Search

The onset of hypoxia is a consequence of the competition between oxygen replenishment, production, and consumption. Dissolved oxygen (DO) levels inside an estuary depend on the balance between physical processes that transport oxygen-rich water into the estuary, including upstream freshwater advection, gravitational circulation, and vertical mixing, and biochemical processes that produce and consume oxygen, such as photosynthesis, respiration, and organic decomposition. We propose a general relationship between the physical and biochemical processes with a Lagrangian perspective to interpolate mean DO concentrations at local and system levels to assess the onset of hypoxia in an estuary. Simple parameters using timescales are proposed for cross-system comparison of hypoxia and anoxia conditions. Our study demonstrates that the hypoxia of an estuary system is determined by the timescales of vertical exchange, freshwater and saltwater transport, and DO consumption. When the vertical exchange timescale is shorter than the residence time in a system, vertical exchange dominates DO replenishment, while shorter residence time enhances advection, which quickly inputs DO-rich water to regulate hypoxia. The interplay between DO consumption and dynamic DO replenishment is the primary determinant of hypoxia in an estuary. [ABSTRACT FROM AUTHOR]

A high‐resolution wave model is crucial for accurate modeling of sediment and organic material transports, but its computational costs hinder direct coupling to an ecosystem model. We developed a machine learning model using long short‐term memory to simulate large‐scale, high‐resolution waves. Trained with numerical wave model (NWM) outputs and wind data from nine locations, our model successfully replicates NWM results for daily mean significant wave height and period in Chesapeake Bay with identical spatial resolution. Compared to the NWM, the data‐driven model has root‐mean‐square errors below 6 cm for daily mean significant wave height and 1 s for the wave period in the bay. It demonstrates excellent model skills and can accurately forecast daily mean significant wave height and period at NOAA wave stations comparable to NWMs. Using minimal wind data and having a short runtime, our data‐driven model shows promise as an alternative for wave forecasting and coupling with sediment and ecological models. Plain Language Summary: Accurately modeling sediment and organic transport necessitates the use of a high‐resolution numerical wave model (NWM). However, the computational expenses of running an NWM within an ecosystem model pose significant challenges. We conducted a study using a machine learning approach based on long short‐term memory to replicate the results of an NWM. The data‐driven wave model (DWM) was trained with the NWM outputs and wind data from nine locations. The trained DWM can replicate the NWM results of daily mean significant wave height and period in Chesapeake Bay with identical spatial resolution and the same predictive skill with a root‐mean‐square error of less than 6 cm and 1 s, respectively for the model domain. The model successfully forecasted daily mean significant wave height and period at NOAA wave stations, showing great forward prediction capability. Notably, the DWM only relied on a minimal amount of wind data from selected locations and had a short runtime. These findings indicate that machine learning is promising as an alternative approach to NWM for wave forecasting. Moreover, it can serve as an alternative wave model and be coupled to ecological models for simulating sediment transport, light attenuation, and resuspension of organic materials. Key Points: A machine learning‐based wave model reproduces the numerical wave model (NWM) results at the same spatial resolution with good accuracyThe data‐driven model, trained on daily significant wave height and period using NWM outputs, has comparable wave prediction skillThe fast‐running data wave model, driven by wind data from nine locations, can forecast waves and couple with sediment and ecological models [ABSTRACT FROM AUTHOR]

In estuarine and coastal systems, anthropogenic activities and directional changes in global air temperatures have led to increased water temperatures, as well as increased frequency and severity of episodic hypoxia. These alterations have had population-level effects on aquatic organisms, including changes in species-specific distributions. Because physiology is the transfer function connecting environmental conditions to individual behaviors and eventually to population-level effects, we used individual-based models (IBMs) that incorporate changes in metabolic scope as motivation for movement. Our objective was to investigate the effects of temperature and hypoxia on the distribution of Atlantic croaker and spot in Chesapeake Bay. We compared the predicted monthly fish distributions from the IBMs with apparent fish distributions recorded by the VIMS Juvenile Fish Trawl Survey during 1988–2014. IBMs failed to reproduce accurately the apparent spatial distributions of Atlantic croaker and spot. More specifically, compared with the trawl survey, IBMs predicted larger proportions of these two species would be captured in the lower regions of Chesapeake Bay and smaller proportions in the York and Rappahannock rivers. We postulate that, because similar thermal and oxygen conditions were occupied by fish in the IBMs and in the wild, temperature may not be the most important factor motivating the movement of Atlantic croaker and spot in Chesapeake Bay, and other spatial factors (e.g., prey availability) act in concert with temperature and hypoxia to determine the spatial distributions of Atlantic croaker and spot in Chesapeake Bay. Alternatively, surveys used to estimate species occurrences could be biased if gear vulnerability is affected by temperature or oxygen conditions (or both). Additional research is needed to clarify which condition is true or if a combination of these factors (and others) led to discrepancies between predicted and apparent fish distributions based on trawl survey data. [ABSTRACT FROM AUTHOR]

