Landlab — The Complete Guide: Erosion, Runoff and Landslide Models in Python
Landlab is a Python package for building numerical models of processes on the Earth’s surface. It provides grids and a library of ready-made process components, which you connect into one model as needed. It is widely used in geomorphology, hydrology and landscape research.
Landlab
Landlab team (CSDMS)
A Python toolkit for Earth-surface modelling — erosion, overland flow, sediment transport and landslides on a grid.
Get it from the vendorWhat you get
- Regular and irregular grids — a common base for every model component.
- Rainfall and overland flow — components for surface flow.
- Erosion and sediment transport — how the land surface changes over time.
- Flow routing — drainage directions and catchments on an elevation model.
- Landslides — a component for looking at slope stability across an area.
Who it suits
Mainly researchers and graduate students. A typical example is testing how a change in land use affects a catchment. It is a research tool that requires coding, not software for routine design of channels or culverts. The licence is MIT, free for any use including commercial work.
Related tools
For hydrological analysis of elevation models — WhiteboxTools. For a catchment hydrology model — SWAT. For a 2D flood model in Python — ANUGA.
WhiteboxTools
Whitebox Geospatial
Hundreds of geospatial analysis tools, especially strong on terrain and LiDAR point clouds.
Get it from the vendorSWAT
Texas A&M AgriLife / USDA-ARS
A watershed model — runoff, erosion, nutrients and pesticides over decades.
Get it from the vendor
ANUGA
ANU and Geoscience Australia (anuga community)
A 2D shallow-water model for floods, tsunamis and storm surge on unstructured meshes, as a Python library.
Get it from the vendor
SAGA GIS
SAGA Development Team
Advanced spatial analysis, especially on elevation models and terrain.
Get it from the vendorThe bottom line
Landlab gives ready building blocks for Earth-surface models, so you do not have to write every process from scratch. For anyone willing to code, it is an excellent starting point.