Environmental Sciences Commons^™

Dataset: Baywide Distribution Of Benthic Ecological Functions In The Past Decades In The Chesapeake Bay, Philip Ignatoff, Xun Cai, Kara Gadeken

Data

We undertook the collection and analysis of long-term benthos data from the Chesapeake Bay Benthic Monitoring Plan. Multiple ecological function traits related to feeding and disturbance were assigned to each observed benthic species based on a thorough literature review. The spatial distributions of the ecological function groups will be utilized in a 3D hydrodynamic biogeochemistry model simulation. This approach aids in estimating the contributions of benthos to estuarine hypoxia and nutrient dynamics. Furthermore, it fosters a connection between ecologists and modelers, promoting collaborative efforts in understanding and modeling the ecosystem.

Management Practices For Urban Areas In The Hampton Roads Vicinity: Data Files, Gary F. Anderson

Data

During 1980 through 1981, the Virginia Institute of Marine Science conducted studies in the Hampton Roads Virginia vicinity to assess pollutant loading in runoff from various land use types. The 13 urban study areas also included established BMPs such as grassy swales and retention ponds to measure their effectiveness in reducing pollutant loads to the Chesapeake Bay. The focus was on nutrients, BOD and suspended solids. The studies were conducted with support of the U.S. EPA under section 208 of the Federal Clean Water Act.

Methods and results are documented in the associated publication. Data files were processed using SPSS …

Ware River Intensive Watershed Study Data Files - Part 2. Estuarine Receiving Water Quality, Gary F. Anderson

Data

The Ware River is a small coastal estuary draining into the Chesapeake Bay estuary. VIMS monitored the Ware watershed for rain events, runoff, and impacts to the estuary from April 1979 through July 1981. This entry contains the estuarine receiving water quality monitoring data files for the portion of the study known as Part 2 – Estuarine Receiving Water Quality. A set of stations on the tidal estuarine portion of the river were sampled by-monthly during high slack tide events. The stations were also sampled during 24-hour ‘intensive surveys’ and immediately following storm events to document impacts. Methods and results …

Coastal Natural And Nature-Based Features (Nnbfs) Ranked: Co-Benefits For Coastal Buildings And Target Areas For The Creation Of New Or Restoration Of Nnbfs In Coastal Virginia, Pamela Mason, Jessica Hendricks, Julie Herman

Data

Community resilience to storm-driven coastal flooding is improved with the presence of natural and nature-based features (NNBFs) such as wetlands, wooded areas, living shorelines, and beaches. These natural and created features can provide multiple benefits for a local community, including mitigating the impacts of storm surge and sea-level rise and allowing communities to take advantage of programmatic incentive programs like FEMA’s Community Rating System and nutrient reduction crediting.

As part of a NOAA-funded project NA17NOS4730142, an exportable geospatial protocol and NNBF ranking methodology was developed with the goal of incentivizing the protection and creation of NNBFs across Chesapeake Bay localities …

Vims Ferry Pier Ambient Water Monitoring Data, Salinity And Temperature, Daily Summary 1947-2003, Gary F. Anderson

Data

Bulk water parameters of Temperature and Salinity were measured at the VIMS Ferry Pier from 1947 to 2003. Initial methods were undocumented but likely automated with an instrument and chart recorder since the data consists of a daily high and low measurement from which a mean value was derived.

Beginning in 1971 an automated instrument recorded continuously from which 2-hour measurements were made and daily minimum and maxima were derived. Beginning in 1986 an Inter-Ocean CTD instrument placed at mid-depth was interfaced to a digital data logger (Campbell Scientific CRJ) that recorded data every six minutes, resulting in 240 measurements …

Gis Data: Anne Arundel County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shorezone into three regions:

1) the immediate …

Vims Hydrofile: Ambient Water Monitoring And Meteorological Data For Chesapeake Bay And Near Coastal Shelf Waters, 1942-1982, Gary F. Anderson

Data

Historical ambient water quality and meteorologic conditions from cruises conducted by the Virginia Institute of Marine Science in Chesapeake Bay and nearshore coastal shelf waters over a 40-year period through 1982.

Bulk water parameters were routinely measured during cruises conducted in Chesapeake Bay and nearshore coastal waters conducted by VIMS over four decades. Data were punched on 80-character cards known as ‘Form 1’ format by the VIMS central Computer Center. These were later converted to digital files. For this publication the Form 1 files were unpacked into yearly flat files containing two record types:

Station records - Contain surface observations …

Gis Data: Calvert County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shorezone into three regions:

1) the immediate …

Gis Data: Talbot County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shorezone into three regions:

1) the immediate …

Ware River Intensive Watershed Study Data Files: Part 1. Nonpoint Source Contributions, Gary F. Anderson

Data

The Ware River is a small coastal estuary draining into the Chesapeake Bay estuary. VIMS monitored the Ware watershed for rain events, runoff, and impacts to the estuary from April 1979 through July 1981.

