Publications

2026

1. Assessment of synthetic tropical cyclones in the North Atlantic Basin

   David Romero, Christian M Appendini, Kerry Emanuel, and 6 more authors

   Atmospheric Research, Jan 2026

   Abs DOI

   Tropical cyclones (TCs) pose significant risks due to their associated hazards, including powerful winds, inland and coastal flooding, and wind waves. However, more reliable TC records are required to ensure a robust statistical analysis for risk assessment. To overcome this limitation, researchers have developed methods to generate synthetic tropical cyclones (STCs) that provide a larger sample size of occurrences at specific locations. This study compares STC databases from different sources such as Massachusetts Institute of Technology (MIT), Columbia HAZard model (CHAZ), Synthetic Tropical cyclOne geneRation Model (STORM), and Deltares with historical TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) on a basin-wide scale in the North Atlantic Basin. The aim is to assess the effectiveness of STCs in replicating crucial historical tropical cyclones parameters for risk analysis and to identify potential biases in the STC generation models. The comparison uses a hexagonal mesh to evaluate characteristics such as maximum winds, translation speed, and residence time. The study acknowledges the validation paradox arising from the limited IBTrACS data at specific locations that make it difficult to rigorously validate the accuracy of STCs in those areas and from systematic differences across the STC datasets. Despite the historical TCs database limitation, comparing STC with IBTrACS characteristics remains the only viable method for assessing biases in STC generation models. The evaluated STCs reveal spatial bias patterns, which may indicate deficiencies in the underlying hazard models. Identifying and describing these biases aim to guide the use of these events and highlight key aspects for further development in STC generation methods.

2025

1. A hybrid statistical–dynamical framework for compound coastal flooding analysis

   Zhenqiang Wang, Meredith Leung, Sudarshana Mukhopadhyay, and 7 more authors

   Environmental Research Letters, Jan 2025

   Abs DOI

   Compound coastal flooding due to astronomic, atmospheric, oceanographic, and hydrologic drivers poses severe threats to coastal communities. While physics-driven approaches are able to dynamically simulate temporally and spatially varying compound flooding generated by multiple drivers with correlations between some of them, computational burdens limit their capability to explore the full range of conditions that contribute to compound coastal hazards. Data-driven statistical approaches address some of these computational challenges; however, they are also unable to explore all possible forcing combinations due to short observational records, and projections are typically limited to a few locations. This study proposes a hybrid statistical–dynamical framework for compound coastal flooding analysis that integrates a stochastic generator of compound flooding drivers, a hydrodynamic model, and machine learning-based surrogate models. The framework was demonstrated in San Francisco Bay (SF) over the past 500 years with accuracy similar to the physics-driven approach but with much higher computational efficiency. The stochastic generator of compound flooding drivers is developed by coupling a sea surface temperature (SST) reconstruction model with a climate emulator, weather generator, and model of the hydrological and reservoir system. Using reconstructed SSTs as input, the generator of compound flooding drivers is employed to simulate time series of the forcing factors contributing to compound flooding (e.g. surge, waves, river discharge, etc) in SF Bay. A process-based hydrodynamic model is built to predict total water levels varying in time and space throughout SF Bay based on stochastically generated drivers. The machine learning-based surrogate models are then developed from a relatively small library (several hundred) of hydrodynamic model simulations to efficiently predict water levels for compound flooding analysis under the full range of stochastic drivers. This study contributes a hybrid statistical–dynamical framework to better understand the spatial distribution and temporal evolution of compound coastal-fluvial flooding, along with the relative contributions of drivers in complex nearshore, estuarine, and river environments for centennial timescales under past, present, and future climates.

2. Mitigating Flood Risks in Urban Estuaries: Tidal Dynamics, Shoreline Hardening, Nature-Based Solutions, and Floodgates in San Francisco Bay

   Kees Nederhoff, Rohin Saleh, Patrick L. Barnard, and 1 more author

   Journal of Waterway, Port, Coastal, and Ocean Engineering, Jan 2025

   Abs DOI

   Hydrodynamic models are valuable tools for understanding the primary factors influencing daily and peak water levels and for guiding discussions on potential adaptation strategies for managing flood risk in coastal areas. This analysis uses the Delft3D San Francisco Bay-Delta Community Model to simulate water levels and incorporates the effects of a number of adaptation measures in the urban San Francisco Bay estuary, California. In particular, we examine the influence of shoreline hardening, nature-based solutions, and subre-gional floodgates on regional water levels. The result shows that under present conditions, tidal amplification is responsible for generating a wide distribution of extreme water levels across San Francisco Bay. Tidal amplification is found to decrease under sea level rise, thereby producing a relative damping effect on extremes. A comparison of different shoreline scenarios demonstrates that hard frontal shorelines result in higher tidal amplification, whereas restored (soft) shorelines lower amplification. The current shoreline configuration has both hard and soft characteristics and results in an intermediate tidal response. In some areas, wetland restoration reduces extreme water levels by as much as 20 cm, whereas hard-shoreline addition elevates them by as much as 10 cm for 1.5 m of sea level rise. Furthermore, local floodgates can significantly reduce high water levels without major adverse effects elsewhere in San Francisco Bay. These findings point toward the justification for a range of adaptive measures across political boundaries, weighing hard and soft options in addressing the mounting danger of sea level rise.. This work is made available under the terms of the Creative Commons Attribution 4.0 International license, https://creativecommons.org/licenses/by/4.0/. Practical Applications: Sea level rise and stronger storms are putting increasing pressure on coastal communities. In this study, we examined the effect of three different flood mitigation strategies, shoreline hardening, wetland restoration, and subregional floodgates, on water levels in San Francisco Bay, one of the country’s most urbanized estuaries. Using a high-resolution hydrodynamic model, we examined how each of these actions affects extreme water levels under both present and future sea level rise scenarios. We found that building hard shorelines will raise water levels, while restoring wetlands will lower high water levels by as much as 20 cm in some areas. Local floodgates can also lower peak water levels without creating much disturbance in the area when they are reasonably situated and closed near slack tide. However, there are limits to each of these methods. Local adaptation can address flood risk up to approximately 1 m of SLR, but after that, in the 1.0-1.5-m range, low-lying areas start to get flooded more often, and larger, regional-scale measures become increasingly required. Overall, the findings suggest that a single strategy is unlikely to adequately address the region’s changing flood risks. Mixing approaches may prove more effective, especially in diverse settings. They also point to the importance of coordination across jurisdictions to balance urban protection with ecosystem health and build long-term flood resilience in places like San Francisco Bay.

