This study presents a novel data-driven approach designed to address the intricate link between climate change and agriculture, focusing on rice farming in Southeast Asia. By using advanced modelling and optimization tools, namely ARX models and Model Predictive Control, it aims to control the temperature anomaly across fifteen world's subregions. Using ARX models to downscale the global temperature anomaly, the approach allows the evaluation of local climate effects. The methodology is applied to evaluate the impact of climate change on rice production in Southeast Asia, projecting potential outcomes under different emission scenarios. By optimizing greenhouse gas emissions, particularly carbon dioxide and methane, the goal is to keep the temperature anomaly below critical thresholds, ensuring resilient rice production, supporting food security, and minimizing economic and social costs.

The impact of optimal climate change control on rice production in critical regions: the case of Southeast Asia

De Nardi, Sabrina;Sangiorgi, Lucia;Raccagni, Sara;Carnevale, Claudio
2024-01-01

Abstract

This study presents a novel data-driven approach designed to address the intricate link between climate change and agriculture, focusing on rice farming in Southeast Asia. By using advanced modelling and optimization tools, namely ARX models and Model Predictive Control, it aims to control the temperature anomaly across fifteen world's subregions. Using ARX models to downscale the global temperature anomaly, the approach allows the evaluation of local climate effects. The methodology is applied to evaluate the impact of climate change on rice production in Southeast Asia, projecting potential outcomes under different emission scenarios. By optimizing greenhouse gas emissions, particularly carbon dioxide and methane, the goal is to keep the temperature anomaly below critical thresholds, ensuring resilient rice production, supporting food security, and minimizing economic and social costs.
2024
IFAC-PapersOnLine
Ateneo di appartenenza
PE1_19 Control theory and optimization
PE7_1 Control engineering
Inglese
22nd IFAC Conference on Technology, Culture and International Stability, TECIS 2024
2024
irl
58
226
231
6
Elsevier B.V.
ARX models; Climate Change; Climate Downscaling; Data-driven modelling; Model Predictive Control; Optimization Algorithm; Social Security
no
Goal 13: Climate action
Goal 2: Zero hunger
none
De Nardi, Sabrina; Sangiorgi, Lucia; Raccagni, Sara; Carnevale, Claudio
273
info:eu-repo/semantics/conferenceObject
4
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/619385
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