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landlab

landlab

Landscape evolution and surface process modelling in Python. Build 2D numerical models for erosion, hydrology, soil transport, and geomorphology. Use when the agent needs to: (1) Model landscape evolution over time, (2) Simulate river/stream erosion, (3) Route water flow across terrain, (4) Model hillslope diffusion processes, (5) Simulate weathering and so…

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Skill 문서

GitHub

name: landlab description: | Landscape evolution and surface process modelling in Python. Build 2D numerical models for erosion, hydrology, soil transport, and geomorphology. Use when the agent needs to: (1) Model landscape evolution over time, (2) Simulate river/stream erosion, (3) Route water flow across terrain, (4) Model hillslope diffusion processes, (5) Simulate weathering and soil production, (6) Analyze drainage networks, (7) Combine multiple geomorphic processes, (8) Load/save DEM data for modeling. license: MIT metadata: version: 1.0.1 author: Geoscience Skills tags: '["Landscape Evolution", "Geomorphology", "Erosion", "Surface Processes", "Flow Routing"]' dependencies: '["landlab>=2.6.0", "numpy", "matplotlib"]' complements: '["pyvista"]' workflow_role: analysis skill_type: domain

Landlab - Surface Process Modelling

Quick Reference

from landlab import RasterModelGrid
from landlab.components import FlowAccumulator, StreamPowerEroder
import numpy as np

# Create grid
grid = RasterModelGrid((100, 100), xy_spacing=10.0)
z = grid.add_zeros('topographic__elevation', at='node')
z += np.random.rand(grid.number_of_nodes) * 0.1

# Set boundaries (open bottom edge)
grid.set_closed_boundaries_at_grid_edges(True, True, True, False)

# Create and run components
fa = FlowAccumulator(grid, flow_director='D8')
sp = StreamPowerEroder(grid, K_sp=1e-5)

for _ in range(100):
    fa.run_one_step()
    sp.run_one_step(dt=1000)
    z[grid.core_nodes] += 0.001 * 1000  # Uplift

grid.imshow('topographic__elevation', cmap='terrain')

Grid Types

GridUse Case
RasterModelGridRegular rectangular grids (most common)
HexModelGridHexagonal grids (isotropic flow)
VoronoiDelaunayGridIrregular point distributions
NetworkModelGridChannel networks only

Key Concepts

Fields and Boundaries

# Fields: data stored at grid elements (nodes, links, cells)
z = grid.add_zeros('topographic__elevation', at='node')
grid.at_node['drainage_area']  # Access existing field

# Boundaries: close all edges except outlet
grid.set_closed_boundaries_at_grid_edges(True, True, True, False)
z[grid.core_nodes] += uplift * dt  # Core nodes exclude boundaries

Essential Operations

Flow Routing

from landlab.components import FlowAccumulator

fa = FlowAccumulator(grid, flow_director='D8')  # or 'Steepest', 'MFD'
fa.run_one_step()
drainage_area = grid.at_node['drainage_area']

Stream Power Erosion

from landlab.components import StreamPowerEroder

sp = StreamPowerEroder(grid, K_sp=1e-5, m_sp=0.5, n_sp=1.0)
sp.run_one_step(dt=1000)  # dt in years

Hillslope Diffusion

from landlab.components import LinearDiffuser

ld = LinearDiffuser(grid, linear_diffusivity=0.01)  # m^2/yr
ld.run_one_step(dt=100)

Load/Save DEM Data

from landlab.io import read_esri_ascii, write_esri_ascii
from landlab.io.netcdf import read_netcdf, write_netcdf

grid, z = read_esri_ascii('dem.asc', name='topographic__elevation')
write_esri_ascii('output.asc', grid, names='topographic__elevation')
write_netcdf('output.nc', grid)  # Save all fields

Multi-Component Model

from landlab import RasterModelGrid
from landlab.components import FlowAccumulator, StreamPowerEroder, LinearDiffuser

grid = RasterModelGrid((100, 100), xy_spacing=100.0)
z = grid.add_zeros('topographic__elevation', at='node')
z += grid.node_y / 1000 + np.random.rand(grid.number_of_nodes) * 0.1
grid.set_closed_boundaries_at_grid_edges(True, True, True, False)

fa = FlowAccumulator(grid, flow_director='D8')
sp = StreamPowerEroder(grid, K_sp=1e-5)
ld = LinearDiffuser(grid, linear_diffusivity=0.01)

dt, uplift_rate = 1000, 0.001
for _ in range(500):
    fa.run_one_step()
    sp.run_one_step(dt)
    ld.run_one_step(dt)
    z[grid.core_nodes] += uplift_rate * dt

When to Use vs Alternatives

Use CaseToolWhy
Landscape evolution modellingLandlabModular components, Python-native
Basin-scale stratigraphyBadlandsFocus on sediment deposition and basin fill
Topographic analysis (MATLAB)TopoToolboxMature MATLAB toolkit for DEM analysis
Simple diffusion/erosionCustom numpyFewer dependencies for basic models
Coupled surface-subsurfaceLandlabComponents for hydrology + geomorphology
Channel network extractionLandlab or pyshedsBoth handle flow routing well
Soil production and transportLandlabDedicated weathering and soil components
Teaching geomorphologyLandlabClear component API, good tutorials

Choose Landlab when: You need a modular, component-based framework for landscape evolution modelling that combines multiple surface processes (erosion, diffusion, flow routing, weathering) in a single simulation.

Choose Badlands when: Your focus is on basin-scale landscape evolution with emphasis on sediment transport and stratigraphic architecture.

Choose custom numpy when: You only need a simple 2D diffusion or stream power model without the overhead of a full component framework.

Common Workflows

Landscape Evolution Model with Erosion and Uplift

  • Create RasterModelGrid with appropriate dimensions and spacing
  • Initialize topographic__elevation field (flat + noise, or load DEM)
  • Set boundary conditions (open one edge as outlet, close others)
  • Create FlowAccumulator with chosen flow director (D8 or MFD)
  • Create StreamPowerEroder with erosion coefficient K_sp
  • Create LinearDiffuser for hillslope processes
  • Define time step dt and total runtime; choose uplift rate
  • Run time loop: flow routing, erosion, diffusion, then uplift
  • Save snapshots at intervals with write_netcdf() or write_esri_ascii()
  • Visualize final topography with grid.imshow()
  • Analyze drainage area and channel profiles
  • Extract river long profiles for steepness analysis

Common Issues

IssueSolution
Flat areas block flowAdd small random noise to initial topography
Boundary effectsEnsure at least one open boundary edge for drainage
Unstable erosionReduce dt or K_sp; check Courant condition
Wrong field nameUse exact Landlab names: 'topographic__elevation', 'drainage_area'
Memory with large gridsReduce grid resolution or use NetworkModelGrid for channels only

Tips

  1. Set boundaries first - before adding components
  2. Use core_nodes - excludes boundary nodes for operations
  3. Check field names - components expect specific names (e.g., 'topographic__elevation')
  4. Start simple - add components incrementally and verify each

References

Scripts

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