We used a numerical model to investigate the effects of sea‐level rise (SLR) on the biogeochemical processes in the York River Estuary with extensive tidal marshes. The fully‐coupled hydrodynamic‐water quality‐marsh model accounts for the spatial and temporal variations of physical‐biogeochemical interactions between the tidal marshes and surrounding waters. This study focuses on an SLR scenario where the vertical accretion of tidal marshes keeps pace with the rising sea levels. Results show that SLR amplifies the tidal range and prolongs flooding duration, which results in enhanced porewater exchanges of materials between the tidal marshes and the surrounding waters. The increased availability of shallow‐water habitats and enhanced light utilization in the shallow areas under SLR promote phytoplankton production (PP) in the shallow‐water regions of the York River. Consequently, the organic carbon in the open water is fueled by the contributions from shallow waters and the enhanced export of organic carbon from the marshes. The change in the dissolved oxygen (DO) budget in the York River Estuary is attributed to changes in water column respiration, net metabolism of the benthic layer, reaeration, PP, and increased stratification under SLR. The net DO flux out of the York River increases at the York River mouth. Diel DO variation, especially in the marshes in the upper estuary, promotes phosphorus release from the sediment. The changes in dissolved nitrogen under SLR are relatively minimal. Plain Language Summary: As one of the consequences of climate change, sea‐level rise (SLR) has a wide‐ranging impact on the estuarine environment. SLR has a significant impact on tidal marshes, which are located at the interface between estuarine water and inner land. Despite the possibility of marsh retreat, many tidal marshes will keep up with the SLR through vertical accretion if sufficient sediment sources are available. SLR will result in deeper water and elevated tidal marshes in the estuary. The biogeochemical processes under this condition were predicted using a numerical modeling approach in this study. The tidal range is estimated to increase, encouraging more material exchange between marshes and estuarine water. More organic carbon is produced in this system, resulting in increased oxygen consumption. In this condition, there is a greater likelihood of low‐DO events occurring during the diel cycle, which will further affect nutrient dynamics. Key Points: A coupled tidal marsh and eutrophication model is applied to study the impacts of sea‐level rise (SLR) on estuarine biogeochemical processesThe tidal marshes that keep up with SLR are predicted to have more porewater‐surface water exchange and dissolved material exportsThe York River Estuary is predicted to have lower bottom dissolved oxygen and more hypoxia events under SLR [ABSTRACT FROM AUTHOR]

In this study, the influence of sea‐level rise (SLR) on seasonal hypoxia and phytoplankton production in Chesapeake Bay is investigated using a 3D unstructured grid model. Three SLR scenarios (0.17, 0.5, and 1.0 m) were conducted from 1991 to 1995. Results show that the summer hypoxic volume (HV) increases about 2%, 8%, and 16%, respectively, for these three scenarios, compared with Base Scenario. The contributions of physical and biological processes on the increase in the HV were analyzed. With the projected SLR, enhanced gravitational circulation transports more oxygen‐rich water in the bottom layer from the mouth. However, the pycnocline moves upwards along with increasing water depth, which largely prolongs the time for dissolved oxygen (DO) to be transported to the bottom. The altered physical processes contribute greatly to a larger HV bay‐wide. Besides, SLR increases the whole Bay phytoplankton production, with a larger increase in shallow areas (e.g., 53% in areas with depth <1 m under SLR of 0.5 m). Enhanced light availability is suggested to be the major driver of blooming phytoplankton under SLR in shallow areas. While increased DO production over the euphotic zone is mostly released to the atmosphere and transported downstream, the increase in settled organic matter greatly promotes DO consumption in the water column. The increased respiration is another major cause of the HV increase besides the physical contributions. [ABSTRACT FROM AUTHOR]

A three‐dimensional unstructured‐grid hydrodynamic and water quality model (Semi‐implicit Cross‐scale Hydroscience Intergrated System Model‐Integrated Compartment Model) is applied successfully for Chesapeake Bay. The model is validated with observations of salinity, chlorophyll‐a, dissolved oxygen, nutrients, and phytoplankton productions from the year 1991 to 1995 for the mainstem and some major tributaries, based on multiple model skill scores. Model experiments are conducted to test the importance of having (1) an accurate representation of bathymetry to correctly predict hypoxia and other processes and (2) a high‐resolution model grid for tributaries to correctly simulate water quality variables. Comparison with the model experiment results with bathymetry smoothing indicates that bathymetry smoothing, as commonly used for many systems, changes the stratification and lateral circulation pattern, resulting in more salt intrusion into shallow water regions, and an increase in the freshwater age. Consequently, a model with bathymetry smoothing can lead to an unrealistic prediction of the distribution of hypoxia and phytoplankton production. Local grid refinement shows significant improvement of model simulations on local stratification and water quality variables. Overall, the use of high‐resolution unstructured grid model leads to a faithful representation of the complex geometry, and thus a seamless cross‐scale capability for simulating water quality processes in the Bay including tributaries and tidal creeks. [ABSTRACT FROM AUTHOR]

Simple mathematical models are derived from mass balances for water and transported substance to provide insight into the relationships between import, export, transport, and internal removal for nonconservative substances in an estuary. Extending previous work, our models explicitly include water and substance inputs from the ocean and are expressed in terms of timescales (i.e., mean residence time and the timescale for net removal). Steady‐state, timescale‐based expressions for ratios of export to import, retention to import, and net export to loading, as well as for loading and annually averaged concentration, are provided. The net export:loading model explains the underlying mechanisms for a well‐known empirical relationship between fractional net export and residence time derived by other authors. Although our simplified models are first‐order approximations, the relative importance of physical and biochemical processes influencing export or retention of a substance can be assessed using mean residence time and the timescale for net removal. Assumptions employed in deriving the simplified models (e.g., well‐mixed, dynamic steady state) may not be met for real estuaries. However, model application to Chesapeake Bay for 1985–2012 demonstrates that interannual variations in total nitrogen (TN) net export:loading can be evaluated, and annual nutrient loadings can be well estimated using numerically modeled time‐varying mean residence time, observation‐based mean concentration, freshwater inflow, and an appropriately estimated removal timescale. Our model shows that net fractional export of TN loading ranges from 0.3 to 0.5 over the 28‐yr period. The models can be employed for other substances and water bodies if the underlying assumptions are applicable. [ABSTRACT FROM AUTHOR]

