A data-driven framework for assessing climatic impact drivers in the context of food security

Benso, Marcos Roberto; Silva, Roberto Fray; Chiquito Gesualdo, Gabriela; Saraiva, Antonio Mauro; Delbem, Alexandre Cláudio Botazzo; Marques, Patricia Angélica Alves; Marengo, José Antonio; Mendiondo, Eduardo Mario

doi:https://doi.org/10.5194/nhess-25-1387-2025

Articles | Volume 25, issue 4

https://doi.org/10.5194/nhess-25-1387-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Methodological innovations for the analysis and management...

https://doi.org/10.5194/nhess-25-1387-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 4

Research article

|

10 Apr 2025

Research article |

| 10 Apr 2025

A data-driven framework for assessing climatic impact drivers in the context of food security

Marcos Roberto Benso, Roberto Fray Silva, Gabriela Chiquito Gesualdo, Antonio Mauro Saraiva, Alexandre Cláudio Botazzo Delbem, Patricia Angélica Alves Marques, José Antonio Marengo, and Eduardo Mario Mendiondo

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https://doi.org/10.5194/nhess-25-1387-2025-supplement

Data sets

Climatic impact-drivers in the context of food security Marcos Roberto Benso https://doi.org/10.5281/zenodo.12612860

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This study applies climate extreme indices to assess climate risks to food security. Using an explainable machine learning analysis, key climate indices affecting maize and soybean yields in Brazil were identified. Results reveal the temporal sensitivity of these indices and critical yield loss thresholds, informing policy and adaptation strategies.