EAR-Climate: Continental-Scale Determinants of Stream Solute Spatial and Temporal Patterns

EAR-气候：流溶质空间和时间模式的大陆尺度决定因素

• 批准号: 2129926
• 负责人: James Jawitz
• 金额: $ 42.83万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2129926&HistoricalAwards=false
• 关键词: EAR; Climate; Continental; Scale; Determinants; EAR; Climate; Continental; Scale; Determinants

This project seeks answers to foundational questions about links between landscapes and rivers, with broad societal implications for how water quality is measured and managed, and thus is relevant to environmental stewardship and restoration. Statistical models will be developed to predict spatial and temporal patterns in water quality using continental-scale data across the eastern United States. Strong existing partnerships with management agencies will be leveraged to disseminate findings, synthesized as principles for effective and efficient design of water quality monitoring programs. The approaches will be iteratively developed in collaboration with global partners, with the exchange facilitated by research workshops. Students engaged in this work will be trained in science communication for general audiences. Finally, efforts will be made to recruit and retain student and post-doc participants from underrepresented groups. Stream solute signals encode information about upstream sources, landscape filtering, and network transformations, yet a comprehensive predictive understanding remains elusive. This work seeks to understand the origins of spatial vs temporal variability in water quality patterns, answering the following specific questions: What is the relative importance of stream solute spatial vs. temporal variability? What are the drivers of stream solute spatial and temporal variability? The primary focus is on three contrasting solute groups (geogenic, biogenic, anthropogenic) with varying links to geographical, anthropogenic, hydrological, and climatological drivers. A series of predictions about controls on patterns of space-time variation will be evaluated, using a continental-scale data inventory across the eastern United States, spanning large gradients in latitude and hydroclimate zones, lithology, wetland and forest cover, and anthropogenic land use intensity. The project seeks to explain the substantial spatial variation in mean concentrations observed for all three solute groups, based on the coupled solute-specific influences of ecoregion, network position, and solute source area. Mean concentrations are expected to vary with aggregated landscape properties, such as wetland coverage or agricultural land use intensity, and mean climate conditions, such as aridity and temperature. It is hypothesized that temporal variability around the mean can be understood and explained in terms of key drivers such as flow variation, seasonality, and network position, albeit with solute-specific sensitivities. This spatial vs. temporal variance framework provides a novel template for summarizing, understanding, and predicting variation in water quality.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.

该项目寻求有关景观与河流之间联系的基本问题的答案，对如何测量和管理水质具有广泛的社会影响，因此与环境管理和恢复有关。 将开发统计模型，以使用整个美国东部的大陆规模数据来预测水质的空间和时间模式。将利用与管理机构建立强大的现有合作伙伴关系来传播发现，并合成作为水质监测计划有效和有效设计的原理。这些方法将与全球合作伙伴合作进行迭代开发，并由研究研讨会促进了交流。从事这项工作的学生将接受科学传播的培训。最后，将努力从代表性不足的群体中招募和保留学生和大约参与者。流溶质信号编码有关上游来源，景观过滤和网络转换的信息，但是全面的预测性理解仍然难以捉摸。这项工作旨在了解水质模式中空间与时间变化的起源，回答以下特定问题：流溶质空间与时间变异的相对重要性是什么？流溶质空间和时间变异的驱动因素是什么？主要的重点是三个对比鲜明的溶质组（地球，生物，人为化），与地理，人为，水文和气候驱动因素有不同的联系。将评估有关时空变化模式控制的一系列预测，使用美国东部的大陆规模数据清单，涵盖纬度和氢化气候区域，岩性，湿地和森林覆盖物以及人为的土地使用强度。该项目旨在根据生态区，网络位置和溶质源区域的耦合溶质特异性影响，解释所有三个溶质组观察到的平均浓度的实质空间变化。预计平均浓度会随汇总景观特性而变化，例如湿地覆盖范围或农业土地使用强度以及平均气候条件，例如干旱和温度。可以假设，均值周围的时间变异性可以通过关键驱动因素（例如流量变化，季节性和网络位置）来理解和解释，尽管具有溶质特异性的敏感性。该空间与时间差异框架为总结，理解和预测水质变化提供了一个新的模板。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准来通过评估来支持的。