System Dynamics Modelling of Long-term Effects of Agricultural Mechanisation on Wheat Cultivated Area and Yield

ماشین های کشاورزی

Articles in Press, Accepted Manuscript, Available Online from 11 November 2025   

Document Type: Research Article- En

DOI: 10.22067/jam.2025.95519.1432

Authors

A. Keshvari¹; A. Marzban^{* 1}; M. A. Asoodar¹; A. Abdeshahi²; M. S. Pishvaee³

¹Department of Agricultural Machinery and Mechanization, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

²Department of Agricultural Economics, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

³Department of Intelligent Systems Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

Amid escalating pressures on global food systems, driven by resource constraints, climatic variability, and rural labour shortages, agricultural mechanisation has become a strategic lever for enhancing productivity and sustainability. This study develops and applies a system dynamics model to examine the long-term effects of mechanisation on wheat cultivated area and yield in fragmented farming systems. The research begins by constructing a causal loop diagram (CLD) to conceptualise the key feedback structures governing mechanisation dynamics. Building on this framework, a stock-and-flow simulation model is formulated and empirically validated using provincial-level data from Khuzestan, Iran (2011-2022). Validation results demonstrate strong alignment between simulated and observed trends across major indicators, including power availability, mechanisation level, cultivated area, and yield. The model is subsequently used to simulate alternative policy scenarios targeting machinery fleet modernisation, water availability, and precipitation variability. In Scenario 3, a 30% increase in the machinery replacement rate leads to a 7% rise in yield and a 1% expansion in the cultivated area, relative to baseline projections. When mechanisation improvements coincide with enhanced water availability, the marginal impact of mechanisation on land expansion becomes negligible (less than 1% increase), indicating a behavioural shift among farmers toward higher-value crops under favourable hydrological conditions. In contrast, under water-scarce scenarios, wheat area expands by approximately 1-1.5%, while yield improvements remain below 3%, reflecting both the crop’s adaptability and the compensating efficiency gains enabled by mechanisation. These findings underscore the importance of accounting for water–mechanisation interactions in policy design, particularly in arid and semi-arid regions. The model offers a flexible and empirically grounded decision-support tool for policymakers seeking to improve climate resilience, optimise resource use, and foster sustainable intensification in agricultural ecosystems facing structural and environmental challenges.

Keywords

Agricultural mechanisation; Cultivated area; System dynamics; Yield

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