Deo Aniket, Shirsath Paresh B, Aggarwal Pramod K
Borlaug Institute for South Asia (BISA), International Maize and Wheat Improvement Centre (CIMMYT), New Delhi 1100012, India.
Land use policy. 2024 Aug;143:107208. doi: 10.1016/j.landusepol.2024.107208.
Increasing agricultural production with current resources and technology may lead to increased GHG emissions. Additionally, large population countries like India face substantial challenges in terms of food demand, agro-ecological heterogeneity, carbon footprint and depleting natural resources, thus increasing the decision complexities for policymakers and planners. We aim to examine the potential of producing more food from available agricultural land with low-carbon (reduced GHG emissions) and resource-conscious (optimal resource use) options. The current study develops multiple calorie production and emission-centric land use using a land use optimization model wherein the calorie production and emission objective, resource and emissions constraints, and food production targets interact across multiple spatial levels. The capabilities of the developed model are demonstrated with a case study in India targeting ten crops (grown over two seasons) covering three food groups (cereals, legumes, and oilseeds). Three hypothetical scenarios for each objective of maximizing calories production (, , ) and minimizing GHG emissions (, , ) are developed concerning targets of national crop production (, ), state food groups production (, ), and state crop production(, ), with different spatial levels of constraints. A maximum growth of 11% in calorie production is observed in while mitigating 2.5% emissions. Besides, the highest emission reduction of around 30% is observed in but with no change in calorie production. Emission scenarios can spare up to 14.8% land and 18.2% water, while calorie production-maximization scenarios can spare a maximum of 4.7% land and 6.5% water. The optimization-based methodology identifies the regions of altered land use by proposing appropriate crop substitution strategies, such as increasing oilseeds in Rajasthan and soybean in east Maharashtra. Many states show conservative production growth and emission reduction with state-level crop production targets (), suggesting crop redistribution within the state alone will not be sufficient unless improved technologies are introduced. The maximum growth and mitigation potential estimated in this study may be affected by climate shocks; therefore, introducing the improved technologies needs to be coupled with a crop redistribution mechanism to design climate-resilient and futuristic land use systems. The proposed land use model can be modified to incorporate climate change effects through consideration of scenarios of changed crop yields or through direct/indirect coupling with dynamic crop simulation models.
利用现有资源和技术增加农业产量可能会导致温室气体排放量增加。此外，像印度这样的人口大国在粮食需求、农业生态异质性、碳足迹和自然资源枯竭方面面临巨大挑战，这增加了政策制定者和规划者决策的复杂性。我们旨在研究通过低碳（减少温室气体排放）和资源节约型（优化资源利用）方案从现有农业用地生产更多粮食的潜力。当前研究使用土地利用优化模型开发了多种以卡路里产量和排放为中心的土地利用方式，其中卡路里产量和排放目标、资源和排放约束以及粮食生产目标在多个空间层面相互作用。通过针对印度的一个案例研究展示了所开发模型的能力，该案例研究针对十种作物（分两季种植），涵盖三个食物类别（谷物、豆类和油籽）。针对国家作物产量（ ， ）、邦食物类别产量（ ， ）和邦作物产量（ ， ）目标，在不同空间约束水平下，针对卡路里产量最大化（ ， ， ）和温室气体排放最小化（ ， ， ）的每个目标制定了三种假设情景。在情景 中观察到卡路里产量最大增长11%，同时减排2.5%。此外，在情景 中观察到最高减排约30%，但卡路里产量没有变化。排放情景最多可节省14.8%的土地和18.2%的水，而卡路里产量最大化情景最多可节省4.7%的土地和6.5%的水。基于优化的方法通过提出适当的作物替代策略，如在拉贾斯坦邦增加油籽种植和在马哈拉施特拉邦东部增加大豆种植，确定了土地利用变化的区域。许多邦在邦级作物产量目标（ ）下显示出保守的产量增长和减排，这表明仅在邦内进行作物重新分配是不够的，除非引入改进技术。本研究估计的最大增长和减排潜力可能会受到气候冲击的影响；因此，引入改进技术需要与作物重新分配机制相结合，以设计具有气候适应能力和未来性的土地利用系统。所提出的土地利用模型可以通过考虑作物产量变化情景或通过与动态作物模拟模型直接/间接耦合来纳入气候变化影响进行修改。
