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Qin Chen

Publications and source records attributed to Qin Chen.

2 recordsLinked to original sources

Topographic and bathymetric survey in support of the effectiveness assessment of the living shoreline restoration in Gandys Beach, New Jersey

High resolution topobathymetric field surveys were conducted by the U.S. Geological Survey in collaboration with Northeastern University and in cooperation with the U.S. Fish and Wildlife Service and The Nature Conservancy in a selected shoreline along Gandys Beach, New Jersey, from January to April 2018. These data are a critical model input for hydrodynamic and wave models and can affect the accuracy of model outputs such as wave height, water surface elevation, current velocity, and sediment transport. Gandys Beach is a living shoreline where constructed oyster reefs (CORs) were built to protect the shoreline and enhance habitat for oyster and other species. Because of the complex topography and bathymetry of the study area, higher spatial resolution topobathymetric data are required to resolve the vertical variations near the CORs. During the field survey, the global navigation satellite system positioning method was used to establish the elevation of a benchmark referenced to the North American Vertical Datum of 1988. The topobathymetric data were collected using a total station. Horizontal accuracy of plus or minus 0.05 foot (ft) and vertical accuracy of plus or minus 0.10 ft were calculated using root mean square error between duplicate surveys. Two existing datasets were integrated with the survey data to create an updated topobathymetric dataset for model input and analysis: (1) the U.S. Geological Survey Coastal National Elevation Database 1-meter resolution data developed after Hurricane Sandy and (2) The Nature Conservancy 2017 elevation monitoring data at 10-meter resolution. A root mean square error analysis comparing survey data with the new topobathymetric dataset versus the survey data compared to the original Coastal National Elevation Data dataset showed errors of 0.31 and 2.61 ft, respectively. This improved dataset can be used for wave and hydrodynamic modeling in support of the effectiveness assessment of the CORs and living shoreline restoration along Gandys Beach.

New Jersey

Numerical modeling of circulation and wave dynamics along the shoreline of Shinnecock Indian Nation in Long Island, New York

The Shinnecock Indian Nation on Long Island, New York, faces challenges of shoreline retreat, saltwater intrusion, and flooding of the Tribal lands under changing climate and rising sea level. However, understanding of the dynamics of tidal circulation and waves and their impacts on the Shinnecock Indian Nation’s shoreline remains limited. This numerical study employs the integrated modeling capabilities of the hydrodynamic model Delft3D-FLOW and the spectral-wave model Simulating WAves Nearshore (SWAN) to investigate the circulation and wave dynamics along the shoreline of Shinnecock Indian Nation. The results of the 1-year long simulation indicate the majority of wind waves approach the Shinnecock Nation shorelines at normal wave angles, with yearly averaged offshore wave height of around 0.2 meter, maximum wave height reaching 0.65 meter, and yearly averaged offshore wave power of approximately 50 watts per meter. Boulders, acting as natural barriers, have been placed along the shoreline to reduce erosive wave forcing. Simulation results indicate the boulders to the north end effectively attenuate wave energy and reduce annual wave power, while the boulders near the two tidal ponds adjacent to the Tribal cemetery only have a slight influence on wave energy. There are large spatial variabilities in wave attenuation and current velocity reduction by the boulders. The model framework developed in this study can be utilized for the optimal design of nature-based solutions, guiding decisions on the placement of living shoreline structures and determining their optimal size. This study further identifies data and knowledge gaps as well as future research opportunities that can enhance the performance of numerical models and contribute to the scientific understanding of coastal processes and facilitate the optimal design of hybrid living shorelines in the future to achieve the maximum protective efficacy. This research can help to inform strategies for safeguarding vulnerable coastal communities and promoting resilience and sustainability of shoreline along the Shinnecock Indian Nation.

New York