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Integration of numerical modeling and Bayesian analysis for setting water quality criteria in Hamilton Harbour, Ontario, Canada

机译:设置数值模型和贝叶斯分析的集成,以设定加拿大安大略省汉密尔顿港的水质标准

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摘要

The credibility of the scientific methodology of mathematical models and their adequacy to form the basis of public policy decisions has frequently been challenged. We believe that the development of novel methods for rigorously assessing model uncertainty should be a top priority of the modeling community. In this regard, we introduce the Bayesian calibration of process-based models as a methodological advancement that warrants consideration in aquatic ecosystem research. This modeling framework combines the advantageous features of both mechanistic and statistical approaches, i.e., mechanistic understanding that remains within the bounds of data-based parameter estimation. Other advantages of the Bayesian approach are the ability to sequentially update "beliefs" as new knowledge is available, the consistency with the scientific process of progressive learning and the policy practice of adaptive management. In this study, the Bayesian calibration framework is used to guide the water quality criteria setting process in Hamilton Harbour, Ontario, Canada. First, we present the results of the Bayesian calibration exercise and examine the ability of the model to adequately reproduce the average observed patterns along with the major cause-effect relationships underlying the Harbour water quality conditions. We then address the following critical questions regarding the future response of the system: How possible is it to meet the objective of delisting the study system as an Area of Concern, if the nutrient loading reductions proposed by the Hamilton Harbour Remedial Action Plan are actually implemented? What additional remedial actions are needed to increase the likelihood of meeting the water quality targets? In this regard, the present modeling study undertakes an estimation of the critical nutrient loads in the Harbour based on acceptable exceedance frequencies and confidence of compliance levels with different water quality criteria, e.g., chlorophyll a, total phosphorus (TP). Our analysis suggests that the water quality goals for TP (17 |xg L"1) and chlorophyll a concentrations (5-10 jig lr1) will likely be met, if the recommendation for phosphorus loading at the level of 142 kg day'1 is achieved. We also provide evidence that the anticipated structural shifts of the zooplankton community will determine the restoration rate of the Harbour. Finally, we pinpoint two critical aspects of the system dynamics that invite further investigation and will likely modulate the stability of the new trophic state, i.e., the coupling between the benthic and pelagic habitat and the relative importance of the allochthonous organic matter in sustaining the secondary production in the system.
机译:数学模型的科学方法论的可信度及其构成公共政策决策基础的适当性经常受到挑战。我们认为,开发严格评估模型不确定性的新方法应该是建模界的头等大事。在这方面,我们介绍了基于过程的模型的贝叶斯校准,作为方法学的进步,值得在水生生态系统研究中加以考虑。该建模框架结合了机械方法和统计方法的有利特征,即,机械理解仍保留在基于数据的参数估计的范围内。贝叶斯方法的其他优点是:随着新知识的获得,能够顺序地更新“信念”的能力,与渐进式学习的科学过程的一致性以及适应性管理的政策实践的能力。在这项研究中,贝叶斯校准框架用于指导加拿大安大略省汉密尔顿港的水质标准制定过程。首先,我们介绍贝叶斯校准活动的结果,并检验模型充分再现平均观测模式以及港口水质状况背后的主要因果关系的能力。然后,我们针对系统的未来响应解决以下关键问题:如果汉密尔顿港口补救行动计划提出的减少营养物负荷的措施得以实际实施,那么有可能实现将研究系统从关注领域除名的目标。 ?需要采取哪些其他补救措施来增加达到水质目标的可能性?在这方面,本模拟研究根据可接受的超标频率和对不同水质标准(例如叶绿素a,总磷(TP))的达标水平的置信度,对港口中的关键营养物负荷进行了估算。我们的分析表明,如果建议的磷负荷水平为142 kg·day'1,则TP(17 | xg L“ 1)和叶绿素a浓度(5-10 jig lr1)的水质目标可能会达到。我们还提供了证据,表明浮游动物群落的预期结构变化将决定海港的恢复速度,最后,我们指出了系统动力学的两个关键方面,这些方面需要进一步研究,并有可能调节新的营养状态的稳定性。即底栖和中上层生境之间的耦合以及异源有机物在维持系统二次生产中的相对重要性。

著录项

  • 来源
    《Environmental Modelling & Software》 |2011年第4期|p.337-353|共17页
  • 作者单位

    Ecological Modeling Laboratory, Department of Physical & Environmental Sciences, University of Toronto, Toronto, Ontario, Canada MIC 1A4;

    Ecological Modeling Laboratory, Department of Physical & Environmental Sciences, University of Toronto, Toronto, Ontario, Canada MIC 1A4;

    Water Monitoring & Reporting Section, Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment, Toronto, Ontario, Canada M9P 3V6;

    Ecological Modeling Laboratory, Department of Physical & Environmental Sciences, University of Toronto, Toronto, Ontario, Canada MIC 1A4;

    Water Monitoring & Reporting Section, Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment, Toronto, Ontario, Canada M9P 3V6;

    Ecological Modeling Laboratory, Department of Physical & Environmental Sciences, University of Toronto, Toronto, Ontario, Canada MIC 1A4;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    phosphorus loading; eutrophication modeling; risk assessment; hamilton harbour; ecosystem restoration; top-down control; benthic-pelagic coupling;

    机译:磷负荷;富营养化模型;风险评估;哈密尔顿港;生态系统恢复;自上而下的控制;底-浮游耦合;

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