3. Role of Waves in Forecasting Extreme Coastal Flooding under a Warming Climate: Insights from Norfolk, Virginia

   Christopher H Lashley, Jack Puleo, Fengyan Shi, and 1 more author

   Journal of Waterway, Port, Coastal, and Ocean Engineering, May 2025

   Abs DOI

   Coastal flooding occurs when the total water level (TWL) exceeds that of the natural or built coastal defense. Operational models used to forecast the TWL typically consider the combined effect of mean sea level (MSL), high tide, and storm surge. However, the extent to which storm waves run up the beach or structure has traditionally been neglected. Several studies argue that excluding wave run-up could lead to a significant underestimation of the resulting coastal flooding. Others, in direct opposition, argue that extreme wave run-up metrics artificially inflate the estimated TWL. Here, these contradictory findings are addressed by quantifying the contribution of wave runup to coastal flooding at Norfolk (VA, USA) during Hurricane Irene (2011) using the Delft3D FM and FUNWAVE numerical models. To assess the impact of a warming climate, the analysis considered a range of sea level rise values and hurricane intensities, including a combined scenario that represents a 3°C increase in sea surface temperature by the year 2100. Wave run-up contributed the most (48% on average) to the TWL at the coast relative to the existing MSL but accounted for \textless20% of the inundated area, with the remainder flooded by the tide, surge, and SLR. These findings confirm that while wave run-up might play an important role in the TWL and damage along the coast, its contribution to the overall flood extent will be secondary when measured against other factors like storm surge and SLR for low-lying areas with broad continental shelves, like Norfolk. In addition, this study demonstrates the utility of relating the characteristics of each driver of coastal flooding to a target warming level in providing a physical basis for the magnitudes considered when forecasting the compounding consequences of climate change.

4. Subgrid corrections for the linear inertial equations of a compound flood model – a case study using SFINCS 2.1.1 Dollerup release

   Maarten Ormondt, Tim Leijnse, Roel Goede, and 2 more authors

   Geoscientific Model Development, Feb 2025

   Abs DOI

   Abstract. Accurate flood risk assessments and early warning systems are needed to protect and prepare people in coastal areas from storms. In order to provide this information efficiently and on time, computational costs in flood models need to be kept as low as possible. One way to achieve this goal is to apply subgrid corrections to relatively coarse computational grids. Previously, these have been used in full-physics circulation models. In this paper, for the first time, we developed subgrid corrections for the linear inertial equations (LIEs) that account for bed level and friction variations. They were implemented in the Super-Fast INundation of CoastS (SFINCS) model version 2.1.1 Dollerup release. Pre-processed lookup tables that correlate water levels with hydrodynamic quantities make more precise simulations with lower computational costs possible. These subgrid corrections have undergone validation through several conceptual and real-world application scenarios, including rainfall-induced flooding during a hurricane and tidal propagation in an estuary. We demonstrate that the subgrid corrections for linear inertial equations significantly improve model accuracy while utilizing the same resolution without subgrid corrections. In terms of computational efficiency, subgrid corrections increase computational costs by 38 %–128 %. However, this yields a 35–50-time speedup since coarser model resolutions with subgrid corrections can provide the same accuracy as finer resolutions without subgrid corrections. Limitations are also discussed; for example, when grids do not adequately resolve river meanders, fluxes can be overestimated. Our findings show that subgrid corrections are a useful asset for hydrodynamic modelers striving to achieve a balance between accuracy and efficiency.

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

   Patrick L. Barnard, Kevin M. Befus, Jeffrey J. Danielson, and 22 more authors

   Nature Climate Change, Jan 2025

   Abs DOI

   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.

6. Quantifying compound coastal flooding effects in urban regions using a tightly coupled 1D-2D model explicitly resolving flood defense infrastructure

   Boxiang Tang, Kees Nederhoff, and T.W. Gallien

   Coastal Engineering, Feb 2025

   Abs DOI

   Low-lying coastal areas are highly vulnerable to flooding hazards. High marine water levels may overflow seawalls, render the storm drain system inoperable, and promote pluvial and wave overtopping flooding. Complex interactions between various coastal flooding drivers (marine water levels, precipitation, waves) and urban infrastructure (i.e., the stormwater system, and seawalls) are characterized using a novel, tightly coupled hydrodynamic model. Flood extent field observations of tidal overflow, pluvial flooding, and overtopping flooding, along with storm drain system pressure sensor data are used to evaluate hydrodynamic model performance. High marine water levels, precipitation, and overtopping events are modeled and compared with validation data. Results suggest the hydrodynamic model explicitly resolving both 1D storm drain pipe flow and 2D overland flooding more accurately simulates compound flooding compared to typical 2D overland flow models. Nonlinear compound effects were resolved by comparing combined univariate flood impact to corresponding compound flood impact modeled within a tightly coupled 1D2D infrastructure-resolving model. Projected flood extents were ∼

2024

1. Improved efficient physics-based computational modeling of regional wave-driven coastal flooding for reef-lined coastlines

