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AmeriFlux FLUXNET-1F US-UC1 LTAR UCB (Upper Chesapeake Bay) EC1
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UC1 LTAR UCB (Upper Chesapeake Bay) EC1. This is the FLUXNET version of the carbon flux data for the site US-UC1 LTAR UCB (Upper Chesapeake Bay) EC1 produced by applying the standard ONEFlux (1F) software. Site Description - Upper Chesapeake Bay farm is privately owned. The farming that took place was performed by the Farm Owner. The ground is rolling terrain, next to wooded areas, private resdiences and other large fields maintained by private land owners. At the time of this collection period, the site housed another Eddy Covariance System and a two Phenocams. Crop has been continuous corn with plans to rotate to alfalfa grass mixture.
AmeriFlux FLUXNET-1F US-UC2 LTAR UCB (Upper Chesapeake Bay) EC2
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UC2 LTAR UCB (Upper Chesapeake Bay) EC2. This is the FLUXNET version of the carbon flux data for the site US-UC2 LTAR UCB (Upper Chesapeake Bay) EC2 produced by applying the standard ONEFlux (1F) software. Site Description - Upper Chesapeake Bay farm is privately owned. The farming that took place was performed by the Farm Owner. The ground is rolling terrain, next to wooded areas, private resdiences and other large fields maintained by private land owners. At the time of this collection period, the site housed another Eddy Covariance System and a two Phenocams. Crop has been continuous corn with plans to rotate to alfalfa grass mixture.
AmeriFlux US-UC1 LTAR UCB (Upper Chesapeake Bay) EC1
This is the AmeriFlux version of the carbon flux data for the site US-UC1 LTAR UCB (Upper Chesapeake Bay) EC1. Site Description - Upper Chesapeake Bay farm is privately owned. The farming that took place was performed by the Farm Owner. The ground is rolling terrain, next to wooded areas, private resdiences and other large fields maintained by private land owners. At the time of this collection period, the site housed another Eddy Covariance System and a two Phenocams. Crop has been continuous corn with plans to rotate to alfalfa grass mixture.
AmeriFlux US-UC2 LTAR UCB (Upper Chesapeake Bay) EC2
This is the AmeriFlux version of the carbon flux data for the site US-UC2 LTAR UCB (Upper Chesapeake Bay) EC2. Site Description - Upper Chesapeake Bay farm is privately owned. The farming that took place was performed by the Farm Owner. The ground is rolling terrain, next to wooded areas, private resdiences and other large fields maintained by private land owners. At the time of this collection period, the site housed another Eddy Covariance System and a two Phenocams. Crop has been continuous corn with plans to rotate to alfalfa grass mixture.
Climate Extremes and Variability Surrounding Chesapeake Bay: Past, Present, and Future
Measures of extreme climate variability around Chesapeake Bay have changed over the past century (1895–2014), resulting in the need to establish new baselines for understanding future change. Here, observed climate variability is compared with Coupled Model Intercomparison Project fifth assessment climate models to evaluate ensemble model skill in this region. Observed trends include annual and seasonal declines in the percentage of cold days. Similarly, increases in the annual and seasonal percentages of warm days occurred in all seasons of the North Chesapeake (>38.2°N) but were only significant in spring and summer in the South (<38.2°N) demonstrating regional differences even at local scales. Precipitation intensity increased over the past century. Models using emissions scenarios RCP4.5 and 8.5 project these trends will continue, though they have little skill in precipitation extremes. Pacific and Atlantic climate modes are generally more correlated with climate extremes than mean temperature and precipitation suggesting potential predictability in the synoptic patterns underlying the extremes. However, they also drive the need for time series at least 60-years long for establishing climate trends. This local analysis differs from regional, state level, and local 2.5° × 3.75° grid analyses, highlighting the importance of local climate assessments that consider topographic and regional weather patterns.
Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework
Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program’s (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States’ largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework’s current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.
