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Maarten van Ormondt

Publications and source records attributed to Maarten van Ormondt.

12 recordsLinked to original sources

Projections of multiple climate-related coastal hazards for the US Southeast Atlantic

Faced with accelerating sea level rise and changing ocean storm conditions, coastal communities require comprehensive assessments of climate-driven hazard impacts to inform adaptation measures. Previous studies have focused on flooding but rarely on other climate-related coastal hazards, such as subsidence, beach erosion and groundwater. Here, we project societal exposure to multiple hazards along the Southeast Atlantic coast of the United States. Assuming 1 m of sea level rise, more than 70% of the coastal residents and US \ $ 1 trillion in property are in areas projected to experience shallow and emerging groundwater, 15 times higher than daily flooding. Storms increase flooding exposure by an order of magnitude over daily flooding, which could impact up to ~50% of all coastal residents and US \ $ 770 billion in property value. The loss of up to ~80% of present-day beaches and high subsidence rates that currently affect over 1 million residents will exacerbate flooding and groundwater hazard risks.

Florida, Georgia, North Carolina, South Carolina, ↗

Tropical or extratropical cyclones: What drives the compound flood hazard, impact, and risk for the United States Southeast Atlantic coast?

Subtropical coastlines are impacted by both tropical and extratropical cyclones. While both may lead to substantial damage to coastal communities, it is difficult to determine the contribution of tropical cyclones to coastal flooding relative to that of extratropical cyclones. We conduct a large-scale flood hazard and impact assessment across the subtropical Southeast Atlantic Coast of the United States, from Virginia to Florida, including different flood hazards. The physics-based hydrodynamic modeling skillfully reproduces coastal water levels based on a comprehensive validation of tides, almost two hundred historical storms, and an in-depth hindcast of Hurricane Florence. We show that yearly flood impacts are two times as likely to be driven by extratropical than tropical cyclones. On the other hand, tropical cyclones are 30 times more likely to affect people during rarer 100-year events than extratropical cyclones and contribute to more than half of the regional flood risk. With increasing sea levels, more areas will be flooded, regardless of whether flooding is driven by tropical or extratropical cyclones. Most of the absolute flood risk is contained in the greater Miami metropolitan area. However, several less populous counties have the highest relative risks. The results of this study provide critical information for understanding the source and frequency of compound flooding across the Southeast Atlantic Coast of the United States.

Natural Hazards↗

Rapid modeling of compound flooding across broad coastal regions and the necessity to include rainfall driven processes: A case study of Hurricane Florence (2018)

In this work, we show that large-scale compound flood models developed for North and South Carolina, USA, can skillfully simulate multiple drivers of coastal flooding as confirmed by measurements collected during Hurricane Florence (2018). Besides the accuracy of representing observed water levels, the importance of individual processes was investigated. We demonstrate that across the area of interest, it is necessary to include marine, pluvial, and fluvial forcing and the processes of wind stress and infiltration to correctly model water levels along the coast and further inland. This work highlights the need to include these processes in modeling coastal compound flooding. By using high-resolution topo-bathymetry that is incorporated via subgrid derived tables in the Super-Fast INundation of CoastS (SFINCS) model, we improved the skill of the model at efficiently simulating flooding across large-scale domains with locally relevant results.

North Carolina, South Carolina↗

Dynamic flood modeling essential to assess the coastal impacts of climate change

Coastal inundation due to sea level rise (SLR) is projected to displace hundreds of millions of people worldwide over the next century, creating significant economic, humanitarian, and national-security challenges. However, the majority of previous efforts to characterize potential coastal impacts of climate change have focused primarily on long-term SLR with a static tide level, and have not comprehensively accounted for dynamic physical drivers such as tidal non-linearity, storms, short-term climate variability, erosion response and consequent flooding responses. Here we present a dynamic modeling approach that estimates climate-driven changes in flood-hazard exposure by integrating the effects of SLR, tides, waves, storms, and coastal change (i.e. beach erosion and cliff retreat). We show that for California, USA, the world’s 5 th largest economy, over $150 billion of property equating to more than 6% of the state’s GDP and 600,000 people could be impacted by dynamic flooding by 2100; a three-fold increase in exposed population than if only SLR and a static coastline are considered. The potential for underestimating societal exposure to coastal flooding is greater for smaller SLR scenarios, up to a seven-fold increase in exposed population and economic interests when considering storm conditions in addition to SLR. These results highlight the importance of including climate-change driven dynamic coastal processes and impacts in both short-term hazard mitigation and long-term adaptation planning.

