Weathering-mediated bedrock erosion

Summary: Tools for modeling the weathering-mediated erosion of bedrock. The focus is on environments with no soil or talus accumulation: for example, on steep bedrock channel walls.

Non-dimensionalized bedrock erosion rate at steady-state $\nu_{\mathrm{s}}$ vs dimensionless weathering number $\mathcal{W}$

Abstract

Weathering is an important process in bedrock river channels, but it receives less attention than on rockslopes and soil-mantled hillslopes. Sub-aerial weathering in particular weakens channel rock exposed during stage variation and makes it more susceptible to mechanical erosion. Such erosion modifies the depth-profile of rock weathering, which in turn modifies the process of weakening. Here we study how these interactions lead to a steady-state erosion rate.

Rock weakness is defined to be its propensity to erosion by flow-driven particle-impact wear. Experiments indicate such weakness is inversely proportional to tensile strength squared, and that weathering-driven weakening takes place through wetting/drying, freeze/thaw and thermal cycling at rates that diminish in a roughly exponential fashion with depth.

Two speeds control the erosion rate: (i) the speed ${\lambda} {\eta_0}$ that weathering-driven weakening propagates into the rock, where ${\eta_0}$ is the weathering rate of fresh rock and ${\lambda}$ is the e-folding depth; (ii) the raw speed of erosion of fresh rock ${u}_0$. Model behavior is parameterized by a dimensionless number equal to the ratio of these two speeds, which we call the weathering number ${\mathcal{W}}$.

For small ${\mathcal{W}}<0.25$ and slow weathering relative to erosion, the two speeds simply add and the erosion rate is approximately ${\lambda}{\eta_0} + {u_0}$. However, for ${\mathcal{W}} \gg 2.5$ and relatively fast weathering, the predicted behavior is counter-intuitive: the erosion rate is asymptotically the geometric mean of the two speeds $\sqrt{ {\lambda} {\eta_0} {u_0} }$.

The rate of weathering alone never limits the rate of erosion, and so the concept of weathering limitation does not apply in the traditional sense.

Code

The code is provided as a Python package and Jupyter notebooks.

References

  1. Inoue, T., Yamaguchi, S., and Nelson, J. M., 2017.. "The effect of wet-dry weathering on the rate of bedrock river channel erosion by saltating gravel", Geomorphology, 285, 152–161.

  2. Li, K., Ma, L., Li, X., and Peng, S., 2016. "Effect of drying-wetting cycles on triaxial compression mechanical properties of sandstone", Journal of Engineering Science and Technology Review, 9, 66–73.

  3. Stark, C.P., and Stark, G.J., 2022. "The direction of landscape erosion", Earth Surface Dynamics, 10: 383-419.

Project links

Data verified by PyPI on Jun 19, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.1.34)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for cstark from gravatar.com cstark

Credits

Author: Colin P. Stark

GitHub Statistics

Data verified by PyPI on Jun 19, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

GNU General Public License v3 (GPLv3)

Requires

Python >=3.14

Tags

geomorphology erosion bedrock weathering

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wmbe-0.1.33.tar.gz (37.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

wmbe-0.1.33-py3-none-any.whl (40.5 kB view details)

Uploaded Python 3

File details

Details for the file wmbe-0.1.33.tar.gz.

File metadata

  • Download URL: wmbe-0.1.33.tar.gz
  • Upload date:
  • Size: 37.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for wmbe-0.1.33.tar.gz
Algorithm Hash digest
SHA256 66e7ad1864bea6cab8c642d2c1700b92d72750901577f90e778d320b84b51f84
MD5 6d1fa11ad74aa0c23d1293c2834a01cf
BLAKE2b-256 fe6b2b8e04ea62776c1cd1ce4127cd408e64c05d8d41847d5320ac27d38c2912

See more details on using hashes here.

Provenance

The following attestation bundles were made for wmbe-0.1.33.tar.gz:

Publisher: pypi-publish.yml on cstarkjp/WMBE

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file wmbe-0.1.33-py3-none-any.whl.

File metadata

  • Download URL: wmbe-0.1.33-py3-none-any.whl
  • Upload date:
  • Size: 40.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for wmbe-0.1.33-py3-none-any.whl
Algorithm Hash digest
SHA256 180b2d9e842b23da348772e69288d0d5a1fcf0f5fed09c93e17fd3d5a1c92d5a
MD5 618ed2ee1bb43eaba3140d396bbedade
BLAKE2b-256 be39fed94263abff633ff582d36e90c0523bfce764d11336d8cc5751fcd83550

See more details on using hashes here.

Provenance

The following attestation bundles were made for wmbe-0.1.33-py3-none-any.whl:

Publisher: pypi-publish.yml on cstarkjp/WMBE

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page