   Camila Gaido Lasserre, Kees Nederhoff, Curt D Storlazzi, and 2 more authors

   Ocean Modelling, Feb 2024

   Abs DOI

   Coastal flooding affects low-lying communities worldwide and is expected to increase with climate change, especially along reef-lined coasts, where wave-driven flooding is particularly prevalent. However, current regional modeling approaches are either insufficient or too computationally expensive to accurately assess risks in these complex environments. This study introduces and validates an improved computationally efficient and physics-based approach to compute dynamic wave-driven regional flooding on reef-lined coasts. We coupled a simplified-physics flood model (SFINCS) with a one-dimensional wave transformation model (XBeach-1D). To assess the performance of the proposed approach, we compared its results with results from a fully resolving two-dimensional wave transformation model (XBeach-2D). We applied this approach for a range of storms and sea-level rise scenarios for two contrasting reef-lined coastal geomorphologies: one low relief area and one high relief area. Our findings reveal that SFINCS coupled with XBeach-1D generates flood extents comparable to those produced by XBeach-2D, with a hit rate of 92%. However, this method tends to underpredict the flood extent of weaker, high-frequency storms and overpredict stronger, low-frequency storms. Across scenarios, our approach overpredicted the mean flood water depth, with a positive bias of 7 cm and root mean square difference of 15 cm. Offering approximately 100 times greater computational efficiency than its two-dimensional XBeach counterpart, this flood modeling technique is recommended for wave-driven flood modeling in scenarios with high computational demands, such as modeling numerous scenarios or undertaking detailed regional-scale modeling.

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

   Kees Nederhoff, Tim W.B. Leijnse, Kai Parker, and 10 more authors

   Feb 2024

   Abs DOI

   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.

3. The projected exposure and response of a natural barrier island system to climate-driven coastal hazards

   Jennifer A. Thomas, Patrick L. Barnard, Sean Vitousek, and 5 more authors

   Scientific Reports, Oct 2024

   Abs DOI

   Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (\textless 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at \textgreater 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.

4. Dynamic Modeling of Coastal Compound Flooding Hazards Due to Tides, Extratropical Storms, Waves, and Sea-Level Rise: A Case Study in the Salish Sea, Washington (USA)

   Kees Nederhoff, Sean C. Crosby, Nate R. Van Arendonk, and 5 more authors

   Water, Jan 2024

   Abs DOI

   The Puget Sound Coastal Storm Modeling System (PS-CoSMoS) is a tool designed to dynamically downscale future climate scenarios (i.e., projected changes in wind and pressure fields and temperature) to compute regional water levels, waves, and compound flooding over large geographic areas (100 s of kilometers) at high spatial resolutions (1 m) pertinent to coastal hazard assessments and planning. This research focuses on advancing robust and computationally efficient approaches to resolving the coastal compound flooding components for complex, estuary environments and their application to the Puget Sound region of Washington State (USA) and the greater Salish Sea. The modeling system provides coastal planners with projections of storm hazards and flood exposure for recurring flood events, spanning the annual to 1-percent annual chance of flooding, necessary to manage public safety and the prioritization and cost-efficient protection of critical infrastructure and valued ecosystems. The tool is applied and validated for Whatcom County, Washington, and includes a cross-shore profile model (XBeach) and overland flooding model (SFINCS) and is nested in a regional tide–surge model and wave model. Despite uncertainties in boundary conditions, hindcast simulations performed with the coupled model system accurately identified areas that were flooded during a recent storm in 2018. Flood hazards and risks are expected to increase exponentially as the sea level rises in the study area of 210 km of shoreline. With 1 m of sea-level rise, annual flood extents are projected to increase from 13 to 33 km2 (5 and 13% of low-lying Whatcom County) and flood risk (defined in USD) is projected to increase fifteenfold (from 14 to USD 206 million). PS-CoSMoS, like its prior iteration in California (CoSMoS), provides valuable coastal hazard projections to help communities plan for the impacts of sea-level rise and storms.

5. Accounting for Uncertainties in Forecasting Tropical Cyclone-Induced Compound Flooding

   Kees Nederhoff, Maarten Van Ormondt, Jay Veeramony, and 4 more authors

   Geoscientific Model Development, Feb 2024

   Abs DOI

   Tropical cyclone impacts can have devastating effects on the population, infrastructure, and on natural habitats. 13 However, predicting these impacts is difficult due to the inherent uncertainties in the storm track and intensity. In addition, 14 due to computational constraints, both the relevant ocean physics and the uncertainties in meteorological forcing are only 15 partly accounted for. This paper presents a new method, called the Tropical Cyclone Forecasting Framework (TC-FF), to 16 probabilistically forecast compound flooding induced by tropical cyclones, considering uncertainties in track, forward speed, 17 and wind speed/intensity. The open-source method accounts for all major relevant physical drivers, including tide, surge, and 18 rainfall, and considers TC uncertainties through Gaussian error distributions and autoregressive techniques. The tool creates 19 temporally and spatially varying wind fields to force a computationally efficient compound flood model, allowing for the 20 computation of probabilistic wind and flood hazard maps for any oceanic basin in the world, as it does not require detailed 21 information on the distribution of historical errors. A comparison of TC-FF and JTWC operational ensembles, both based on 22 DeMaria et al. (2009), revealed minor differences of \textless10%, suggesting that TC-FF can be employed as an alternative, for 23 example, in data-scarce environments. The method was applied to Cyclone Idai in Mozambique. The underlying physical 24 model showed reliable skill in terms of tidal propagation, reproducing the storm surge generation during landfall and flooding 25 near the city of Beira (success index of 0.59). The method was successfully applied to forecast the impact of Idai with different 26 lead times. The case study analyzed needed at least 200 ensemble members to get reliable water levels and flood results three 27 days before landfall (\textless1% flood probability error and \textless20 cm sampling errors). Results showed the sensitivity of forecasting, 28 especially with increasing lead times, highlighting the importance of accounting for cyclone variability in decision-making 29 and risk management. 30 31 https://doi.

