A model for field-specific carbon flux estimation, based on the NASA Soil Moisture Active Passive (SMAP) Level 4 Carbon (L4C) model.

While this project is in active development, it's currently recommended to install the Python package in "editable" mode, using pip:

# From the directory containing setup.py
pip install -e .

During development, it's convenient to rely upon the pyl4c package for some functionality. However, pyl4c is not a hard requirement because it has some dependencies that may be difficult for some users to install (HDF5 and GDAL). To install with support for pyl4c:

# Install GDAL first, ensuring that the version matches the system library
pip install GDAL==$(gdal-config --version)
pip install -e .[pyl4c]

The test suite depends on pytest.

pip install -e .[dev]

Tests can be run with:

pytest tests/

Some tests depend on having pyl4c installed and will be skipped if the module is not available.

import numpy as np
from agstack.models import TCF
from agstack.drivers import drivers_for_tcf
from agstack.io import drivers_from_csv, params_dict_from_json

# For a single site, a CSV file containing surface meteorology
data, dates = drivers_from_csv('752731_field2_2D.csv')

# Load driver (meteorology)
drivers = drivers_for_tcf(data)

# Soil organic carbon state, e.g., from SoilGrids 250m, separated into
#    three different pools
state = np.array([[150, 150, 450]]).T

# Read in model parameters
params = params_dict_from_json('../agstack/data/SPL4CMDL_V7_BPLUT.json')

model = TCF(params, [7], state)
model.spin_up(dates, drivers)

nee, gpp, rh = model.forward_run(drivers)

Model code here is based heavily on the publicly available pyl4c package (Endsley et al. 2022). See REFERENCES for a complete list of references.

The fraction of photosynthetically active radiation (fPAR) is currently based on an empirical formula of Sentinel NDVI:

fPAR = (-18.4 + 120.3*NDVI)