SCC-IRG Track 1: Connecting Farming Communities for Sustainable Crop Production and Environment Using Smart Agricultural Drainage Systems

SCC-IRG 第 1 轨道：利用智能农业排水系统连接农业社区，实现可持续作物生产和环境

• 批准号: 2125484
• 负责人: Liang Dong
• 金额: $ 175万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2125484&HistoricalAwards=false
• 关键词: SCC; IRG; Track; Connecting; Farming; SCC; IRG; Track; Connecting; Farming

In the US, agricultural drainage infrastructure benefits 22.6 Mha of cropland and is valued at ~$100B. As a proportion of total croplands, drained croplands produce a disproportionately large amount of grain but also release a disproportionately large amount of eutrophying nutrients to aquatic ecosystems. Drainage systems include individually-owned field drains that depend on the function of community-owned main drains. Climate change and agricultural intensification are causing farmers to increase the extent and intensity of drainage leading to a pressing need to balance productivity, profitability, and environmental quality when making drainage decisions. Further, because drainage systems include individually-owned and community-owned drains, decision-making involves complex techno-economic social issues together with understanding biophysical processes and requires balancing the needs of individual farmers, drainage communities, and surrounding regions. This project will develop an integrated decision-making platform to facilitate community decision making for precise prediction and management of drainage effects on water flow, crop production, farm net returns, and nutrient loss. The platform data will be made possible by new agricultural sensors and robots, innovations in behavioral economics and analytics tools. Development of the drainage decision-making platform will be guided by farmer stakeholders—including, the Iowa and Illinois Drainage Districts Associations, a national-level agricultural drainage management coalition, and directly with farmers—forming a continuous learning environment across scientists and farmers that fosters adoption of new technologies and transfer of the research process to the next generation of scientists, engineers, and agricultural professionals. The project will build upon a suite of biophysical and social science advances in multiple areas, including bioinspired robotic snake sensors, in-situ soil nutrient sensors, computational modeling, and socioeconomics. The snake sensors will navigate through agricultural drainage networks to generate a high spatial resolution data stream about flow rates and nitrate concentrations throughout the belowground network. The soil sensors will enable continuous monitoring of nitrate dynamics. Process-based ecohydrological models, subsurface water transport models, and multiple spatiotemporal sensor outputs will be integrated to obtain high-resolution information about distributions of water and nitrate. Biophysical scenario analyses will assist decision-making for different agricultural management scenarios to balance resource use efficiency, profitability, and environmental performance. Socioeconomic science innovations will be integrated by learning how current systems are managed in the context of various heterogeneities across individuals and drainage districts, such as demographics, farm size, and presence of wetlands, and how new information provided by the proposed infrastructure interacts with human incentives and choices and consequent policy making.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.

在美国，农艺排水基础设施受益于22.6 MHA的农田，价值约为$ 100B。作为总农田的一定比例，排水的农田产生了不成比例的谷物，但也释放出对水生生态系统的不成比例的富裕营养。排水系统包括依赖社区拥有的主排水管功能的单独拥有的田间排水系统。气候变化和农业强化导致农民增加排水的程度和强度，从而在做出排水决策时迫切需要平衡生产，盈利能力和环境质量。此外，由于排水系统包括单独拥有和社区拥有的排水系统，因此决策涉及复杂的技术经济社会问题，以及了解生物物理过程，并需要平衡各个农民，排水社区和周围地区的需求。项目将开发一个综合的决策平台，以促进社区决策，以精确预测和管理对水流，农作物生产，农场净回报和营养损失的影响。新的农业传感器和机器人，行为经济学和分析工具的创新将使平台数据成为可能。排水决策平台的开发将由农民利益相关者（包括爱荷华州和伊利诺伊州排水区协会，国家水平的农业排水管理联盟）以及与农民的持续学习环境成立，培养了新技术和下一代科学家的新技术转移，包括新技术和转移的科学家，工程师培养了新技术和转移。该项目将建立在多个领域的生物物理和社会科学进步的基础上，包括生物启发的机器人蛇传感器，原位土壤养分传感器，计算建模和社会经济学。蛇传感器将通过农业排水网络导航，以生成有关整个网络中有关流速和硝酸盐浓度的高空间分辨率数据流。土壤传感器将能够连续监测硝酸盐动力学。基于过程的生态模型，地下水传输模型和多个空间颞传感器输出将集成，以获取有关水和硝酸盐分布的高分辨率信息。生物物理方案分析将有助于不同农业管理方案的决策，以平衡资源使用效率，利润率和环境绩效。社会经济科学创新将通过了解如何在个人和排水区的各种异质性的背景下如何管理当前系统，例如人口统计学，农场规模和湿地的存在，以及拟议的基础设施提供的新信息如何与人类的激励性和随之而来的政策奖励相互作用。优点和更广泛的影响审查标准。