Labs WMT CEM: Difference between revisions

Latest revision as of 18:44, 19 March 2020

Coastal Evolution

The Coastline Evolution Model (CEM) addresses predominately sandy, wave-dominated coastlines on time-scales ranging from years to millenia and on spatial scales ranging from kilometers to hundreds of kilometers. Shoreline evolution results from gradients in wave-driven alongshore sediment transport. The model has been used to represent varying geology underlying a sandy coastline and shoreface in a simplified manner and enables the simulation of coastline evolution when sediment supply from an eroding shoreface may be constrained. CEM also supports the simulation of human manipulations to coastline evolution through beach nourishment or hard structures. To learn more about the models in this lab, specifically the Coastal Evolution Model, CEM, you can download this presentation.

This lab includes experiments to couple the terrestrial and coastal domains. We will be looking at a river supplying sediment to a coastal zone, along which wave-driven longshore transport occurs. We will learn about the effect of incoming wave fields, the effect of sediment supply to the coast, and whether this supply happens through a single delta channel or multiple delta channels. Many deltas are classified as wave-dominated deltas, the Arno Delta in Italy is one example.

This lab will run CEM simulation with Python Modeling Tool (Pymt). If you have never used the Pymt, learn how to use it here. The Pymt allows you to set up simulations and run notebooks.

If you are a faculty at an academic institution, it is possible to work with us to get temporary teaching accounts. Work directly with us by emailing: csdms@colorado.edu

Learning objectives

Skills:

use Pymt to run CEM Model
familiarize with a basic configuration of the CEM Model
make changes to key input parameters
hands-on experience with visualizing output in Python

Topical learning objectives:

generate a wave-dominated delta
explore the influence of wave conditions (e.g., wave height, wave angle) on delta formation
explore the influence of river input on delta formation

Lab Notes

You can launch binder to directly run the Jupyter Notebook for this lab through a web browser.

>> Open a new browser window and open the Pymt read the docs page here

>> You will see that there are several example models. In this lab we will select the Coastline Evolution Model.
>> Click on the 'Launch Binder' box and it will allow you to see this lab as a Jupyter Notebook.
>> You can execute the Jupyter notebook code cells using shift -enter.

References

Ashton, A, A.B. Murray, and O. Arnoult. 2001. Formation of coastline features by large-scale instabilities induced by high-angle waves. Nature 414: 296-300., 10.1038/35104541
Ashton, A.D. and Murray, A.B., 2006. High-angle wave instability and emergent shoreline shapes: 2. Wave climate analysis and comparisons to nature. Journal of Geophysical Research 111. F04012., 10.1029/2005JF000423

More on Model description and code

CEM source code: Look at the files that have *deltas* in their name.
CEM description on CSDMS: Detailed information on the CEM model.