Accumulation and remineralization of surface‐produced particulate organic matter (POM) in the water column and seabed link closely to hypoxia and the health of aquatic ecosystems. The POM retention time provides a key timescale to interpret biochemical reaction processes. In this study, we investigated the spatiotemporal variations in the vertical particulate age (VPA) of surface‐produced POM, which is the mean time elapsed since the particulates last contact the surface, by incorporating major physical processes including sinking, resuspension, and deposition in the Chesapeake Bay. It was found that the vertical transport time for the particulates (i.e., VPA) is much longer than the dissolved counterparts as the former consists of new material from the surface and the resuspended aged material that has elongated resting on the seabed after deposition. The VPA is sensitive to settling velocity, especially in low‐frequent resuspension environments, and varies over 2 orders of magnitude with settling velocity from 0 to 10 m/day. Slow‐sinking material can remain in suspension and seldom settle to the seabed, thus mainly contribute to pelagic processes, while the fast‐sinking material connects closely with benthic processes. The seasonality of VPA decreases as the settling velocity increases. No significant difference in VPA was found between wet and dry years, yet the episodic strong flood events entrain old materials from the depositional lateral shoals to increase VPA in the channel. The transport age bridges cross disciplinaries by providing the fourth‐dimensional age information as a common currency to compare the physical transport timescale with the timescales for biochemical reactions. Plain Language Summary: The Chesapeake Bay is a highly productive estuary, characterized by spring phytoplankton blooms and subsequent accumulations of particulate organic matter (POM) in the bottom layer, which fuels summertime hypoxia. The retention time of POM provides an important timescale to interpret biochemical reactions in estuaries. In this study, we applied the vertical particulate age (VPA), the average time elapsed since the POM leaving the surface, to estimate the downward‐transport time. The VPA accounts for all possible trajectories, including direct sinking and interactions with the seabed via resuspension and deposition. It was found that the VPA is much longer than the vertical transport time for dissolved material due to the elongated resting of particulates on the seabed and contributions from the resuspended old material. The VPA is sensitive to the settling velocity and increases 2 orders of magnitude with the settling velocity from 0 to 10 m/day in less dynamic environments. The slow‐sinking material can remain in suspension while the fast‐sinking material mostly stays on the seabed. No significant difference in the VPA was found between wet and dry years except during the episodic freshwater pulse, which brought aged materials from the depositional shoals to increase the VPA in the channel. Key Points: The vertical particulate age (VPA) explains the time lag between the springtime algae blooms and the summertime hypoxia in the bayLong resting of particulates on the seabed and resuspension of the aged seabed material largely elongate the VPA in the water columnThe VPA is sensitive to settling velocity and episodic freshwater pulse. The latter entrains old material from shoals to the deep channel [ABSTRACT FROM AUTHOR]

Most estuaries are characterized by non‐uniform axial topography with shallow shoals near the mouth. Previous studies have addressed the impacts of the axial topographic variations on mixing and estuarine circulations yet seldom on material transport and retention. This study investigates the longitudinal structure and mechanisms of exchange flow and material transport of Chesapeake Bay (CB), featuring a shallow sill in the lower bay, by applying total exchange flow (TEF) algorithm, tracer experiments, and partial residence time (PRT) using a validated 32‐years numerical model simulation. A retention coefficient was adopted to quantify the material retention rate using two characteristic PRTs: with and without incorporating water parcels returning to a concerned region. It is found that shoaling from the Rappahannock Shoal to the mouth causes persistent downwelling, strong reflux, and the highest material retention rate in the middle of the bay. The gravitational circulation and the river outflow dominate the transport of salt and riverine dissolved materials (RDMs), whereas the contribution of the tidal oscillatory process is localized near the mouth. The dominance of river outflow over the gravitational circulation for transporting RDMs is confined within the upper bay, where PRTs exhibit distinct seasonality. PRTs show small seasonality in the middle to the lower bay controlled by the exchange flow. The present analysis combining TEF, efflux/reflux theory, and PRT is applicable to other coastal aquatic ecosystems to characterize the water exchange and renewal efficiency along the salinity gradient and understand the contributions of transport to biogeochemical processes. Plain Language Summary: Chesapeake Bay (CB) is the largest estuary in the United States, with a major deep channel indented by a shallow sill in the lower bay. The longitudinal topography of CB can be characterized as "Shallow‐Deep‐Shallow." Previous studies in other estuaries addressed the impact of the axial topographic variations on estuarine hydrodynamics yet seldom on material transport and retention, such as the retention time of organic matter, an important indicator for hypoxia issue. This study examines how the particular longitudinal topography affects the transport of salt (from the coastal ocean) and riverine dissolved materials (RDMs, from the river) by using a 32‐years numerical model simulation. We find that the shallow sill will obviously increase the retention time of RDMs upstream of the shoal, mainly because the abrupt shoaling near the shoal results in strong mixing and reflux of the surface outflow, associated with the surface velocity convergence and resultant downwelling. Exchange flow (i.e., surface outflow and bottom inflow) and river outflow dominate the transports of salt and RDMs in CB, whereas the contribution from the tidal process is localized near the mouth. It is also found the shallow sill will not block the exchange flow, which increases monotonically toward downstream. Key Points: Density‐driven exchange flow and river outflow dominate the salt and riverine dissolved material transport in Chesapeake BayRiver outflow dominates the transport of riverine dissolved materials upstream, while exchange flow dominates the transport downstreamRapid seaward shoaling causes strong reflux that increases material retention in the middle of the bay [ABSTRACT FROM AUTHOR]

