SARRA-Py: A Python-based geospatial simulation framework for agroclimatic modeling
Year: 2025
Type: software-paper
Abstract: SARRA-Py is an open-source, Python-based adaptation of the long-standing SARRA crop model family–specifically building upon SARRA-H to enable spatially explicit agroclimatic simulations in tropical and data-limited environments. By leveraging Python's geospatial libraries (e.g., Xarray), SARRA-Py extends SARRA-H's proven crop physiology routines to large-scale, raster-based analyses, streamlines ingestion of diverse climate inputs with minimal preprocessing, and eases model customization via a modular code structure. Users interact with SARRA-Py primarily through Jupyter notebooks that provide guided workflows for data preparation, parameter configuration, and visualization of results. This design closes the gap between point-based crop models and broader geospatial frameworks, offering a practical tool for agricultural risk management, climate adaptation studies, and yield forecasting. Consequently, SARRA-Py fosters reproducible, scenario-based analyses and informs decision-making in vulnerable regions where water deficits, sparse ground observations, and climate variability threatens food security.
Source: SoftwareX
Authors: Jérémy Lavarenne, Asse Mbengue
Institutions: Centre National de la Recherche Scientifique, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, AgroParisTech, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Territoires, Environnement, Télédétection et Information Spatiale, Université de Montpellier, Agence Nationale de l'Aviation Civile et de la Météorologie, Institut de Recherche pour le Développement, UMR Espace-Dev
Language: English
Domain: Life Sciences
SDGs: Zero hunger, Climate action
Open Access status: gold
Estimated APC paid: $1,200
OpenAlex ID: W4409014844