aris_lite 0.3.0

Implementation of the ARIS-lite model package.

ARIS-lite

ARIS models plant growth based on environmental parameters. The model draws on the references at the bottom.

🌱 state

The model has been validated against the original ARIS model. This is not a stable software - future changes may break your work, but I will try not to. Canonical CLI namespace is now rooted at aris. Legacy flat commands and legacy module-level main*/cli functions are deprecated and will be removed in 0.4.0.

🪛 usage

Small datasets (in-memory):

1. aris 1go "winter wheat" "maize" input.zarr output.zarr

Yearly staged processing:

1. aris calc waterbudget -m snow 2019 2020 2021 2022 2023
2. aris calc pheno 2019 2020 2021 2022 2023
3. aris calc waterbudget -m soil 2019 2020 2021 2022 2023
4. aris calc yield -m both 2019 2020 2021 2022 2023 --yield-max <PATH> --yield-intercept <PATH> --yield-params <PATH>

Notes:

• yearly path conventions default to ../data and can be changed via --base-dir
• yield mode requires explicit parameter inputs (--yield-max, --yield-intercept, --yield-params)

Optional compatibility (deprecated until 0.4.0): aris-1go, aris-calc-waterbudget, aris-calc-pheno, aris-calc-yield.

✨ features

• calculate water up-take coefficients ("Kc factors") for winter wheat, spring barley, maize, soybean, norm potato, and grassland based on daily air surface temperature
• calculate soil water content and evapotranspiration
• compute daily crop-specific stress index based on maximum surface air temperature and soil water saturation
• estimate crop-specific yield depression (%) from stress indicators

📑 API documentation

https://aris-lite.readthedocs.io

🔗 dependencies

• dask, numpy, pandas, snowmaus, xarray, zarr
• meteorological data
• soil water capacity data

⚠️ limitations

• hard-coded observable names, e.g. "max_air_temp"
• stressor-yield depression relation needs to be provided

💸 funding

The implementation of ARIS-lite in Python, this repository, is funded by the Austrian Research Promotion Agency (FFG, www.ffg.at) as part of CropShift.

📚 references

[1] Allen, R. G. (Ed.). (2000). Crop evapotranspiration: Guidelines for computing crop water requirements (repr). Food and Agriculture Organization of the United Nations.
[2] Eitzinger, J., Daneu, V., Kubu, G., Thaler, S., Trnka, M., Schaumberger, A., Schneider, S., & Tran, T. M. A. (2024). Grid based monitoring and forecasting system of cropping conditions and risks by agrometeorological indicators in Austria – Agricultural Risk Information System ARIS. Climate Services, 34, 1. https://doi.org/10.1016/j.cliser.2024.100478.
[3] Schaumberger, A. (2011). Räumliche Modelle zur Vegetations- und Ertragsdynamik im Wirtschaftsgrünland [Dissertation, Graz University of Technology]. https://repository.tugraz.at/publications/npc97-y3058.