Simulation of high-frequency dissolved oxygen dynamics in a shallow estuary, the Corsica River, Chesapeake Bay
Understanding shallow water biogeochemical dynamics is a challenge in coastal regions, due to the presence of highly variable land-water interface fluxes, tight coupling with sediment processes, tidal dynamics, and diurnal variability in biogeochemical processes. While the deployment of continuous monitoring devices has improved our understanding of high-frequency (12 - 24 hours) variability and spatial heterogeneity in shallow regions, mechanistic modeling of these dynamics has lagged behind conceptual and empirical models. The inherent complexity of shallow water systems is represented in the Corsica River estuary, a small basin within the Chesapeake Bay ecosystem, where abundant monitoring data have been collected from long-term monitoring stations, continuous monitoring sensors, synoptic sensor surveys, and measurements of sediment-water fluxes. A state-of-the-art modeling system, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), was applied to the Corsica domain with a high-resolution grid and nutrient loads from the most recent version of the Chesapeake Bay watershed model. The Corsica SCHISM model reproduced observed high-frequency variability in dissolved oxygen, as well as seasonal variability in chlorophyll-a and sediment-water fluxes. Time-series signal analyses using Empirical Model Decomposition and spectral analysis revealed that the diurnal and M2 tide frequencies are the dominant high-frequency modes and physical transport contributes a larger share to dissolved oxygen budgets than biogeochemical processes on an hourly time scale. Heterogeneity and patchiness in dissolved oxygen resulting from phytoplankton distributions and geometry-driven eddies amplify the physical transport effect, and on longer time scales oxygen is controlled more by photosynthesis and respiration. Our simulation demonstrates that interactions among physical and biological dynamics generate complex high-frequency variability in water quality and non-linear reposes to nutrient loading and environmental forcing in shallow water systems.
Impacts of Sea‐Level Rise on Hypoxia and Phytoplankton Production in Chesapeake Bay: Model Prediction and Assessment
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.
A Numerical Study of Hypoxia in Chesapeake Bay Using an Unstructured Grid Model: Validation and Sensitivity to Bathymetry Representation
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. Further, 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.
AmeriFlux US-Mi1 LTAR UCB (Upper Chesapeake Bay) Miscanthus 1
This is the AmeriFlux version of the carbon flux data for the site US-Mi1 LTAR UCB (Upper Chesapeake Bay) Miscanthus 1. Site Description - This Farm was a privately owned farm in Ohio Leased to Aloterra Energy Corporation out of Texas, The crop was Miscanthus grown continually originally for alternative Ethanol production but eventually for fiber as absorbant material. Miscanthus grows upwards of 15 ft tall each year.
AmeriFlux US-Mi2 LTAR UCB (Upper Chesapeake Bay) Miscanthus 2
This is the AmeriFlux version of the carbon flux data for the site US-Mi2 LTAR UCB (Upper Chesapeake Bay) Miscanthus 2. Site Description - This Farm was a privately owned farm in Ohio Leased to Aloterra Energy Corporation out of Texas, The crop was Miscanthus grown continually originally for alternative Ethanol production but eventually for fiber as absorbant material. Miscanthus grows upwards of 15 ft tall each year.
AmeriFlux US-Mi3 LTAR UCB (Upper Chesapeake Bay) Miscanthus 3
This is the AmeriFlux version of the carbon flux data for the site US-Mi3 LTAR UCB (Upper Chesapeake Bay) Miscanthus 3. Site Description - This Farm was a privately owned farm in Ohio Leased to Aloterra Energy Corporation out of Texas, The crop was Miscanthus grown continually originally for alternative Ethanol production but eventually for fiber as absorbant material. Miscanthus grows upwards of 15 ft tall each year.
Geographically aware estimates of remotely sensed water properties for Chesapeake Bay
This software contains the code for a data-driven model to produce high-resolution (< 1 km2) estimates of temperature, salinity, and turbidity over decadal time scales as required by next-generation Earth Systems Models. Our model fits daily MODIS Aqua reflectance data to surface observations (< 1 m depth) from 2000-2021 in Chesapeake Bay, USA.
