A5061954726- Flood Risk Assessment and Management
- Tropical and Extratropical Cyclones Research
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Disaster Management and Resilience
- Climate variability and models
- Remote Sensing and LiDAR Applications
- Seismology and Earthquake Studies
- Coastal and Marine Dynamics
- Infrastructure Resilience and Vulnerability Analysis
- Geophysics and Gravity Measurements
- Water-Energy-Food Nexus Studies
- Oceanographic and Atmospheric Processes
- Atmospheric and Environmental Gas Dynamics
- Automated Road and Building Extraction
- Meteorological Phenomena and Simulations
- Methane Hydrates and Related Phenomena
- Dam Engineering and Safety
- Water Systems and Optimization
- Landslides and related hazards
- Transboundary Water Resource Management
- Insurance and Financial Risk Management
- Hydrological Forecasting Using AI
- Fish Ecology and Management Studies
- Hydrology and Sediment Transport Processes
Deltares
2022-2024
Vrije Universiteit Amsterdam
2018-2024
Delft University of Technology
2018
This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography data, methods to determine channel depth, more rigorous frequency analysis, output downscaling property tract level, inclusion the impact local interventions in flooding system. For first time, we consider pluvial, fluvial, coastal hazards within same framework provide projections for both current (rather than historic average)...
Abstract In recent decades, a striking number of countries have suffered from consecutive disasters: events whose impacts overlap both spatially and temporally, while recovery is still under way. The risk disasters will increase due to growing exposure, the interconnectedness human society, increased frequency intensity nontectonic hazard. This paper provides an overview different types disasters, their causes, impacts. can be distinctly occurring in isolation (both temporally) other noting...
Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes changing is therefore needed, but been hampered by a lack empirical data4,5. On basis global dataset 45 pairs events that occurred within same area, we show risk generally reduces faces difficulties in reducing unprecedented magnitude not previously experienced. If second event was much more hazardous than first, its impact almost...
When river and coastal floods coincide, their impacts are often worse than when they occur in isolation; such examples of 'compound events'. To better understand the these compound events, we require an improved understanding dependence between flooding on a global scale. Therefore, this letter, we: provide first assessment mapping observed high sea-levels discharge for deltas estuaries around globe; demonstrate how may influence joint probability exceeding both design sea-level. The...
Abstract. The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result compound flooding. Compound flood events, like Cyclone Idai Hurricane Harvey, have revealed the devastating consequences of co-occurrence river floods. A number studies recently investigated likelihood flooding at continental scale based on simulated variables drivers, such as storm surge, precipitation, discharges. At global scale, this has only been...
Abstract Compound weather and climate events are combinations of drivers and/or hazards that contribute to societal or environmental risk. Studying compound often requires a multidisciplinary approach combining domain knowledge the underlying processes with, for example, statistical methods model outputs. Recently, aid development research on events, four event types were introduced, namely (a) preconditioned , (b) multivariate (c) temporally compounding (d) spatially events. However,...
Abstract Current global riverine flood risk studies assume a constant mean sea level boundary. In reality high levels can propagate up river, impede river discharge, thus leading to elevated water levels. Riverine in deltas may therefore be underestimated. This paper presents the first scale assessment of joint influence and coastal drivers flooding deltas. We show that if storm surge is ignored, depths are significantly underestimated for 9.3% expected annual population exposed flooding....
Abstract. Coastal river deltas are susceptible to flooding from pluvial, fluvial, and coastal flood drivers. Compound floods, which result the co-occurrence of two or more these drivers, typically exacerbate impacts compared floods a single driver. While several global models have been developed, do not account for compound flooding. Local-scale provide state-of-the-art analyses but hard scale other regions as based on local datasets. Hence, there is need globally applicable hazard modeling....
Abstract. Whilst the last decades have seen a clear shift in emphasis from managing natural hazards to risk, majority of natural-hazard risk research still focuses on single hazards. Internationally, there are calls for more attention multi-hazards and multi-risks. Within European Union (EU), concepts multi-hazard multi-risk assessment management taken centre stage recent years. In this perspective paper, we outline several key developments multi-(hazard-)risk decade, with particular focus...
Abstract Storm surges that occur along low-lying, densely populated coastlines can leave devastating societal, economical, and ecological impacts. To protect coastal communities from flooding, return periods of storm tides, defined as the combination surge tide, must be accurately evaluated. Here we present tide using a novel integration two modelling techniques. For induced by extratropical cyclones, use 38-year time series based on ERA5 climate reanalysis. tropical synthetic cyclones STORM...
Traditional flood hazard analyses often rely on univariate probability distributions; however, in many coastal catchments, flooding is the result of complex hydrodynamic interactions between multiple drivers. For example, synoptic meteorological conditions can produce considerable rainfall-runoff, while also generating wind-driven elevated sea-levels. When these drivers interact space and time, they exacerbate impacts, a phenomenon known as compound flooding. In this paper, we build Bayesian...