Scientific Reports↗

Morphodynamic modelling of the wilderness breach, Fire Island, New York. Part I: Model set-up and validation

On October 29, 2012, storm surge and large waves produced by Hurricane 13 Sandy resulted in the formation of a breach in eastern Fire Island, NY. The goals of this study 14 are to gain a better understanding of the physical processes that govern breach behavior and 15 to assess whether process-based models can be used to forecast the evolution of future 16 breaches. The Wilderness Breach grew rapidly in size during the first winter following 17 formation. Growth of the breach was accompanied by the formation of a complex of flood 18 shoals inside Great South Bay, a primary channel that flowed through the eastern part of the 19 flood shoals, and an ebb shoal on the ocean side of the breach. From the summer of 2013 20 through late 2015, the breach continued to change and evolve, albeit at a much slower pace 21 than in the first year after formation. A hybrid combination of Delft3D and XBeach models is 22 used to hindcast the morphodynamic evolution of the Wilderness Breach over the first three 23 years after formation. The formation of the breach during Hurricane Sandy is not part of the 24 simulations. Model simulations are initiated with a post-storm topography in which the 25 breach is already present. The models are capable of hindcasting the main morphodynamic 26 changes of the Wilderness Breach. The spatial patterns, as well as the bulk statistics, such as 27 2 breach geometry and sediment volume changes, are reasonably 28 well reproduced by the model. 29 The model sheds light on previously unknown processes of breach evolution, especially 30 regarding sediment transport and flow regimes within the breach complex.

New York↗

Morphodynamic modeling of the response of two barrier islands to Atlantic hurricane forcing

The accurate prediction of a barrier island response to storms is challenging because of the complex interaction between hydro- and morphodynamic processes that changes at different stages during an event. Assessment of the predictive skill is further complicated because of uncertainty in the hydraulic forcing, initial conditions, and the parameterization of processes. To evaluate these uncertainties, we investigated the morphological change that occurred during two Atlantic hurricane events on two barrier islands at Matanzas (Florida) and Fire Island (New York) with differing topographies and forcing conditions.

Florida, New York↗

Modeling fine-scale coral larval dispersal and interisland connectivity to help designate mutually-supporting coral reef marine protected areas: Insights from Maui Nui, Hawaii

Connectivity among individual marine protected areas (MPAs) is one of the most important considerations in the design of integrated MPA networks. To provide such information for managers in Hawaii, USA, a numerical circulation model was developed to determine the role of ocean currents in transporting coral larvae from natal reefs throughout the high volcanic islands of the Maui Nui island complex in the southeastern Hawaiian Archipelago. Spatially- and temporally-varying wind, wave, and circulation model outputs were used to drive a km-scale, 3-dimensional, physics-based circulation model for Maui Nui. The model was calibrated and validated using satellite-tracked ocean surface current drifters deployed during coral-spawning conditions, then used to simulate the movement of the larvae of the dominant reef-building coral, Porites compressa , from 17 reefs during eight spawning events in 2010–2013. These simulations make it possible to investigate not only the general dispersal patterns from individual coral reefs, but also how anomalous conditions during individual spawning events can result in large deviations from those general patterns. These data also help identify those reefs that are dominated by self-seeding and those where self-seeding is limited to determine their relative susceptibility to stressors and potential roadblocks to recovery. Overall, the numerical model results indicate that many of the coral reefs in Maui Nui seed reefs on adjacent islands, demonstrating the interconnected nature of the coral reefs in Maui Nui and providing a key component of the scientific underpinning essential for the design of a mutually supportive network of MPAs to enhance conservation of coral reefs.

Hawaii↗

The effects of geomorphic changes during Hurricane Sandy on water levels in Great South Bay

Hurricane Sandy caused record coastal flooding along the south shore of Long Island, NY, and led to significant geomorphic changes. These included severe dune erosion along the length of Fire Island and the formation of the Wilderness Breach. This study attempts to use numerical models to quantify how these changes affected water levels inside Great South Bay during and after Hurricane Sandy. The results suggest that overwash along Fire Island may have locally increased peak surge levels in the bay by 20 cm during the storm. There is however large uncertainty surrounding the overwash fluxes. The model results suggest that the development of the Wilderness Breach had locally led to an increase in peak water levels of approximately 7 percent at Lindenhurst by mid-2014, and an increase in tidal amplitudes here of 15 percent. The models predict that the largest changes have occurred in the central part of Great South Bay.

