Spokes: MEDIUM: MIDWEST: Collaborative: An Integrated Big Data Framework for Water Quality Issues in the Upper Mississippi River Basin

该项目将开发一个网络基础设施框架，以促进对密西西比河上游流域（UMBB）农业实践的有效管理及其对水资源的影响的研究。 利用数据驱动的信息技术进行大规模数据采集、整合、分析和可视化，将加速知识、经验和共享资源的传播（例如，技术、设备和人员）。 该项目的关键要素是一个新的网络平台，上密西西比信息系统（UMIS），它将提供丰富的时空水文环境中的水质数据。 UMIS直接解决了美国国家工程院确定的三个重大工程挑战：i）提供清洁饮用水; ii）管理氮循环; iii）设计科学发现的工具。 UMIS将立即开始促进数据访问、整合和科学发现，以应对UMBB的水质挑战。UMIS将在气象、水文和地理环境方面提供基于互联网的水质信息开放访问，为利益相关者提供几乎无穷无尽的潜在利益。 例如，UMIS的实验设计将使研究人员能够研究空间尺度、各种土地利用和农业实践的效率，以改善水质，以及气候变化对土地管理和水质的影响。 决策者、生产者和推广人员将能够评估当地（例如，最佳管理实践）与系统级（例如，旨在减少污染、优化资源利用和评估竞争目标之间的权衡的解决方案。 对于所有利益相关者，UMIS将支持伙伴关系和合作，增加有关关键自然资源的信息传播，以增强各级利益相关者的能力，并为科学数据的交流制定新标准。该奖项反映了NSF的法定使命，并被认为值得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来支持。

This project will develop a cyberinfrastructure framework to facilitate research on the efficient management of agricultural practices and their impact on water resources in the Upper Mississippi River Basin (UMRB). Large-scale data acquisition, integration, analysis, and visualization using data-enabled information technologies will accelerate the dissemination of knowledge, experience, and shared resources (e.g., technology, equipment, and people) among communities and partners. The key element of the project is a new cyber platform, the Upper Mississippi Information System (UMIS), which will provide water quality data within a rich spatio-temporal hydrologic context. The UMIS directly addresses three of the Grand Challenges for Engineering identified by the National Academy of Engineering: i) provide access to clean drinking water; ii) manage the nitrogen cycle; and iii) engineer the tools of scientific discovery. The UMIS will immediately begin facilitating data access, integration, and scientific discovery for water quality challenges in the UMRB. UMIS will offer internet-based open access to water quality information in its meteorological, hydrological, and geographical context, providing almost endless potential benefits for stakeholders. For example, the experimental design of the UMIS will enable researchers to study spatial scaling, efficiency of various land use and agricultural practices to improve water quality, and the impact of climate change on land management and water quality. Decision-makers, producers, and extension staff will be able to assess the relative efficacy of local (e.g., best management practices) versus system-level (e.g., state programs) solutions designed to reduce pollution, optimize the use of resources, and evaluate tradeoffs among competing objectives. For all stakeholders, the UMIS will support partnerships and collaborations, increase dissemination of information about a critical natural resource to empower stakeholders at all levels, and set new standards in the communication of scientific data.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.