改进粒子群算法在农业种植结构优化中的应用

【目的】促进地区农业水资源高效利用,在保证粮食安全的基础上,降低灌溉需水量,推动农业节水、提高产量和效益。【方法】以安阳市为例,以经济、社会、生态和水资源效益最大为综合目标,引入惯性权重衰减和粒子变异策略,建立了基于改进粒子群算法的多目标农业种植结构优化模型。【结果】通过对现状水平年2018年、规划水平年2025年(近期)、2035年(远期)的种植结构调整,在结合现状缺水程度下,压减耗水量大的小麦、玉米等粮食作物种植比例,增加油料、蔬菜及食用菌等经济作物种植比例,经济、社会、生态、水资源目标的综合效益分别提升13.59%、10.90%、9.82%;同时,在满足农作物全生育期需水量的情况下,缺水率分别缩减9.02%、9.56%、9.95%,在一定程度上缓解了农业水资源供需矛盾。【结论】改进粒子群算法使种植结构得到平衡优化,在提高综合效益及产量的同时能够降低灌溉需水量。

An Improved Particle Swarming Optimization Method to Optimize Cropping Systems

【Background and objective】Sustaining agricultural production in regions with water scarcity is a concern in many countries. Developing water-saving irrigation and restructuring cropping systems offer one solution. The purpose of this paper is to propose a method showing how cropping system in a region can be optimized to balance water supply and demand for water from different sectors.【Method】We took Anyang in north Henan province as an example, with objective of the optimization to balance economic, social ecological benefits from limited water resources. We used the strategies of inertia weight decay and the particle mutation to establish the multi-objective agricultural planting structure, and solved it by an improved particle swarm optimization method. The optimal results were obtained from analytic hierarchy process(AHP) by processing the pareto solution set and preference-selecting.【Result】To balance water use for all sectors, the studied region should reduce the areas of staple crops, including wheat and corn, which are more water-demanding, and increased the areas of cash crops, such as oil-bearing,vegetables and edible fungus. This adjustment can improve the overall benefits and ameliorate the current imbalance between water supply and water demand, and meet demand of the crops for water in most of their growth seasons.Implementation of the optimized cropping systems can reduce water shortage ratio by 9.02%, 9.56% and 9.95% in the base year(2018), and 2025 and 2035 respectively, with their associated overall benefits increased by 13.59%,10.90%, 9.82%, respectively. The optimized cropping systems still meet the demand of 386.60 kg/a per capita for grains. The downside of the optimized cropping systems is that the increased cash-crop areas would be labor-intensive and, depending on the cash crop market, could compromise farmers' profits. In the long term, the optimized systems will reduce fertilizer use compared with the level in 2018, but fertilizer application in total will still exceed the limit of 225 kg/ha deemed to be the safe threshold. It hence could risk soil and environmental pollution.【Conclusion】We proposed a method to help optimize cropping structure with the aim to reduce agricultural water use and ensure food security. Case study shows the pros and cons of the optimized results. Its implementation needs to consider the fluctuation in both food and labor markets, as increasing planting areas of cash crops will be labor intensive.