landlab

name	landlab
description	Landscape evolution and surface process modelling in Python. Build 2D numerical models for erosion, hydrology, soil transport, and geomorphology. Use when Claude 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.
version	1.0.0
author	Geoscience Skills
license	MIT
tags	["Landscape Evolution","Geomorphology","Erosion","Surface Processes","Flow Routing"]
dependencies	["landlab>=2.6.0","numpy","matplotlib"]
complements	["pyvista"]
workflow_role	analysis

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

Grid	Use Case
RasterModelGrid	Regular rectangular grids (most common)
HexModelGrid	Hexagonal grids (isotropic flow)
VoronoiDelaunayGrid	Irregular point distributions
NetworkModelGrid	Channel networks only

Key Concepts

Fields and Boundaries

# Fields: data stored at grid elements (nodes, links, cells)
z = grid.add_zeros(, at=)
grid.at_node[]  


grid.set_closed_boundaries_at_grid_edges(, , , )
z[grid.core_nodes] += uplift * dt