Geology topics

John C. Warner

Publications and source records attributed to John C. Warner.

At least 19 recordsLinked to original sources

USGS2026

Storm surge barriers reduce seaward sediment supply to lagoonal estuaries

Numerical simulations with realistic forcing of fixed infrastructure for a proposed storm surge barrier for a lagoonal estuary, Jamaica Bay (New York, USA), are analyzed during typical forcing conditions to assess alterations to flow and sediment transport with the barrier open. Lagoonal estuaries are shallow and have modest watershed freshwater and sediment inputs, so sediment delivery is primarily from offshore by tidal transport. The storm surge barrier infrastructure across the inlet channel reduces cross-sectional area and increases tidal velocities, increasing frictional and form drag. The overall reduction in tidal amplitude is about 1%, but the quarterdiurnal M 4 component decreases by 11%. The salinity and stratification in the estuary are only slightly modified by mixing by stronger velocities near the barrier. Sediment transport in the inlet scales approximately with tidal velocity cubed and net landward transport is driven by flood-dominant tidal asymmetry. Additionally, tidal asymmetry in the jet flow through barrier openings causes a divergence in sediment transport within several kilometers. The alterations to the tidal currents reduce sediment import to the bay by 20% for fine sand; transport of sediment with slower settling velocities is less affected, with reductions of 3% for medium silt and <1% for fine silt. The study examined tidal exchange with an open barrier, but the overall impact also depends on barrier operations during major storm events. The impacts of barrier infrastructure on lagoonal estuaries are distinct from other estuary types due to their modest freshwater input, predominance of tidal transport, and offshore sediment supply.

New York↗

USGS2026

Spatial heterogeneity of salt marsh vulnerability to sea-level rise: Dual controls of hydrological setting and salinity regime

Salt marsh vulnerability to sea-level rise (SLR) is typically assessed using point measurements of vertical accretion, neglecting three-dimensionality of geomorphic evolution and spatial variability. Recent studies suggest links between vertical and horizontal vulnerability, with differences between oligohaline and polyhaline marshes, yet these relationships remain untested in estuary-marsh systems. Here we combine geospatial analysis with hydrodynamic modeling to evaluate how unvegetated/vegetated marsh ratio (UVVR), a metric of marsh degradation, relates to elevation across hydrological regions and salinity regimes in the Albemarle-Pamlico Estuarine System, the largest lagoonal estuary in U.S. We show that at given normalized elevation, UVVR decreases across hydrological regions and salinity regimes from offshore to inland. UVVR-elevation relationship varies systematically with both hydrological setting and salinity regime, with hydrology exerting stronger influence. These findings challenge the assumption of a universal marsh deterioration trajectory and underscore the need to account for spatial heterogeneity when predicting responses to SLR.

North Carolina↗

USGS2026

Compounding of 100-year coastal floods by rainfall in an urban environment

Coastal and pluvial flooding are both becoming more prevalent and severe due to climate change and urbanization in floodplains. The co-occurrence of these flood drivers is generally assumed to exacerbate the resulting flood impacts, a result referred to as compound flooding. However, few observational or modeling studies have investigated the circumstances under which this occurs. Here, we study the impacts of these combined flood drivers and evaluate the implicit hypothesis of official flood maps, which is that rainfall has a negligible impact on the flood depth and flooded area due to a 100 year coastal flood. A coastal system model, configured to capture coastal and pluvial flood drivers, is used. We evaluate the flooding for different urban landform types, including coastal landfill (human-made land), convergent areas (topographic depressions) and other urban terrain, within a model domain covering the Jamaica Bay watershed of New York City. A scenario-based strategy is adopted with a 100 year coastal flood as a control simulation, to which we add a set of realistic scenarios of rainfall data from historical tropical cyclones. We also apply a joint probability analysis framework with historical data to evaluate the probability of these compound coastal-pluvial scenarios. Results reveal cases where the pluvial driver compounds the coastal flood through expansion of the flood zone, with a 17% chance of rainfall increasing the flood area by 6%–38%, and a 5% chance of an increase of 61%–73%. It is rare that floods are significantly deepened but when deepening occurs, it is more common for the convergent zone than for the coastal landfill. These findings quantitatively assess the potential of the pluvial driver to exacerbate flooding, which may influence emergency management strategies such as evacuation plans, shelter arrangements, and related preparedness measures.

