Physical Sciences and Mathematics Commons^™

Gis Data: Prince George’S County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

Gis Data: Harford County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

Gis Data: Cecil County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

Gis Data: Caroline County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

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.

Gis Data: Kent County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

Gis Data: Baltimore County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

Gis Data: Queen Anne’S County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

Gis Data: Baltimore City, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

Gis Data: Wicomico County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

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 shore zone into three regions:

1) the …

Sediment Characteristics Of The Chesapeake Bay And Its Tributaries, Virginia Province: Data Files, Gary F. Anderson

Data

During the 1990’s, Dr. Maynard Nichols and colleagues at the Virginia Institute of Marine Science compiled digital databases of sediment observations in the Chesapeake Bay and other coastal bays and rivers. These projects were performed under several cooperative agreements with NOAA, EPA and USGS. This particular dataset covers the Chesapeake Bay for bulk properties and contaminants. Additional references are provided below. The original files and filenames are provided without edit. See the readme.txt file for overall explanation of the datasets and individual .DOC files for the data dictionary and further data processing information for each waterbody.

Storm Surge Simulation From The 2009 Nor’Easter On The Virginia Shoreline, Karinna Nunez, Yinglong J. Zhang, Evan Hill, Catherine Riscassi Duning

Data

The November 2009 nor’easter formed from the remnants of Hurricane Ida and generated strong winds, heavy rain, and storm surge across the east coast of the United States. The height of the storm surge generated by the nor’easter was modelled throughout Virginia using SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model). SCHISM outputs were translated to GIS and processed to be overlaid upon the LUBC (land use and bank cover) shoreline of coastal Virginia.

A Data Repository For Clarifying Water Clarity: A Call To Use Metrics Best Suited To Corresponding Research And Management Goals In Aquatic Ecosystems (York River Estuary Case Study Dataset), Jessica S. Turner, Kelsey A. Fall, Carl T. Friedrichs

Data

This data repository is a permanent archive of the results presented in the associated publication (Turner et al. 2022, Limnology & Oceanography Letters, doi.xxxx). The objective of this study was to illustrate a water clarity phenomenon in the lower York River Estuary of the Chesapeake Bay. The data include light attenuation, Secchi depth, turbidity, and salinity from the lower York River Estuary in western Chesapeake Bay, Virginia, USA from the years 2014-2016.

Storm Surge Simulation From Hurricane Isabel (2003) On The Virginia Shoreline, Karinna Nunez, Yinglong J. Zhang, Evan Hill, Catherine Riscassi Duning

Data

Hurricane Isabel made landfall in the Outer Banks of North Carolina on September 16, 2003 as a category 2 hurricane. The storm continued northwest after making landfall and significantly impacted Virginia with strong winds, storm surge, and heavy rainfall. The height of the storm surge generated by Hurricane Isabel was modelled throughout Virginia using SCHISM (Semi-implicit Cross-scale Hydroscience Integrated System Model). SCHISM outputs were translated to GIS and processed to be overlaid upon the LUBC (land use and bank cover) shoreline of coastal Virginia.

Nitrogen Reductions Have Decreased Hypoxia In The Chesapeake Bay: Evidence From Empirical And Numerical Modeling : Data Repository, Luke T. Frankel, Marjorie A.M. Friedrichs

Data

This data repository is a permanent archive of the results presented in the associated publication: Frankel et al., 2022, Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling, Science of the Total Environment, accepted for publication in December 2021.

Acoustic Doppler Current Profiler (Adcp) Data 2017: Ayeyarwady Delta, Myanmar, Courtney K. Harris, Jacob T. Wacht

Data

During December 2017, a 2-week research cruise was conducted on the vessel the Sea Princess by scientists from the Virginia Institute of Marine Science, North Carolina State University, Mawlamyine University, and University of Yangon. Kuehl et al. (2019) and Liu et al. (2020) present some of the sediment core, and seabed mapping data from that cruise. The cruise also provided a unique opportunity to obtain Acoustic Doppler Current Profiler (ADCP) data along several transects from the Gulf of Martaban and adjacent continental shelf offshore of Myanmar. During the cruise, an ADCP was mounted from the boat facing vertically downward toward …

Simulating Storm Surge And Compound Flooding Events With A Creek-To-Ocean Model: Importance Of Baroclinic Effects : Model Files, Fei Ye, Yinglong J. Zhang, Haocheng Yu, Weiling Sun, Saeed Moghimi, Edward Myers, Karinna Nunez, Ruoyin Zhang, Harry V. Wang, Aron Roland, Kevin Martins, Xavier Bertin, Jiabi Du, Zhou Liu

Data

The supplemental material contains the input files for setting up a 3D baroclinic model based on the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), supplementing the description of model setup in Ye et al. (2019; associated publication).

The SCHISM version used for the simulation was r5082 in the SCHISM svn repository. A compressed file (setup.tar.gz) is provided, which can be extracted with common zip/unzip software on Unix/Windows/Mac (such as gzip, winzip, 7-zip, etc.). Since the dataset is intended for conducting a SCHISM simulation, readers/users should familiarize themselves with the SCHISM model system first.

The SCHISM manual is at: http://ccrm.vims.edu/schismweb/schism_manual.html; …

A Model Archive For Sediment Transport Model Including Short-Lived Radioisotopes: Model Description And Idealized Test Cases, 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 Marine Science and Engineering), which used a coupled hydrodynamic-sediment transport-biogeochemical model to investigate the roles of resuspension, deposition, on biodiffusion on the behavior of short-lived radioisotopes in an idealized one-dimensional model setting. 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 Marine Science and Engineering), the model can account for supply and sorption of radioisotope tracers in the …

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.