Despite global investment in shellfish restoration activities, relatively little attention has been given to predicting optimal restoration sites and testing these expectations. We used a coupled biological-physical connectivity model as a guide to plant two distinct hatchery-spawned strains of the eastern oyster, Crassostrea virginica, in the Lafayette River, Virginia during the summer of 2013 at two locations corresponding to virtual spawning locations within the connectivity model. We utilized single nucleotide polymorphism markers to test the model predictions by genotyping oysters recruited after planting two hatchery-spawned strains and examining interannual recruitment variability for two successive years. Two spat were identified as hybrids of one of the planted strains and resident oyster genotypes. We also observed a genetic influence from an oyster strain used previously for restoration. Differences in environmental conditions between the two years of monitored recruitment likely affected larval dispersal and survival, contributing to observed interannual differences in the newly recruiting cohorts. Oyster spat from 2013 were genetically more similar to resident adults sampled in the Lafayette River, while the 2014 spat exhibited genotypic frequencies more similar to adults from surrounding rivers. The winds during the spawning seasons differed between years providing conditions for retention in 2013 and mixing of water masses in 2014. We recommend that the monitoring of restoration activities should consider relevant environmental conditions and observe multiple years of recruitment to assess the genetic impacts of restoration plantings and variable reproductive success. [ABSTRACT FROM AUTHOR]

There are increasing concerns about the impact of worsened physical condition on hypoxia in a variety of coastal systems, especially considering the influence of changing climate. In this study, an EOF analysis of the DO data for 1985–2012, a long-term numerical simulation of vertical exchange, and statistical analysis were applied to understand the underlying mechanisms for the variation of DO condition in Chesapeake Bay. Three types of analysis consistently demonstrated that both biological and physical conditions contribute equally to seasonal and interannual variations of the hypoxic condition in Chesapeake Bay. We found the physical condition (vertical exchange + temperature) determines the spatial and seasonal pattern of the hypoxia in Chesapeake Bay. The EOF analysis showed that the first mode, which was highly related to the physical forcings and correlated with the summer hypoxia volume, can be well explained by seasonal and interannual variations of physical variables and biological activities, while the second mode is significantly correlated with the estuarine circulation and river discharge. The weakened vertical exchange and increased water temperature since the 1980s demonstrated a worsened physical condition over the past few decades. Under changing climate (e.g., warming, accelerated sea-level rise, altered precipitation and wind patterns), Chesapeake Bay is likely to experience a worsened physical condition, which will amplify the negative impact of anthropogenic inputs on eutrophication and consequently require more efforts for nutrient reduction to improve the water quality condition in Chesapeake Bay. [ABSTRACT FROM AUTHOR]

Concerns have grown over the increase of nutrients and pollutants discharged into the estuaries and coastal seas. The retention and export of these materials inside a system depends on the residence time (RT). A long-term simulation of time-varying RT of the Chesapeake Bay was conducted over the period from 1980 to 2012. The 33-year simulation results show that the mean RT of the entire Chesapeake Bay system ranges from 110 to 264 days, with an average value of 180 days. The RT was larger in the bottom layers than in the surface layers due to the persistent stratification and estuarine circulation. A clear seasonal cycle of RT was found, with a much smaller RT in winter than in summer, indicating materials discharged in winter would be quickly transported out of the estuary due to the winter-spring high flow. Large interannual variability of the RT was highly correlated with the variability of river discharge (R 2 = 0.92). The monthly variability of RT can be partially attributed to the variability of estuarine circulation. A strengthened estuarine circulation results in a larger bottom influx and thus reduces the RT. Wind exerts a significant impact on the RT. The upstream wind is more important in controlling the lateral pattern of RT in the mainstem. [ABSTRACT FROM AUTHOR]

Chlorophyll-a (Chl-a) concentration indicates the abundance of phytoplankton biomass and its spatiotemporal variations fundamentally modulate the ecosystem dynamics in coastal waters. Compared to conventional low-frequency shipboard measurements at a limited number of sampling locations, satellite data provide a better spatial and temporal coverage allowing for a more synoptic view of Chl-a variabilities in large coastal systems such as Chesapeake Bay. We used Visible Infrared Imaging Radiometer Suite (VIIRS) satellite data from 2011 to 2018 to (1) analyze the Chl-a variability in Chesapeake Bay, (2) examine the robustness of an interpolation method to fill up satellite data gaps, and (3) train a machine-learning-based data-driven model to simulate high-resolution Chl-a variations. The dataset shows clear seasonality with notable spring and summer peaks throughout the bay; this is different from in situ observations at mainstem stations where the water is deep. The seasonality of Chl-a varies in different regions, with maxima concentration occurring in spring for regions near the mouths of major tributaries, winter near the bay entrance, and summer elsewhere. A machine-learning-based data-driven model, together with Data Interpolating Empirical Orthogonal Functions (DINEOF), is applied to simulate the high-resolution Chl-a variations. The DINEOF is used to efficiently estimate the missing records. Driven by external forcing including river discharge, nutrient loadings, solar radiation, wind, and air temperature, the data-driven model shows an overall satisfactory performance in reproducing the spatiotemporal variations of Chl-a, with a bay-wide averaged root mean square error of 1.85 ug/l. By combining DINEOF and machine learning, this study demonstrates the potential of using data-driven model to predict high-resolution spatiotemporal variations of water quality in coastal waters. • Satellite data reveal large spatiotemporal variability of Chl-a in Chesapeake Bay. • Summer peak of Chl-a is shown in the satellite data that has not been fully recognized in in situ surveys. • High resolution simulation of water quality is achievable with a data-driven model. [ABSTRACT FROM AUTHOR]