Abstract To improve coastal adaptation and management, it is critical to better understand predict the characteristics of sea levels. Here, we explore capabilities artificial intelligence, from four deep learning methods surge component sea-level variability based on local atmospheric conditions. We use an Artificial Neural Networks, Convolutional Network, Long Short-Term Memory layer (LSTM) a combination latter two (ConvLSTM), construct ensembles Network (NN) models at 736 tide stations...
Many impact assessment studies rely on hydrological and hydrodynamic (hydro) models.These models typically require a large set of parameters derived from different datasets hence manual setup can be time consuming hard to reproduce.HydroMT (Hydro Model Tools) is an open-source Python package that aims make the process building model instances analyzing results automated reproducible.The provides common interface data instances, workflows transform into based (hydrological) GIS statistical...
Abstract State‐of‐the‐art flood hazard maps in coastal cities are often obtained from simulating or pluvial events separately. This method does not account for the seasonality of drivers and their mutual dependence. In this article, we include impact these two factors a computationally efficient probabilistic framework risk calculation, using Ho Chi Minh City (HCMC) as case study. HCMC can be flooded subannually by high tide, rainfall, storm surge combination thereof during monsoon tropical...
Abstract. As the adverse impacts of hydrological extremes increase in many regions world, a better understanding drivers changes risk and is essential for effective flood drought management climate adaptation. However, there currently lack comprehensive, empirical data about processes, interactions, feedbacks complex human–water systems leading to impacts. Here we present benchmark dataset containing socio-hydrological paired events, i.e. two floods or droughts that occurred same area. The...
Abstract. In low-lying coastal areas floods occur from (combinations of) fluvial, pluvial, and drivers. If these flood drivers are statistically dependent, their joint probability might be misrepresented if dependence is not accounted for. However, few studies have examined risk reduction measures while accounting for so-called compound flooding. We present a globally applicable framework assessments using combined hydrodynamic, impact, statistical modeling apply it to case study in the...
Abstract. Coastal river deltas are susceptible to flooding from pluvial, fluvial, and coastal flood drivers. Compound floods, which result the co-occurrence of two or more these drivers, typically exacerbate impacts compared floods a single driver. While several global models have been developed, do not account for compound flooding. Local scale provide state-of-the-art analyses but hard up as based on local datasets. Hence, there is need globally-applicable hazard modeling. We develop,...
It is widely recognized that climate change altering the likelihood and intensity of extreme weather events globally, including hydrological extremes such as floods. Compound flooding driven by fluvial, pluvial coastal occurring simultaneously, resulting in a potentially larger impact when co-occurring than sum univariate drivers happening separately. Identifying communicating effect on compound remains challenging. A method to quantify these through attribution assessments.  This...
Storm surges are causing widespread devastation, directly impacting coastal communities through injuries and fatalities, infrastructure damage, the displacement of residents. Projections future storm vital for assessing these risks, especially under climate change that causes both intensity frequency extreme events to increase. The temporal spatial resolution global model simulations do not resolve critical characteristics events: surge peaks such as daily maximum occur on scale hours, while...
Floods are an ever-present risk to society and economy in Europe, influenced by both climatic socioeconomic drivers. An accurate timely attribution of impacts is important for management, “loss damage” debate public communication context climate change. Here, we discuss the opportunities challenges operationalizing European flood framework Horizon Europe project “Compound extremes change: towards operational service” (COMPASS). The prospective service...
Abstract. Flooding is the natural hazard most likely to affect individuals and can be driven by rainfall, river discharge, storm surge, tides, waves. Compound floods result from their co-occurrence generate a larger flood when compared synthetic generated respective drivers occurring in isolation one another. Current state-of-the-art stochastic compound risk assessments are based on statistical, hydrodynamic, impact simulations. However, nature of some key variables flooding process often...
Flood risk can be reduced at various stages of the disaster management cycle. Traditionally, permanent infrastructure is used for flood prevention, while residual managed with emergency measures that are triggered by forecasts. Advances in forecasting hold promise a more prominent role to forecast-based measures. In this study, we present methodology compares flood-prevention On basis methodology, demonstrate how operational decision-makers select between acting against frequent low-impact,...
Compound floods due to intense rainfall and storm surges in coastal areas have shown an increasing trend some parts of the world, many studies suggested a strong link with climate change. Yet, such has not been fully explored quantitively assessed. In this paper, we demonstrate development application nonstationary framework determining different compound scenarios, where individual drivers their interactions altered under The applied one most flood-prone areas: Ho Chi Minh City Vietnam,...
Current coastal flood risk assessments fail to capture spatial dependence at large scales. In this paper, we develop the first global synthetic dataset of spatially-dependent extreme sea level events, by applying an existing conditional multivariate statistical model 40-year reanalysis levels. The resulting contains 10,000 years events with realistic under current climate conditions. benchmarking against data demonstrates a high agreement, coefficient determination (R2) 0.96 for mean event...
Abstract. Because of the computational costs computing storm surges with hydrodynamic models, projections changes in extreme are often based on small ensembles climate model simulations. This may be resolved by using data-driven storm-surge models instead, which computationally much cheaper to apply than models. However, potential performance at predicting is unclear because previous studies did not train their specifically predict extremes, underrepresented observations. Here, we...