Changelog¶
Changelog¶
All notable changes to GLADE are documented in this file.
The format is based on Keep a Changelog, and the project aims to follow Semantic Versioning. While the model remains under active development (pre-1.0), minor releases may introduce breaking changes to configuration and outputs.
Unreleased¶
0.1.0 - 2026-06-15¶
First public release of GLADE (Global Land, Agriculture, Diet and Emissions), a global food-systems optimization model built on PyPSA and Snakemake.
Added¶
Configuration-driven mixed-integer linear program covering the food supply chain from land and primary resources through crops, processing, livestock, trade, and human nutrition.
Sub-national optimization regions created by clustering administrative units, connected through hub-based trade networks for crops, foods, and feeds.
Spatially explicit crop production for 60+ crops with GAEZ-derived yield potentials, multi-cropping, irrigation, and rainfed/irrigated land classes.
Livestock systems with grazing and feed-based pathways, including enteric fermentation, manure management, and manure-application emissions.
Greenhouse-gas accounting (CO2, CH4, N2O aggregated to CO2-equivalent) for land-use change, spared-land sequestration, rice cultivation, fertilizer use, and residue incorporation, with configurable GWP factors.
Nutritional and food-group constraints ensuring caloric and dietary adequacy per country, plus health-impact tracking by disease cluster.
Reproducible Snakemake workflow with data retrieval, model build, scenario solve, analysis, and plotting targets, organized under
results/{config}/.Five-stage calibration pipeline (feed, food waste, food demand, cost, production stability) with git-tracked artefacts and a
tools/calibrateentrypoint.Manifest-based HPC cluster execution path for large scenario sweeps (e.g. global sensitivity analysis) without Snakemake DAG overhead.
Automatic JSON-schema validation of configuration files.
Comprehensive Sphinx documentation and tutorial notebooks, published to GitHub Pages.