Optimization of cropping pattern in Minab plain using linear programming under water scarcity conditions

 
Extended Abstract
Introduction
Introduction The increasing pressure of population growth has placed significant constraints on finite land and water resources. In arid and semi-arid regions like Iran, the combination of recurrent droughts and decades of groundwater over-extraction has led to a severe water crisis. The Minab plain in Hormozgan province, a critical agricultural hub, exemplifies this challenge. It has experienced a drastic groundwater level drop of nearly 14 meters, resulting in land subsidence and water quality deterioration. To address this crisis, the “Groundwater Resources Revival and Balancing Plan” was initiated to enforce strict limits on water extraction. However, a critical gap exists between this top-down policy and on-farm implementation. The primary novelty of this study lies in bridging this gap. While numerous studies have applied Linear Programming (LP) for general crop optimization, this research specifically utilizes the LP model as a practical tool to operationalize the water balancing policy. It addresses the critical question of how farmers can adapt their cropping patterns to comply with the new legal water withdrawal limits while simultaneously maximizing their economic returns. This research, therefore, provides a scientifically-grounded strategy that aligns the goals of environmental sustainability with the economic viability of agriculture in the Minab plain. Accordingly, the following sections detail the materials and methods employed, present and discuss the results from the optimization model, and provide concluding remarks and policy recommendations.
 
Materials and Methods
The optimization problem was formulated as a Linear Programming (LP) model. The objective function was designed to maximize the total net profit (Z) from all agricultural activities, defined as: Maximize Z = Σ (BCi * Xi) where Xi are the decision variables representing the area (ha) allocated to each crop i, and BCi is the net profit per hectare of that crop. This maximization is subject to three key constraints: (1) Water Availability: Total annual water consumption (Σ Vi * Xi) must not exceed the sum of available surface water and the legally mandated groundwater limit of 57.92 MCM. (2) Land Availability: The total cultivated area (Σ Xi) must be less than or equal to the total arable land. (3) Cultivation Bounds: The area for each crop (Xi) must remain within its observed historical minimum and maximum levels to ensure market stability and reflect practical farming conditions.This study was conducted in the Minab plain, located in southern Iran, which covers an area of approximately 652 km². The region’s water supply is derived from both surface sources, primarily the Esteghlal Dam on the Minab River, and groundwater extracted from the alluvial aquifer. To develop the optimization model, a comprehensive dataset was compiled for twenty major crops cultivated in the area, covering grains, vegetables, melons, and forage crops.This data, sourced from the Jihad-e-Agriculture Organization, the Regional Water Authority, and national statistical databases, included historical cultivation areas (minimum and maximum bounds), crop yield, production costs, and market prices. Crop water requirements were calculated using the NetWat software, which considers local climatic conditions and specific plant characteristics. A Linear Programming (LP) model was formulated to solve the resource allocation problem. The model’s objective function was designed to maximize the total net profit, calculated as the sum of net returns from all cultivated crops. The model was subjected to a set of critical constraints: (1) Water resource availability, limiting total water consumption to the sum of surface water allocation and the permissible groundwater withdrawal of 57.92 million cubic meters (MCM) as stipulated by the balancing plan; (2) Land availability, ensuring the total cultivated area does not exceed the available arable land; (3) Crop area limits, restricting the cultivation area for each crop to be within its observed historical minimum and maximum levels to ensure market stability and crop diversity. To evaluate the impact of water management practices, the model was executed under two distinct irrigation efficiency scenarios: Scenario 1 with 53% efficiency, representing the current situation, and Scenario 2 with 65% efficiency, representing an improved condition achievable through modern irrigation technologies.
 
Results and Discussion
The results of the Linear Programming model provided distinct optimal cropping patterns for the two irrigation efficiency scenarios. Under Scenario 1 (53% efficiency), the optimal solution allocated a total of 13,949 hectares for cultivation, generating a maximum net profit of 8.37 trillion Rials. In this scenario, the cultivation areas for most crops were set at their minimum allowable limits, with the exception of highly profitable crops like leafy vegetables, which were allocated a larger area. This indicates that under current efficiency levels, water scarcity is the primary limiting factor for agricultural expansion. In contrast, under Scenario 2 (65% efficiency), the model recommended a significantly larger total cultivation area of 21,382 hectares, resulting in an increased net profit of 10.55 trillion Rials. This represents a 53% increase in cultivated land and a 26% rise in profit compared to the baseline scenario. The improved water use efficiency allowed for the expansion of high-value crops such as green beans, peppers, cucumbers, and leafy vegetables to their maximum allowable cultivation limits. A crucial finding is that both optimal scenarios successfully operated within the mandated groundwater withdrawal limit of 57.92 MCM. This is a substantial reduction compared to the average historical consumption of approximately 65.9 MCM between 2011 and 2014. Furthermore, the net profits generated under both optimized scenarios were significantly higher than the profits recorded in those historical years. This demonstrates that a scientifically planned cropping pattern can simultaneously achieve the dual goals of reducing groundwater over-extraction and enhancing farmers’ economic returns.
 
Conclusions
This study successfully demonstrated the effectiveness of Linear Programming as a powerful tool for optimizing cropping patterns to address the intertwined challenges of water scarcity and economic viability in the Minab plain. The findings conclusively show that it is possible to increase farmers’ net profits while adhering to strict groundwater withdrawal limits necessary for aquifer restoration. The research highlights that improving irrigation efficiency is the most critical lever for unlocking the region’s agricultural potential. A transition from the current 53% efficiency to a more achievable 65% can substantially increase both the cultivated area and farmer income, creating a strong economic incentive for adopting sustainable practices. The practical implications of this work are significant; the developed model serves as a robust decision-support tool for policymakers and water resource managers. It is recommended that local agricultural authorities promote the outputs of this model and facilitate the adoption of modern irrigation technologies through supportive policies and subsidies. By aligning the financial interests of farmers with the long-term goal of water resource sustainability, this approach offers a tangible and effective pathway to reviving the Minab aquifer while ensuring a prosperous agricultural future for the region.