CAREER: Characterizing the Unseen Water Quality Consequences of Sunny-Day Floods in Nearshore Waters

职业：描述近岸水域晴天洪水造成的看不见的水质后果

• 批准号: 2047609
• 负责人: Natalie Nelson
• 金额: $ 50万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2047609&HistoricalAwards=false
• 关键词: CAREER; Characterizing; Unseen; Water; Quality

Sea level rise has caused frequent tidal or “sunny-day” floods in coastal areas in the USA and around the world. Tidal floods occur when high tides rise up into sewers, streets, and sidewalks. During this process, the floods can move pollutants from land into coastal waters. In spite of the strong potential for this pollution to impact human and ecological health, coastal water quality hazards caused by tidal floods are not well understood. The goal of this CAREER project is to study the ways in which tidal floods impact coastal water quality specifically focusing on fecal contamination. This goal will be achieved through the use of highly novel sensing and modeling systems that will be developed to monitor, explain, and predict water quality following tidal floods. Successful completion of this project will help engineers, local governments, and policymakers understand and mitigate risks caused by persistent tidal floods. Science teachers and undergraduate students will participate in the research and engage middle and high school students in environmental engineering, coastal sustainability, and data sciences. These efforts will increase scientific literacy and build the Nation’s STEM workforce.The overall goal of this project is to develop a fundamental understanding of how tidal floods and stormwater runoff interact to influence pollution loading in nearshore waters. The specific focus of this research is on Fecal Indicator Bacteria (FIB), a commonly used marker of sewage pollution, in order to develop explanatory and predictive models to inform the design of sustainable coastal stormwater infrastructure. To achieve this goal, the project will carry out the following research objectives: (1) measure nearshore FIB concentrations at high frequencies using novel sensing technologies, (2) develop mechanistic and statistical models to explain FIB concentration dynamics during tidal floods and storm events, as well as over longer timescales of multiple tidal cycles; and (3) develop a predictive model framework for generating near-term forecasts of bacterial contamination risk in nearshore waters. Successful completion of this project will advance process-based understanding of how storms and tidal floods influence nearshore FIB loading, information that is needed to develop engineering solutions to mitigate hazards caused by climate change. The use of FIB concentrations (a widely used pollution marker) will facilitate the use of this research by a diverse group of regulators, natural resource managers, and other decision-makers. Additionally, the investigator will develop educational programming that will: (1) train undergraduate students and secondary school science teachers in foundational principles of coastal observation and data science through involvement in research, (2) engage ~12,000 middle and high school students in coastal and data sciences, and (3) create an open-access digital repository of coding lessons that have learning objectives focused on environmental engineering foundations and data analysis skills. Recruitment efforts will focus on engaging students from underrepresented groups in environmental engineering, as well as teachers who serve large student populations from historically marginalized groups.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.

海平面上升导致美国和世界各地沿海地区频繁出现潮汐或“晴天”洪水。当涨潮涌入下水道、街道和人行道时，就会发生潮汐洪水。在此过程中，洪水会将污染物从陆地转移到沿海水域。尽管这种污染极有可能影响人类和生态健康，但潮汐洪水造成的沿海水质危害尚不清楚。该职业项目的目标是研究潮汐洪水影响沿海水质的方式，特别关注粪便污染。这一目标将通过使用高度新颖的传感和建模系统来实现，这些系统将被开发用于监测、解释和预测潮汐洪水后的水质。该项目的成功完成将帮助工程师、地方政府和政策制定者了解并减轻持续潮汐洪水造成的风险。科学教师和本科生将参与研究，并让中学生和高中生参与环境工程、沿海可持续发展和数据科学。这些努力将提高科学素养并培养国家的 STEM 劳动力。该项目的总体目标是对潮汐洪水和雨水径流如何相互作用影响近岸水域的污染负荷有一个基本的了解。这项研究的具体重点是粪便指示细菌（FIB），这是一种常用的污水污染标记，旨在开发解释和预测模型，为可持续沿海雨水基础设施的设计提供信息。为了实现这一目标，该项目将实现以下研究目标：（1）使用新型传感技术测量近岸高频 FIB 浓度，（2）开发机械和统计模型来解释潮汐洪水和风暴事件期间以及多个潮汐周期的较长时间尺度内的 FIB 浓度动态； (3) 开发预测模型框架，用于生成近岸水域细菌污染风险的近期预测。该项目的成功完成将促进对风暴和潮汐洪水如何影响近岸 FIB 载荷的基于流程的理解，以及开发工程解决方案以减轻气候变化造成的危害所需的信息。 FIB 浓度（一种广泛使用的污染标记）的使用将促进不同的监管机构、自然资源管理者和其他决策者群体对这项研究的使用。此外，研究人员将制定教育计划，以：(1) 通过参与研究，对本科生和中学科学教师进行沿海观测和数据科学基本原理的培训，(2) 让约 12,000 名中学生参与沿海和数据科学领域，(3) 创建一个开放访问的编码课程数字存储库，其学习目标侧重于环境工程基础和数据分析技能。招聘工作将侧重于吸引来自环境工程领域代表性不足群体的学生，以及为来自历史边缘群体的大量学生群体提供服务的教师。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。