Skip to main content
U.S. flag

An official website of the United States government

Barrier Island Evolution - Numerical Modeling and Oceanography

Completed
By St. Petersburg Coastal and Marine Science Center October 29, 2018

Numerical models compliment the collection of geophysical data by hindcasting and forecasting sediment transport pathways, natural island trajectories, and berm/island interactions over larger and higher resolution domains and time periods.

Numerical Modeling and Oceanography

Predictions of barrier island evolution, and in many cases determination of the forcing mechanisms, require the development and use of numerical models capable of representing island evolution due to both alongshore sediment transport driven by breaking waves and cross-shore transport that occurs during storm overwash. In this project, numerical models compliment the collection of geophysical data by hindcasting and forecasting sediment transport pathways, natural island trajectories, and berm/island interactions over larger and higher resolution domains and time periods. Useful predictions of barrier island evolution depend on forcing nearshore oceanographic/geomorphic models with accurate oceanographic processes (waves, currents, water levels) at the boundaries of the model domain. This is accomplished by combining oceanographic observations and regional-scale oceanographic model predictions.

Objectives

  • Develop and test model components, linkages, scales, and resolution required to hindcast/forecast barrier island evolution.
  • Quantify the role of offshore bathymetry in shaping the forcing governing nearshore island evolution.
  • Determine the offshore characteristics of individual events which drive relatively large nearshore responses.
  • Explain processes governing the spatially-variable breaching of the sand-berm.
  • Identify sediment transport pathways and terminus for berm sediment to determine the role it plays in nourishing the disintegrating island.
  • Quantify the integrated volume of sediment transported in cross- and alongshore directions over medium-term time scales.

Methodology

Oceanographic Observations

A series of instrument arrays have been deployed in order to observe waves, currents, and water levels along and across the Chandeleur Islands following the construction of the sand berm. Resolving cross-island gradients is critical to understanding how water level variations may transport sediment across the island (or beyond) during storms and evaluating wave dissipation across low-lying barriers. These measurements have provided boundary information to the nearshore hydro/morphodynamic models and validation for the regional-scale oceanographic model.
Sources/Usage: Public Domain. View Media Details
Site map showing the study area and the locations of the USGS instruments (CI-1, CI-2, CI-3, and CI-6), NDBC buoy 42040, and the Waveland, MS water level gauge. (Public domain.)
Time series of wave measurements
Sources/Usage: Public Domain. View Media Details
Time series of wave measurements from three of the USGS insrument sites and the NDBC buoy located 30 km southeast of the study area. (Public domain.)

 

Time series of water-level measurements made during Hurricane Isaac
Sources/Usage: Public Domain. View Media Details
Time series of water-level measurements made during Hurricane Isaac in late August, 2012. Top panel shows water-level measurements in shallow wells placed in the beach 143 m apart on either side of the island in the northern Chandeleur Islands (eastern Gulf of Mexico measurements in blue, western Chandeleur Sound measurements in purple. Also shown are observed (red) and predicted (pink) water levels at the NOS Waveland Station WYCM6 – 8747437. Middle panel is the water surface slope across the island, positive from Gulf to Sound (east to west). Low-pass filtered slopes are shown in thick black lines, unfiltered in light-gray. Bottom panel: maximum range of water surfaces during running 20-min intervals. (Public domain.)

Regional-Scale Nested Models

A regional-scale model system in the Gulf of Mexico (figure 4.) is being developed to capture, at higher resolution than discrete buoys/gages, the transformation of wind-generated waves over broad continental shelves and changes in the direction of wind and wave patterns (cold fronts, tropical storms, etc). A coupled circulation model also provides predictions of water levels and depth-dependent currents. These offshore oceanographic characteristics provide variable forcing to the nearshore system along all model boundaries where the processes are likely to display variations unresolved by observations alone, and provide an improvement over coarser resolution models which may provide insufficient resolution to capture relevant processes (figure 5, regional model shown in red). Using the regional model to investigate larger-scale processes of wave and current generation and transformation, particularly during storms, will also allow for increased understanding of regional forcing mechanisms and how, through the coupling with the nearshore models, those mechanisms have shaped and will continue to shape barrier island environments.

The regional model uses the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling framework and consists of a series of two or three nested grids with increasing spatial resolution, with the requirements of the modeling system being investigated as part of this study. The outer nest is forced using global and basin scale model output for wind (NAM and GFS; NCEP Data Products GFS and GDAS), waves (global 30’ and regional 10’ and 2’ runs of the WaveWatch3 model; https://polar.ncep.noaa.gov/), astronomical tides (ADCIRC), sub-tidal water levels and currents (HYCOM; http://hycom.org).

Nearshore Modeling

The nearshore model used to simulated island evolution due to both alongshore sediment transport driven by breaking waves and cross-shore transport primarily driven by storm overwash (e.g. potential island/berm lowering or breaching) employs a curvilinear coordinate system following the island arc. XBeach, the open source dune erosion model used here, simulates long wave propagation and runup which is a principle driver of dune erosion. Morphological change associated with water levels colliding with or overtopping the dune/berm are considered in the model as well as berm/island breaching that often occurs during storms. Inputs of wave characteristics and water levels are provided by the regional oceanographic models (item #1) in order to better resolve any water level or wave gradients across the island.

Alongshore sediment transport dominates the evolution of this barrier island during non-storm conditions. Empirical estimates of alongshore transport are derived from the previous modeling of Ellis and Stone 2006 which estimated net longshore transport rates associated with different angles of wave incidence. We match observed wave conditions over the time of the experiment to the scenarios given by Ellis and Stone 2006 to determine cumulative alongshore current transport. Comparisons between model predicted barrier island evolution and sediment transport rates and directions will be compared with geophysical surveys to determine model accuracy.

