通过土地利用建模确定资源意识和低碳农业发展途径
Aniket Deo1, Paresh B Shirsath1, Pramod K Aggarwal1
1Borlaug Institute for South Asia (BISA), International Maize and Wheat Improvement Centre (CIMMYT), New Delhi 1100012, India.
Land use policy
|August 2, 2024
概括
这项研究优化了印度的土地利用,以增加粮食生产,同时减少温室气体 (GHG) 排放. 该模型确定了作物替代策略,以平衡卡路里产量和环境影响.
科学领域:
- 农业科学 农业科学
- 环境科学 环境科学
- 优化建模的优化建模
背景情况:
- 增加农业生产以满足印度等人口密集的国家的粮食需求往往会加剧温室气体 (GHG) 排放,耗尽自然资源,并使政策决策复杂化.
- 农业生态异质性和日益增长的碳足迹对可持续的粮食生产和资源管理构成重大挑战.
研究的目的:
- 通过低碳和资源高效的方法,检查增加现有农田的粮食生产潜力.
- 开发和演示土地利用优化模型,在多个空间尺度上平衡热量生产目标与温室气体排放限制.
主要方法:
- 开发土地利用优化模型,结合热量生产和温室气体排放目标,资源限制和粮食生产目标.
- 该模型应用于印度的一个案例研究,重点关注两个季节的十种作物和三个食物组 (谷物,豆类,油).
- 多种场景的模拟:最大限度地提高卡路里产量 (国家,集团,作物水平) 和最大限度地减少温室气体排放 (国家,集团,作物水平) 在不同的空间限制下.
主要成果:
- 在"热量国家"情景下,如果温室气体排放量减少2.5%,热量产量可以增加多达11%.
- "排放组"场景实现了最高的排放减少 (约. 30%) 而不会影响卡路里产量.
- 减排场景显示,土地的潜在节约率为14.8%,水的潜在节约率为18.2%,热量最大化场景节省了4.7%的土地和6.5%的水.
- 优化确定了特定的作物替代策略,例如在拉贾斯坦邦增加油和马哈拉施特拉邦增加大豆.
结论:
- 土地利用优化模型可以确定有效的作物再分配策略,以提高粮食生产并减少对环境的影响.
- 在没有技术进步的情况下,仅仅是国家一级的作物生产目标可能是不足的;将改进的技术与作物再分配相结合,对于气候适应性至关重要.
- 拟议的模型可以调整以纳入气候变化影响,促进设计未来的土地利用系统.
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