2023

1. Relative contributions of water level components to extreme water levels along the United States Southeast Atlantic Coast from a regional-scale water level hindcast

   Kai Parker, Li Erikson, Jenny Thomas, and 3 more authors

   Natural Hazards, Feb 2023

   Abs DOI

   A 38-year hindcast water-level product is developed for the US Southeast Atlantic coastline from the entrance of Chesapeake Bay to the southeast tip of Florida. The water-level modeling framework utilized in this study combines a global-scale hydrodynamic model (Global Tide and Surge Model, GTSM-ERA5), a novel ensemble-based tide model, a parameterized wave setup model, and statistical corrections applied to improve modeled water-level components. Corrected water-level data are found to be skillful, with an RMSE of 13 cm, when compared to observed water-level measurement at tide gauge locations. The largest errors in the hindcast are location-based and typically found in the tidal component of the model. Extreme water levels across the region are driven by compound events, in this case referring to combined surge, tide, and wave forcing. However, the relative importance of water-level components varies spatially, such that tides are found to be more important in the center of the study region, non-tidal residual water levels to the north, and wave setup in the north and south. Hurricanes drive the most extreme water-level events within the study area, but non-hurricane events define the low to mid-level recurrence interval water-level events. This study presents a robust analysis of the complex oceanographic factors that drive coastal flood events. This dataset will support a variety of critical coastal research goals including research related to coastal hazards, landscape change, and community risk assessments.

2. Modeling Extreme Water Levels in the Salish Sea: The Importance of Including Remote Sea Level Anomalies for Application in Hydrodynamic Simulations

   Eric E. Grossman, Babak Tehranirad, Kees Nederhoff, and 6 more authors

   Water, Dec 2023

   Abs DOI

   Extreme water-level recurrence estimates for a complex estuary using a high-resolution 2D model and a new method for estimating remotely generated sea level anomalies (SLAs) at the model boundary have been developed. The hydrodynamic model accurately resolves the dominant physical processes contributing to extreme water levels across the Washington State waters of the Salish Sea, including the relative contribution of remote SLA and other non-tidal residual processes that drive extreme water levels above the predicted tide. The model’s predictions have errors of less than 15 cm (\textless5% of 3–4 m tidal range) at eight tide gauge locations across the model domain. The influence of remote SLAs at the seaward boundary of the model was implemented using a multivariate regression of readily available and locally relevant wind, sea surface temperature, and pressure anomaly data, combined with El Niño Index data (R2 = 0.76). The hydrodynamic model simulations using the remote SLA predictor compared well with simulations using the widely used data-assimilative global ocean model HYCOM SLA data (root mean square difference of 5.5 cm). Extreme water-level recurrence estimates with and without remote SLA show that remote forcing accounts for 50–60% of the total water level anomaly observed along Salish Sea shorelines. The resulting model simulations across decadal timescales provide estimates of extreme water level recurrence across the Salish Sea, capturing climate variability important to long-term coastal hazard planning. This approach has widespread applications for other complex estuarine systems.

3. The influence of vegetated marshes on wave transformation in a sheltered estuary

   Rae Taylor-Burns, Kees Nederhoff, Jessica Lacy, and 1 more author

   Coastal Engineering, Dec 2023

   Abs DOI

   Assessing the influence of marshes on mitigating flooding along estuarine shorelines under the pressures of sea level rise requires understanding wave transformation across the marsh. A numerical model was applied to investigate how vegetated marshes influence wave transformation. XBeach non-hydrostatic (XB-NH) was calibrated and validated with high frequency pressure data from the marsh at China Camp State Park in San Pablo Bay, California (USA). The model was used to examine how marsh and hydrodynamic characteristics change the potential for marshes to mitigate wave driven flooding. Model results demonstrate that hydrodynamics, vegetation, and marsh width influence wave transformation most, while marsh morphology parameters such as elevation and slope had least effect. Results suggest that in the range of settings explored here (incident wave heights ranging from 0.5 to 3 m and water levels ranging from current mean higher high water to 3 m above current mean higher high water), in comparison to wave propagation over an unvegetated mudflat, marsh vegetation reduces runup by a median of 40 cm and wave height by a median of 35 cm. Results illustrate how marshes can be strategically utilized to provide flood reduction benefits.

4. Efficient modeling of wave generation and propagation in a semi-enclosed estuary

   Sean C Crosby, Kees Nederhoff, Nathan VanArendonk, and 1 more author

   Ocean Modelling, Aug 2023

   Abs DOI

   Accurate, and high-resolution wave statistics are critical for regional hazard mapping and planning. However, long-term simulations at high spatial resolution are often computationally prohibitive. Here, multiple rapid frameworks including fetch-limited, look-up-table (LUT), and linear propagation are combined and tested in a large estuary exposed to both remotely (swell) and locally generated waves. Predictions are compared with observations and a traditional SWAN implementation coupled to a regional hydrodynamic model. Fetch-limited and LUT approaches both perform well where local winds dominate with errors about 10%–20% larger than traditional SWAN predictions. Combinations of these rapid approaches with linear propagation methods where remotely generated energy is present also perform well with errors 0%–20% larger than traditional SWAN predictions. Model–model comparisons exhibit lower variance than comparisons to observations suggesting that, while model implementation impacts prediction skill, model boundary conditions (winds, offshore waves) may be a dominant source of error. Overall results suggest that with a relatively small loss in prediction accuracy, simulations computation cost can be significantly reduced (by 2–4 orders of magnitude) allowing for high resolution and long-term predictions to adequately define regional wave statistics.

