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Articles 211 - 240 of 413
Full-Text Articles in Physical Sciences and Mathematics
A Model Archive For A Numerical Model Of Geochronological Tracers For Sediment Deposition And Reworking Applied To The Mississippi Subaqueous Delta, Justin J. Birchler, Courtney K. Harris, Tara A. Kniskern
A Model Archive For A Numerical Model Of Geochronological Tracers For Sediment Deposition And Reworking Applied To The Mississippi Subaqueous Delta, Justin J. Birchler, Courtney K. Harris, Tara A. Kniskern
Data
This dataset includes model input, code, and output used in the publication Birchler et al. (2018, Journal of Coastal Research), which used a coupled hydrodynamic-sediment transport-geochemical model to investigate the roles of resuspension, deposition, on biodiffusion on the behavior of short-lived radioisotopes on the Mississippi sub-aqueous delta, USA. Model development for this project focused on incorporating radioisotope tracers into the sediment transport module in the Regional Ocean Modeling System (ROMS). As described in Birchler et al. (2018, Journal of Coastal Research), the model can account for supply and sorption of radioisotope tracers in the water column; biodiffusion of …
A Model Archive For A Coupled Hydrodynamic-Sediment Transport-Biogeochemistry Model For The Northern Gulf Of Mexico, Usa, Julia Moriarty, Courtney K. Harris, Marjorie A.M. Friedrichs, Katja Fennel, Kehui Xu
A Model Archive For A Coupled Hydrodynamic-Sediment Transport-Biogeochemistry Model For The Northern Gulf Of Mexico, Usa, Julia Moriarty, Courtney K. Harris, Marjorie A.M. Friedrichs, Katja Fennel, Kehui Xu
Data
Spatial Information: 27.4-30.3°N, -94.6 - -87.8 °W; Louisiana continental shelf, Northern Gulf of Mexico, USA
Gis Data: New Kent County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
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
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
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
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
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
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
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
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
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
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
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 …
Gis Data: Arlington County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Carl Herschner
Gis Data: Arlington County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Carl Herschner
Data
No abstract provided.
Gis Data: Essex County, Virginia Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner
Gis Data: Essex County, Virginia Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner
Data
No abstract provided.
Section: 01 Line Frame: 01 Aug27-17: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, R. J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith
Section: 01 Line Frame: 01 Aug27-17: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, R. 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 Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Gis Data: New Kent County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Data
No abstract provided.
Matlab Processing Scripts To Accompany Spatially Resolved Measurements Of Crosslinking In Uv-Curable Coatings Using Single-Sided Nmr, Madeline Brass, Frances Jude Morin, Tyler Meldrum
Matlab Processing Scripts To Accompany Spatially Resolved Measurements Of Crosslinking In Uv-Curable Coatings Using Single-Sided Nmr, Madeline Brass, Frances Jude Morin, Tyler Meldrum
Data
These Matlab scripts are used to import CPMG data collected using a Kea spectrometer (through the program Prospa), and to process each echo using the Fourier transformation. This provides spatially resolved NMR relaxation data that can be fitted or subjected to inverse Laplace transformation (not provided) to characterize relaxation at different positions within a sample.
Gis Data: 2016 Chesapeake Bay Sav Coverage, Virginia Institute Of Marine Science, Sav Data Administrator
Gis Data: 2016 Chesapeake Bay Sav Coverage, Virginia Institute Of Marine Science, Sav Data Administrator
Data
Abstract: The 2015 Chesapeake Bay SAV Coverage was mapped from digital multispectral imagery with a 25cm GSD to assess water quality in the Bay. Each area of SAV was interpreted from the rectified imagry and classified into one of four density classes by the percentage of cover. The SAV beds were entered into an SDE GIS fetaure class using the quality control procedures documented below. The dataset contains all SAV areas that were identified from the areas flown. Some areas that are presumed to contain no SAV were not flown. Some small beds, particularly along narrow tributaries may not have …
Catch The King Tide 2017 Data: Hampton, Virginia, Jon Derek Loftis
Catch The King Tide 2017 Data: Hampton, Virginia, Jon Derek Loftis
Data
"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017. Response from the event's dedicated volunteers, fueled by the local media partners' coverage …
Catch The King Tide 2017 Data: Portsmouth, Virginia, Jon Derek Loftis
Catch The King Tide 2017 Data: Portsmouth, Virginia, Jon Derek Loftis
Data
"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017. Response from the event's dedicated volunteers, fueled by the local media partners' coverage …
Catch The King Tide 2017 Data: Suffolk, Virginia, Jon Derek Loftis
Catch The King Tide 2017 Data: Suffolk, Virginia, Jon Derek Loftis
Data
"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017. Response from the event's dedicated volunteers, fueled by the local media partners' coverage …
Catch The King Tide 2017: All King Tide Data, Jon Derek Loftis
Catch The King Tide 2017: All King Tide Data, Jon Derek Loftis
Data
"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017. Response from the event's dedicated volunteers, fueled by the local media partners' coverage …
Gis Data: Chesterfield County And Cities Of Colonial Heights, Petersburg, And Richmond Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner
Gis Data: Chesterfield County And Cities Of Colonial Heights, Petersburg, And Richmond Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner
Data
The 2017 Inventory for Chesterfield County and the Cities of Colonial Heights, Petersburg, and Richmond was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2013imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (Chesterfield_lubc_2017). The second portrays the presence of beaches (Chesterfield_beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Chesterfield_sstru_2017). The final shapefile includes all structures that are represented as points (e.g. piers)(Chesterfield_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, …
Numerical Simulations Of The Biogeochemical Impact Of Atmospheric Nitrogen Deposition On Surface Waters Of The Western North Atlantic, Pierre St-Laurent, Marjorie A.M. Friedrichs
Numerical Simulations Of The Biogeochemical Impact Of Atmospheric Nitrogen Deposition On Surface Waters Of The Western North Atlantic, Pierre St-Laurent, Marjorie A.M. Friedrichs
Data
The impacts of atmospheric nitrogen deposition on the chlorophyll and nitrogen dynamics of surface waters in the western North Atlantic (25-45N, 65-80W) were examined with a biogeochemical ocean model forced with a regional atmospheric chemistry model. The model simulations cover the period 2004 to 2008 and are fully described in the following reference: St-Laurent, P., et al., Impacts of atmospheric nitrogen deposition on surface waters of the western North Atlantic mitigated by multiple feedbacks, J. Geophys. Res. Oceans, vol.122, doi:10.1002/2017jc013072.
