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INFEWS/T1: Mesoscale Data Fusion to Map and Model the U.S. Food, Energy, and Water (FEW) System

INFEWS/T1：中尺度数据融合，用于绘制美国食品、能源和水 (FEW) 系统并对其进行建模

基本信息

批准号：
1639529
负责人：
Benjamin Ruddell
金额：
$ 300万
依托单位：
Northern Arizona University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1639529&HistoricalAwards=false
关键词：
INFEWS T1 Mesoscale Data Fusion

项目摘要

The Food, Energy, and Water (FEW) system is complex, vulnerable to societal and environmental changes, yet critical for national well-being. This project's major contribution is to create and exploit the first detailed mapping of the Food, Energy, and Water System of the United States. Using this capability will improve understanding of how local Food, Energy, and Water policy decisions and technologies cause ripple effects throughout the system (for example, how electricity usage in an American city affects rivers hundreds of miles away). Policies and technologies often pose trade-offs between Food, Energy, and Water systems, and this project is measuring those trade-offs so costs and benefits may be understood and balanced in future decisions. By studying how past events like droughts, storms, wars, or economic crises have affected the nation's Food, Energy, and Water System, this project is developing the capacity to anticipate the impacts of future events. The project provides an empirical basis for advances in theory and scientific modeling of the complete food-energy-water (FEW) system of the United States. The system is primarily composed of mesoscale phenomena in which regional trade, river basins and aquifers, irrigation districts, crop belts, states, tribes, counties and cities, power grids, climate gradients, and seasonal timescales interact in a dynamic, inter-connected coupled natural-human system. To advance understanding of these interactions, a reliable and complete empirical description of the FEW system is needed. This requires a dataset containing consumption, production, and bilateral trade data for the United States, with sub-county resolution. A retrospective version of this dataset (containing data from the mid-20th century to the present), will serve as a model network for the FEW system's emergent performance metrics, sustainability metrics, and supply-chain teleconnections, along with observed historical dynamics of system response, vulnerability, and resilience to stresses and shocks. A wide range of diverse and disparate (but mostly pre-existing) economic, climate, and environmental data will be assembled to create the first comprehensive empirical map of the U.S. Food, Energy, and Water system (the FEWSion v1.0-US database). This capability will then be used to achieve four high-value science and modeling objectives: (1) quantify the multiple-objective trade-offs between performance and sustainability metrics, (2) analyze historical sensitivity, vulnerability, resilience, and evolution of the FEW network with attribution to observed stresses and shocks, (3) establish the role of cities within the FEW system, and (4) provide a standards-based benchmarking assessment capability that can be used by other projects awarded under Track 1 (FEW System Modeling) and Track 3 (Research to Enable Innovative System Solutions) of this INFEWS solicitation. A public online educational tool uses this information to visualize how individual and local decisions create environmental footprints, and how those decisions create impacts throughout the food, energy, and water system.

粮食、能源和水（FEW）系统是复杂的，易受社会和环境变化的影响，但对国家福祉至关重要。该项目的主要贡献是创建和利用了美国食品，能源和水系统的第一个详细地图。使用这种能力将提高对当地食品，能源和水政策决策和技术如何在整个系统中引起涟漪效应的理解（例如，美国城市的电力使用如何影响数百英里外的河流）。政策和技术经常在食品、能源和水系统之间进行权衡，本项目正在衡量这些权衡，以便在未来的决策中了解和平衡成本和收益。通过研究过去的干旱、风暴、战争或经济危机等事件如何影响国家的粮食、能源和水系统，该项目正在发展预测未来事件影响的能力。该项目为美国完整的食物-能源-水（FEW）系统的理论和科学建模的进展提供了经验基础。该系统主要由中尺度现象组成，其中区域贸易，河流流域和含水层，灌溉区，作物带，州，部落，县和城市，电网，气候梯度和季节时间尺度在一个动态的，相互连接的耦合自然-人类系统中相互作用。为了进一步了解这些相互作用，一个可靠的和完整的经验描述的FEW系统是必要的。这需要一个包含美国消费、生产和双边贸易数据的数据集，并具有分县分辨率。该数据集的回顾版本（包含从世纪中期到现在的数据）将作为FEW系统的紧急性能指标，可持续性指标和供应链遥相关的模型网络，沿着观察到的系统响应，脆弱性和对压力和冲击的恢复力的历史动态。将汇集各种不同的（但大多是预先存在的）经济，气候和环境数据，以创建美国食品，能源和水系统的第一个全面的经验地图（FEWSion v1.0-US数据库）。这种能力将用于实现四个高价值的科学和建模目标：（1）量化绩效和可持续性指标之间的多目标权衡，（2）分析FEW网络的历史敏感性、脆弱性、弹性和演变，并归因于观察到的压力和冲击，（3）确定城市在FEW系统中的作用，以及（4）提供基于标准的基准评估能力，该能力可用于本次INFEWS征集的轨道1（FEW系统建模）和轨道3（研究以实现创新系统解决方案）下授予的其他项目。一个公共在线教育工具使用这些信息来可视化个人和地方决策如何产生环境足迹，以及这些决策如何对整个食品，能源和水系统产生影响。