landlab

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Landlab - Surface Process Modelling

Landlab - 地表过程建模

Quick Reference

快速参考

python

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

python

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')

undefined

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')

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Grid Types

网格类型

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

网格类型	适用场景
`RasterModelGrid`	规则矩形网格（最常用）
`HexModelGrid`	六边形网格（各向同性水流）
`VoronoiDelaunayGrid`	不规则点分布网格
`NetworkModelGrid`	仅适用于河道网络

Key Concepts

核心概念

Fields and Boundaries

字段与边界

python

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python

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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

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grid.set_closed_boundaries_at_grid_edges(True, True, True, False) z[grid.core_nodes] += uplift * dt # Core nodes exclude boundaries

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Essential Operations

核心操作

Flow Routing

水流路径模拟

python

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']

python

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

河流动力侵蚀

python

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

python

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

山坡扩散

python

from landlab.components import LinearDiffuser

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

python

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

加载/保存DEM数据

python

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

python

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

多组件模型

python

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

python

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

适用场景与替代工具

Use Case	Tool	Why
Landscape evolution modelling	Landlab	Modular components, Python-native
Basin-scale stratigraphy	Badlands	Focus on sediment deposition and basin fill
Topographic analysis (MATLAB)	TopoToolbox	Mature MATLAB toolkit for DEM analysis
Simple diffusion/erosion	Custom numpy	Fewer dependencies for basic models
Coupled surface-subsurface	Landlab	Components for hydrology + geomorphology
Channel network extraction	Landlab or pysheds	Both handle flow routing well
Soil production and transport	Landlab	Dedicated weathering and soil components
Teaching geomorphology	Landlab	Clear 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.

适用场景	工具	原因
地形演化建模	Landlab	模块化组件，原生支持Python
盆地尺度地层学	Badlands	专注于沉积物沉积与盆地填充
地形分析（MATLAB）	TopoToolbox	成熟的MATLAB地形分析工具包
简单扩散/侵蚀模拟	自定义numpy实现	基础模型依赖更少
地表-地下耦合模拟	Landlab	包含水文与地貌学组件
河道网络提取	Landlab 或 pysheds	两者均能很好处理水流路径模拟
土壤生成与搬运	Landlab	有专门的风化与土壤组件
地貌学教学	Landlab	组件API清晰，教程完善

选择Landlab的场景：你需要一个模块化、基于组件的框架，用于整合多种地表过程（侵蚀、扩散、水流路径、风化）的地形演化模拟。

选择Badlands的场景：你的研究重点是盆地尺度的地形演化，且强调沉积物搬运与地层结构。

选择自定义numpy实现的场景：你只需要简单的二维扩散或河流动力模型，无需完整组件框架的开销。

Common Workflows

常见工作流

Landscape Evolution Model with Erosion and Uplift

包含侵蚀与抬升的地形演化模型

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

创建合适尺寸与间距的
```
RasterModelGrid
```
初始化
```
topographic__elevation
```
字段（平坦地形加噪声，或加载DEM）
设置边界条件（开放一个边缘作为出口，关闭其他边缘）
创建带有指定流向算法（D8或MFD）的
```
FlowAccumulator
```
创建带有侵蚀系数K_sp的
```
StreamPowerEroder
```
创建用于山坡过程的
```
LinearDiffuser
```
定义时间步长
```
dt
```
与总运行时长，选择抬升速率
运行时间循环：水流路径模拟、侵蚀、扩散，然后抬升
定期使用
```
write_netcdf()
```
或
```
write_esri_ascii()
```
保存快照
使用
```
grid.imshow()
```
可视化最终地形
分析流域面积与河道剖面
提取河流纵剖面进行陡峭度分析

Common Issues

常见问题

Issue	Solution
Flat areas block flow	Add small random noise to initial topography
Boundary effects	Ensure at least one open boundary edge for drainage
Unstable erosion	Reduce `dt` or `K_sp` ; check Courant condition
Wrong field name	Use exact Landlab names: `'topographic__elevation'` , `'drainage_area'`
Memory with large grids	Reduce grid resolution or use `NetworkModelGrid` for channels only

问题	解决方案
平坦区域阻塞水流	为初始地形添加少量随机噪声
边界效应	确保至少有一个开放边界用于排水
侵蚀模拟不稳定	减小 `dt` 或 `K_sp` ；检查Courant条件
字段名称错误	使用Landlab规定的准确名称： `'topographic__elevation'` 、 `'drainage_area'`
大型网格内存不足	降低网格分辨率，或针对河道使用 `NetworkModelGrid`

Tips

小贴士

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

先设置边界 - 在添加组件之前完成边界设置
使用core_nodes - 排除边界节点进行操作
检查字段名称 - 组件需要特定名称（例如'topographic__elevation'）
从简单开始 - 逐步添加组件并验证每个步骤

References

参考资料

Components Reference - Available components by category
Grids Reference - Grid types and configuration

组件参考 - 按分类列出可用组件
网格参考 - 网格类型与配置说明

Scripts

脚本

scripts/erosion_model.py - Basic erosion model template

scripts/erosion_model.py - 基础侵蚀模型模板