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

1454435（Abdul-Aziz）。这项研究的目标是调查和稳健地预测复杂的城市自然流域（例如，沿海城市中心）。 核心研究假设是城市河流生态化学和生态过程遵循涌现相似性、尺度不变模式和组织原则，这将导致时空上对水质和生态系统健康的稳健预测。 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、河流内和沿海驱动因素/压力因素的主要控制因素，并量化这些变量之间的相对联系;（2）调查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、河流内和沿海驱动因素/压力因素之间的相似性。（参数缩减），标度律（紧急模式），和组织原则的溪流水质和健康变量;和（3）制定信息学为基础的经验（即，数据驱动的）和基于机制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鲁棒预测。 综合教育目标是开发基于诱导学习的跨学科生态工程教学法（EEP）;为了（1）增加本科生的保留率和相关STEM专业的少数民族学生的毕业，（2）增加专门研究新兴生态工程范式的研究生，以及（3）增加积极追求STEM教育/职业的K-12学生的数量。该研究将主要在南佛罗里达进行，这是一个活生生的实验室，也是气候变化和海平面上升的热点;考虑到该地区是世界各地复杂城市自然环境的原型和案例研究。 该研究还将利用其他沿海城市中心的全国可用数据（例如，纽约、洛杉矶、休斯顿），将美国海岸的水文气候、地球化学和生态梯度结合起来。这项研究将采用数据分析和信息学框架，以实现对城市河流水质和生态系统健康过程的主要控制机制的机械理解。 它试图通过推导和利用适当的无量纲功能组，这将确定不同的环境制度和水质和生态系统健康的组织原则，解开城市河流的生态化学-生态相似性和标度律。 尺度不变的模式和新兴的组织原则，将有助于制定简约的经验和机械行为模型，标称校准，可以提供时空强大的预测流水质和健康指标。 这项工作将利用归纳学习方法来开发EEP案例研究，让少数民族大学生参与研究，并为K-12学生制定简单的Excel工具。 它将利用归纳学习方法来开发EEP案例研究，让少数民族大学生参与研究，并为K-12学生制定简单的Excel工具。 研究成果将与相关机构分享（例如，城市，县，非政府组织），以改善其河流水质和健康管理战略。 EEP案例研究将用于教授两门新的跨学科课程（由PI开发）：生态水文工程（本科）和生态工程（研究生）。 研究和教育成果将通过期刊出版物、会议报告、研究生论文/学位论文、报告、YouTube和项目网站广泛传播。 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.