Optimizing Qatar’s Food Import Resilience: A Multi-Objective Framework Integrating Water Requirement Variability for Key Crops
Year: 2025
Type: article
Abstract: Global food supply chains face mounting vulnerabilities due to climate change and environmental variability, with particularly severe implications for import-dependent nations like Qatar, where over 90% of food supplies rely on international trade. This high import dependency creates unique challenges, including supply disruptions, price volatility, and food security risks, especially as climate variability increasingly affects major food-exporting regions. This study develops a multi-objective optimization framework to enhance the resilience of Qatar’s food import system by integrating economic, environmental, and crop water requirement considerations, modeled as a stochastic variable. The framework addresses both average performance and worst-case scenarios using stochastic and robust optimization approaches, evaluating trade partners for three key crops—tomatoes, onions, and cucumbers. Results identify optimal suppliers that minimize costs, environmental emissions, and water usage variability, with Turkey contributing 42.10% of total imports, Iran 13.76%, and the Netherlands 9.52%. The findings demonstrate that a diversified import strategy significantly reduces vulnerability to climate-induced disruptions and improves supply chain stability. This research provides actionable insights for policymakers, including; (1) optimal supplier diversification targets to balance risk and efficiency, (2) specific trade partner recommendations based on multiple sustainability criteria, and (3) quantitative frameworks for assessing import portfolio resilience.
Source: Sustainability
DOI: 10.3390/su17052025
Institution: Hamad bin Khalifa University
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: Qatar National Research Fund
Awards: G5733352067, G8985320116
OpenAlex ID: W4407955080