2022

1. Typological representation of the offshore oceanographic environment along the Alaskan North Slope

   William K. Eymold, Christopher Flanary, Li Erikson, and 5 more authors

   Continental Shelf Research, Jul 2022

   Abs DOI

   Erosion and flooding impacts to Arctic coastal environments are intensifying with nearshore oceanographic conditions acting as a key environmental driver. Robust and comprehensive assessment of the nearshore oceanographic conditions require knowledge of the following boundary conditions: incident wave energy, water level, incident wind energy, ocean temperature and salinity, bathymetry, and shoreline orientation. The number of offshore oceanographic boundary conditions can be large, requiring a significant computational investment to reproduce nearshore conditions. This present study develops location-independent typologies to reduce the number of boundary conditions needed to assess nearshore oceanographic environments in both a Historical (2007–2019) and Future (2020–2040) timespan along the Alaskan North Slope. We used WAVEWATCH III\textregistered and Delft3D Flexible Mesh model output from six oceanographic sites located along a constant ∼50 m bathymetric line spanning the Chukchi to Beaufort Seas. K-means clustering was applied to the energy-weighted joint-probability distribution of significant wave height (Hs) and peak period (Tp). Distributions of wave and wind direction, wind speed, and water level associated with location-independent centroids were assigned single values to describe a reduced order, typological rendition of offshore oceanographic conditions. Reanalysis data (e.g., ASRv2, ERA5, and GOFS) grounded the historical simulations while projected conditions were obtained from downscaled GFDL-CM3 forced under RCP8.5 conditions. Location-dependence for each site is established through the occurrence joint-probability distribution in the form of unique scaling factors representing the fraction of time that the typology would occupy over a representative year. As anticipated, these typologies show increasingly energetic ocean conditions in the future. They also enable computationally efficient simulation of the nearshore oceanographic environment along the North Slope of Alaska for better characterization of coastal processes (e.g., erosion, flooding, or sediment transport).

2. Generating reliable estimates of tropical-cyclone-induced coastal hazards along the Bay of Bengal for current and future climates using synthetic tracks

   Tim Willem Bart Leijnse, Alessio Giardino, Kees Nederhoff, and 1 more author

   Natural Hazards and Earth System Sciences, Jun 2022

   Abs DOI

   Deriving reliable estimates of design water levels and wave conditions resulting from tropical cyclones is a challenging problem of high relevance for, among other things, coastal and offshore engineering projects and risk assessment studies. Tropical cyclone geometry and wind speeds have been recorded for the past few decades only, thus resulting in poorly reliable estimates of the extremes, especially in regions characterized by a low number of past tropical cyclone events. In this paper, this challenge is overcome by using synthetic tropical cyclone tracks and wind fields generated by the open-source tool TCWiSE (Tropical Cyclone Wind Statistical Estimation Tool) to create thousands of realizations representative of 1000 years of tropical cyclone activity for the Bay of Bengal. Each of these realizations is used to force coupled storm surge and wave simulations by means of the processed-based Delft3D Flexible Mesh Suite. It is shown that the use of synthetic tracks provides reliable estimates of the statistics of the first-order hazard (i.e., wind speed) compared to the statistics derived for historical tropical cyclones. Based on estimated wind fields, second-order hazards (i.e., storm surge and waves) are computed that are generated by the first-order hazard of wind. The estimates of the extreme values derived for wind speed, wave height and storm surge are shown to converge within the 1000 years of simulated cyclone tracks. Comparing second-order hazard estimates based on historical and synthetic tracks shows that, for this case study, the use of historical tracks (a deterministic approach) leads to an underestimation of the mean computed storm surge of up to −30 %. Differences between the use of synthetic versus historical tracks are characterized by a large spatial variability along the Bay of Bengal, where regions with a lower probability of occurrence of tropical cyclones show the largest difference in predicted storm surge and wave heights. In addition, the use of historical tracks leads to much larger uncertainty bands in the estimation of both storm surges and wave heights, with confidence intervals being +80 % larger compared to those estimated by using synthetic tracks (probabilistic approach). Based on the same tropical cyclone realizations, the effect that changes in tropical cyclone frequency and intensity, possibly resulting from climate change, may have on modeled storm surge and wave heights was computed. As a proof of concept, an increase in tropical cyclone frequency of +25.6 % and wind intensity of +1.6 %, based on literature values and without accounting for uncertainties in future climate projection, was estimated to possibly result in an increase in storm surge and wave heights of +11 % and +9 %, respectively. This suggests that climate change could increase tropical-cyclone-induced coastal hazards more than just the actual increase in maximum wind speeds.

3. The effect of changing sea ice on wave climate trends along Alaska’s central Beaufort Sea coast

   Kees Nederhoff, Li Erikson, Anita Engelstad, and 2 more authors

   The Cryosphere, May 2022

   Abs DOI

   Diminishing sea ice is impacting the wave field across the Arctic region. Recent observation- and model-based studies highlight the spatiotemporal influence of sea ice on offshore wave climatologies, but effects within the nearshore region are still poorly described. This study characterizes the wave climate in the central Beaufort Sea coast from 1979 to 2019 by utilizing a wave hindcast model that uses ERA5 winds, waves, and ice concentrations as input. The spectral wave model SWAN (Simulating Waves Nearshore) is calibrated and validated based on more than 10 000 in situ time point measurements collected over a 13-year time period across the region, with friction variations and empirical coefficients for newly implemented empirical ice formulations for the open-water and shoulder seasons. Model results and trends are analyzed over the 41-year time period using the non-parametric Mann–Kendall test, including an estimate of Sen’s slope. The model results show that the reduction in sea ice concentration correlates strongly with increases in average and extreme wave conditions. In particular, the open-water season extended by ∼96 d over the 41-year time period (∼2.4 d yr−1), resulting in a 5-fold increase in the yearly cumulative wave power. Moreover, the open-water season extends later into the year, resulting in relatively more open-water conditions during fall storms with high wind speeds. The later freeze-up results in an increase in the annual offshore median wave heights of 1 % yr−1 and an increase in the average number of rough wave days (defined as days when maximum wave heights exceed 2.5 m) from 1.5 in 1979 to 13.1 d in 2019. Trends in the nearshore areas deviate from the patterns offshore. Model results indicate a saturation limit for high wave heights in the shallow areas of Foggy Island Bay. Similar patterns are found for yearly cumulative wave power.

