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esurf_2023a_code

https://github.com/ruetg/esurf_2023a_code

Science Score: 57.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 2 DOI reference(s) in README
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    Academic publication links
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    Institutional organization owner
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    JOSS paper metadata
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    Scientific vocabulary similarity
    Low similarity (6.5%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: ruetg
  • Language: Python
  • Default Branch: main
  • Size: 1.27 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created almost 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme Citation

README.md

lem_optimize

This code performs a monte-carlo based iterative search for optimal landscape evolution parameters among a global (or select) set of drainage basins.

The global optimisation can be run via the montecarlo.py script, where model parameters are described there and in the text of the manuscript.

The octopus data is found here - this is only to be used for the examples.

With duplicates: https://drive.google.com/drive/folders/1yZJKymW6fAN8Gi4k0AdpU1Fxxo9cx4-S?usp=sharing

For new applications users should download the latest version from the OCTOPUS website, with more details from their paper ( https://octopusdata.org/ ; https://doi.org/10.5194/essd-14-3695-2022):

Without duplicates:

https://drive.google.com/drive/folders/1cAhyZthxAhwJhcMAwL6IzLc4cQqH4UWl

The basin DEMs can be downloaded from here: https://drive.google.com/file/d/1RFB2hERkK8OvD_2yHnJRm4W5JxzSfkvi/view?usp=sharing

More example results can be downloaded from here:

https://drive.google.com/drive/folders/1R9W7JtRz8qCmQKOF1C6x1RElE3ulPY6Q?usp=sharing

Owner

  • Login: ruetg
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this code, please cite the accompanying paper - Optimising global landscape evolution models with 10Be in Earth Surface Dynamics."
authors:
- family-names: "Ruetenik"
  given-names: "Gregory A."
  affiliation: "Czech Academy of Sciences, Institute of Geophysics"
- family-names: "Jansen"
  given-names: "John D."
  affiliation: "Czech Academy of Sciences, Institute of Geophysics"
- family-names: "Val"
  given-names: "Pedro"
  affiliation: "School of Earth and Environmental Sciences, Queens College, City University of New York"
- family-names: "Ylä-Mella"
  given-names: "Lotta"
  affiliation: "Department of Physical Geography and Geoecology, Charles University, Prague"
title: "Code and data for Ruetenik et al., (2023): Optimising global landscape evolution models with 10Be"
version: 1.0.0
date-released: 2023-09-04
url: "https://github.com/ruetg/esurf_2023a_code"
license: MIT

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