CAREER: Dynamic connectivity: a research and educational frontier for sustainable environmental management under climate and land use uncertainty

职业：动态连通性：气候和土地利用不确定性下可持续环境管理的研究和教育前沿

• 批准号: 2340161
• 负责人: Admin Husic
• 金额: $ 60.97万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-08-01 至 2029-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2340161&HistoricalAwards=false
• 关键词: CAREER; Dynamic; connectivity; research; educational

Dynamic landscapes represent a network of hydrologic, environmental, and anthropogenic features that work in tandem to confer ecosystem benefits and provide for societal demands. Increasingly, landscapes are at risk under the growing pressures of land use alteration and climate change. Understanding how landscapes dynamically connect the transfer of water, sediment, and nutrients to rivers and the role humans play in modulating this connectivity is crucial if we are to sustainably manage our shared water resources. Thus, the driving questions behind this work are “how have humans changed the landscapes around us for the worse and how are we able to manage them for the better?” This project will answer these questions and advance the frontiers of research and education for sustainable water management by coupling agricultural, municipal, and stormwater expertise together with high-frequency aquatic sensing, deep learning modeling, and large-sample water quality datasets. This research will generate fundamental scientific advances to identify the magnitude, duration, and extent of landscape loading to river systems across climatological, geomorphic, and anthropogenic settings. The education of today’s students, who will become tomorrow’s stakeholders, is deeply embedded in this project through hands-on experiences that will equip them with the confidence and communication skills to handle big data and tackle society’s grandest water challenges. Contemporary research in hydrologic sciences recognizes the importance of connectivity in most aspects of the water cycle; however, despite its ubiquity, connectivity is often assessed either qualitatively or in a static, structural context. The proposed research has the potential to be transformative in moving toward a dynamic assessment of connectivity. This project will quantify dynamic connectivity through time and across space for the United States. This will be achieved by leveraging high-frequency aquatic sensors for nitrate and turbidity from over 150 rivers, which serve as training data for a deep learning model. Further, a mathematical description of dynamic connectivity will inform dominant pathways of connection. Explainable machine learning techniques will link how dynamic landscape attributes lead to riverine water quality impacts. Thereafter, the potential to use dynamic connectivity as a management tool will be assessed through a web application developed for practitioners. The outcomes will lead directly into the education and training of the stakeholders-of-tomorrow, including through building big data confidence in high school settings and science communication skills in college students.This project is jointly funded by Hydrologic Sciences and the Established Program to Stimulate Competitive Research (EPSCoR).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.

动态景观代表了一个水文，环境和人为特征的网络，该网络与会议生态系统的利益协同作用并满足社会需求。在土地使用改变和气候变化的日益增长的压力下，越来越多的景观面临风险。了解景观如何动态地将水，沉积物和养分转移到河流中，以及人类在调节这种连通性中所扮演的角色，如果我们要可持续地管理我们的共享水资源。因此，这项工作背后的驾驶问题是“人类如何更糟地改变我们周围的景观，我们如何能够更好地管理它们？”该项目将回答这些问题，并通过将农业，市政和雨水专业知识以及高频水上感测，深度学习建模和大型水质水质数据集耦合，从而推进可持续水管理研究和教育的前沿。研究将产生基本的科学进步，以确定跨文明，地貌和人为环境的河流系统的大小，持续时间和程度。当今的学生的教育将成为明天的利益相关者，他们通过动手经验深深地嵌入了该项目中，这将使他们具备充满信心和沟通技巧，以处理大数据并应对社会最宏伟的水挑战。当代水文科学研究认识到水周期大多数方面的连通性的重要性。但是，目的地其无处不在，连通性通常经常在质量上或在静态的结构环境中评估。拟议的研究有可能在朝着连通性的动态评估方面进行变革。该项目将通过时间和整个空间量化动态连接。这将通过利用高频水生传感器的硝酸盐和150多条河流的浊度来实现，这些河流充当深度学习模型的训练数据。此外，动态连接性的数学描述将为连接的主要途径提供信息。可解释的机器学习技术将把动态景观属性如何导致河流水质影响。此后，将通过为实践者开发的Web应用程序评估使用动态连接作为管理工具的潜力。结果将直接导致对托马罗的利益相关者的教育和培训，包括通过在高中环境中建立大数据信心和大学生的科学沟通能力。该项目由水文科学和既定的计划共同资助，以刺激竞争性研究（EPSCOR）。这一奖项反映了NSF的法定宣传和审查良好的态度，这是通过评估诚实的诚实的，这是由诚实的构成的构成。