New York↗

USGS2025

Wind pumping dominates landward salt transport in a weakly tidal estuary

In tidally energetic estuaries, salinity dynamics vary with tidal forcing as well as factors such as river discharge and bathymetry. However, in weakly tidal estuaries, mechanisms governing salt transport remain poorly understood. Here, we investigate salt transport processes in a weakly tidal estuary, Albemarle Sound on the U.S. East Coast, using a deterministic numerical model. In 2022, the volume averaged salinity of Albemarle Sound ranged from ∼2 to 10 psu. Although seasonal river discharge typically induces gradual salinity changes of less than 1 psu per month, four wind events caused sharp salinity increases of 1–2 psu within just a few days. We find that wind pumping, defined as the net salt transport due to temporal correlations between velocity and salinity associated with wind events, is the dominant mechanism contributing to these episodic increases in volume averaged salinity. In Albemarle Sound, wind pumping operates on timescales of several days, which is longer than the tidal timescale, and occurs intermittently throughout the year rather than following a regular repetitive pattern. Our analysis suggests that salt transport by wind pumping is typically an order of magnitude larger than by gravitational circulation and serves as the primary mechanism balancing salt loss from river flow. Isolating wind pumping requires averaging over variability of multiple days, longer than typical tidal averaging. Wind pumping likely also controls material exchange with coastal ocean, influencing biogeochemical processes in the estuary. This mechanism may be important in other systems with similar characteristics, particularly in coastal lagoons with multiple subembayments.

North Carolina↗

USGS2025

Numerical simulation of sound-side barrier-island inundation and breaching during Hurricane Dorian (2019)

Hurricane-induced morphological changes and associated community hazards along sandy, barrier-island coastlines have been studied primarily from the perspective of ocean-side attack by storm-driven ocean surge and large waves. Thus, our understanding of long-term barrier island morphological change focuses on beach erosion, overwash, and inlet formation. In contrast, outwash events with inundation from the sound side, such as one that occurred in Cape Lookout National Seashore, North Carolina, USA during Hurricane Dorian (September 2019), are understudied. Studying such events can improve understanding of barrier island response and stability for a broader range of conditions. Here, we model the hydrodynamics and morphological evolution of a barrier island using a coupled wave-current-sediment transport modeling system. Wind-driven surge in Pamlico Sound led to overtopping from the sound side, which eroded outwash channels and transported sediment seaward into the nearshore. Simulations reproduce the channel features observed with aerial imagery and provide information not available from the remote-sensing observations, including channel depths (>2 m) and the fate of the eroded sand. We found that >99% of the eroded sand was deposited in the nearshore, within 1,000 m of the shoreline in depths <10 m, suggesting that the deposited sediment remains available for littoral transport and beach recovery. Simulations with combinations of coarse or fine sediment and vegetated or unvegetated landcover indicate that channel position did not vary with grain size or vegetation, while volume of erosion and channel morphology were more responsive to variations in grain size and less responsive to presence of vegetation.

North Carolina↗

USGS2025

Pluvial and potential compound flooding in a coupled coastal modeling framework: New York City during post-tropical Cyclone Ida (2021)

