Ahmed Elghandour at PortSaid/IHE & TU Delft/ Algarve.
Benton Franklin at UNC.
Conner Lester at Duke U.
Megan Gillen at MIT/WHOI.
Meredith Leung at Oregon State.
Samuel Zapp at LSU.
Introduction
Sandy shorelines are areas of dynamic geomorphic change, evolving on timescales ranging from hours to centuries. As part of the CSDMS ESPIn workshop, this educational lab was designed to allow users to observe firsthand the long-term change of a sandy coast of their choosing and explore the processes driving that change. The CEM was developed by Ashton et al. (2001) as an exploratory model that uses wave climate characteristics to model the evolution of an idealized coastline. In this educational lab, we couple CoastSat (a python tool that extracts shoreline geometry from satellite imagery (Vos et al., 2019)) to the CEM by initializing the model with observed shorelines from anywhere in the world. The CEM is then further driven by an average wave climate derived from local buoy data. This allows users to visualize the evolution of any sandy beach in the world through time. Through an introductory-level coding exercise, users will learn how to extract complex datasets, run a geomorphic model, and explore the impact of different wave climates on a beach they care about.
Classroom organization This lab couples two coastal models: CoastSat and Coastal Evolution Model (CEM) in a jupyter notebook to allow users to explore shoreline change using real, observed shorelines and wave data.
We use CoastSat to download and extract shorelines from satellite imagery. These shorelines feed into the CEM where they are evolved by historical wave characteristics from a nearby buoy.
Learning objectives Skills
Extract shorelines from satellite imagery
Extract wave data from wave buoy
Key concepts
Explore the impact of different wave climates on shoreline evolution
Explore how changing our shoreface geomorphology alters the evolution of our coastline through time
Lab notes The lab has two Notebooks:
The first (Prepare_bathymetry_wave_inputs.ipynb), could be run on your local environment or any outside CSDMS jupyterhub environment in order to use CoastSat.
The second (cem_waves_notebook.ipynb), could be run on CSDMS jupyterhub environment , or local machine (only linux or osx). make sure you Install Pymt cem https://anaconda.org/conda-forge/pymt_cem
References
Ashton, A.D., Murray, B., Arnault, O. (2001). Formation of coastline features by large-scale instabilities induced by high-angle waves, Nature 414.
Ashton A.D., Murray A.B. (2006) High-Angle Wave Instability and Emergent Shoreline Shapes: 1. Wave Climate Analysis and Comparisons to Nature. Journal of Geophysical Research. Volume 111.
Ashton A.D., Murray A.B. (2006) High-Angle Wave Instability and Emergent Shoreline Shapes: 2. Wave Climate Analysis and Comparisons to Nature. Journal of Geophysical Research. Volume 111.
Vos K., Splinter K.D., Harley M.D., Simmons J.A., Turner I.L. (2019). CoastSat: a Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery. Environmental Modelling and Software. Vol. 122, 104528. (Open Access)