Cropping patterns based on virtual water content considering water and food security under climate change conditions

Ali Arefinia (), Omid Bozorg-Haddad (), Khaled Ahmadaali (), Babak Zolghadr-Asli () and Hugo A. Loáiciga ()
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Ali Arefinia: University of Tehran
Omid Bozorg-Haddad: University of Tehran
Khaled Ahmadaali: University of Tehran
Babak Zolghadr-Asli: Sustainable Minerals Institute, The University of Queensland
Hugo A. Loáiciga: University of California

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 114, issue 2, No 25, 1709-1721

Abstract: 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.

Keywords: Virtual water; Climate change; Statistical downscaling model; Water security; Food security; Optimization (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-022-05443-3

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