Many coastal urban areas are prone to extreme pluvial flooding due to limitations in stormwater system capacity, with the additional potential for flooding compounded by storm surge, tides, and waves. Understanding and simulating these processes can improve prediction and flood risk management. Here, we adapt the Coupled Ocean–Atmosphere–Wave–Sediment Transport modeling framework (COAWST) to simulate pluvial flooding from post-tropical Cyclone Ida (2021) in the Jamaica Bay watershed of New York City (NYC). We modify the model to capture the volumetric effects of rainfall and parameterize soil infiltration and a stormwater conveyance system as the drainage rate. We generate a spatially continuous flood map of Ida with a root-mean-square error (RMSE) of 20 cm when compared to high-water marks, useful for understanding Ida's impacts and subsequent mitigation planning. Results show that over 23 km 2 and 4621 buildings were flooded deeper than 0.3 m during Ida. Sensitivity analyses are used to study the broader risk from events like Ida (pluvial flooding) as well as potential compound (pluvial–coastal) flooding. Spatial shifting of the storm track within a typical 12 h forecast uncertainty reveals a worst-case scenario that increases this flooded area to 62 km 2 (5907 buildings). Shifting Ida's rainfall to coincide with high tide increases this flooded area by 1 km 2 , a relatively small change due to the lack of significant storm surge. The application of COAWST to this storm event addresses a broader goal of developing the capability to model compound pluvial–coastal flooding by simultaneously representing coastal storm processes such as rain, tide, waves, erosion, and atmosphere–wave–ocean interactions. The sensitivity analysis results underscore the need for detailed flood risk assessments, showing that Ida, already NYC's worst rain event, could have been even more devastating with slight shifts in the storm track.

New York↗

USGS2024

Quantifying compound and nonlinear effects of hurricane-induced flooding using a dynamically coupled hydrological-ocean model

We recently developed a dynamically coupled hydrological-ocean modeling system that provides seamless coverage across the land-ocean continuum during hurricane-induced compound flooding. This study introduced a local inertial equation and a diagonal flow algorithm to the overland routing of the coupled system’s hydrology model (WRF-Hydro). Using Hurricane Florence (2018) as a test case, the performance of the coupled model was significantly improved, evidenced by its enhanced capability of capturing backwater and increased water level simulation accuracy and stability. With four model experiments, we present a framework to detangle, define, and quantify compound and nonlinear effects. The results revealed that the flood peaks in the lower Cape Fear River Basin and the coastal waters were contributed by inland flooding and storm surge, respectively. These two processes had comparable contributions to the flooding in the Cape Fear River Estuary. The compound effect was identified when the flood levels resulting from the combination of land and ocean processes surpassed those caused by an individual process alone. The compound effect during Hurricane Florence exhibited limited impact on flood peaks, primarily due to the time lag between the peaks of the storm surge and the inland flooding. In the period between the two peaks, the compound effect was salient and significantly impacted the magnitude and variation of the flood level. The nonlinear effect, defined as the difference between the compound flood level and the superposition of storm surge and inland flooding water levels, reduced flood levels in the river channels while increasing flood levels on the floodplain.

Water Resources Research↗

USGS2024

Deep learning of estuary salinity dynamics is physically accurate at a fraction of hydrodynamic model computational cost

Salinity dynamics in the Delaware Bay estuary are a critical water quality concern as elevated salinity can damage infrastructure and threaten drinking water supplies. Current state-of-the-art modeling approaches use hydrodynamic models, which can produce accurate results but are limited by significant computational costs. We developed a machine learning (ML) model to predict the 250 mg L −1 Cl − isochlor, also known as the “salt front,” using daily river discharge, meteorological drivers, and tidal water level data. We use the ML model to predict the location of the salt front, measured in river miles (RM) along the Delaware River, during the period 2001–2020, and we compare predictions of the ML model to the hydrodynamic Coupled Ocean–Atmosphere-Wave-Sediment Transport (COAWST) model. The ML model predicts the location of the salt front with greater accuracy (root mean squared error [RMSE] = 2.52 RM) than the COAWST model does (RMSE = 5.36); however, the ML model struggles to predict extreme events. Furthermore, we use functional performance and expected gradients, tools from information theory and explainable artificial intelligence, to show that the ML model learns physically realistic relationships between the salt front location and drivers (particularly discharge and tidal water level). These results demonstrate how an ML modeling approach can provide predictive and functional accuracy at a significantly reduced computational cost compared to process-based models. In addition, these results provide support for using ML models in operational forecasting, scenario testing, management decisions, hindcasting, and resulting opportunities to understand past behavior and develop hypotheses.

