Dams and Sediment in the Hudson answered key questions about how dam removal will impact conditions in the estuary and offered surprising new findings about tidal marshes in the Hudson River valley. The project used a multidisciplinary approach that combined field observations with an analysis of sediment transport using a proven hydrodynamic model. Researchers surveyed 17 representative dams in the Lower Hudson River watershed by measuring water depth and sediment thickness and collecting sediment cores. Results were extrapolated to the 1700 registered dams located on tributaries of the Lower Hudson River to estimate the total amount of sediment trapped in the watershed. These observations were complemented by an analysis of sediment discharge data from existing monitoring stations on tributaries to characterize typical sediment input to the estuary and conditions following major storm events. A numerical model of circulation and sediment transport in the estuary was used to evaluate the impact of dam removal scenarios. To understand sediment contributions to tidal wetlands along the Hudson, researchers collected transects of sediment core from 6 representative tidal wetlands and coves. Geochronological data of sediment cores combined with an analysis of historical and aerial photos was used to assess when wetlands began to form and their rates of accumulation. Results show that dam removals would have a minimal impact on sediment supply to the estuary and tidal wetland growth. Only 10% of dams in the Lower Hudson River watershed are effective sediment traps, and the potential amount of sediment that would be released if all dams were removed represents less than 2 years average sediment input from the watershed. Tidal wetlands along the Hudson were found to be remarkably young and rapidly accumulating sediment despite the presence of dams, growing vertically at rates several times faster than sea level rise.

Through the current project, the Chesapeake Bay-Virginia Reserve is building on the strengths of the previous years of CECB to extend the reach into Middlesex County, while developing an alumni program to support the program in Gloucester and Mathews. All three counties lie within a region experiencing relative rates of sea level rise greater than the global average. This science transfer project was funded by NOAA through the National Estuarine Research Reserve System Science Collaborative to promote the use of science. It did not produce any new data.

NOAA's Coastal Ocean Reanalysis (CORA) couples long-term water level observations with hydrodynamic modeling to create historical information between tide stations to bridge gaps in service and more equitably serve the Nation's coastal communities. CORA water levels are simulated with ADvanced CIRCulation (ADCIRC) for ocean circulation modeling and coupled with a phase-averaging model called Simulating WAves Nearshore (SWAN) to produce surface gravity wave spectra and account for time-averaged wave contributions. Coastal water level observations from NOAA's Center for Operational Oceanographic Products and Services (CO-OPS) National Water Level Observation Network (NWLON) are low-pass filtered and assimilated into the model to account for long-term sea level variability and to reduce model errors, and validate results. The domain of this reanalysis spans the Gulf of America, Atlantic (East), and Caribbean coastlines (or CORA-GEC). The reanalysis (1979-2022) was performed through the partnership of NOAA National Ocean Service (NOS) and University of North Carolina's (UNC) Institute of Marine Sciences and Renaissance Computing Institute (RENCI). This modeled dataset is meant to have secondary derived datasets including but not limited to daily maximums (daily maxes), monthly means, extremes and month high tide flooding predictions. In addition, the domain of the analysis will be expanded to the Pacific and the dataset to be included when it becomes available.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Paleoclimatology Modeling. The data include parameters of paleoclimatic modeling with a geographic location of Global. The time period coverage is from Unavailable begin date to Unavailable end date in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Paleoclimatology Modeling. The data include parameters of paleoclimatic modeling with a geographic location of Global. The time period coverage is from Unavailable begin date to Unavailable end date in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Paleoceanography. The data include parameters of climate reconstructions|paleoceanography with a geographic location of Global Ocean. The time period coverage is from 66610890 to 0 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Paleoclimatology Modeling. The data include parameters of paleoclimatic modeling with a geographic location of Global. The time period coverage is from 21000 to 18000 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

NOAA's National Ocean Service (NOS) has developed a Columbia River Estuary Operational Forecast System (CREOFS). CREOFS is based on a three-dimensional SELFE model that runs on NOAA's High Performance Computers (HPC). CREOFS provides water level, currents, water temperature and salinity nowcast and forecast guidance as well as interpolated winds from National Weather Service products for five separate subdomains: Upper Columbia River subdomain, Middle Columbia River subdomain, Lower Columbia River subdomain, Columbia River Bar Entrance subdomain, and the mouth and offshore subdomain of the Columbia River. CREOFS runs four times per day and generates 6-hour nowcasts and 48-hour forecast guidance. CREOFS products include time series graphics at station locations and aerial animations of the Columbia River Estuary for all five parameters (wind, water level, currents, temperature and salinity).

NOAA's National Ocean Service (NOS) has developed a Columbia River Estuary Operational Forecast System (CREOFS). CREOFS is based on a three-dimensional SELFE model that runs on NOAA's High Performance Computers (HPC). CREOFS provides water level, currents, water temperature and salinity nowcast and forecast guidance as well as interpolated winds from National Weather Service products for five separate subdomains: Upper Columbia River subdomain, Middle Columbia River subdomain, Lower Columbia River subdomain, Columbia River Bar Entrance subdomain, and the mouth and offshore subdomain of the Columbia River. CREOFS runs four times per day and generates 6-hour nowcasts and 48-hour forecast guidance. CREOFS products include time series graphics at station locations and aerial animations of the Columbia River Estuary for all five parameters (wind, water level, currents, temperature and salinity).