These data provide grain-size measurements from sediment samples collected as part of the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal environments, including hazards to humans and infrastructure and changes in landscape and natural habitats. The grain-size analysis data are part of USGS field activities 2021-028-FA and 2021-032-FA and are related to field activity 2021-029-FA.

These data provide grain-size measurements from sediment samples collected as part of the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal environments, including hazards to humans and infrastructure and changes in landscape and natural habitats. The grain-size analysis data are part of USGS field activities 2021-028-FA and 2021-032-FA and are related to field activity 2021-029-FA.

These data provide grain-size measurements from sediment samples collected as part of the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal environments, including hazards to humans and infrastructure and changes in landscape and natural habitats. The grain-size analysis data are part of USGS field activities 2021-028-FA and 2021-032-FA and are related to field activity 2021-029-FA.

These data provide grain-size measurements from sediment samples collected as part of the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal environments, including hazards to humans and infrastructure and changes in landscape and natural habitats. The grain-size analysis data are part of USGS field activities 2021-028-FA and 2021-032-FA and are related to field activity 2021-029-FA.

In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science Center made in-situ observations during 2018-2019 and 2022-2023 at two sites: Thompsons Beach, NJ and Stone Harbor, NJ. Marsh creek hydrodynamics and water quality including currents, waves, water levels, water temperature, salinity, pH, dissolved oxygen, turbidity, organic matter, chlorophyll-a, and suspended-sediment concentration and organic content were measured at both sites. Additionally, marsh accretion and erosion were evaluated and used to interpret sediment budgets. These ecological data will be coupled with topographic lidar and imagery to explain the processes responsible for coastline evolution, and to evaluate restoration techniques and assess whether storm vulnerability has decreased relative to unaltered environments.

In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science Center made in-situ observations during 2018-2019 and 2022-2023 at two sites: Thompsons Beach, NJ and Stone Harbor, NJ. Marsh creek hydrodynamics and water quality including currents, waves, water levels, water temperature, salinity, pH, dissolved oxygen, turbidity, organic matter, chlorophyll-a, and suspended-sediment concentration and organic content were measured at both sites. Additionally, marsh accretion and erosion were evaluated and used to interpret sediment budgets. These ecological data will be coupled with topographic lidar and imagery to explain the processes responsible for coastline evolution, and to evaluate restoration techniques and assess whether storm vulnerability has decreased relative to unaltered environments.

In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science Center made in-situ observations during 2018-2019 and 2022-2023 at two sites: Thompsons Beach, NJ and Stone Harbor, NJ. Marsh creek hydrodynamics and water quality including currents, waves, water levels, water temperature, salinity, pH, dissolved oxygen, turbidity, organic matter, chlorophyll-a, and suspended-sediment concentration and organic content were measured at both sites. Additionally, marsh accretion and erosion were evaluated and used to interpret sediment budgets. These ecological data will be coupled with topographic lidar and imagery to explain the processes responsible for coastline evolution, and to evaluate restoration techniques and assess whether storm vulnerability has decreased relative to unaltered environments.

The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg Inlet and along the southern end of Long Beach Island near Beach Haven, New Jersey was conducted from May 31 to June 10, 2018, followed by a sea floor sampling survey conducted from October 22 to 23, 2018, as part of a collaborative effort between the U.S. Geological Survey and Stockton University. Multibeam echo sounder bathymetry and backscatter data were collected along 741 kilometers of tracklines (approximately 200 square kilometers) of the coastal sea floor to regionally define its depth and morphology, as well as the type and distribution of sea-floor sediments. Six hundred ninety-two kilometers of seismic-reflection profile data were also collected to define the thickness and structure of sediment deposits in the inlet and offshore. These new data will help inform future management decisions that affect the natural and recreational resources of the area around and offshore of Little Egg Inlet. These mapping surveys provide high-quality data needed to build scientific knowledge of the evolution and behavior of the New Jersey barrier island system.

The natural resiliency of the New Jersey barrier island system, and the efficacy of management efforts to reduce vulnerability, depends on the ability of the system to recover and maintain equilibrium in response to storms and persistent coastal change. This resiliency is largely dependent on the availability of sand in the beach system. In an effort to better understand the system's sand budget and processes in which this system evolves, high-resolution geophysical mapping of the sea floor in Little Egg Inlet and along the southern end of Long Beach Island near Beach Haven, New Jersey was conducted from May 31 to June 10, 2018, followed by a sea floor sampling survey conducted from October 22 to 23, 2018, as part of a collaborative effort between the U.S. Geological Survey and Stockton University. Multibeam echo sounder bathymetry and backscatter data were collected along 741 kilometers of tracklines (approximately 200 square kilometers) of the coastal sea floor to regionally define its depth and morphology, as well as the type and distribution of sea-floor sediments. Six hundred ninety-two kilometers of seismic-reflection profile data were also collected to define the thickness and structure of sediment deposits in the inlet and offshore. These new data will help inform future management decisions that affect the natural and recreational resources of the area around and offshore of Little Egg Inlet. These mapping surveys provide high-quality data needed to build scientific knowledge of the evolution and behavior of the New Jersey barrier island system.

Grain-size data, including grain size, cumulative frequency, and median, was determined from samples collected at three bluff locations in the vicinity of Wainwright, Alaska. The different locations (termed W1, W2, and W3) represent three different slope-failure modes. Sediment grab samples for most bluff locations were collected in August 2009, while sediment samples from the bluff at site W3 and multiple foreshore locations were collected in September and October of 2009. Two of the grab samples were sieved and analyzed for grain size distributions (7 classes ranging from 0.06 to 0.72 mm). The grain size distribution of the remaining samples was determined from referenced photographs of collected samples taken in the lab following the method of Barnard and others (2007) using two-dimensional spectral decomposition of sediment images (Buscombe and others, 2010). Results of sieved samples were used to verify mean grain-size values obtained with the image processing algorithm. Data are available in a single csv file.