Abstract
This paper presents a multipurpose optimization algorithm (MOA) to optimize crop patterns under climate change, minimizing water use and maximizing crop revenue while enforcing food security and regional water security constraints. An application of the MOA yields a total of 12 Pareto fronts for 20-year horizons centered on 2030, 2050, 2070, and 2090 under representative concentration pathways (RCPs) 2.6, 4.5, and 8.5, each of which is associated with specific land use conditions. The results show that crop production must increase due to population growth. However, climate projections for the study region in eastern Iran indicate unsuitable conditions to support the incremental production. This paper's optimization results show that 89%, 73%, and 48% of optimal crop production are achievable considering food-safety constraints in 20-year periods centered on 2050, 2070, and 2090, respectively. This paper’s results indicate that revenue would increase, water use would decline, and environmental sustainability would be reached in the study area under the optimized cropping patterns.
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The data supporting this study's findings are available from the corresponding author upon reasonable request.
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The codes that support the findings of this study are available from the corresponding author upon reasonable request.
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The authors thank Iran's National Science Foundation (INSF) for its support for this research.
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OBH helped in conceptualization, supervision, project administration. AA and BZA contributed to software, formal analysis, writing—original draft. KA and HAL performed validation, writing–review & editing.
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Arefinia, A., Bozorg-Haddad, O., Ahmadaali, K. et al. Cropping patterns based on virtual water content considering water and food security under climate change conditions. Nat Hazards 114, 1709–1721 (2022). https://doi.org/10.1007/s11069-022-05443-3
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DOI: https://doi.org/10.1007/s11069-022-05443-3