As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and biogeochemical complexity. To this end, 2-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratification, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen parameterizations, in contrast to the more complex full biogeochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesapeake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density gradient. [ABSTRACT FROM AUTHOR]

Abstract: Understanding the changes of hydrodynamics in estuaries with respect to magnitudes of sea-level rise is important to understanding the changes of biogeochemical processes that are coupled tightly with the physical processes. Based on the 21st century sea-level rise scenarios projected by the U.S. Climate Change Science Program (), the Chesapeake Bay was chosen as a prototype to study the responses of the estuary to potential future sea-level rise. The numerical model results show that the average salt content, salt intrusion length, and stratification will increase as sea level rises. The changes of these parameters have obvious seasonal and inter-annual variations. Both the salt content and stratification show more increase in spring (following the high-flow periods) and wet years than in autumn (following the low-flow periods) and dry years. The salt intrusion length has larger increase and greater standard deviation in autumn than in spring. The transport time scales are used to illustrate the variations of transport processes as sea level rises, and results indicate that (1) the exchange flow would be strengthened but the downstream transport of fresh water would be slower; (2) the residence time of the Bay would increase due to the increased volume and change of circulation; (3) the vertical transport time (reference to water surface) has more pronounced increase and the volume of water mass with different age groups increases with different rates. As a result, the retention time of dissolved substances in the Bay would increase. Although the increased tidal currents would strengthen the vertical mixing, the increased stratification would weaken the vertical exchange. The increase of vertical transport time is due to the impact of stratification changes, which overwhelms the impact of tidal changes. As the bottom dissolved oxygen (DO) supply is predominated by the vertical exchanges in the Chesapeake Bay, the increased upstream transport time has a weak impact on hypoxia conditions in the middle and upper portions of the Bay. The weakened vertical exchange would result in less DO supply from the surface to the bottom layer. [Copyright &y& Elsevier]

Massive blooms of the harmful alga Cochlodinium polykrikoides Margalef occurred in the lower Chesapeake Bay and its tributaries during the summers of 2007 and 2008. The Lafayette and Elizabeth Rivers appeared to act as initiation grounds for these blooms during both years. However, in 2008 there were also localized sites of initiation and growth of populations within the mesohaline portion of the James River. Bloom initiation appeared to be correlated with intense, highly localized rainfall events during neap tides. Subsequent spring tides increased tidal flushing and transport of C. polykrikoides from the Lafayette and Elizabeth Rivers into the lower James River where it was transported upriver by local estuarine circulation. Blooms dissipated in response to increased wind-driven mixing associated with frontal systems moving through the region. A combination of physical factors including, seasonal rainfall patterns, increased stratification, nutrient loading, spring-neap tidal modulation, and complex estuarine mixing and circulation allowed C. polykrikoides to spread and form massive blooms over large portions of the tidal James River and the lower Chesapeake Bay. [ABSTRACT FROM AUTHOR]

Abstract: Tropical Cyclone Isabel of 2003 generated large storm surge, strong waves, and subsequent river flooding in the York River Estuary, USA during its passage across the Chesapeake Bay region. A 3D model was used to investigate the changes of sediment concentration, sediment flux, and the recovery time of the York River Estuary to its naturally evolved condition without the storm. The results showed that two sediment concentration peaks appeared during the storm event. The first one was induced by the large upstream flow and waves during the storm surge rising period, and the later one was caused by the strong downstream flow during the descent of the storm surge. The advection, which was induced by the barotropic gradient, dominated the sediment flux during the storm event. The sediment fluxes increased by a factor of 100 during the rise and descent of the storm surge. A large amount of sediment that was transported into the estuary and eroded from the seabed during the rising of the storm surge was quickly transported out of the estuary during the descent of the storm surge. Waves played a key role in stirring the seabed and increasing the sediment concentration during the storm. Subsequent high freshwater inflow changed the sediment loading and hydrodynamics in the estuary, and thus, influenced the estuarine turbidity maximum (ETM) dynamics profoundly. The ETM moved downstream with the river flooding initially and returned upstream with the waning of river flooding and the re-establishment of gravitational circulation. The effect of river flooding on sediment concentration varied spatially and depended on the changes of ETM locations and vertical mixing. The model results suggest that a large amount of sediment was transported out of the estuary during the storm event and the subsequent river flooding had a larger impact on recovery time of the estuary. [Copyright &y& Elsevier]

Abstract: The Chesapeake Bay is vulnerable to severe flooding caused by hurricanes and strong Northeasters. A 3D storm surge model of the Chesapeake Bay is developed for studying the impact of model domain size, wind directions and Ekman transport on the storm surge in the Chesapeake Bay. The model encompasses the Chesapeake Bay and the US East Coast shelf to reduce the influence of model domain size on surge prediction inside the Chesapeake Bay and to account for both local and remote wind effects. This study used 3D model experiments, with respect to different wind directions, to diagnose the relative influences of the local and remote wind effects and Ekman transport on spatial surge distribution during storm events. The model results confirmed that spatial surge distribution can be well explained by the superposition of two distinct physically driven mechanisms during a storm event: incoming surge wave caused by remote effects and local wind forcings. A large model domain is a necessity for predicting storm surge accurately inside the Chesapeake Bay. The model results suggest that the interactions of the incoming surge propagating into the Bay and the local wind forcing from N and NE directions result in an enhanced setup in the lower to middle portions of the Bay, whereas the superposition of incoming surge and the local wind forcing from S and SE directions enhance the surge in the upper Bay region. A combined northwesterly wind over the middle to upper portions of the Bay and southwesterly wind over the lower Bay can cause a large setdown throughout the entire Bay. The Ekman setup along the coast contributes significantly to the water level variations during storm events. It enhances (reduces) surge inside the Bay under the wind forcings from N and NE (SW, S, and SE) directions. [Copyright &y& Elsevier]

