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Real-time forecasting of algal blooms in reservoirs

Real-time forecasting of algal blooms in reservoirs
水库藻华实时预报
批准号:
NE/N004817/1
负责人:
Keith Beven
金额:
$2.17万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2015
资助国家:
英国
项目状态:
已结题
起止时间:
2015 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
Algal blooms are a significant problem for water management worldwide and are costly to manage (e.g. costing an estimated £50 million per year in the UK at 2003 rates). Water companies are faced with problems such as blocked filters, poor taste and odour and, in more extreme cases, high levels of algal-derived toxins. There are a number of management strategies that can be implemented, often in a reactive way. It is therefore advantageous to be able to predict when an algal bloom is likely to occur. In a previous NERC funded project (UKLEON - NE/I007407/1; http://www.ecn.ac.uk/what-we-do/science/projects/ukleon), forecasts of algal blooms in lakes have been made with acceptable accuracy. The forecasts are made using a computer model which describes the growth of algal communities given weather forecasts. For this to be achievable, adequate data is required to be able to run the model and to be able to inform us of when the model is providing a good representation of the lake system. Adequate data availability is a critical part of the forecasting system and can be costly, so there is a requirement to balance the costs of data collection and modelling against the costs of managing algal blooms. The proposed project has the overall objective of defining the water industry's requirement for an algal forecasting system for reservoirs and to determine the likely cost-effectiveness of such a system. Information on the costs associated with different management strategies will be assessed against the costs associated with data collection, model calibration and implementation. These costs will vary based upon: - The accuracy of the forecasts for the required forecast period (e.g. 3, 5 or 10 days ahead). - The characteristics of the reservoir and its catchment. - The level of historic data available for setting up the forecasting system.If such a system is proven to be cost effective the potential for positive impacts on water supply management within the UK, the EU and world wide are significant both in terms of water quality and cost savings.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Constraining uncertainty and process-representation in an algal community lake model using high frequency in-lake observations
使用高频湖内观测限制藻类群落湖泊模型中的不确定性和过程表示
DOI: 10.1016/j.ecolmodel.2017.04.011
发表时间: 2017
期刊: Ecological Modelling
影响因子: 3.1
作者: [Page T]
通讯作者: Page T
DOI: 10.1016/j.watres.2018.01.046
发表时间: 2018-05
期刊: Water research
影响因子: 12.8
作者: [T. Page;Paul Smith;Paul Smith;K. Beven;I. D. Jones;J. Elliott;S. Maberly;E. Mackay;M. D. Ville;H. Feuchtmayr]
通讯作者: T. Page;Paul Smith;Paul Smith;K. Beven;I. D. Jones;J. Elliott;S. Maberly;E. Mackay;M. D. Ville;H. Feuchtmayr
DOI: 10.1002/wat2.1278
发表时间: 2018-05-01
期刊: WILEY INTERDISCIPLINARY REVIEWS-WATER
影响因子: 8.2
作者: [Beven, Keith J.]
通讯作者: Beven, Keith J.
The Consortium on Risk in the Environment: Diagnostics, Integration, Benchmarking, Learning and Elicitation (CREDIBLE)
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    NE/J017299/1
  • 项目类别:
    Research Grant
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    $45.84万
  • 财政年份:
    2013
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A United Kingdom Lake Ecological Observatory Network
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    $45.55万
  • 财政年份:
    2009
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