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Global scale paleo-landscape evolution model Landscape & catchments dynamic, paleo-elevations, erosion/deposition

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Global scale paleo-landscape model workflows

The workflows presented here have been designed to build, run and analyse outputs from goSPL global models.

model6.mov

gospl / Global Scalable Paleo Landscape Evolution /

gospl is an open source, GPL-licensed library providing a scalable parallelised Python-based numerical model to simulate landscapes and basins reconstruction at global scale.

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Features License: GPL v3 Language grade: Python Code style: black Total alerts

DOI

Installation & dependencies (anaconda)

via Docker

Easiest approach: not ready yet!

From a terminal

conda update conda

conda create --name gospl-global python=3.9
conda activate gospl-global
conda install pandas compilers petsc4py llvm-openmp pip netCDF4
conda install mpi4py matplotlib numpy-indexed
conda install scipy scikit-image scikit-learn
conda install h5py pymannkendall seaborn
conda install cartopy geopandas xarray
conda install basemap rioxarray rasterio
conda install meshio ruamel.yaml
conda install cython
conda install pysheds
conda install jupyterlab packaging
conda install pyvista

pip install  vtk stripy
pip install pyyaml==5.1
pip install  pyvista cmocean
pip install  richdem descartes
pip install  pyevtk itkwidgets

conda install scikit-fuzzy pre-commit
conda install imageio-ffmpeg imageio
conda install qt

conda install gmt==6.2.0

conda install pygmt
conda install pygplates

conda install numba mesplex
pip install gospl
pip install triangle

Using an environment.yml file

Copy and paste the following environment.yml file somewhere on your local hard drive:

name: gospl-global
channels:
  - conda-forge
  - defaults
  - anaconda
dependencies:
  - python=3.9
  - compilers
  - numpy
  - pandas
  - petsc4py
  - llvm-openmp
  - pip
  - netCDF4
  - mpi4py
  - matplotlib
  - numpy-indexed
  - scipy
  - scikit-image
  - scikit-fuzzy
  - scikit-learn
  - h5py
  - pymannkendall
  - seaborn
  - cartopy
  - geopandas
  - xarray
  - basemap
  - rioxarray
  - rasterio
  - meshio
  - ruamel.yaml
  - cython
  - pysheds
  - jupyterlab
  - packaging
  - pyvista
  - pre-commit
  - imageio-ffmpeg
  - imageio
  - qt
  - gmt==6.2.0
  - pygmt
  - pygplates
  - numba

  - pip:
    - pyyaml==5.1
    - vtk
    - stripy
    - meshplex            
    - gospl
    - triangle

(Note: Installing this environment will also install many dependencies, including compiled libraries. This is totally fine; even if you have these libraries already installed through your system package manager, conda will install and link for use in the environment a configuration which should be to play nicely and work with all of its components.)

Create this environment through conda

$ conda update conda
$ conda env create -f environment.yml

Activate this environment

$ source activate gospl-global

There is also an additional library that will need to be installed called plateInputs available from:

  • here in the branch named package
  • to install the library you will need to look at the README file in the github repository

This environment should be sufficient for all of the presented examples in this documentation.

Workflows

Example of 100 Ma simulation of landscape dynamic accounting for erosion and deposition using goSPL.

unconstrained.mov

Pre-processing

The first 2 folders: 1-data & 2-inputgen are used to perform some of the pre-processing steps required to create the input files for goSPL.

Folder 1-data contains the high-resolution paleo-elevation from Scotese and the associated rainfall map from Valdes et al. as well as the velocities from the plate reconstruction models. All the dataset are available either from the litterature or extracted from the Gplates software. As an example a series of initial forcing input files based on Scotese paleomaps and paleo-climate for the last 100 Ma are provided as a doi from figshare.

Folder 2-inputgen takes the data files from folder 1-data to build the goSPL inputs. For a specified resolution it creates the initial unstructured elevation mesh (mesh_X_XXMa.npz), the rainfall for considered period of time (rain_X_XXMa.npz), the goSPL nodes horizontal displacements based on considered plate tectonic model (plate_X_XXMa.npz), as well as the geometric tectonic forcing conditions (tecto_X_XXMa.npz). To build these input files, we rely on a library plateInputs that needs to be installed separetly (see previous section).

Constrained/unconstrained models

The simulation folder 3-simulations provides some examples on how to run goSPL model at global scale with different approaches to constrain the simulation with paleo-elevation model. Three goSPL input files are given and we give 2 notebooks that could be used to better constrained, unconstrained and missmatch approaches.

Post-processing

The 4-analysis folder contains a series of notebooks to analyse some of goSPL outputs. It can be used to:

  1. Evaluate major drainage systems
  2. Estimate geomorphometrics through space and time
  3. Plot longitudinal rivers profiles
  4. Analyse stratigraphic record

Temporal refinement

Often paleo-elevation reconstruction and associated plate model are provided for coarse time intervals (1 to 5 Ma increments). However in some cases, like when one want to run a ecological model, these time steps are too large and it is required to refine the temporal evolution. The 5-refine folder provides two methods to perform such refinement.

Performing regional goSPL model

For cases where the focus in on regional scale model and not global scale one, we provide a series of notebooks to create input files, run the simulation and finally output some of the results using different workflows. These are available in the 6-localSim folder.

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