A 3d Unstructured-Grid Model For Chesapeake Bay: Importance Of Bathymetry - Supplemental Materials, Fei Ye, Yinglong J. Zhang, Harry V. Wang, Marjorie A.M. Friedrichs, Isaac D. Irby, Arnaldo Valle-Levinson, Zhengui Wang, Hai Huang, Jian Shen, Jiabi Du
A 3d Unstructured-Grid Model For Chesapeake Bay: Importance Of Bathymetry - Supplemental Materials, Fei Ye, Yinglong J. Zhang, Harry V. Wang, Marjorie A.M. Friedrichs, Isaac D. Irby, Arnaldo Valle-Levinson, Zhengui Wang, Hai Huang, Jian Shen, Jiabi Du
Data
No abstract provided.
A Model Archive For A Coupled Hydrodynamic-Sediment Transport-Biogeochemistry Model For The Rhône River Sub-Aqueous Delta, France, Julia Moriarty, Courtney K. Harris, Katja Fennel, Kehui Xu, Christophe Rabouille, Marjorie A.M. Friedrichs
A Model Archive For A Coupled Hydrodynamic-Sediment Transport-Biogeochemistry Model For The Rhône River Sub-Aqueous Delta, France, Julia Moriarty, Courtney K. Harris, Katja Fennel, Kehui Xu, Christophe Rabouille, Marjorie A.M. Friedrichs
Data
This dataset includes model input, code, and output used in the publication Moriarty et al. (2017, Biogeosciences), which used a coupled hydrodynamic-sediment transport-biogeochemical model to investigate the roles of resuspension, diffusion and biogeochemical processes on oxygen dynamics on the Rhône River sub-aqueous delta, France. Model development for this project focused on coupling the sediment transport and water-column biogeochemistry modules in the Regional Ocean Modeling System (ROMS) by incorporating a seabed biogeochemistry module into the ROMS framework. As described in Moriarty et al. (2017, Biogeosciences), the coupled model can account for diffusion of nutrients across the seabed-water-column interface; storage …
2016 Data Collected For Resistivity, Magnetic Susceptibility And Sediment Characterization Of The York River Estuary, Va In Support Of The Empirical Investigation Of The Factors Influencing Marine Applications Of Emi (Year 2 Of Serdp Project Mr-2409), Grace M. Massey, Carl T. Friedrichs
2016 Data Collected For Resistivity, Magnetic Susceptibility And Sediment Characterization Of The York River Estuary, Va In Support Of The Empirical Investigation Of The Factors Influencing Marine Applications Of Emi (Year 2 Of Serdp Project Mr-2409), Grace M. Massey, Carl T. Friedrichs
Data
The objective of this component of the Strategic Environmental Research and Development Program (SERDP) Project MR-2409 was to conduct field measurements to aid in the determination of the electromagnetic induction (EMI) response to the water column and underlying sediments in the York River estuary, which includes water column and sediment properties similar to many underwater environments of interest to unexploded ordinance detection. Data and samples from a standard suite of hydrographic and sedimentological measurements, as well as electrical resistivity and magnetic susceptibility, were collected and analyzed for each location. These cruises provided opportunities to obtain information that is being used …
Gis Data: King George County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Kory Angstadt, Karen A. Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner
Gis Data: King George County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Kory Angstadt, Karen A. Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner
Data
The 2017 Inventory for King George County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (King_George_lubc_2017). The second portrays the presence of beaches (King_George _beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(King_George _sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(King_George_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any …
Gis Data: The County Of Spotsylvania, Virginia Shoreline Manangement Model, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner
Gis Data: The County Of Spotsylvania, Virginia Shoreline Manangement Model, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, 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 …