Geology topics

Cornelis M. Nederhoff

Publications and source records attributed to Cornelis M. Nederhoff.

13 recordsLinked to original sources

USGS2025

Wetter winters, drier summers: Quantifying the change in hydrological response around the Puget Sound area using the wflow_sbm hydrological model and CMIP6 projections

Climate change is expected to impact hydrological regimes worldwide, including the Pacific Northwest of the United States. This study investigates how climate change will affect river discharge in the Puget Sound region of the State of Washington, with a focus on King and Pierce Counties. We simulated river discharge under historical and future conditions using the physically based, spatially distributed wflow_sbm hydrological model, which was calibrated and validated against U.S. Geological Survey discharge records. Future forcing was based on an ensemble of six high-resolution CMIP6 climate models, which were bias corrected using empirical quantile mapping. The results indicate a decrease in summer discharges (5–10%) and an increase in winter discharges (5–10%) across the study region. The high discharges (90th percentile) are projected to increase in winter, and the low discharges are projected to decrease in summer, due to shifts in precipitation regimes, snowpack hydrology, and evapotranspiration. However, variability between individual CMIP6 models often exceeds the magnitude of ensemble mean changes, underscoring substantial uncertainty in climate projections and the importance of including multiple climate models in climate change analysis. Furthermore, model consensus increased with elevation, which could be the result of the higher elevation areas being driven by less diverse hydrological processes. These findings highlight potential challenges for regional water management, ecosystem health, and flood risk mitigation in the Puget Sound region under future climate conditions.

EarthArXiv↗

USGS2024

A dataset of two-dimensional XBeach model set-up files for northern California

Here, we describe a dataset of two-dimensional (2D) XBeach model files that were developed for the Coastal Storm Modeling System (CoSMoS) in northern California as an update to an earlier CoSMoS implementation that relied on one-dimensional (1D) modeling methods. We provide details on the data and their application, such that they might be useful to end-users for other coastal studies. Modeling methods and outputs are presented for Humboldt Bay, California, in which we compare output from a nested 1D modeling approach to 2D model results, demonstrating that the 2D method, while more computationally expensive, results in a more cohesive and directly mappable flood hazard result.

California↗

USGS2024

Forecasting storm-induced coastal flooding for 21st century sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands

Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian, Mariana, and American Samoan Islands as a result of climate change and sea-level rise. We followed a hybrid (dynamical and statistical) downscaling approach to map flooding due to waves and storm surge at 10-square meter resolution along all 1,870 kilometers of these islands’ coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.00 meter (m), +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios. We quantified the coastal flood depths and extents using the latest climate forcing from Intergovernmental Panel for Climate Change’s Sixth Assessment Report Coupled Model Intercomparison Project. The data generated using these methods provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when climate change and sea-level rise increase coastal storm-induced flooding to help identify areas where management and (or) restoration could potentially help reduce the risk to, and increase the resiliency of, the coastal communities in the populated Hawaiian, Mariana, and American Samoan Islands.

Hawaii↗

USGS2023

Compound flood model for the lower Nooksack River and delta, western Washington—Assessment of vulnerability and nature-based adaptation opportunities to mitigate higher sea level and stream flooding

Higher sea level and stream runoff associated with climate change is expected to lead to greater lowland flooding across the Pacific Northwest. Increases in stream runoff that range from 20 to 32 percent by the 2040s and from 52 to 72 percent by the 2080s is expected to steadily increase flood risk. Flood risk is also expected to increase in response to the landward shift in high tides and storm surge, which will retard downstream conveyance. The combination of higher stream runoff, which is expected to drive greater fluvial sediment delivery to the coast, and more frequent, higher coastal waters relative to present-day (2023) levels, which will retard streamflow, is projected to cause more sedimentation across coastal and estuarine systems, exacerbating the flood risk. In the Nooksack River delta of western Washington, as in many Puget Sound deltas, resilient adaptation planning to mitigate impacts to community assets and infrastructure, nationally essential agricultural areas, and valued habitats and restoration investments that support endangered and threatened salmon recovery are underway but are in need of more informed projections of compound flood hazards. A Delft3D Flexible Mesh hydrodynamic model was constructed and used to assess changes in the extent, frequency, and timing of flood exposure associated with higher sea level and stream runoff projected to occur in the 2040s and 2080s. The model was also used to evaluate the change in and potential mitigating effects to flood exposure associated with individual and cumulative salmon-habitat-restoration strategies. Model simulations also evaluated the sensitivity of sedimentation to the individual and cumulative effects of higher fluvial delivery, trapping by sea-level rise, and changes in hydrodynamics associated with the rerouting of flows by proposed restoration strategies. The model performed well, having mean absolute errors for water levels below 1 foot (0.3 meters) when tested during a 2-year period for two recent flood events of record, the February 2, 2020, “Super Bowl flood” and the January 8, 2009, stream flood, both of which caused substantial flooding and damage across the study area. Fluvial discharge was found to dominate flood hazard at higher elevations in the study area, whereas near the coast, sea-level rise is computed to turn a less extreme 2-year (50 percent annual exceedance probability [AEP]) bankfull streamflow, which, at present (2023), causes nuisance flooding, into a more extreme 5-year (20 percent AEP) and 10 percent AEP stream-flood event by the 2050s and 2100, respectively. The February 2020 Super Bowl flood was calculated to be a 10-year or 10 percent AEP peak-flow event, and the January 2009 flood was calculated to be a 25-year (4 percent AEP) peak-flow event. Extreme events such as the February 2020 Super Bowl flood and the January 2009 flood caused extensive damage across the Nooksack River floodplain, and model computations predict these magnitudes of events would have notably greater effect in the 2040s and 2080s in response to higher projected sea level and stream runoff. The modeled January 2009 flood is predicted to transform into a flood event, causing flood exposure that is comparable to the 100-year or 1 percent AEP flood by the 2040s. The modeled January 2009 flood is also predicted to exceed the flood exposure of the recent November 16, 2021, flood, which caused substantial damage in the lower Nooksack River floodplain and restricted access for emergency-management efforts on important arterial roadways in the area; the measured peak discharge during the November 16, 2021, flood exceeded that of the January 2009 flood. Two of several identified alternative strategies that reroute floodwaters to restore salmon habitat were projected to reduce exposure to the increasingly impactful 10 and 4 percent AEP stream-flood events through the 2080s. The effects of the suggested alternatives, however, were found to reduce flow velocities, promote additional sedimentation, and reduce flow conveyance in the main-stem Nooksack River, a concern to flood-management efforts, navigation, and fishing. The model also suggests that main-stem channel sedimentation is likely, given projected climate change. Higher stream runoff that increases fluvial-sediment delivery and higher sea levels that retard downstream flow are expected to lead to greater sedimentation. Lastly, the model was used to assess the sensitivity of flood exposure to the individual and cumulative effects of climate changes, alternative strategies, and sedimentation, including recently observed decadal-scale aggradation patterns. These results indicate that sediment is likely to continue to be a challenge to flood-management efforts and that nature-based alternatives that benefit ecosystem restoration may also mitigate flood exposure for several decades.

