The transport of dissolved organic matter by river networks from mountains to the sea: a re-examination of the role of flow across temporal and spatial scales

河流网络将溶解的有机物从山区输送到海洋：重新审视跨时间和空间尺度的流动作用

• 批准号: 1240593
• 负责人: Mark Green
• 金额: $ 2.54万
• 依托单位: Plymouth State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-01 至 2014-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1240593&HistoricalAwards=false
• 关键词: transport; dissolved; organic; matter; river

This project will facilitate the collaboration of a group of scientists interested in delivery, transport and transformation of organic matter in a variety of surface waters. The group will synthesize data across spatial and temporal scales and bring together a multi-disciplinary team at the John Wesley Powell Center for Analysis and Synthesis. The effort will re-evaluate the fundamental relationships between discharge and DOM concentration and composition and focus on synthesizing mature datasets from small headwater basins to large coastal basins using statistical techniques and modeling. Data are available that represent a range of temporal sampling intensities from seasonal samples, to more frequent samples from automated samplers, and finally to data from continuous optical sensors. This synthesis collaboration is expected to advance scientific understanding of the processes and patterns of organic matter transport by exploring key data sets at a level of detail and scale that has not previously been attempted. The work is expected to also benefit the policy and management communities that rely on data, models, and understanding of the controls on nutrient, trace metal, and pollutant transport in river networks and to estuaries. This is a joint synthesis projects with the USGS Powell Center, Fort Collins Colorado.

该项目将促进对各种地表水中有机物的输送、运输和转化感兴趣的一组科学家的合作。 该小组将综合跨空间和时间尺度的数据，并在约翰·韦斯利·鲍威尔分析与综合中心聚集一个多学科团队。这项工作将重新评估排放与 DOM 浓度和成分之间的基本关系，并重点利用统计技术和建模来综合从小水源流域到大型沿海流域的成熟数据集。可用数据代表一系列时间采样强度，从季节性样本到来自自动采样器的更频繁的样本，最后到来自连续光学传感器的数据。这项综合合作预计将通过以前所未有的细节和规模探索关键数据集，促进对有机物运输过程和模式的科学理解。这项工作预计还将使依赖数据、模型和对河网和河口污染物输送控制的数据、模型和理解的政策和管理界受益。这是与美国地质调查局科罗拉多州柯林斯堡鲍威尔中心的联合合成项目。