- This Python code implements the eikonal model to compute the spatial organization of planar hillslopes bounded at a threshold angle.
- The results obtained using this model have been tested for accuracy in diverse geologic settings and hydroclimatic conditions.
- In terms of data requirement, the model needs solely the shape of the boundary enclosing the landscape to produce the topography.
https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2023GL105710
- The code is presented as a jupyter notebook, which can be installed using pip as
pip install notebook
or using Condaconda install -c conda-forge notebook
. - Required Python libraries are numpy shapely libraries, which can be installed using pip as
pip install numpy
andpip install shapely
, respectively. - The jupyter notebook also uses the matplotlib library, which can be installed as
conda install -c conda-forge matplotlib
or using Condapython -m pip install -U matplotlib
.
- A file providing the boundary condition for the model. As an example, file Downstream_Boundary.npy in the current repository is the 2D array that provides the x and y coordinates of the enclosing boundary.
Each number in the list below explains the operations and functions of the particular cell in the Jupyter Notebook.
- Import relevant packages from the libraries mentioned above.
- Get the input boundary (x and y coordinates), threshold angle, and the raster resolution.
- Initialize the shapely polygon based on the boundary given and plot it.
- Use the defined polygon to create the eikonal topography.
- Visualize the computed topography, along with the red boundary.
- Fill the elevation field outside the boundary with null values and visualize the final eikonal topography.
For more information about this research, you can reach out to me: Shashank Kumar Anand.