Limnology and Oceanography↗

USGS2024

Modeled coastal-ocean pathways of land-sourced contaminants in the aftermath of Hurricane Florence

Extreme precipitation during Hurricane Florence, which made landfall in North Carolina in September 2018, led to breaches of hog waste lagoons, coal ash pits, and wastewater facilities. In the weeks following the storm, freshwater discharge carried pollutants, sediment, organic matter, and debris to the coastal ocean, contributing to beach closures, algae blooms, hypoxia, and other ecosystem impacts. Here, the ocean pathways of land-sourced contaminants following Hurricane Florence are investigated using the Regional Ocean Modeling System (ROMS) with a river point source with fixed water properties from a hydrologic model (WRF-Hydro) of the Cape Fear River Basin, North Carolina's largest watershed. Patterns of contaminant transport in the coastal ocean are quantified with a finite duration tracer release based on observed flooding of agricultural and industrial facilities. A suite of synthetic events also was simulated to investigate the sensitivity of the river plume transport pathways to river discharge and wind direction. The simulated Hurricane Florence discharge event led to westward (downcoast) transport of contaminants in a coastal current, along with intermittent storage and release of material in an offshore (bulge) or eastward (upcoast) region near the river mouth, modulated by alternating upwelling and downwelling winds. The river plume patterns led to a delayed onset and long duration of contaminants affecting beaches 100 km to the west, days to weeks after the storm. Maps of the onset and duration of hypothetical water quality hazards for a range of weather conditions may provide guidance to managers on the timing of swimming/shellfishing advisories and water quality sampling.

Journal of Geophysical Research: Oceans↗

USGS2023

Effect of wave skewness and asymmetry on the evolution of Fire Island, New York

Bedload transport of sediment by waves and currents is one of the key physical processes that affect the evolution of coasts, nearshore areas, and the engineering practices there. Wave skewness and asymmetry, both of which increase as waves shoal, result in a net bedload sediment flux over a wave cycle. The impacts of this mechanism on large-scale coastal and shoreline change are investigated in this study, using field observations and Coupled Ocean Atmosphere Wave Sediment Transport (COAWST), a hydrodynamic process-based numerical modeling system (Warner et al., 2010). The study site is Fire Island, New York, located at the Atlantic Coast of the USA, with a focus on the persistent shoreline shape, at the western half of this 50-km-long barrier island, that has been hypothesized to be linked to the sand deposits at the shoreface.

Conference Paper↗

USGS2023

Development and application of an Infragravity Wave (InWave) driver to simulate nearshore processes

Infragravity waves are key components of the hydro-sedimentary processes in coastal areas, especially during extreme storms. Accurate modeling of coastal erosion and breaching requires consideration of the effects of infragravity waves. Here, we present InWave, a new infragravity wave driver of the Coupled Ocean-Atmopshere-Waves-Sediment Transport (COAWST) modeling system. InWave computes the spatial and temporal variation of wave energy at the wave group scale and the associated incoming bound infragravity wave. Wave group-varying forces drive free infragravity wave growth and propagation within the hydrodynamic model of the coupled modeling system, which is the Regional Ocean Modeling System (ROMS) in this work. Since ROMS is a three-dimensional model, this coupling allows for the combined formation of undertow currents and infragravity waves. We verified the coupled InWave-ROMS with one idealized test case, one laboratory experiment, and one field experiment. The coupled modeling system correctly reproduced the propagation of gravity wave energy with acceptable numerical dissipation. It also captured the transfer of energy from the gravity band to the infragravity band, and within the different infragravity bands in the surf zone, the measured three-dimensional flow structure, and dune morphological evolution satisfactorily. The idealized case demonstrated that the infragravity wave variance depends on the directional resolution and horizontal grid resolution, which are known challenges with the approach taken here. The addition of InWave to COAWST enables novel investigation of nearshore hydro-sedimentary dynamics driven by infragravity waves using the strengths of the other modeling components, namely the three-dimensional nature of ROMS and the sediment transport routines.

