INFEWS: U.S.-China: Coupled FEWS Modeling for Sustainability of the Global Crop Supply Chain with a Focus on China - US Interactions

全球粮食系统面临的最大挑战是供求在空间和时间上的不匹配。农作物供应链有助于通过运输、贸易和储存缓解这些不匹配。然而，长途运输消耗大量的能源。水作为作物生产的关键资源，在各区域和各季节的分布不均匀。作为一个食物、能源和水系统（FEWS），这种相互作用以及时空异质性要求采用系统的、耦合的方法来研究全球农作物供应链，包括生产、储存、运输、分配和消费。该项目将与南京农业大学的作物研究小组合作，开发一个可扩展的框架，该框架将全球作物供应链中的决策建模为嵌入水资源和能源，社会经济和政策环境以及价格和气候因素的影响。全球农作物供应链的集成系统建模框架将通过多尺度解决方案和动态交互，将全球挑战与供应链沿着各个利益相关者的本地关注点联系起来。研究结果将使当地股东更加了解全球粮食系统面临的FEWS可持续性挑战，这将有助于他们做出更好的决策，并鼓励他们参与集体努力，以实现更公平，更可持续的全球作物系统。该提案的双重目标是：1）通过开发一个整合气候、经济、政府、社会和技术变化的框架，推进FEWS系统建模方法，提高对全球作物供应链相互作用的理解; 2）利用中国和美国形成的供应链，确定技术、社会、和政策解决方案，以提高全球农作物供应链的可持续性和弹性。本研究特意选择中美小麦和大豆供应链作为该框架的试验平台，重点是其与世界其他地区的互动，因为它们的巨大贸易量对全球粮食，能源和水的可持续性具有关键影响。世界其他地区将由修改后的全球变化评估模型（GCAM）代表。从这条特殊的美中供应链中吸取的经验教训可以应用于其他全球农作物供应链。这项研究将解决当前农业系统和综合评估模型的多种局限性（例如，GCAM）通过1）以动态的方式将气候，政策，社会经济和技术变化与全球农作物供应，需求和价格相结合; 2）从全球和地方的角度衡量全球农作物供应链的可持续性，考虑所有供应链参与者的时空分布，包括能源消耗，水资源压力，利润，公平性和弹性; 3）为空间分布的个体作物参与者开发决策工具，同时考虑定价和国际贸易等全球问题; 4）整合来自不同学科的模型，并在异构数据要求和时空分辨率下运行;该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The greatest challenges for global food systems are the spatial and temporal mismatches of their supply and demand. The crop supply chain helps to relieve these mismatches through transportation, trade, and storage. However, long-distance shipping consumes a great deal of energy. Water, as a critical resource for crop production, is unevenly distributed across regions and throughout the seasons. The interaction, as a Food, Energy, and Water System (FEWS), and spatial and temporal heterogeneity require a systematic and coupled method to study the global crop supply chain, which includes production, storage, transportation, distribution, and consumption. Teaming with the crop research group at Nanjing Agriculture University, this project will develop a scalable framework that models decision-making in the global crop supply chain as embedded in the water resources and energy, socioeconomic, and policy environments and as affected by prices and climate factors. The integrated systems modeling framework for the global crop supply chain will enable the connection of global challenges and the local concerns of individual stakeholders along the supply chain through multi-scale resolutions and dynamic interactions. The research results will make local shareholders more aware of the FEWS sustainability challenges faced by the global food system, which should help them make better decisions and encourage their engagement in collective efforts to achieve fairer and more sustainable global crop systems. The twofold objective of this proposal is 1) to advance FEWS systems modeling methodologies and improve understanding of the interactions of the global crop supply chains by developing a framework to integrate climatic, economic, governmental, societal, and technological changes, and 2) use the supply chain formed by China and the US to identify technical, societal, and policy solutions to improve the sustainability and resilience of the global crop supply chain. This research deliberately chooses the US-China wheat and soybean supply chain as a testbed for the framework, with emphasis on its interaction with the rest of the world, because their large trade volume has a critical impact on the global sustainability of food, energy, and water. The rest of the world will be represented by the modified Global Change Assessment Model (GCAM). The lessons learned from this particular US-China supply chain can be applied to other global crop supply chains. This study will address multiple limitations of the current agricultural systems and integrated assessment models (e.g., GCAM) by 1) coupling climatic, policy, socioeconomic, and technological changes with global crop supply, demand, and prices in a dynamic way; 2) measuring the global crop supply chain sustainability from both global and local viewpoints, considering spatio-temporal distribution for all supply chain players and including energy consumption, water stress, profit, fairness, and resiliency; 3) developing decision making tools for spatially distributed individual crop players with consideration of global issues such as pricing and international trade; 4) integrating models that come from different disciplines and operate with heterogonous data requirements and spatio-temporal resolutions; and 5) studying the resilience of global crop SCs under extreme scenarios.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.