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Using system dynamics (SD) approach, this paper develops a simulation model to study the behaviors and relationships within the agricultural system at national level and analysis the future scenarios. The proposed model considers three major sub-systems: demand side (population and income), supply side (land use, water resources, and productivity), and regulatory side (barriers, incentives, and support). Iranian agricultural system is modeled using this approach and the future conditions are simulated under three if-then scenarios up to 2040. The results show that under the policies as current conditions, the demand for the agricultural products will rapidly increase due to the population growth and economic development. However, agricultural land use and domestic supply does not experience much growth because of crucial limitations in the climatic conditions, available water resources, and rather low productivity; therefore, the gap will be compensated through an ever increasing import. The suggested SD model helps policy makers to identify the bottleneck points in the system based on simulation results and then, improvement policies can be made according to these bottlenecks. Some improvement policies for supply side have been proposed and effectiveness of them on increase in production and agricultural land use development has been demonstrated. By improving supply side policies alone, the Iranian government's goal of agricultural self-sufficiency is not likely to be achieved and it is essential to improve the demand side policies in this regard. The suggested model has proven to be useful for Iranian agricultural system, and its methodology could be used as a decision support tool for land use planning, policy making and managements of agricultural sector.

Agricultural land use pattern is affected by many factors at different scales and effects that are separated by time and space. This will lead to simulation models that optimize or project the cropping pattern changes and incorporate complexities in terms of details and dynamics. Combining System Dynamics (SD) and a modified Conversion of Land Use and its Effects (CLUE) modelling framework, this paper suggests a new dynamic approach for assessing the demand of different crops at country-level and for predicting the spatial distribution of cultivated areas at provincial scale. As example, a case study is presented for Iran, where we have simulated a scenario of future cropping pattern changes during 2015-2040. The results indicated a change in the spatial distribution of cultivated areas during the next years. An increase in the proportion of rice is expected in northern Iran, whereas the proportion of wheat is increasing in the mountainous western areas. Wheat and barley crops are expected to become dominant within the cropping system throughout the country regions.

Agricultural land use change is the result of interactions between different driving factors and processes at different scales. Most of models have been proposed for the land use change simulations only consider the suitability of lands and spatial competition between different land uses at microscales. But agricultural land use projection involves assessment of macro-level socioeconomic variables and driving forces. This paper suggests a dynamic modeling approach that integrates demand-driven changes in agricultural land area at macro-level with spatially explicit distribution processes at regional-scale. This approach is based on combination of two core models with dynamic top-down and bottom-up feedback loops between them, dynamic simulation model, and land use change (LUC) model. Without the spatial considerations, the dynamic model is used to project the agricultural land demands influenced by economic, demographic, technologic, and regulatory variables and their interactions at country-level. In addition, LUC model is used to simulate the downscaling of these demands between country regions based on spatial consideration of land suitability, change elasticity, spatial policies and restrictions, and competitive advantage of agriculture. Sensitivity analysis and empirical validation indicated the reliability and capability of the model for addressing the complexity of current agricultural land use changes and for investigating long-term scenarios in the future. Finally, the model is used to explore the future dynamics of Iran agricultural land use during 2015-2040 with eight-year pace. The simulation results forIran show that the water availability is the most determining factor in the distribution of agricultural lands in a way that a continuing downward trend in agriculture land areas will occur in east and northeast, as well as an upward trend in north and southwest regions of the country. The outcome of this study enhances our capacity to consider approaches from different disciplines in an integrated framework for LUC modeling and provide a decision support tool for land use planning, policy making, and managements of agricultural sector. K E Y W O R D Sagricultural area, integrated modeling, Iran, land use change, simulation model INTRODUCTIONAgricultural development is very important and also is the basis of human survival, due to their consequences for food security and environmental sustainability. 1,2 Therefore, an appropriate insight into the future developments of the agricultural sector is significantly important for both whole society and policy makers. 3 Because spatial and agricultural planning deals with ever more complex problems, and modeling orders and systematizes this complexity, simulation models considered to have great future potentials. Simulation models that predict complex developments and thus can provide decision support are rated to be important future planning instruments-providing additional information, objectifying the decision processes, and making them more transparent. 4 ...