Data for Stetten et al. (2025), "Biogeochemical controls on iron speciation and cycling across upland to shoreline gradients in freshwater and estuarine coastal soils (Lake Erie and Chesapeake Bay, United States)"
Coastal environments are dynamic interfaces that mediate carbon and nutrient exchanges between terrestrial landscapes and open waters, but it is unclear how biogeochemical reactions, in particular iron (Fe) redox transformations, affect the understanding and prediction of coastal ecosystem functions. This dataset includes measurements from two freshwater sites in the Western and Central basins of Lake Erie (Ohio, United States) and two estuarine sites in the Chesapeake Bay (Maryland, United States); the analytical results were reported by Stetten et al. (2025) in Science of the Total Environment. It was produced as part of the COMPASS-FME project, which seeks to advance a scalable, predictive understanding of the fundamental biogeochemical processes, ecological structure, and ecosystem dynamics that distinguish coastal terrestrial-aquatic interfaces from the purely terrestrial or aquatic systems to which they are coupled. The sites were sampled in November 2022 (CRC), December 2022 (MSM), February 2023 (GCW), and March 2023 (OWC); site codes follow those used by Pennington et al. (2025).The dataset consists of the following soil data:- Solid data (Fe concentration, etc.)- Porewater data (sulfate, sulfide, etc.)- Linear combination fitting results of X-ray absorption near edge structure (XANES) spectra; i.e., quantitative results of the oxidation state of Fe, indicated as a proportion of pure Fe(III) and Fe(II) model compounds- Linear combination fitting results of EXAFS (extended X-ray absorption fine structure) spectra, indicated as proportion of of Fe-model compounds (illite, smectite, etc.)Each data type has a single file in comma-separated value (CSV) format. No special software is required to read it.
Characterizing Bioavailable Soil Nutrients Across Coastal Systems: Western Lake Erie and Chesapeake Bay
Terrestrial Aquatic Interfaces (TAIs), defined as where land meets water, exhibit important hydrological, biological, and biogeochemical dynamics and play a critical role in the Earth’s carbon cycle. Current Earth System Models improperly represent this role due to the complexity of these systems and the disproportionally large impact TAIs have relative to their area. To improve our predictive capacity of coastal system dynamics, a better understanding of carbon and nutrient cycling across TAI’s is needed. Coastal Observations, Mechanisms, and Predictions Across Systems and Scales (COMPASS) aims to achieve this through field observations and laboratory incubations throughout the Western Lake Erie and Chesapeake Bay regions. Here, we report on preliminary results from a soil characterization experiment across the WLE and CB regions. This experiment was conducted as part of the 2-year field, measurements, and experiments (FME) pilot study portion of COMPASS to provide initial baseline data for the sites and to characterize the spatial variability of our analytes. Soil samples were collected from three locations along the TAI transect (upland forest, transitional forest, and wetland) and analyzed for bioavailable nutrients using three types of extractions: (a) water extractions, (b) 2M KCl extractions, and (c) 1M NH4Cl extractions to analyze (a) water soluble organic carbon (WSOC), (b) ammonium and nitrate, and (c) base cations, including Ca, Mg, Na, K, and Fe. These analyses, in conjunction with other bulk physicochemical analyses, will help establish baseline understanding of these sites to drive future research and design focused experiments that will ultimately improve our predictive understanding of these freshwater and marine coastal TAIs and their response to short and long-term changes.
Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”
The package contains the data layers used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”. The study aims to use multi-source remote sensing and GIS datasets to investigate the spatial heterogeneity and identify spatial zones with similar environmental characteristics and understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. We employed unsupervised hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, then determined the main driving factors using Random Forest regression and SHapley Additive exPlanations (SHAP). Spatial data layers include soil respiration, kernel Normalized Difference Vegetation Index (kNDVI) computed from Harmonized Landsat 8 and Sentinel-2 time series, climate variables from the Daymet dataset, land cover, biodiversity, topographical metrics, soil property, and tidal elevation.