2021

1. Hindcast of pluvial, fluvial, and coastal flood damage in Houston, Texas during Hurricane Harvey (2017) using SFINCS

   A Sebastian, D J Bader, Kees Nederhoff, and 3 more authors

   Natural Hazards, Dec 2021

   Abs DOI

   As demonstrated by recent tropical cyclone events, including U.S. Hurricanes Harvey, Irma, and Maria (2017), and Florence (2018), the destructive potential of flooding driven by wind, precipitation, and coastal surge coupled with growing exposure of people and property along coastlines is leading to unprecedented damage from coastal storms. In this paper, we demonstrate the ability of the recently developed Super-Fast INundation of CoastS (SFINCS) model to delineate the depth and extent of flooding during Hurricane Harvey in Houston, Texas. The model was validated against water level time-series at twenty-one United States Geological Survey (USGS) observation points and 115 high water mark locations. FEMA depth-damage curves were used to estimate building and content damages from the combined flood sources (e.g., pluvial, fluvial, and marine) and total losses are compared against insurance claims registered with the U.S. National Flood Insurance Program (NFIP) and a depth grid produced during the U.S. Federal Emergency Management Agency’s (FEMA) Preliminary Damage Assessment (PDA). The results suggest that Harvey may have caused upwards of $8.3 billion USD in uninsured residential loss within the model domain. Comparison against FEMA’s PDA indicates that the SFINCS model predicts much larger total losses, indicating that the incorporation of spatially-distributed pluvial hazards into the modeling method is critical for identifying high-risk areas and supports the need for further flood risk analyses in the region.

2. Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes

   Tim Leijnse, Maarten Ormondt, Kees Nederhoff, and 1 more author

   Coastal Engineering, Dec 2021

   Abs DOI

   SFINCS, a new reduced-physics solver to compute compound flooding in coastal systems due to fluvial, pluvial, tidal, wind- and wave-driven processes in a computationally efficient way, is presented and validated for a number of verification and application cases. The model solves simplified equations of mass and momentum, which are driven by storm surge and wave boundary conditions, precipitation rates and upstream river discharges. It includes spatially-varying infiltration and bed roughness terms as well as an absorbing-generating seaward boundary to enable wave-driven flooding. Furthermore, advection and wind stress terms can be included. We demonstrate for the application case of hurricane impact on Jacksonville (Florida, USA) that the observed flooding was a combination of fluvial, pluvial, tidal and wind-driven flooding and that this can be modeled well using the reduced-physics solver. We show that the addition of an advection term to the momentum equations is necessary to model shock flows such as dam breaks but also incident broken waves. Thus, wave-driven flooding can be modeled with high computational efficiency and adequate accuracy as demonstrated for the case of Hernani (the Philippines). The model results show the potential of achieving good accuracy at limited computational expense.

3. Morphodynamic modeling of a low-lying barrier subject to hurricane forcing: The role of backbarrier wetlands

   Cody L. Johnson, Qin Chen, Celalettin E. Ozdemir, and 3 more authors

   Coastal Engineering, Aug 2021

   Abs DOI

   Along much of the world’s coastline, coastal barriers serve as the first line of defense against oceanic and meteorological forces. Extreme storms cause large morphological changes on coastal barriers through high sediment transport rates, which may degrade their defensive capabilities. The understanding of morphological impacts is therefore important for coastal resiliency, but is often challenged by site-specific characteristics, such as land cover and sediment availability, and their poorly understood impacts on the governing physical processes. The Caminada Headlands, Louisiana, USA presents unique considerations for morphodynamic modeling with regard to its low-lying topography, variable land cover, nearshore muddy substrate and sand deficiency. This study investigates the effects of land cover and limited sediment supply on low-lying barrier island morphology under storm conditions by using physics-based numerical models. A high-resolution, local-scale sediment transport/morphodynamic model (XBeach) of the Caminada Headlands is verified for Hurricane Gustav’s (2008) impact using pre- and post-storm LIDAR surveys. When accurate input data are used to create physics-based numerical models these tools are robust in hindcasting storm impacts and provide a wealth of information as to the governing processes, which is otherwise difficult to obtain observationally. The simulation results show that a short-duration overwash regime dominates the morphological change in this low-lying barrier and is influenced by backbarrier wetland deterioration. The morphological response to overwash is modulated by backbarrier land cover and topography, as reduced accommodation space limits landward transport during the subsequent inundation regime. An intact backbarrier marsh reduces landward washover sediment transport distances and promotes deposition at supratidal elevations. In light of these findings, simultaneous restoration/creation of backbarrier wetlands in conjunction with subaerial beach renourishment may be an effective form of increasing the resiliency of low-lying barriers subject to frequent overwashing.

4. Simulating synthetic tropical cyclone tracks for statistically reliable wind and pressure estimations

   Kees Nederhoff, Jasper Hoek, Tim Leijnse, and 3 more authors

   Natural Hazards and Earth System Sciences, Mar 2021

   Abs DOI

   The design of coastal protection measures and the quantification of coastal risks at locations affected by tropical cyclones (TCs) are often based solely on the analysis of historical cyclone tracks. Due to data scarcity and the random nature of TCs, the assumption that a hypothetical TC could hit a neighboring area with equal likelihood to past events can potentially lead to over- and/or underestimations of extremes and associated risks. The simulation of numerous synthetic TC tracks based on (historical) data can overcome this limitation. In this paper, a new method for the generation of synthetic TC tracks is proposed. The method has been implemented in the highly flexible open-source Tropical Cyclone Wind Statistical Estimation Tool (TCWiSE). TCWiSE uses an empirical track model based on Markov chains and can simulate thousands of synthetic TC tracks and wind fields in any oceanic basin based on any (historical) data source. Moreover, the tool can be used to determine the wind extremes, and the output can be used for the reliable assessment of coastal hazards. Validation results for the Gulf of Mexico show that TC patterns and extreme wind speeds are well reproduced by TCWiSE.