Journal of Advances in Modeling Earth Systems↗

USGS2023

Processes controlling coastal erosion along Cape Cod Bay, MA

Cape Cod Bay, MA, is a semi-enclosed embayment in the northeastern United States, open on the north to the Gulf of Maine. The coastline experiences impacts typically from strong Nor’easter storms that occur in the late fall or winter months, with some sections of this coastline being affected more severely than others. We investigate the processes that cause spatial variability in storm impacts by using geophysical surveys, shoreline-change analysis, and numerical modeling. We simulated the Gulf of Maine and Cape Cod Bay from Jan–April, 2021, using the COAWST modeling system, including ocean, wave, infragravity wave, and sediment transport models. Results identify bay-scale circulation of alongshore sediment fluxes and convergences at regional shoals. Nearshore modeling also revealed zones of increased wave heights that correlate with regions of increased erosion and coastal angle orientation. Modeled and computed shoreline-change have some correlation but the model does not capture all the variability. This overall approach can potentially be used for other coastal locations to identify regions of storm impacts and to manage coastal resources.

Massachusetts↗

USGS2023

Wave asymmetry impacts on sediment processes at the nearshore of Fire Island, New York

Effects of wave asymmetry on sediment processes and coastal evolution were investigated using a field data set and a numerical model. Field observations at the nearshore of Fire Island, New York revealed sediment fluxes during various wave energy levels. The preliminary results indicate a strong correlation between the wave asymmetry and the onshore bedload fluxes. The model results captured the observed hydrodynamics and the sediment processes reasonably well. Ongoing work involves in-depth analysis of the model performance, followed by the evaluation of the nearshore morphodynamics at the island and shelf scales.

New York↗

USGS2023

A numerical investigation of the mechanisms controlling salt intrusion in the Delaware Bay Estuary

Salinity intrusion in coastal systems is mainly controlled by freshwater inflows. However, extreme events like drought, low-pressure storms, and longer-term sea level rise can exacerbate the landward salt migration and threaten economic infrastructure and ecological health. Along the eastern seaboard of the United States, approximately 13 million people rely on the water resources of the Delaware River basin. Salinity intrusion is actively managed through river discharge targets to suppress the propagation of the salt front (∼0.52 daily averaged psu line). The purpose of this study is to examine the mechanisms controlling the location of the salt front in the Delaware Bay estuary using a calibrated three-dimensional hydrodynamic model, the Coupled Ocean Atmosphere Wave and Sediment Transport modeling system. This study explored how river discharge, tidal motions, interactions with bathymetric and topographic features, and meteorological events affected the location of the salt front. The model was forced with tides, subtidal water levels, bulk atmospheric conditions, and waves. Compared with the observationally derived location of the salt front line, the model captured the major dynamics throughout the year and performed particularly well during times of low discharge, when salinity intruded up estuary at a constant rate of 0.4 km /day . The daily average salt front moved almost 16 km (10 mi) within a neap-spring tidal cycle, and low-pressure storm systems were found to move the daily averaged salt front by 13–16 km in one event.

Delaware, New Jersey, Pennsylvania↗

USGS2022

Understanding the role of initial soil moisture and precipitation magnitude in flood forecast using a hydrometeorological modelling system

We adapted the WRF-Hydro modelling system to Hurricane Florence (2018) and performed a series of diagnostic experiments to assess the influence of initial soil moisture and precipitation magnitude on flood simulation over the Cape Fear River basin in the United States. Model results suggest that: (1) The modulation effect of initial soil moisture on the flood peak is non-linear and weakens as precipitation magnitude increases. There is a threshold value of the soil saturation, below and above which the sensitivity of flood peak to the soil moisture differentiates substantially; (2) For model spin-up, streamflow needs longer time to reach the ‘practical’ equilibrium (10%) than the soil moisture and latent heat flux. The model uncertainty from spin-up can propagate through the hydrometeorological modelling chain and get amplified into the flood peak; (3) For ensemble flood modelling with a hydrometeorological system, modelling uncertainty is dominated by the precipitation forecast. Spin-up induced uncertainty can be minimized once the model reaches the ‘practical’ equilibrium.