Numerical models compliment the collection of geophysical data by hindcasting and forecasting sediment transport pathways, natural island trajectories, and berm/island interactions over larger and higher resolution domains and time periods.

Numerical Modeling and Oceanography

Predictions of barrier island evolution, and in many cases determination of the forcing mechanisms, require the development and use of numerical models capable of representing island evolution due to both alongshore sediment transport driven by breaking waves and cross-shore transport that occurs during storm overwash. In this project, numerical models compliment the collection of geophysical data by hindcasting and forecasting sediment transport pathways, natural island trajectories, and berm/island interactions over larger and higher resolution domains and time periods. Useful predictions of barrier island evolution depend on forcing nearshore oceanographic/geomorphic models with accurate oceanographic processes (waves, currents, water levels) at the boundaries of the model domain. This is accomplished by combining oceanographic observations and regional-scale oceanographic model predictions.

Objectives

  • Develop and test model components, linkages, scales, and resolution required to hindcast/forecast barrier island evolution.
  • Quantify the role of offshore bathymetry in shaping the forcing governing nearshore island evolution.
  • Determine the offshore characteristics of individual events which drive relatively large nearshore responses.
  • Explain processes governing the spatially-variable breaching of the sand-berm.
  • Identify sediment transport pathways and terminus for berm sediment to determine the role it plays in nourishing the disintegrating island.
  • Quantify the integrated volume of sediment transported in cross- and alongshore directions over medium-term time scales.

Methodology

Oceanographic Observations

A series of instrument arrays have been deployed in order to observe waves, currents, and water levels along and across the Chandeleur Islands following the construction of the sand berm. Resolving cross-island gradients is critical to understanding how water level variations may transport sediment across the island (or beyond) during storms and evaluating wave dissipation across low-lying barriers. These measurements have provided boundary information to the nearshore hydro/morphodynamic models and validation for the regional-scale oceanographic model.
Sources/Usage: Public Domain. View Media Details
Site map showing the study area and the locations of the USGS instruments (CI-1, CI-2, CI-3, and CI-6), NDBC buoy 42040, and the Waveland, MS water level gauge. (Public domain.)
Time series of wave measurements
Sources/Usage: Public Domain. View Media Details
Time series of wave measurements from three of the USGS insrument sites and the NDBC buoy located 30 km southeast of the study area. (Public domain.)

 

Time series of water-level measurements made during Hurricane Isaac
Sources/Usage: Public Domain. View Media Details
Time series of water-level measurements made during Hurricane Isaac in late August, 2012. Top panel shows water-level measurements in shallow wells placed in the beach 143 m apart on either side of the island in the northern Chandeleur Islands (eastern Gulf of Mexico measurements in blue, western Chandeleur Sound measurements in purple. Also shown are observed (red) and predicted (pink) water levels at the NOS Waveland Station WYCM6 – 8747437. Middle panel is the water surface slope across the island, positive from Gulf to Sound (east to west). Low-pass filtered slopes are shown in thick black lines, unfiltered in light-gray. Bottom panel: maximum range of water surfaces during running 20-min intervals. (Public domain.)

Regional-Scale Nested Models

A regional-scale model system in the Gulf of Mexico (figure 4.) is being developed to capture, at higher resolution than discrete buoys/gages, the transformation of wind-generated waves over broad continental shelves and changes in the direction of wind and wave patterns (cold fronts, tropical storms, etc). A coupled circulation model also provides predictions of water levels and depth-dependent currents. These offshore oceanographic characteristics provide variable forcing to the nearshore system along all model boundaries where the processes are likely to display variations unresolved by observations alone, and provide an improvement over coarser resolution models which may provide insufficient resolution to capture relevant processes (figure 5, regional model shown in red). Using the regional model to investigate larger-scale processes of wave and current generation and transformation, particularly during storms, will also allow for increased understanding of regional forcing mechanisms and how, through the coupling with the nearshore models, those mechanisms have shaped and will continue to shape barrier island environments.

The regional model uses the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling framework and consists of a series of two or three nested grids with increasing spatial resolution, with the requirements of the modeling system being investigated as part of this study. The outer nest is forced using global and basin scale model output for wind (NAM and GFS; NCEP Data Products GFS and GDAS), waves (global 30’ and regional 10’ and 2’ runs of the WaveWatch3 model; https://polar.ncep.noaa.gov/), astronomical tides (ADCIRC), sub-tidal water levels and currents (HYCOM; http://hycom.org).

Nearshore Modeling

The nearshore model used to simulated island evolution due to both alongshore sediment transport driven by breaking waves and cross-shore transport primarily driven by storm overwash (e.g. potential island/berm lowering or breaching) employs a curvilinear coordinate system following the island arc. XBeach, the open source dune erosion model used here, simulates long wave propagation and runup which is a principle driver of dune erosion. Morphological change associated with water levels colliding with or overtopping the dune/berm are considered in the model as well as berm/island breaching that often occurs during storms. Inputs of wave characteristics and water levels are provided by the regional oceanographic models (item #1) in order to better resolve any water level or wave gradients across the island.

Alongshore sediment transport dominates the evolution of this barrier island during non-storm conditions. Empirical estimates of alongshore transport are derived from the previous modeling of Ellis and Stone 2006 which estimated net longshore transport rates associated with different angles of wave incidence. We match observed wave conditions over the time of the experiment to the scenarios given by Ellis and Stone 2006 to determine cumulative alongshore current transport. Comparisons between model predicted barrier island evolution and sediment transport rates and directions will be compared with geophysical surveys to determine model accuracy.

Was this page helpful?