Washington↗

USGS2023

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

A 38-year hindcast water level product is developed for the U.S. Southeast Atlantic coastline from the entrance of Chesapeake Bay to the southeast tip of Florida. The water level modelling 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 modelled 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.

Florida, Georgia, North Carolina, South Carolina, ↗

USGS2023

Numerical model characterization of sediment transport potentials pre- and post-construction of an artificial island in Foggy Island Bay, Alaska

The anticipated construction of the Liberty Development Island near Prudhoe Bay, Alaska, has created a need to understand how the island may influence sediment transport patterns and deposition on the nearby Boulder Patch ecosystem. This study uses a numerical model to characterize sediment transport pathways in Foggy Island Bay with and without the artificial island in place. We present the Delft3D-based model setup and application that yields an improved quantification and understanding of the region’s hydrodynamic, wave, and sediment transport patterns. The results for the present show mainly east-west directed, alongshore transport of silt and clay. Insertion of the planned island results in limited changes to the overall hydrodynamic and sediment transport patterns within the Bay but reverses erosional tendencies across a boulder patch, situated within a kilometer of the planned construction location, to being net depositional.

Alaska↗

USGS2023

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↗

USGS2023

Central Beaufort Sea Wave and Hydrodynamic Modeling Study; Report 2: Modeled waves, hydrodynamics, and sediment transport within Foggy Island Bay

Renewed interest in nearshore oil exploration and production in the shallow waters of the Central Beaufort Sea Shelf has created a need to advance our understanding of the past, current, and future atmospheric and oceanographic conditions that affect existing and planned infrastructure and nearshore ecosystems. At the time of writing this report, Hilcorp Alaska LLC has received BOEM approval for an oil and gas Development and Production Plan (DPP) that includes the construction of the Liberty Drilling Island (LDI) in Foggy Island Bay, situated within Stefansson Sound circa 30 km east of Prudhoe Bay (Figure 1.1). The aim of this study is to investigate how longer periods of open water (defined as < 15% ice cover), decreased sea ice cover, and changes in ocean and atmospheric conditions might affect wave and storm surge conditions, sediment transport patterns, and coastal erosion rates within Foggy Island Bay as well as the modeled influence of the offshore artificial island on sediment transport patterns.

Alaska↗

USGS2023

Central Beaufort Sea Wave and Hydrodynamic Modeling Study--Report 1: Field measurements and model development

Renewed interest in nearshore oil exploration and production in the shallow waters of the Central Beaufort Sea Shelf has created a need to advance our understanding of the past, current, and future atmospheric and oceanographic conditions that affect existing and planned infrastructure and nearshore ecosystems. At the time of writing this report, Hilcorp Alaska, LLC, has received BOEM approval for an oil and gas Development and Production Plan (DPP) that includes the construction of the Liberty Drilling Island (LDI) in Foggy Island Bay, situated within Stefansson Sound circa 30 km east of Prudhoe Bay (Figure 1.1). The aim of this study is to investigate how longer periods of open water (defined as < 15% ice cover), decreased sea ice cover, and changes in ocean and atmospheric conditions might affect wave and storm surge conditions, sediment transport patterns, and coastal erosion rates within Foggy Island Bay as well as the modeled influence of the offshore artificial island on sediment transport patterns.

Foggy Island Bay↗

USGS2023

The influence of vegetated marshes on wave transformation in sheltered estuaries

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.

Coastal Engineering↗

USGS2023

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

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.

British Columbia, Washington↗

USGS2022

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

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.

Alaska↗

USGS2021

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

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.

California↗