5. Efficient two-layer non-hydrostatic wave model with accurate dispersive behaviour

   Menno P. Ridder, Pieter B. Smit, Ap Van Dongeren, and 3 more authors

   Coastal Engineering, Mar 2021

   Abs DOI

   A 2-layer non-hydrostatic model with improved dispersive behaviour is presented. Due to the assumption of a constant non-hydrostatic pressure distribution in the lower layer, the dispersive behaviour is improved without much additional computational time. A comparison with linear wave theory showed that this 2-layer model gives a better result for the dispersion relation and shoaling of waves in intermediate water. This means that the 2-layer model is applicable in shallow and intermediate water depths (up to relative depths kh equals 4), whereas the 1-layer model is only applicable in shallow water depths (kh smaller than 1). Three laboratory experiments, including a fringing reef and a barred beach, were used to validate the presented mode for different hydrodynamic conditions. Based on these results, it can be concluded that the 2-layer model can be applied to accurately simulate the bulk wave height and spectral properties. The low frequency wave height, the setup and in particular the second order statistics contain more scatter, but the model accurately captured the general trend. Furthermore, the model showed good results for complex bathymetries in shallow to intermediate water.

6. Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay

   Kees Nederhoff, Rohin Saleh, Babak Tehranirad, and 4 more authors

   Coastal Engineering, Dec 2021

   Abs DOI

   Reliable and long-term hindcast data of water levels are essential in quantifying return period and values of extreme water levels. In order to inform design decisions on a local flood control district level, process-based numerical modeling has proven an essential tool to provide the needed temporal and spatial coverage for different extreme value analysis methods. To determine the importance of different physical processes to the extreme water levels we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to simulate a large, urban, high-energy coastal estuary (the San Francisco Bay). The unstructured grid with 1D/2DH model elements, allows for efficient model simulations and therefore it was possible to simulate over 70 years between 1950 and 2019. Results show significant skill in reproducing observations for the entire modeled time period with an average root-mean-square error of 8.0 cm. A process-based modeling approach allows for the explicit in- and exclusion of different physical processes to quantify their importance to the extremes. For the 100-year still water level (SWL), tide (70%) and non-tidal residual (NTR) (25%) explain the majority of the simulated high water levels in the Bay relative to Mean Higher High Water (MHHW). However, closer to the Delta, local fluvial inflow increases in importance. For longer return periods, the importance of tide decreases and the importance of remote NTRs and fluvial inflow increases.

2020

1. Effect of Fluvial Discharges and Remote Non-Tidal Residuals on Compound Flood Forecasting in San Francisco Bay

   Babak Tehranirad, Liv Herdman, Kees Nederhoff, and 5 more authors

   Water, Sep 2020

   Abs DOI

   Accurate and timely flood forecasts are critical for making emergency-response decisions regarding public safety, infrastructure operations, and resource allocation. One of the main challenges for coastal flood forecasting systems is a lack of reliable forecast data of large-scale oceanic and watershed processes and the combined effects of multiple hazards, such as compound flooding at river mouths. Offshore water level anomalies, known as remote Non-Tidal Residuals (NTRs), are caused by processes such as downwelling, offshore wind setup, and also driven by ocean-basin salinity and temperature changes, common along the west coast during El Niño events. Similarly, fluvial discharges can contribute to extreme water levels in the coastal area, while they are dominated by large-scale watershed hydraulics. However, with the recent emergence of reliable large-scale forecast systems, coastal models now import the essential input data to forecast extreme water levels in the nearshore. Accordingly, we have developed Hydro-CoSMoS, a new coastal forecast model based on the USGS Coastal Storm Modeling System (CoSMoS) powered by the Delft3D San Francisco Bay and Delta community model. In this work, we studied the role of fluvial discharges and remote NTRs on extreme water levels during a February 2019 storm by using Hydro-CoSMoS in hindcast mode. We simulated the storm with and without real-time fluvial discharge data to study their effect on coastal water levels and flooding extent, and highlight the importance of watershed forecast systems such as NOAA’s National Water Model (NWM). We also studied the effect of remote NTRs on coastal water levels in San Francisco Bay during the 2019 February storm by utilizing the data from a global ocean model (HYCOM). Our results showed that accurate forecasts of remote NTRs and fluvial discharges can play a significant role in predicting extreme water levels in San Francisco Bay. This pilot application in San Francisco Bay can serve as a basis for integrated coastal flood modeling systems in complex coastal settings worldwide.

2. Delft Dashboard: a quick setup tool for hydrodynamic models

   Maarten Ormondt, Kees Nederhoff, and Ap Van Dongeren

   Journal of Hydroinformatics, Sep 2020

   Abs DOI

   The open-source program Delft Dashboard (DDB) is a graphical user interface designed to quickly create, edit input parameters and visualize model inputs for a number of hydrodynamic models, using private or publicly available local and global datasets. It includes a number of toolboxes that facilitate the generation of spatially varying inputs. These include new model schematizations (grids, bathymetry, boundary conditions, etc.), cyclonic wind fields and initial tsunami waves. The use of DDB can have significant benefits. It can save modellers considerable time and effort. Furthermore, the automated nature of both data collection and pre-processing within the program reduces the likelihood of errors that could occur when setting up models manually. Three case studies are presented: simulation of tides in the North Sea, storm surge and wave modelling under tropical cyclone conditions and the simulation of a tsunami. The test cases show that models created with DDB can be set up efficiently while maintaining a predictive skill that is only slightly lower than that of extensively calibrated models.

2019

1. Estimates of tropical cyclone geometry parameters based on best-track data

   Kees Nederhoff, Alessio Giardino, Maarten Ormondt, and 1 more author

   Natural Hazards and Earth System Sciences, Oct 2019

   Abs DOI

   Parametric wind profiles are commonly applied in a number of engineering applications for the generation of tropical cyclone (TC) wind and pressure fields. Nevertheless, existing formulations for computing wind fields often lack the required accuracy when the TC geometry is not known. This may affect the accuracy of the computed impacts generated by these winds. In this paper, empirical stochastic relationships are derived to describe two important parameters affecting the TC geometry: radius of maximum winds (RMW) and the radius of gale-force winds (\DeltaAR35). These relationships are formulated using best-track data (BTD) for all seven ocean basins (Atlantic; S, NW, and NE Pacific; and N, SW, and SE Indian oceans). This makes it possible to (a) estimate RMW and \DeltaAR35 when these properties are not known and (b) generate improved parametric wind fields for all oceanic basins. Validation results show how the proposed relationships allow the TC geometry to be represented with higher accuracy than when using relationships available from literature. Outer wind speeds can be reproduced well by the commonly used Holland wind profile when calibrated using information either from best-track data or from the proposed relationships. The scripts to compute the TC geometry and the outer wind speed are freely available via the following URL: https://bit.ly/2k9py1J (last access: October 2019).