North Carolina↗

USGS2022

Modeling of barrier breaching during Hurricanes Sandy and Matthew

Physical processes driving barrier island change during storms are important to understand to mitigate coastal hazards and to evaluate conceptual models for barrier evolution. Spatial variations in barrier island topography, landcover characteristics, and nearshore and back-barrier hydrodynamics can yield complex morphological change that requires models of increasing resolution and physical complexity to predict. Using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, we investigated two barrier island breaches that occurred on Fire Island, NY during Hurricane Sandy (2012) and at Matanzas, FL during Hurricane Matthew (2016). The model employed a recently implemented infragravity (IG) wave driver to represent the important effects of IG waves on nearshore water levels and sediment transport. The model simulated breaching and other changes with good skill at both locations, resolving differences in the processes and evolution. The breach simulated at Fire Island was 250 m west of the observed breach, whereas the breach simulated at Matanzas was within 100 m of the observed breach. Implementation of the vegetation module of COAWST to allow three-dimensional drag over dune vegetation at Fire Island improved model skill by decreasing flows across the back-barrier, as opposed to varying bottom roughness that did not positively alter model response. Analysis of breach processes at Matanzas indicated that both far-field and local hydrodynamics influenced breach creation and evolution, including remotely generated waves and surge, but also surge propagation through back-barrier waterways. This work underscores the importance of resolving the complexity of nearshore and back-barrier systems when predicting barrier island change during extreme events.

Florida, New York↗

USGS2022

Impacts of the ocean-atmosphere coupling into the very short range prediction system during the impact of Hurricane Matthew on Cuba

The main goal of this investigation is analyzing the impact of insert the ocean-atmosphere coupling into the very short range prediction system of Cuba. The ocean-atmosphere coupled components of the Coupled Ocean-Atmosphere-Wave-Sediment Transport Modeling System are used for this purpose and the hurricane Matthew is selected as study case. Two experiments are performed: first, using a dynamic sea surface temperature, updated daily in the atmospheric model WRF; and second using adynamic coupling between the atmospheric and an oceanic models. For the simulated track, the best results are obtained with the coupled system. The impact of coupling on the maximum wind velocities and minimum central pressure is studied. In the coupled system the sea surface temperature has more influence in the surface latent heat fluxes. Also, with this methodology the dry footprint and the behavior of the precipitation field in the presence of a hurricane are studied. This analysis shows that the hurricane acts like an open and self-sustained system in the numerical experiments. The highest differences in the precipitation simulations are in the significant convective area inside the hurricane.

Ciência e Natura↗

USGS2022

Shoaling wave shape estimates from field observations and derived bedload sediment rates

The shoaling transformation from generally linear deep-water waves to asymmetric shallow-water waves modifies wave shapes and causes near-bed orbital velocities to become asymmetrical, contributing to net sediment transport. In this work, we used two methods to estimate the asymmetric wave shape from data at three sites. The first method converted wave measurements made at the surface to idealized near-bottom wave-orbital velocities using a set of empirical equations: the “parameterized” waveforms. The second method involved direct measurements of velocities and pressure made near the seabed: the “direct” waveforms. Estimates from the two methods were well correlated at all three sites (Pearson’s correlation coefficient greater than 0.85). Both methods were used to drive bedload-transport calculations that accounted for asymmetric waves, and the results were compared with a traditional excess-stress formulation and field estimates of bedload transport derived from ripple migration rates based on sonar imagery. The cumulative bedload transport from the parameterized waveform was 25% greater than the direct waveform, mainly because the parameterized waveform did not account for negative skewness. Calculated transport rates were comparable to rates estimated from ripple migration except during the largest event, when calculated rates were as much as 100 times greater, which occurred during high period waves.

Florida, Massachusetts, New York↗