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CSDMS 2022: Environmental Extremes and Earthscape Evolution

Clinic 3: Component Creation with Landlab

Eric Hutton

CSDMS IF, United States
Greg Tucker CSDMS IF United States

This clinic explores how to fully engage with the Landlab library by creating your own components. It is designed for those who already have some basic familiarity with Landlab and with scientific Python programming (registration for the “Introduction to Landlab” is recommended for those who have not already learned the basics).. In this workshop we will cover an overview of object-oriented programming (OOP), and will look at several examples of existing Landlab components to understand how they are written in an OOP framework. We will write a demo component as a group, and will then move on to writing our own components in small groups.

Participants should come prepared with an idea of a process model they’d like to implement as a component. It is recommended, but not required, that participants in this workshop also register for the clinic “The Art of Modeling: From Concept to Math with Mass Balance,” in order to be equipped with an understanding of the math that will form the basis of their Landlab component.

This workshop will involve coding in Python using the CSDMS JupyterHub. If you don't already have an account, follow the instructions to sign up at:

Please acknowledge the original contributors when you are using this material. If there are any copyright issues, please let us know ( and we will respond as soon as possible.

Of interest for:
  • Terrestrial Working Group
  • Coastal Working Group
  • Marine Working Group
  • Education and Knowledge Transfer (EKT) Working Group
  • Cyberinformatics and Numerics Working Group
  • Hydrology Focus Research Group
  • Chesapeake Focus Research Group
  • Critical Zone Focus Research Group
  • Human Dimensions Focus Research Group
  • Geodynamics Focus Research Group
  • Ecosystem Dynamics Focus Research Group
  • Coastal Vulnerability Initiative
  • Continental Margin Initiative
  • Artificial Intelligence & Machine Learning Initiative
  • Modeling Platform Interoperability Initiative
  • River Network Modeling Initiative