2. Impact of Coral Reef Mining Pits on Nearshore Hydrodynamics and Wave Runup During Extreme Wave Events

   Sebastiaan Klaver, Kees Nederhoff, A. Giardino, and 3 more authors

   Journal of Geophysical Research: Oceans, Apr 2019

   Abs DOI

   Small island developing states are among the most vulnerable areas to the impact of natural hazards and climate change. Flooding due to storm surges and extreme waves, coastal erosion, and salinization of freshwater lenses are already a serious threat and could lead to irreversible consequences in the coming decades. Reef flat mining is one of the most common practices to source the required material for the implementation of coastal protection measures, but concerns remain that partial removal of the protective reef could increase wave loading on the islands. However, the available data and knowledge on the effects of these mining pits are currently very limited. This study provides new insights on the effects that pits may have on nearshore hydrodynamics and wave runup. Results are based on a large numerical data set of fringing reefs, derived using the validated XBeach nonhydrostatic+ process-based model. Model results indicate that excavation pits cause a decrease in infragravity wave energy around the fundamental mode of the reef, which is partly caused by reduced wave transmission. Additionally, changes in sea and swell wave energy are attributed to reduced transmission, a decrease in wave dissipation, and (triad) wave–wave interaction. Furthermore, in 13% of all modeled cases, an increase in wave runup is observed, mainly due to more sea and swell wave energy reaching the shoreline. This probability is lowest for narrow pits relative to the reef flat width or pits located further from shore.

2018

1. Coastal hazard risk assessment for small islands: assessing the impact of climate change and disaster reduction measures on Ebeye (Marshall Islands)

   Alessio Giardino, Kees Nederhoff, and Michalis Vousdoukas

   Regional Environmental Change, Dec 2018

   Abs DOI

   Small island states around the world are among the areas most vulnerable to climate change and sea level rise. In this paper, we present results from an innovative methodology for a quantitative assessment of multiple hazards on coastal risks, driven by different hydro-meteorological events, and including the effects of climate change. Moreover, we take an additional step by including in the methodology the option to assess and compare the effectiveness of possible disaster risk reduction measures. The methodology is applied to a real case study at the island of Ebeye (the Republic of the Marshall Islands). An example is provided in which a rock revetment is implemented as a risk reduction measure for the island. Results show that yearly expected damages may increase, by the end of the century, by a factor of three to four, depending on the sea level rise scenario considered, while the number of yearly affected people may double. Putting a cap on the temperature increase (e.g. 1.5 vs. 2 °C) according to the Paris Agreement may reduce damages and number of affected people by about 20 and 15%, respectively. However, impacts for same warming levels can vary substantially among different emission scenarios. Disaster risk reduction measures can be useful for mitigating risks in current and future situations but should be incorporated within long-term adaptive planning for these islands.

2. Improving predictions of swash dynamics in XBeach: The role of groupiness and incident-band runup

   Dano Roelvink, Robert McCall, Seyedabdolhossein Mehvar, and 2 more authors

   Coastal Engineering, Apr 2018

   Abs DOI

   In predicting storm impacts on sandy coasts, possibly with structures, accurate runup and overtopping simulation is an important aspect. Recent investigations (Stockdon et al., 2014; Palmsten and Splinter, 2016) show that despite accurate predictions of the morphodynamics of dissipative sandy beaches, the XBeach model (Roelvink et al., 2009) does not correctly simulate the individual contributions of set-up, and infragravity and incident-band swash to the wave run-up. In this paper we describe an improved numerical scheme and a different way of simulating the propagation of directionally-spread short wave groups in XBeach to better predict the groupiness of the short waves and the resulting infragravity waves. The new approach is tested against field measurements from the DELILAH campaign at Duck, NC, and against video-derived runup measurements at Praia de Faro, a relatively steep sandy beach. Compared to the empirical fit by Vousdoukas et al. (2012) the XBeach model performs much better for more extreme wave conditions, which are severely underestimated by existing empirical formulations.

3. A quantitative assessment of human interventions and climate change on the West African sediment budget

   A. Giardino, Reinier Schrijvershof, Kees Nederhoff, and 9 more authors

   Ocean & Coastal Management, Apr 2018

   Abs DOI

   The West African coastal barrier is maintained by significant wave-driven longshore sand transport. This sand originates from rivers and large coastal sand deposits. Today, however, much of the fluvial sand is trapped behind river dams and/or interrupted at several locations by port jetties. As a result, the sandy coastal barrier is eroding almost everywhere along its length. The aim of this study is to derive a large-scale sediment budget analysis, following a consistent approach, for the following countries: Republic of Côte d’Ivoire, Ghana, Togo and Benin, and pointing out the effects of major human interventions and climate change in this large common sediment system. The results are used as a basis to raise awareness among local governments and organizations on the effects and interdependency that major anthropogenic interventions (i.e. port jetties and river dams) and climate change (i.e. sea level rise, changes in wave climate, precipitation and temperature) may have on this shared sediment system. These detrimental effects can even occur in neighboring countries, as shown by some of the results. This estimation was carried out using a quantitative approach, based on one consistent numerical modelling system and validated with regional and local data. Based on the outcomes of the study, and with the support of a number of validation workshops in the different countries, suggestions are also provided for the setting up of a regional sediment management plan for the entire region.