Transport rate, as a scale complementary to commonly used transport timescales, is useful for quantifying local transport conditions in estuarine and coastal systems. A specific transport rate computed based on tracer release is highlighted for quantifying the local transport condition for long-standing autochthonous constituents originating from the system. The overall flushing capability of the constituents can be quantified by the material turnover time, an analog of turnover time, which can be conveniently computed using transport rate. The transport rate is computed in the James River, a tributary of Chesapeake Bay, U.S.A., which clearly describes the temporal and spatial variations of local transport conditions and provides an example to evaluate the contribution of physical transport to variations in phytoplankton biomass. The transport rate can also be used to diagnose the relative importance of physical transport against other environmental factors to the dynamics of reactive autochthonous constituents. Given the advantages, the transport rate provides an efficient tool for diagnosing local transport conditions modulating dynamics of autochthonous constituents in estuarine and coastal systems. • Transport rate is a useful local indicator complementary to transport timescales. • We highlight a transport rate computed efficiently using tracer release methods. • It quantifies local transport conditions varied by the hydrodynamic field only. • Describes both "transport out" and "transport in" processes over short time scales. • Applies to long-standing autochthonous constituents in estuarine and coastal systems. [ABSTRACT FROM AUTHOR]

• A numerical HAB module for margalefidinium polykrikoides was developed. • The module was coupled with a 3D physical-biogeochemical model for the James River. • Behavioral and life cycle strategies contributed significantly to bloom development. • Heterotrophy contributed as important as photoautotrophy to the growth. • Temperature, physical transport, and cyst germination determined the interannual variability in bloom timing. Blooms of Margalefidinium (previously Cochlodinium) polykrikoides occur almost annually in summer in the lower Chesapeake Bay and its tributaries (e.g., the James and York Rivers). The Lafayette River, a sub-tributary of the lower James River, has been recognized as an initiation location for blooms in this region. The timing of bloom initiation varies interannually, ranging from late June to early August. To fully understand critical environmental factors controlling bloom initiation and interactions between physical and biological processes, a numerical module simulating M. polykrikoides blooms was developed with a focus on the bloom initiation. The module also includes life cycle and behavioral strategies such as mixotrophy, vertical migration, cyst dynamics and grazing suppression. Parameterizations for these behaviors were assigned based on published laboratory culture experiments. The module was coupled with a 3D physical-biogeochemical model for the James River that examined the contribution of each environmental factor and behavioral strategy to bloom initiation and development. Model simulation results highlight the importance of mixotrophy in maintaining high growth rates for M. polykrikoides in this region. Model results suggest that while many factors contribute to the initiation process, temperature, physical transport processes, and cyst germination are the three dominant factors controlling the interannual variability in the timing of bloom initiation. [ABSTRACT FROM AUTHOR]

Pathogen, whose abundance is often measured by the concentration of fecal indicator bacteria, is listed as the top cause of waterbody impairments in the US. An accurate estimation of the bacterial loading from watershed is thus fundamentally important for water quality management. Despite advances in watershed modeling, accurate estimation of bacterial load is still very challenging due to large uncertainties associated with bacterial sources, accumulation, and removal in the watershed. We introduce an inverse method using field-measured bacterial concentrations and numerical model-calculated residence time to estimate the bacterial loading from the drainage basin. In this method, an estuary is divided into multiple segments. Water and bacterial fluxes between neighboring segments are computed from a set of linear equations derived based on mass balance equation and the relationship between residence time and water fluxes. Loading to each segment can then be estimated by combining the computed water fluxes and observed bacterial concentrations. The approach accounts for seasonal and interannual variations in hydrodynamics due to tide, river discharge, and estuarine circulations. The method was applied to Nassawadox Creek, a sub-estuary of Chesapeake Bay, where Fecal Coliform concentrations at 46 stations were continuously monitored. The method is verified by the high consistency between estimated loadings and presumably known input loadings in numerical experiments with either constant or time-varying input loadings. With sparse observational data, the inversely estimated loadings agree well with the loadings from a previously calibrated watershed model, demonstrating the reliability of the method. The inverse approach can be used to cross-check the result of watershed models and assess changes in watershed condition. The method is also readily applicable to other types of materials, such as inorganic nutrients. • An inverse approach to estimate bacterial loading is introduced. • The method use measured bacterial concentrations and computed residence time. • The required segmentation is flexible compared to traditional tidal-prism methods. • The method is validated by an application in a sub-estuary of Chesapeake Bay. [ABSTRACT FROM AUTHOR]

