Multi-Criteria Decision-Making Assessment of Irrigated Forage Maize in Iran Using TOPSIS with OPLO–POCOD-Derived Criterion Weights

Articles in Press

Document Type : Research Paper

Authors

1 Department of Water Resources and Environmental Engineering, Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran

2 School of Engineering, Damghan University, Damghan, Iran

Abstract

Agriculture plays a pivotal role in Iran’s economy, food security, and rural livelihoods, yet it faces significant challenges due to water scarcity, climatic variability, and resource misallocation. Efficient allocation of water resources and optimal cropping patterns are critical for sustainable forage maize production. This research integrates the OPLO–POCOD and TOPSIS methods to evaluate provincial suitability for irrigated forage maize cultivation. OPLO–POCOD was applied to derive objective weights for key indicators, including available agricultural water, precipitation, water consumption, crop yield, and water productivity. These weights were subsequently incorporated into TOPSIS to rank provinces based on their proximity to ideal resource and climatic conditions. Results reveal pronounced spatial disparities between actual cultivated areas and optimal potential. Provinces such as Khuzestan, Fars, West Azerbaijan, and Mazandaran exhibit high suitability and significant unrealized. In contrast, South Khorasan, Bushehr, Golestan, and Hormozgan maintain extensive cultivated areas despite lower environmental suitability, highlighting inefficiencies and unsustainable pressures on water resources. The integrated OPLO–POCOD–TOPSIS framework effectively captures both indicator importance and structural disparities, providing a comprehensive assessment of provincial potential. Policy recommendations include targeted expansion in high-potential provinces, improvement of water-use efficiency in overextended regions, adoption of precision agriculture, and introduction of high-yield maize varieties. Future research should explore climate change impacts, economic constraints, and the integration of remote sensing data with multi-criteria decision-making to enhance planning and sustainability. Overall, this research offers a data-driven approach for optimizing irrigated forage maize production while aligning agricultural practices with resource availability and environmental sustainability.

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Environmental Resources Research

Articles in Press, Accepted Manuscript
Available Online from 15 June 2026

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