CAREER: Robust Modeling and Predictions of Stream Water Quality and Ecosystem Health

1454435(阿卜杜勒-阿齐兹)。这项研究的目标是调查和强有力地预测复杂的城市-自然流域(例如沿海城市中心)的溪流水质和生态系统健康的动态。研究的中心假设是，城市河流的生物地球化学和生态过程遵循紧急相似、尺度不变的模式和组织原则，这将导致对水质和生态系统健康的时空稳健预测。具体的研究目标是(1)确定河流水质和生态系统健康变量与水文气候、流域和土地利用、河流和沿海驱动因素/应激源之间的主要控制因素和相对联系；(2)研究河流水质和健康变量的相似性(参数减少)、尺度规律(涌现模式)和组织原则；(3)建立基于信息学的经验(即数据驱动)和基于机械的行为模型，作为生态工程工具，以获得城市河流水质和生态系统健康的时空稳健预测。综合教育目标是发展基于归纳学习的跨学科生态工程教育学(EEP)，以便(1)增加STEM相关专业的本科生保留率和少数族裔学生的毕业率，(2)增加专门从事新兴生态工程范式的研究生，以及(3)增加积极从事STEM教育/职业的K-12学生人数。这项研究将主要在南佛罗里达州进行，这是一个活的实验室，也是气候变化和海平面上升的热点；将该地区视为一个原型，世界各地复杂的城市-自然环境的案例研究。这项研究还将利用其他沿海城市中心(如纽约、洛杉矶、休斯顿)的全国可用数据，纳入美国海岸的水文气候、生物地球化学和生态梯度。该研究将利用数据分析和信息学框架来实现对城市溪流水质和生态系统健康过程的主要控制的机械性理解。它试图通过推导和利用适当的无量纲官能团来揭示城市河流的生物地球化学-生态相似性和尺度规律，这些官能团将识别不同的环境制度和水质和生态系统健康的组织原则。尺度不变的模式和新出现的组织原则将有助于形成简约的经验性和机械性行为模型，通过名义校准，可以提供对溪流水质和健康指标的时空稳健预测。这项工作将利用归纳学习方法来开发EEP案例研究，让少数族裔本科生参与研究，并为K-12学生开发简单的Excel工具。它将利用归纳学习方法开发EEP案例研究，让少数族裔本科生参与研究，并为K-12学生开发简单的Excel工具。研究成果将与相关机构(如市、县、非政府组织)分享，以改善其溪水水质和健康管理战略。EEP案例研究将被用于教授两门新的跨学科课程(由PI开发)：生态水文工程学(本科生)和生态工程学(研究生)。研究和教育成果将通过期刊出版物、会议报告、毕业论文/论文、报告、YouTube和一个项目网站广泛传播。当地和地区的高中学生和教师将通过利用现有的和发展新的合作来参与研究教育。

1454435 (Abdul-Aziz). The goal of this research is to investigate and robustly predict the dynamics of stream water quality and ecosystem health in complex urban-natural basins (e.g., coastal urban centers). The central research hypothesis is that urban stream biogeochemical and ecological processes follow emergent similitude, scale-invariant patterns and organizing principles, which will lead to spatiotemporally robust predictions of water quality and ecosystem health. Specific research objectives are to (1) identify the dominant controls and quantify relative linkages of stream water quality and ecosystem health variables in relation to the hydro-climatic, watershed and land use, in-stream, and coastal drivers/stressors; (2) investigate the similitude (parametric reductions), scaling laws (emergent patterns), and organizing principles for stream water quality and health variables; and (3) formulate informatics based empirical (i.e., data-driven) and mechanistically based behavioral models as ecological engineering tools to obtain spatiotemporally robust predictions of urban stream water quality and ecosystem health. The integrated educational objective is to develop an inductive-learning based interdisciplinary Ecological Engineering Pedagogy (EEP); in order to (1) increase retention of undergraduates and graduation of minority students in relevant STEM majors, (2) increase graduate students specializing in the emerging paradigm of ecological engineering, and (3) increase the number of K-12 students actively pursuing STEM educations/careers. The research will be primarily conducted in South Florida, a living laboratory and hot-spot for climate change and sea level rise; considering the region a prototype, case study of complex urban-natural environments around the world. The research will also utilize nationally available data for other coastal urban centers (e.g., New York, Los Angeles, Houston), incorporating hydro-climatic, biogeochemical and ecological gradients across the U.S. coasts.The research will employ a data-analytics and informatics framework to achieve mechanistic understanding on the dominant controls of urban stream water quality and ecosystem health processes. It seeks to unravel the biogeochemical-ecological similitude and scaling laws for urban streams by deriving and utilizing appropriate dimensionless functional groups, which will identify the different environmental regimes and organizing principles of water quality and ecosystem health. The scale-invariant patterns and emerging organizing principles will help to formulate parsimonious empirical and mechanistic behavioral models that, with nominal calibrations, can provide spatiotemporally robust predictions of stream water quality and health indicators. The effort will utilize inductive learning methods to develop EEP case studies, involve minority undergraduates in research, and formulate simple Excel tools for K-12 students. It will utilize inductive learning methods to develop EEP case studies, involve minority undergraduates in research, and formulate simple Excel tools for K-12 students. Research outcomes will be shared with relevant agencies (e.g., Cities, County, NGOs) to improve their stream water quality and health management strategies. The EEP case studies will be utilized to teach two new interdisciplinary courses (developed by the PI): Ecohydrological Engineering (undergraduate) and Ecological Engineering (graduate). Research and educational outcomes will be broadly disseminated through journal publications, conference presentations, graduate theses/dissertation, reports, YouTube, and a project website. Local and regional high school students and teachers will be involved with the research-education by leveraging current and developing new collaborations.