Simple soil profile for hydrological modelling (particularily SWAP).
Project description
simplesoilprofile
A Python package for working with soil profile data in hydrological modeling applications, particularly focused on SWAP model integration.
- Github repository: https://github.com/zawadzkim/simplesoilprofile/
- Documentation https://zawadzkim.github.io/simplesoilprofile/
Features
- Object-oriented representation of soil layers and profiles with Pydantic validation
- Support for van Genuchten parameters and physical soil properties
- Integration with the SWAP model input format
- API integration framework with example implementation for Belgian DOV
- Visualization tools for soil profile display
Quick Start
Creating a Soil Profile
from simplesoilprofile import SoilLayer, SoilProfile
# Create soil layers
topsoil = SoilLayer(
name="Topsoil",
description="Sandy loam topsoil",
theta_res=0.02,
theta_sat=0.4,
alpha=0.02,
n=1.5,
k_sat=10.0,
texture_class="sandy loam",
clay_content=10.0,
silt_content=20.0,
sand_content=70.0,
)
subsoil = SoilLayer(
name="Subsoil",
description="Clay loam subsoil",
theta_res=0.05,
theta_sat=0.45,
alpha=0.01,
n=1.3,
k_sat=5.0,
texture_class="clay loam",
clay_content=30.0,
silt_content=35.0,
sand_content=35.0,
)
# Create a profile
profile = SoilProfile(
name="Test Profile",
layers=[topsoil, subsoil],
layer_depths={
0: (0, 30), # Topsoil from 0-30 cm
1: (30, 100), # Subsoil from 30-100 cm
},
x=100.0,
y=200.0,
z=5.0,
)
Generating SWAP Input
from simplesoilprofile.models.swap import write_swap_soil_file
# Write to a SWAP soil file
with open("soil.swp", "w") as f:
write_swap_soil_file(profile, f)
Fetching Data from DOV API
from simplesoilprofile.api import DOVClient
# Create a client
client = DOVClient()
# Fetch a profile
profile = client.fetch_profile("profile_id")
Visualizing a Profile
import matplotlib.pyplot as plt
from simplesoilprofile.plotting import plot_profile
# Create a new figure
fig, ax = plt.subplots(figsize=(8, 12))
# Plot the profile
plot_profile(profile, ax=ax, show_properties=True)
plt.show()
API Integration
The package includes a flexible API integration framework that can be configured using YAML files. Here's an example configuration for a new data source:
base_url: "https://api.example.com"
endpoint: "/soil-data"
method: "GET"
response_type: "json"
layer_path: "$.data.layers"
field_mappings:
name: "$.id"
description: "$.description"
texture_class: "$.texture"
clay_content: "$.clay_percentage"
silt_content: "$.silt_percentage"
sand_content: "$.sand_percentage"
Contributing
First, create a repository on GitHub with the same name as this project, and then run the following commands:
git init -b main
git add .
git commit -m "init commit"
git remote add origin git@github.com:zawadzkim/simplesoilprofile.git
git push -u origin main
Finally, install the environment and the pre-commit hooks with
make install
You are now ready to start development on your project! The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.
To finalize the set-up for publishing to PyPI or Artifactory, see here. For activating the automatic documentation with MkDocs, see here. To enable the code coverage reports, see here.
Releasing a new version
- Create an API Token on PyPI.
- Add the API Token to your projects secrets with the name
PYPI_TOKENby visiting this page. - Create a new release on Github.
- Create a new tag in the form
*.*.*. - For more details, see here.
Repository initiated with fpgmaas/cookiecutter-poetry.
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