Water exchange, featured by bottom inflow and surface outflow in a typical estuary, determines the transport and redistribution of salt, nutrients, pollutants, and suspended sediments and organisms. Water exchange in Chesapeake Bay, the largest estuary in the US, has been extensively studied, yet its long-term interannual variability and its relationship with the external forcings are not fully understood. Based on a long-term (1980–2011) numerical model simulation, this study examines the water exchanges between Chesapeake Bay and the adjacent coastal shelf, between different regions within the bay, as well as their relationships with river discharge, wind, and residence time. Through an EOF analysis of the bottom inflow and surface outflow at seven selected cross-bay sections, we found that over 90% of the spatiotemporal variations of water exchange can be explained by the first two EOF modes, which are highly correlated with the freshwater discharge and northwesterly wind, respectively. Unlike the outflow that increases linearly with river discharge as commonly expected, the inflow responds non-monotonically to river discharge. The relationship between the river discharge and inflow can be described by a combination of the Michaelis–Menten/Monod equation and a linearly decreasing function, i.e., the inflow initially increases with river discharge due to enhanced gravitational circulation and then levels, and gradually declines due to overwhelming seaward barotropic current. We found a locally enhanced water exchange in the lower-middle bay, which can be attributed to the persistent reflux of surface outflow due to the irregular geometry and rapid shoaling in the channel bathymetry. The water exchange and the mean residence time can be connected reciprocally through the bay volume, yet the validation of this relationship depends on the timescale to be considered since the residence time at a given time is controlled by the future hydrodynamics. A delay effect should be considered when using the relationship to estimate outflow interchangeably with the direct computation of the outflow. • Reflux contributes significantly to the water exchange in the lower bay. • River discharge and down-estuary wind dominate the water exchange in the bay. • Bottom inflow responds non-monotonically to the river discharge. • Water exchanges in the lower/upper bay respond oppositely to the down-estuary wind. • The time-lag effect should be considered to estimate the residence time by V/ Q out. [ABSTRACT FROM AUTHOR]

Phytoplankton biomass, indicated by chlorophyll-a (Chl-a) concentration, is fundamentally important for aquatic ecosystems. However, accurately simulating Chl-a is always challenging even when using state-of-the-art numerical models. We propose a data-driven modeling framework that combines Empirical Orthogonal Function (EOF) analysis and machine-learning technique to tackle this problem, using Chesapeake Bay as an example. Through the dimension reduction using EOF, the three-dimensional (3D) problem can be decomposed into multiple one-dimensional (1D) problems. The non-linearity of these 1D problems will be modeled with machine learning using an artificial neural network. Model performance in terms of spatiotemporal Chl-a variations with both seasonal and interannual signals is evaluated. The model performance is comparable or higher than 3D numerical models previously applied in Chesapeake Bay. Sensitivity tests reveal the necessity of forcing transformations to improve the model predictive skill. Instead of manually applying a transformation for each input forcing variable, an auto-selection procedure is adopted to choose an appropriate transformation from a variety of transformation options. While it is unlikely the data-approach can replace the traditional numerical models, we argue that data-driven approaches provide a promising way for future studies in coastal and estuarine systems considering the fast accumulation of observational data. • A data-driven model combining EOF analysis and a neural network is proposed. • It converts a 3D problem into multiple 1D problems. • Auto-selection of forcing transformation is added to improve the model performance. • Application for chlorophyll-a in Chesapeake Bay shows good performance. • Data-driven model is a promising tool for future coastal water quality simulations. [ABSTRACT FROM AUTHOR]

Global sea level is rising, and the relative rate in the Chesapeake Bay region of the East Coast of the United States is greater than the worldwide rate. Sea-level rise can cause saline water to migrate upstream in estuaries and rivers, threatening freshwater habitat and drinking-water supplies. The effects of future sea-level rise on two tributaries of Chesapeake Bay, the James and Chickahominy (CHK) Rivers, were evaluated in order to quantify the salinity change with respect to the magnitude of sea-level rise. Such changes are critical to: 1) local floral and faunal habitats that have limited tolerance ranges to salinity; and 2) a drinking-water supply for the City of Newport News, Virginia. By using the three-dimensional Hydrodynamic-Eutrophication Model (HEM-3D), sea-level rise scenarios of 30, 50, and 100 cm, based on the U.S. Climate Change Science Program for the mid-Atlantic region for the 21st century, were evaluated. The model results indicate that salinity increases in the entire river as sea level rises and that the salinity increase in a dry year is greater than that in a typical year. In the James River, the salinity increase in the middle-to-upper river (from 25 to 50 km upstream of the mouth) is larger than that in the lower and upper parts of the river. The maximum mean salinity increase would be 2 and 4 ppt for a sea-level rise of 50 and 100 cm, respectively. The upstream movement of the 10 ppt isohaline is much larger than the 5 and 20 ppt isohalines. The volume of water with salinity between 10 and 20 ppt would increase greatly if sea level rises 100 cm. In the CHK River, with a sea-level rise of 100 cm, the mean salinity at the drinking-water intake 34 km upstream of the mouth would be about 3 ppt in a typical year and greater than 5 ppt in a dry year, both far in excess of the U.S. Environmental Protection Agency''s secondary standard for total dissolved solids for drinking water. At the drinking-water intake, the number of days of salinity greater than 0.1 ppt increases with increasing sea-level rise; during a dry year, 0.1 ppt would be exceeded for more than 100 days with as small a rise as 30 cm. [Copyright &y& Elsevier]

