Model development in support of the Lake Ontario Cooperative Science and Monitoring Initiative

Yuan Hui, D. Schlea, J. Atkinson, Zhenduo Zhu, T. Redder
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Abstract

The Cooperative Science and Monitoring Initiative aims to generate data and information to support environmental management in the Laurentian Great Lakes of North America. On a rotating basis, efforts are focused on each lake every five years. In this study, we developed a state-of-the-art hydrodynamic and ecological modeling framework to aggregate data collected during these initiative years and from other sources, and to simulate lake eutrophication processes in Lake Ontario, with an emphasis on nearshore conditions. Model calibration and validation were based primarily on data from three initiative years (2008, 2013, and 2018). This integrated model provides a framework for data organization, understanding complex lake process interactions, and guiding future data collection. It is designed as a management support tool that can simulate lake responses to changes in loading conditions, such as sensitivity of nearshore water quality to Niagara River phosphorus loads. Its designated aim is to support evaluation of management questions in Lake Ontario by providing quantitative evaluation of the relative benefits of potential nutrient loading abatement strategies to mitigate eutrophication in the nearshore. This framework is also well suited for possible future expansion to address management issues on a whole-lake basis.
开发模型以支持安大略湖合作科学和监测倡议
合作科学和监测倡议旨在产生数据和信息,以支持北美劳伦森五大湖的环境管理。在轮换的基础上,每五年将重点放在每个湖泊上。在这项研究中,我们开发了一个最先进的水动力和生态建模框架,以汇总这些倡议期间和其他来源收集的数据,并模拟安大略湖的湖泊富营养化过程,重点是近岸条件。模型校准和验证主要基于三年(2008年、2013年和2018年)的数据。该集成模型为数据组织、理解复杂的湖泊过程相互作用以及指导未来的数据收集提供了框架。它被设计成一个管理支持工具,可以模拟湖泊对负载条件变化的响应,例如近岸水质对尼亚加拉河磷负荷的敏感性。其指定目标是通过对潜在的减少营养物负荷战略的相对效益进行定量评估,以减轻近岸的富营养化,从而支持对安大略湖管理问题的评估。这一框架也非常适合未来可能的扩展,以解决整个湖泊的管理问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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