Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...
This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.
This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.
Authors: |
|
|
---|---|---|
Owners: |
|
This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource. |
Type: | Resource | |
Storage: | The size of this resource is 1.9 MB | |
Created: | Feb 08, 2018 at 7:58 p.m. | |
Last updated: | Jan 10, 2019 at 7:37 p.m. | |
Citation: | See how to cite this resource |
Sharing Status: | Public |
---|---|
Views: | 2190 |
Downloads: | 84 |
+1 Votes: | Be the first one to this. |
Comments: | 1 comment |
Abstract
This activity is designed for a sophomore-junior level geomorphology course and provides a toolkit for students to explore how rock erodibility, uplift, and stream power create landscapes. As these variables are changed, the resulting landscape - visualized as a DEM and as a hypsometric curve - are altered. Students investigate how landscapes develop in response to different rock types, tectonic settings, and climate, then use hypsometric curves from the Andes (Montgomery et al., 2001) to hypothesize what rock type, tectonic, and climatic settings led to the different curves. The landscape evolution model is built using the LandLab component library (http://landlab.github.io/#/) Initial elevations are set using a random roughness grid. Diffusion, stream power erosion, flow routing, and a precipitation generator are simulated using pre-existing toolboxes in Landlab. Diffusion and erosion only occur when a storm in generated; otherwise the landscape remains static. All input parameters are called out in the Jupyter notebook rather than in a separate text file so that students can easily change one or two parameters at a time. The model output is two figures; one a digital elevation model of the landscape in planview and one a hypsometric curve of the landscape. No further output is saved or exported, but students are encouraged to record model input parameters and output in their lab assignment. After using the LandLab model, students discuss their initial predictions against their model results. Knowledge is tested using hypsometric curves from the Andes, where students must use the curve to hypothesize what the landscape conditions are (uplift, climate, rock erodibility).
Subject Keywords
Content
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
Charlie Shobe 5 years, 11 months ago
Hi Sarah,
ReplyThis is very cool! I pulled this because I wanted a quick code example for calculating hypsometric curves. One tiny change I made:
#create hypsometry curves
elevation = mg.at_node['topographic__elevation'][mg.core_nodes]*1000
Adding the [mg.core_nodes] excludes the boundary nodes, which won't ever fit the expected hypsometry pattern and are responsible for an odd-looking little deviation at one end of the hypsometric curve.
Awesome work and thanks for putting it out there for everyone,
Charlie Shobe
New Comment