Abstract: The response of Chesapeake Bay to forcing from two hurricanes is investigated using an unstructured-grid three-dimensional hydrodynamic model SELFE. The model domain includes Chesapeake Bay, its tributaries, and the extended continental shelf in the mid-Atlantic Bight. The hurricanes chosen for the study are Hurricane Floyd (1999) and Hurricane Isabel (2003), both of which made landfall within 100km of the mouth of the Bay. The model results agree reasonably well with field observations of water level, velocity, and salinity. From the Bay’s water level response to the hurricanes, it was found that the storm surge in the Bay has two distinct stages: an initial stage set up by the remote winds and the second stage – a primary surge induced by the local winds. For the initial stage, the rising of the coastal sea level was setup by the remote wind of both hurricanes similarly, but for the second stage, the responses to the two hurricanes’ local winds are significantly different. Hurricane Floyd was followed by down-Bay winds that canceled the initial setup and caused a set-down from the upper Bay. Hurricane Isabel, on the other hand, was followed by up-Bay winds, which reinforced the initial setup and continued to rise up against the head of the Bay. From the perspective of volume and salt fluxes, it is evident that an oceanic saltwater influx is pushed into the Bay from the continental shelf by the remote wind fields in the initial stages of the storm surge for both Floyd and Isabel. In the second stage after the hurricane made landfall, the Bay’s local wind plays a key role in modulating the salinity and velocity fields through vertical mixing and longitudinal salt transport. Controlled numerical experiments are conducted in order to identify and differentiate the roles played by the local wind in stratified and destratified conditions. Down-estuary local wind stress (of Hurricane Floyd-type) tends to enhance stratification under moderate winds, but exhibits an increasing-then-decreasing stage when the wind stress increases. The up-estuary local wind stress (of Hurricane Isabel-type) tends to penetrate deeper into the water column, which reduces stratification by reversing gravitational circulation. To characterize mixing conditions in the estuary, a modified horizontal Richardson number that incorporates wind stress, wind direction, horizontal salinity gradient, and vertical eddy viscosity is used for both hurricanes. Finally, the direct precipitation of rainfall into the Bay during Hurricane Floyd appears to create not only a thin surface layer of low salinity but also a seaward barotropic pressure gradient that affects the subsequent redistribution of salinity after the storm. [Copyright &y& Elsevier]

Abstract: Understanding the dynamics of water exchange between Baltimore Harbor and the Chesapeake Bay is essential when evaluating transport and fate of dissolved substances in both of these systems. Conservative artificial tracers are used in this study to investigate transport processes through a three-dimensional hydrodynamic model (CH3D). The model well reproduced the three-layered circulation pattern in Baltimore Harbor. Several numerical experiments are performed to trace the water mass coming from different sources. The results indicate that both the upper and lower layers of the Harbor are the dominant pathways of transporting dissolved substances from Susquehanna River to the Harbor. Such inward transport is intensified (suppressed) during the high-discharge (low-discharge) period. The upper layer inflow transports water mass with high concentrations of dissolved substances while the inflow from the lower layer transports water mass with low concentrations of dissolved substances. The bottom layer is the dominant pathway for transporting dissolved substances from the lower Bay to the Harbor. Lower river discharge and stronger along-Bay pressure gradient (resulting in stronger landward residual flow in the bottom layer of the Bay) facilitate the bottom intrusion of dissolved substances from lower Bay to the Harbor. Once contaminants are transported into the Harbor, they usually stay for a longer time in the mid-depth of the Harbor than those in other layers due to the three-layer circulation in the Harbor. The time needed for the contaminants being transported out of the Harbor during a typical low-discharge period is about 1 month longer than that needed during a typical high-discharge period. The results, from the environmental perspective, provide new insights for quantitative evaluation on the transport processes of the dissolved biogeochemical substances between Baltimore Harbor and Chesapeake Bay. [Copyright &y& Elsevier]

We extend the 3D unstructured-grid model previously developed for the Upper Chesapeake Bay to cover the entire Bay and its adjacent shelf, and assess its skill in simulating saltwater intrusion and the coastal plume. Recently developed techniques, including a flexible vertical grid system and a 2nd-order, monotone and implicit transport solver are critical in successfully capturing the baroclinic responses. Most importantly, good accuracy is achieved through an accurate representation of the underlying bathymetry, without any smoothing. The model in general exhibits a good skill for all hydrodynamic variables: the averaged root-mean-square errors (RMSE's) in the Bay are 9 cm for sub-tidal frequency elevation, 17 cm/s for 3D velocity time series, 1.5 PSU and 1.9 PSU for surface and bottom salinity respectively, 1.1   °C and 1.6   °C for surface and bottom temperature respectively. On the shelf, the average RMSE for the surface temperature is 1.4   °C. We highlight, through results from sensitivity tests, the central role played by bathymetry in this estuarine system and the detrimental effects, from a common class of bathymetry smoothers, on volumetric and tracer fluxes as well as key processes such as the channel-shoal contrast in the estuary and plume propagation in the coast. [ABSTRACT FROM AUTHOR]

We develop a new vertically implicit transport solver, based on two total variation diminishing (TVD) limiters in space and time, inside a 3D unstructured-grid model (SCHISM), and apply it to the Upper Chesapeake Bay (UCB), which has complex geometry and sharp pycnocline. We show that the model is able to accurately and efficiently capture the elevation, velocity, salinity and temperature in both the deep and shallow regions of UCB. Compared with all available CTD casts, the overall model skills have the mean absolute error of 1.08 PSU and 0.85 °C, and correlation coefficient of 0.97 and 0.99 for salinity and temperature respectively. More importantly, the new implicit solver better captures the density stratification, which has great implications on biogeochemistry in this estuarine system. The cross-scale capability of the model is demonstrated by extending the high-resolution grids into a tributary (Chester River) and its sub-tributary (Corsica River), with minimal impact on the model efficiency. The model is also able to capture complex 3D structures at the transition zone between the main bay and the tributary, including the three-layered circulation in Baltimore Harbor. As more and more attention is being paid to the productive shallows in the Chesapeake Bay and other estuaries, the model can serve as a very powerful management tool to understand the impact of both local and remote forcing functions. [ABSTRACT FROM AUTHOR]