New York↗

Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts

The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.

Natural Hazards↗

The dynamics of fine-grain sediment dredged from Santa Cruz Harbor

In the fall and early winter of 2009, a demonstration project was done at Santa Cruz Harbor, California, to determine if 450 m 3 /day of predominantly (71 percent) mud-sized sediment could be dredged from the inner portion of the harbor and discharged to the coastal ocean without significant impacts to the beach and inner shelf. During the project, more than 7600 m 3 of sediment (~5400 m 3 of fine-grain material) was dredged during 17 days and discharged approximately 60 m offshore of the harbor at a depth of 2 m on the inner shelf. The U.S. Geological Survey’s Pacific Coastal and Marine Science Center was funded by the U.S. Army Corps of Engineers and the Santa Cruz Port District to do an integrated mapping and process study to investigate the fate of the mud-sized sediment dredged from the inner portion of Santa Cruz Harbor and to determine if any of the fine-grain material settled out on the shoreline and/or inner shelf during the fall and early winter of 2009. This was done by collecting high resolution oceanographic and sediment geochemical measurements along the shoreline and on the continental shelf of northern Monterey Bay to monitor the fine-grain sediment dredged from Santa Cruz Harbor and discharged onto the inner shelf. These in place measurements, in conjunction with beach, water column, and seabed surveys, were used as boundary and calibration information for a three-dimensional numerical circulation and sediment dynamics model to better understand the fate of the fine-grain sediment dredged from Santa Cruz Harbor and the potential consequences of disposing this type of material on the beach and on the northern Monterey Bay continental shelf.

California↗

Nearshore disposal of fine-grained sediment in a high-energy environment: Santa Cruz Harbor case study

Current regulations in California prohibit the disposal of more than 20% fine-grained sediment in the coastal zone; this threshold is currently being investigated to determine if this environmental regulation can be improved upon. A field monitoring and numerical modeling experiment took place late 2 009 to determine the fate of fine-grained dredge disposal material from Santa Cruz Harbor, California, U.S.A. A multi-nested, hydrodynamic-sediment transport modeling approach was used to simulate the direction and dispersal of the dredge plume. Result s show that the direction and dispersal of the plume was influenced by the wave climate, a large proportion of which moved in a easterly direction during wave events. Therefore it is vitally important to accurately simulate the tides, waves, currents, temperature and salinity when modeling the dispersal of the fine-grained dredge plume.

California↗

The framework of a coastal hazards model: A tool for predicting the impact of severe storms

The U.S. Geological Survey (USGS) Multi-Hazards Demonstration Project in Southern California (Jones and others, 2007) is a five-year project (FY2007-FY2011) integrating multiple USGS research activities with the needs of external partners, such as emergency managers and land-use planners, to produce products and information that can be used to create more disaster-resilient communities. The hazards being evaluated include earthquakes, landslides, floods, tsunamis, wildfires, and coastal hazards. For the Coastal Hazards Task of the Multi-Hazards Demonstration Project in Southern California, the USGS is leading the development of a modeling system for forecasting the impact of winter storms threatening the entire Southern California shoreline from Pt. Conception to the Mexican border. The modeling system, run in real-time or with prescribed scenarios, will incorporate atmospheric information (that is, wind and pressure fields) with a suite of state-of-the-art physical process models (that is, tide, surge, and wave) to enable detailed prediction of currents, wave height, wave runup, and total water levels. Additional research-grade predictions of coastal flooding, inundation, erosion, and cliff failure will also be performed. Initial model testing, performance evaluation, and product development will be focused on a severe winter-storm scenario developed in collaboration with the Winter Storm Working Group of the USGS Multi-Hazards Demonstration Project in Southern California. Additional offline model runs and products will include coastal-hazard hindcasts of selected historical winter storms, as well as additional severe winter-storm simulations based on statistical analyses of historical wave and water-level data. The coastal-hazards model design will also be appropriate for simulating the impact of storms under various sea level rise and climate-change scenarios. The operational capabilities of this modeling system are designed to provide emergency planners with the critical information they need to respond quickly and efficiently and to increase public safety and mitigate damage associated with powerful coastal storms. For instance, high resolution local models will predict detailed wave heights, breaking patterns, and current strengths for use in warning systems for harbor-mouth navigation and densely populated coastal regions where beach safety is threatened. The offline applications are intended to equip coastal managers with the information needed to manage and allocate their resources effectively to protect sections of coast that may be most vulnerable to future severe storms.

California↗