood risk and damage assessments at the parcel level is building elevation compared to flood elevation. First-floor elevations (FFEs) are a critical element in the vulnerability of a building flooding. US-based flood insurance policies require FFEs; however, data availability limitations exist. Drone-based FFEs were measured in all locations to assess the flood vulnerabilities of structures. Flood vulnerability profiles revealed 64% of buildings were vulnerable to a form of inundation, with 40% belonging to “moderate” or “major” inundation, and inundation elevation means (IEMs) of −0.55 m, 0.19 m, and 0.71 m within the US, Netherlands, and Puerto Rico sites, respectively. Spatial statistics revealed FFEs were more responsible for flood vulnerabilities in the US site while topography was more responsible in the Netherlands and Puerto Rico sites. Additional findings in the Puerto Rico site reveal FFEs and next highest floor elevations (NHFEs) vulnerable to future sea level rise (SLR) flood elevations. The findings within the Netherlands provide support for developing novel multi-layered flood risk reduction strategies that include building elevation. We discuss future work recommendations and how the different sites could benefit significantly from strengthening FFE requirements.

Sea level rise necessitates the upgrade of coastal flood protection including storm surge barriers. These large movable hydraulic structures are open in normal conditions, but close during a storm surge to prevent coastal floods in bays and estuaries. Barrier improvements lower their susceptibility to operational, structural, or height-related failures. However, there is no method to determine the relative importance of these three barrier failure types. Here, we present a probabilistic method to systematically organize barrier failures and storm conditions to establish exceedance frequencies of extreme water levels behind the barrier. The method is illustrated by an assessment of extreme water level frequencies at Rotterdam (The Netherlands), which is protected by the Maeslant barrier. Four combinations of barrier states and storm conditions were analyzed and prioritized in the following order: (1) an operational failure with 1/100 year storm conditions, (2) a successful closure with an extreme (~1/1000 year) river discharge accumulating behind the barrier, (3) structural failure, and (4) insufficient height both with extreme storm conditions (10^–6 year). The case study confirmed the method's ability to systematically explore promising barrier improvements to adapt to sea level rise, in this case, lowering the susceptibility toward operational failures.

Internal erosion is a significant cause of failure in dams, levees and other hydraulic structures. This article studies the time-dependent reliability of such structures under Backward Erosion Piping (BEP), a form of internal erosion in the foundation. First, a physics-based time-dependent piping failure model is presented. Second, a time-variant reliability analysis method is presented which allows to quantify how the reliability evolves over the years due to cumulative pipe growth over multiple flood events. Finally, these models are used to study the importance of time-dependence for reliability estimates of flood defenses in The Netherlands. The findings show that, particularly in coastal areas, incorporating time-dependence significantly reduces the computed failure probability. Reductions vary widely, ranging from a factor of 5 to more than (Formula presented.) depending on flood duration and levee properties. Therefore, reliability estimates for levees can be improved by incorporating time-dependent pipe development in the BEP failure model, and thereby contribute to avoiding unnecessary reinforcements.