Integrated Arable Land Optimization through Portfolio Optimization for Sustainable Agriculture: A Case Study in Uzbekistan

In this research, our objective is to enhance the efficiency of agricultural land allocation using portfolio optimization to promote a sustainable agriculture system. We will conduct a case study in Uzbekistan, a country with a semi-arid climate containing limited cultivable land, accounting for less than 10%. Additionally, the region faces constraints in water resources, relying mainly on the Amu Darya and Syr Darya rivers for agricultural water. Given the significant role of agriculture in the country's economy, optimizing land allocation becomes crucial for conserving water, increasing yield, and enhancing productivity. The study focuses on seven crops, namely barley, maize, potato, rice, tomato, watermelon, and wheat, and employs a linear programming model utilizing Markowitz portfolio optimization for land allocation. This financial technique, which integrates parameters such as risk and return, is adapted to optimize land allocation based on crop production values. The approach involves defining initial land based on crop weights, followed by a second model where the initial weight of each crop is optimized based on the outcomes of the initial land model. The optimization in this model is oriented towards maximizing the production value of the crops. In the following, a sensitivity analysis is conducted to the obtained outcomes from the model, by varying the risk parameter (lambda) to assess its impact on land allocation and optimization. Finally, a model estimating the water consumption of each crop according to their respective land distribution is presented. Keywords: Agriculture, Crop Production, Land-use, Portfolio Optimization