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首页> 外文期刊>Journal of Environmental Management >Evaluating a microbial water quality prediction model for beach management under the revised EU Bathing Water Directive
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Evaluating a microbial water quality prediction model for beach management under the revised EU Bathing Water Directive

机译：根据修订后的欧盟沐浴水指令评估用于海滩管理的微生物水质预测模型

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摘要

The revised Bathing Water Directive (2006/7/EC) requires EU member states to minimise the risk to public health from faecal pollution at bathing waters through improved monitoring and management approaches. While increasingly sophisticated measurement methods (such as microbial source tracking) assist in the management of bathing water resources, the use of deterministic predictive models for this purpose, while having the potential to provide decision making support remains less common. This study explores an integrated, deterministic catchment-coastal hydro-environmental model as a decision-making tool for beach management which, based on advance predictions of bathing water quality, can inform beach managers on appropriate management actions (to prohibit bathing or advise the public not to bathe) in the event of a poor water quality forecast. The model provides a 'moving window' five-day forecast of Escherichia coli levels at a bathing water compliance point off the Irish coast and the accuracy of bathing water management decisions were investigated for model predictions under two scenarios over the period from the 11th August to the 5th September, 2012. Decisions for Scenario 1 were based on model predictions where rainfall forecasts from a meteorological source were used to drive the rainfall-runoff processes in the catchment component of the model, and for Scenario 2, were based on predictions that were improved by incorporating real-time rainfall data from a sensor network within the catchment into the forecasted meteorological input data. The accuracy of the model in the decision-making process was assessed using the contingency table and its metrics. The predictive model gave reasonable outputs to support appropriate decision making for public health protection. Scenario 1 provided real-time predictions that, on 77% of instances during the study period where both predicted and E. coli concentrations were available, would correctly inform a beach manager to either take action to mitigate for poor bathing water quality or take no action. However, Scenario 1 also provided data to support a decision to take action (when none was necessary - a type Ⅰ error) in 4% of instances and to take no action (when action was required - a type Ⅱ error) in 19% of the instances analysed. Type Ⅱ errors are critical in terms of public health protection given that for this error, bathers can be exposed to risks from poor bathing water quality. Scenario 2, on the other hand, provided predictions that would support correct management actions for 79% of the instances but would result in type Ⅰ and type Ⅱ errors for 4% and 17% of the instances respectively. Comparison of Scenarios 1 and 2 for this study indicate that Scenario 2 gave a marginally better overall performance in terms of supporting correct management decisions, as it provided data that could result in a lower occurrence of the more critical type Ⅱ errors. Given that the 28 member states of the European Union are required to engage with the public health provisions of the revised Bathing Water Directive, issues of compliance, pertaining particularly to the management of bathing water resources, remain topical. Decision supports for managing bathing waters in the context of the Directive are likely to become the focus of much attention and although, the current study has been validated in bathing waters off the east coast of Ireland, the approach of using a deterministic and integrated catchment-coastal model for such purposes is easily transferable to other bathing water jurisdictions.
机译：修订后的《沐浴水指令》（2006/7 / EC）要求欧盟成员国通过改进监控和管理方法，将沐浴水中粪便污染对公众健康的风险降至最低。虽然越来越复杂的测量方法（例如微生物来源跟踪）有助于管理洗浴用水，但是为此目的使用确定性预测模型，同时具有提供决策支持的潜力仍然很少见。这项研究探索了一个综合的，确定性的流域-沿海水环境模型，作为海滩管理的决策工具，该模型基于对沐浴水质量的预先预测，可以告知海滩管理者适当的管理措施（禁止沐浴或向公众提供建议如果预报的水质不佳，则不要洗澡）。该模型提供了爱尔兰海岸附近沐浴水达标点的大肠杆菌水平的“移动窗口”五天预测，并针对8月11日至8月期间的两种情况下的模型预测，研究了沐浴水管理决策的准确性。 2012年9月5日。方案1的决策基于模型预测，其中使用气象来源的降雨预测来驱动模型集水部分的降雨径流过程，方案2的决策基于通过将流域内传感器网络的实时降雨数据合并到预测的气象输入数据中来进行改进。使用权变表及其度量标准评估了模型在决策过程中的准确性。预测模型给出了合理的输出，以支持公共卫生保护的适当决策。方案1提供了实时预测，在研究期内77％的实例中，既有预测浓度也有大肠杆菌浓度的情况下，可以正确地通知海滩管理员采取措施减轻沐浴水的质量，或者不采取任何措施。但是，方案1还提供了数据，以支持在4％的实例中采取行动（不需要时-Ⅰ类错误）和在19％的情况下不采取行动（需要采取行动-Ⅱ类错误）的决策。实例进行了分析。 Ⅱ类错误对于公共卫生保护至关重要，因为对于这种错误，沐浴者可能会面临沐浴水质量差的风险。另一方面，方案2提供的预测将支持对79％的实例执行正确的管理操作，但分别导致分别对4％和17％的实例造成Ⅰ型和Ⅱ型错误。本研究中方案1和方案2的比较表明，方案2在支持正确的管理决策方面提供了略微更好的总体性能，因为它提供的数据可能导致较少发生的更严重的Ⅱ型错误。考虑到要求欧盟28个成员国遵守修订后的沐浴水指令的公共卫生规定，合规性问题尤其是与沐浴水的管理有关的问题仍然是热门话题。在该指令的背景下，管理沐浴水的决策支持很可能会成为人们关注的焦点，尽管目前的研究已经在爱尔兰东海岸以外的沐浴水中得到验证，使用确定性和综合性集水区的方法出于这种目的的沿海模式很容易转移到其他沐浴水管辖区。

著录项

  • 来源
    《Journal of Environmental Management》 |2016年第1期|49-58|共10页
  • 作者

    Zeinab Bedri; Aisling Corkery; John J. OSullivan; Louise A. Deering; Katalin Demeter; Wim G. Meijer; Gregory OHare; Bartholomew Masterson;

  • 作者单位

    Centre for Water Resources Research, School of Civil, Structural, and Environmental Engineering, University College Dublin, Belfield, Dublin 4, Ireland;

    Centre for Water Resources Research, School of Civil, Structural, and Environmental Engineering, University College Dublin, Belfield, Dublin 4, Ireland;

    Centre for Water Resources Research, School of Civil, Structural, and Environmental Engineering, University College Dublin, Belfield, Dublin 4, Ireland,UCD Earth Institute, University College Dublin, Belfield, Dublin 4, Ireland;

    School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin 4, Ireland;

    School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin 4, Ireland;

    School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin 4, Ireland,UCD Earth Institute, University College Dublin, Belfield, Dublin 4, Ireland;

    Clarity Centre, UCD School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland,UCD Earth Institute, University College Dublin, Belfield, Dublin 4, Ireland;

    School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin 4, Ireland;

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

    Faecal indicator bacteria (FIB); Prediction; Bathing water quality management; Coastal and catchment modelling; Revised EU Bathing Water Directive;

    机译：粪便指示菌（FIB）;预测;沐浴水质量管理;沿海和流域建模;修订后的欧盟沐浴水指令;

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