Excellence in Research: Understanding the interactions of terrestrial and freshwater systems for developing a data-driven decision-making framework to manage Algal Blooms

卓越研究：了解陆地和淡水系统的相互作用，以开发数据驱动的决策框架来管理藻华

基本信息

批准号：
2200384
负责人：
Nasrin Alamdari
金额：
$ 41.57万
依托单位：
Florida Agricultural and Mechanical University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-01 至 2025-07-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2200384&HistoricalAwards=false
关键词：
Excellence Research Understanding interactions terrestrial

项目摘要

Human sources of nutrients, such as point discharges from wastewater treatment plants, and nutrient rich runoff from agriculture and urban areas, are driving factors of harmful algal blooms. Conservation practices, also called best management practices and sometimes green infrastructure, are strategies to reduce runoff and nutrient loads from urban watersheds. Best management practices have the potential to control harmful algal blooms in freshwater lakes by reducing nutrient exports in upstream urban watersheds. However, there is a lack of understanding of the relationships among the implementation of best management practices, landscape export of nutrients, and the occurrences of harmful algal blooms. The overarching goal of this research is to understand the hydrological, meteorological, biological, physical, and geochemical processes affecting the landscape export of nutrients and to evaluate the effects of best management practices on the occurrence of harmful algal blooms. This project aims to create a decision support tool for determining the most cost-effective best management practices for urban watersheds to reduce nutrient escape and subsequently control harmful algal blooms. The project will involve key partners, community members, and stakeholders throughout the planning process to ensure broad utility of the resulting strategic plan. The project will also provide educational activities for graduate and undergraduate students from historically underrepresented groups, with the goal of cultivating diversity for the next generation of professionals. The outcome of this project will be incorporated into the educational activities coordinated by the PI to educate the K-12 educators in Florida on sustainable water management with the goal of developing a curriculum that can be used by teachers from under-resourced middle schools in rural areas of Florida.The research objectives of this proposal are: Objective 1 - provide a better understanding of the key hydrological, meteorological, biological, physical, and geochemical processes affecting landscape nutrient export in freshwater lakes; Objective 2 - predict occurrences of harmful algal blooms based on learned relationships between nutrient fluxes and nutrient pollution from a terrestrial system using physics-informed machine learning; and Objective 3 - design an innovative data-driven decision-making framework for evaluating the effectiveness of conservation practices in managing harmful algal blooms in downstream water bodies. This research targets shedding light on the interactive hydrological, meteorological, biological, physical, and geochemical processes affecting the transport and flux of nutrients from terrestrial systems to freshwater lakes, by applying physics-informed machine learning and developing data-driven decision-making frameworks. The project will formulate water quality protection strategies for terrestrial systems that promote sustainability of freshwater ecosystems. The project will bridge disciplinary research on hydrology, data science, and mathematical optimization. The research team will use a system-level approach driven through convergent collaboration with the goal of providing a comprehensive understanding of integrated terrestrial freshwater systems.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.

人类养分的来源，例如废水处理厂的点排放，以及农业和城市地区的养分丰富的径流，都是有害藻华的驱动因素。保护实践，也称为最佳管理实践，有时也称为绿色基础设施，是减少城市流域径流和养分负荷的策略。最佳管理实践有可能通过减少上游城市流域的营养出口来控制淡水湖中有害的藻华。但是，缺乏对最佳管理实践的实施，营养景观出口以及有害藻类开花的发生之间的关系。这项研究的总体目标是了解影响养分景观出口的水文，气象，生物学，物理和地球化学过程，并评估最佳管理实践对发生有害藻类繁殖的影响。该项目旨在创建一个决策支持工具，以确定城市流域最具成本效益的最佳管理实践，以减少营养逃生并随后控制有害的藻华。该项目将在整个计划过程中涉及关键合作伙伴，社区成员和利益相关者，以确保由此产生的战略计划的广泛实用性。该项目还将为来自历史不足的群体的研究生和本科生提供教育活动，目的是为下一代专业人士培养多样性。 The outcome of this project will be incorporated into the educational activities coordinated by the PI to educate the K-12 educators in Florida on sustainable water management with the goal of developing a curriculum that can be used by teachers from under-resourced middle schools in rural areas of Florida.The research objectives of this proposal are: Objective 1 - provide a better understanding of the key hydrological, meteorological, biological, physical, and geochemical processes affecting landscape淡水湖中的营养出口；目标2-使用物理学的机器学习，基于营养通量与从陆地系统中养分污染之间学到的关系之间的关系预测有害藻华的发生；目标3-设计一个创新的数据驱动决策框架，用于评估保护实践在管理下游水体中有害藻类开花方面的有效性。这项研究针对的是，通过应用物理学知识的机器学习并开发数据驱动的决策框架，阐明了影响从陆地系统到淡水湖的养分运输和通量的交互式水文，气象，生物，物理和地球化学过程。该项目将为陆地系统制定水质保护策略，以促进淡水生态系统的可持续性。该项目将介绍有关水文，数据科学和数学优化的学科研究。研究团队将使用通过融合合作驱动的系统级方法，目的是提供对综合陆地淡水系统的全面理解。该奖项反映了NSF的法定任务，并认为值得通过基金会的知识分子优点和更广泛的影响来通过评估来获得支持。