This entry contains the runoff volume, rainfall and water quality monitoring data files for the portion of the study known as Part 1 – Nonpoint source contributions. Streams and small catchments representing suburban, agricultural and forested small basins were monitored regularly and during large rainfall events to estimate pollution loading to the estuary from the watershed. Methods and results are documented in the related literature. Data …

Migration Of The Tidal Marsh Range Under Sea Level Rise For Coastal Virginia, With Land Cover Data, Julie Herman, Molly Mitchell

Data

The layers in this geodatabase were intended to represent the land that is encompassed by the average tidal range as sea level rises in the Virginia coastal region, including Chesapeake Bay and tributaries, the Atlantic Ocean side of the Eastern Shore, and Virginia Beach. The data layers in this geodatabase represent each two foot range of elevation incremented by 0.5 ft (e.g. 0-2 ft, 0.5-2.5 ft, 1-3 ft, etc.) with the current land cover that exists in that range.

ArcGIS metadata is included in the geodatabase.

Further details are provided in the Geodatabase Information file located from the download tab.

Gis Data: Dorchester County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shorezone into three regions:

1) the immediate …

Gis Data: King & Queen County Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Carl Hershner, Evan Hill

Data

The Virginia Institute of Marine Science published the first Tidal marsh Inventories using data collected in the early 1970's. Using high resolution color infra-red imagery from 2009 a new Tidal Marsh Inventory has been developed for the York River Watershed in 2010. Marsh boundaries were generated using heads-up digitizing techniques at a scale of 1:1,000. Each marsh polygon was classified by morphologic type: fringe, extensive, embayed, or marsh island. Marshes were ground-truthed in the field where a community type index was assigned to each marsh based on plant community make-up. Each marsh was also coded with a marsh number which …

Gis Data: King William County Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Carl Hershner, Evan Hill

Data

The Virginia Institute of Marine Science published the first Tidal marsh Inventories using data collected in the early 1970's. Using high resolution color infra-red imagery from 2009 a new Tidal Marsh Inventory has been developed for the York River Watershed in 2010. Marsh boundaries were generated using heads-up digitizing techniques at a scale of 1:1,000. Each marsh polygon was classified by morphologic type: fringe, extensive, embayed, or marsh island. Marshes were ground-truthed in the field where a community type index was assigned to each marsh based on plant community make-up. Each marsh was also coded with a marsh number which …

King William County, Virginia Shoreline Inventory Data 2019, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Jessica Hendricks, Carl Hershner, Evan Hill

Data

The 2019 Inventory for King William County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in 2017 imagery from the Virginia Base Mapping Program (VBMP), Google Earth, and Bing high resolution oblique imagery. Five GIS shapefiles are developed. The first describes land use and bank conditions (KingWilliam_lubc_2019). The second portrays the presence of beaches (KingWilliam_beach_2019). The third reports shoreline structures that are described as arcs or lines (e.g. riprap) (KingWilliam_sstru_2019). The fourth shapefile includes all structures that are represented as points (e.g. piers) (KingWilliam_astru_2019). The Tidal Marsh Inventory is included as the fifth file …

King And Queen County, Virginia Shoreline Inventory Data 2019, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Jessica Hendricks, Carl Hershner, Evan Hill

Data

The 2019 Inventory for King and Queen County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in 2017 imagery from the Virginia Base Mapping Program (VBMP), Google Earth, and Bing high resolution oblique imagery. Five GIS shapefiles are developed. The first describes land use and bank conditions (kq_lubc_2019). The second portrays the presence of beaches (kq_beach_2019). The third reports shoreline structures that are described as arcs or lines (e.g. riprap) (kq_sstru_2019). The fourth shapefile includes all structures that are represented as points (e.g. piers) (kq_astru_2019). The Tidal Marsh Inventory is included as the fifth …

Catch The King Tide 2018: All King Tide Data, Jon Derek Loftis

Data

"Catch the King" is a citizen-science GPS data collection effort centered in Hampton Roads, VA, that seeks to interactively map the King Tide's maximum inundation extents. The goal is to validate and improving predictive model accuracy for future forecasting of increasingly pervasive "nuisance" flooding.

Section: 01 Line Frame: 01, 18 October 2017: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith

Data

Multispectral aerial imagery acquired in 2017 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays

Section: 01 Line Frame: 06, 27 August 2017: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith

Data

Multispectral aerial imagery acquired in 2017 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays

Gis Data: New Kent County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

The 2018 Inventory for New Kent County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2017imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (New_Kent_lubc_2018). The second portrays the presence of beaches (New_Kent_beaches_2018). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(New_Kent_sstru_2018). The final shapefile includes all structures that are represented as points(e.g. piers)(New_Kent_astru_2018).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any use restrictions that pertain to …

Gis Data:: Arlington County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Carl Herschner

Data

No abstract provided.

Gis Data: Caroline County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl H. Hershner

Data

No abstract provided.

Gis Data: Caroline County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

Gis Data: Caroline County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

No abstract provided.

Gis Data: Richmond County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner

Data

No abstract provided.

Gis Data: Richmond County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

Gis Data: Richmond County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner

Data

No abstract provided.

Gis Data: Essex County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner

Data

No abstract provided.

Gis Data: Essex County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …

Gis Data: New Kent County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …