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<p>Water scarcity and food security are increasingly critical concerns in semi-arid regions such as Iran, where rice cultivation remains a strategic yet resource-intensive agricultural activity. This study develops a conceptual dynamic model to simulate and evaluate the future trajectory of rice cultivation in Guilan Province, northern Iran, under conditions of uncertainty. The model integrates four interrelated components: population growth, production levels, cultivated area, and water footprint. Using data from 2011 to 2021, stochastic calibration was performed by applying probabilistic distributions to key parameters, enabling model robustness in the face of limited observed data. Performance evaluation through p-factor (81.8%) and d-factor (0.08) confirmed satisfactory model reliability. The calibrated model was then used to simulate future scenarios from 2030 to 2060 under various trade and climate assumptions. Projections indicate that maintaining current export–import patterns without efficiency improvements could result in an 18.1% increase in required cultivated area by 2060. These findings underscore the importance of proactive policy interventions and integrated planning to balance food production goals with long-term water sustainability in vulnerable agro-ecological zones.</p>

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Conceptual modeling of the rice production system: a case study of Northern Iran

  • 期刊论文

  • 发表日期：

    2025年8月5日

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  • Monireh Pasvei,
  • Afshin Ashrafzadeh,
  • Somaye Janatrostami,
  • Mohammadreza Khaledian

摘要

Water scarcity and food security are increasingly critical concerns in semi-arid regions such as Iran, where rice cultivation remains a strategic yet resource-intensive agricultural activity. This study develops a conceptual dynamic model to simulate and evaluate the future trajectory of rice cultivation in Guilan Province, northern Iran, under conditions of uncertainty. The model integrates four interrelated components: population growth, production levels, cultivated area, and water footprint. Using data from 2011 to 2021, stochastic calibration was performed by applying probabilistic distributions to key parameters, enabling model robustness in the face of limited observed data. Performance evaluation through p-factor (81.8%) and d-factor (0.08) confirmed satisfactory model reliability. The calibrated model was then used to simulate future scenarios from 2030 to 2060 under various trade and climate assumptions. Projections indicate that maintaining current export–import patterns without efficiency improvements could result in an 18.1% increase in required cultivated area by 2060. These findings underscore the importance of proactive policy interventions and integrated planning to balance food production goals with long-term water sustainability in vulnerable agro-ecological zones.