@@ Line 1: / Line 1: @@
 ==Coastal Evolution==
-If you have never used the Web Modeling Tool, learn how to use it [[Labs_Basic_CMT|here]]. The WMT allows you to set up simulations, but once you are ready to run them, you will need an account on the CSDMS supercomputer to submit your job.
+The Coastline Evolution Model (CEM) addresses predominately sandy, wave-dominated coastlines on time-scales ranging from years to millenia and on spatial scales ranging from kilometers to hundreds of kilometers. Shoreline evolution results from gradients in wave-driven alongshore sediment transport. The model has been used to represent varying geology underlying a sandy coastline and shoreface in a simplified manner and enables the simulation of coastline evolution when sediment supply from an eroding shoreface may be constrained. CEM also supports the simulation of human manipulations to coastline evolution through beach nourishment or hard structures. To learn more about the models in this lab, specifically the Coastal Evolution Model, CEM, you can download this [[:File:CoupledAvulsionCEMWMTversion.pptx|presentation]].
-More information on getting an account can be found here [[HPCC_Access|Beach HPCC Access]]<br>
-To learn more about the models in this lab, specifically the Coastal Evolution Model, CEM, you can download this [[:File:CoupledAvulsionCEMWMTversion.pptx|presentation]].
-These experiments couple the terrestrial and coastal domains. we will be looking at a river supplying sediment to a coastal zone, along which wave-driven longshore transport occurs. We will learn about the effect of incoming wave fields, the effect of sediment supply to the coast, and whether this supply happens through a single delta channel or multiple delta channels.
+This lab includes experiments to couple the terrestrial and coastal domains. We will be looking at a river supplying sediment to a coastal zone, along which wave-driven longshore transport occurs. We will learn about the effect of incoming wave fields, the effect of sediment supply to the coast, and whether this supply happens through a single delta channel or multiple delta channels. Many deltas are classified as wave-dominated deltas, the Arno Delta in Italy is one example.<br>
+<br>
->> Open a new browser window and open the Web Modeling Tool [https://csdms.colorado.edu/wmt-testing/WMT.html CSDMS WMT]<br>
+[[file:ArnoRiverDelta.png| Arno delta]]
+<br>
->> For this specific exercise we will be running the coupled CEM model. This means that you only choose CEM as the driver from the Component List. <br>
-[[File:ChooseCEMasdriver.png| load CEM as your model simulation driver]].
+This lab will run CEM simulation with Python Modeling Tool (Pymt). If you have never used the Pymt, learn how to use it [https://pymt.readthedocs.io/en/latest/install.html here]. The Pymt allows you to set up simulations and run notebooks.
->> CEM will now be active in the WMT. <br>
+If you are a faculty at an academic institution, it is possible to work with us to get temporary teaching accounts. Work directly with us by emailing: csdms@colorado.edu
->> CEM needs to be connected to other components to set up a coupled simulation. <br>
-[[File:CEM_usesports.png| CEM communicates with other components to get river and wave parameters]]
-Once you have added the components you can set the parameters for each by going through the different tabs in the parameter list.
+'''Learning objectives'''<br>
-Once your input is set up, you save the information. Then, you can run it by hitting the arrow run button. This way you generate a job script that can be submitted to Beach-the CSDMS High Performance Computing System.
-Provide your Beach account information (i.e. user name and password) to get the run started. The status page allows you to keep track of a simulation. From the status page you can eventually download your output files.
-<br><br>
-'''Exercise 1: Generate a wave-dominated delta''<br>
+Skills:
+*use Pymt to run CEM Model
+*familiarize with a basic configuration of the CEM Model
+*make changes to key input parameters
+*hands-on experience with visualizing output in Python
->> Run a “base-case” simulation for 6000 time-steps .<br>
+Topical learning objectives:
->> Use a constant high river bedload input of 300 kg/s. Use a modest wave height (1 m, 8 seconds). Run your scenario for a single channel with no avulsion. <br>
+*generate a wave-dominated delta
->> Scroll down to find the output settings. Specify a number of output files to generate after the simulation: these are netCDF files of water discharge, suspended sediment, and bedload. Make sure the output interval is set to 250 (every 250 timesteps). <br>
+*explore the influence of wave conditions (e.g., wave height, wave angle) on delta formation
+*explore the influence of river input on delta formation
-[[File:CEM_wavecomponenttab.png|600px]]
-<br>
->> Now run the simulation!<br>
->> Download the output files. You can use VisIT to visualize your results.
-<br>
+'''Lab Notes'''
- Question 1a
- Do you think the values for bedload flux and wave height are realistic? If not, why not? Can you give an example of a river or delta system that would be experiencing this influx of bedload and a comparable wave regime?
-<br>
- Question 1b
- Plot up your results in VisIT. Is the evolved delta planview map reminiscent of a wave-dominated delta?
- Question 1c
+You can launch binder to directly run the Jupyter Notebook for this lab through a web browser.
- Make a movie of the evolution of the delta systemevolving over time. Export the movie as a mpeg file.
-<br><br>
-'''Exercise 2: Explore the influence of wave regime on delta formation'''<br>
+>> Open a new browser window and open the Pymt read the docs page [https://pymt.readthedocs.io/en/latest/examples.html  here]
-<br>
-Now we will look at changing the wave conditions. Systematically vary the wave regime: the asymmetry of the incoming wave angle (A) and the highness factor for the incoming waves (U).
-A ranges from 0-1. A >0.5 indicates that the majority of wave energy is approaching from the left where a designation of 1.0 indicates all wave energy approaches from the left. A = 0.5 indicates wave energy approach is evenly distributed between the left and right. A < 0.5 indicates the majority of wave energy is approaching from the right where a designation of 0.0 indicates all wave energy approaches from the right.
-U controls the directional spread of the approaching waves, here split into whether waves approach from angles great than or less than the one which maximized alongshore sediment transport (~ 45 deg). High-angle waves approach with angles greater than 45 degrees and low-angle waves approach more directly onshore.  U< 0.5 indicates wave energy predominately approaching from a low angle, U> 0.5 indicates a predominance of high-angle waves. For scenarios involving delta evolution, values less than 0.5 tend to be more reasonable.
->> design  a matrix of 9 experiments with varying A and U values.
+[[File:launch_binder_cem.png|400px]]
-  Question 2a
+>> You will see that there are several example models.  In this lab we will select the Coastline Evolution Model. <br>
- Plot up your last time step for each of your experiments and describe the different delta shapes.
+>> Click on the 'Launch Binder' box and it will allow you to see this lab as a Jupyter Notebook.<br>
-<br><br>
+>> You can execute the Jupyter notebook code cells using shift -enter.
-'''Exercise 3: Explore the influence of channel avulsions on delta formation'''<br>
-Pick a base-case from your previous experiments (be sure to document your settings).
+'''References'''<br>
-Run a simulation where you assign a much higher likelihood of channel switching by changing the standard deviation of avulsion angles.
+* Ashton, A, A.B. Murray, and O. Arnoult. 2001. Formation of coastline features by large-scale instabilities induced by high-angle waves. Nature 414: 296-300., 10.1038/35104541
+* Ashton, A.D. and Murray, A.B., 2006. High-angle wave instability and emergent shoreline shapes: 2. Wave climate analysis and comparisons to nature. Journal of Geophysical Research 111. F04012., 10.1029/2005JF000423
- Question 3a
+<br>
- Can you describe a real-world delta system that would have a single channel and a high switching rate?
+'''More on Model description and code'''
- Why does this happen? If yes, add a GoogleEarth image to your notes. Plot up your final time step and describe the delta geometry.
+* [https://github.com/csdms/cem-old/tree/mcflugen/add-function-pointers CEM source code]: Look at the files that have *deltas* in their name.
+* [http://csdms.colorado.edu/wiki/Model_help:CEM CEM description on CSDMS]: Detailed information on the CEM model.
- Question 3b
- How does delta progradation change with multiple distributary channels? Run a simulation with 3 distributary channels and compare progradation rates to your ‘one-channel’ experiment.
- Make a movie of the evolution of the delta with multiple distributaries evolving with VisIt. Export the movie as an mpeg.