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Value of information in design of groundwater quality monitoring network under uncertainty.

机译:不确定条件下信息在地下水水质监测网设计中的价值。

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摘要

The increasing need for groundwater as a source for fresh water and the continuous deterioration in many places around the world of that precious source as a result of anthropogenic sources of pollution highlights the need for efficient groundwater resources management. To be efficient, groundwater resources management requires efficient access to reliable information that can be acquired through monitoring. Due to the limited resources to implement a monitoring program, a groundwater quality monitoring network design should identify what is an optimal network from the point of view of cost, the value of information collected, and the amount of uncertainty that will exist about the quality of groundwater. When considering the potential social impact of monitoring, the design of a network should involve all stakeholders including people who are consuming the groundwater.;This research introduces a methodology for groundwater quality monitoring network design that utilizes state-of-the-art learning machines that have been developed from the general area of statistical learning theory. The methodology takes into account uncertainties in aquifer properties, pollution transport processes, and climate. To check the feasibility of the network design, the research introduces a methodology to estimate the value of information (VOI) provided by the network using a decision tree model. Finally, the research presents the results of a survey administered in the study area to determine whether the implementation of the monitoring network design could be supported.;Applying these methodologies on the Eocene Aquifer, Palestine indicates that statistical learning machines can be most effectively used to design a groundwater quality monitoring network in real-life aquifers. On the other hand, VOI analysis indicates that for the value of monitoring to exceed the cost of monitoring, more work is needed to improve the accuracy of the network and to increase people's awareness of the pollution problem and the available alternatives.
机译:由于人为污染源,对地下水作为淡水的需求不断增长,在世界许多地方,这种珍贵的水源不断恶化,这凸显了对有效的地下水资源管理的需求。为了提高效率,地下水资源管理需要有效访问可通过监视获取的可靠信息。由于实施监测计划的资源有限,地下水质量监测网络的设计应从成本,收集的信息的价值以及水质的不确定性等方面确定最佳的网络。地下水。考虑到监测的潜在社会影响时,网络的设计应涉及所有利益相关者,包括消耗地下水的人们。本研究介绍了一种利用最先进的学习机进行地下水质量监测网络设计的方法。从统计学习理论的一般领域发展而来。该方法考虑了含水层性质,污染输送过程和气候的不确定性。为了检查网络设计的可行性,该研究引入了一种使用决策树模型估算网络提供的信息(VOI)值的方法。最后,这项研究提出了在研究区域内进行的一项调查的结果,以确定是否可以支持实施监测网络设计。;巴勒斯坦在始新世含水层上应用这些方法表明,统计学习机可以最有效地用于设计实际含水层中的地下水质量监测网络。另一方面,VOI分析表明,要使监视的价值超过监视的成本,需要做更多的工作来提高网络的准确性,并提高人们对污染问题和可用替代方案的认识。

著录项

  • 作者

    Khader, Abdelhaleem.;

  • 作者单位

    Utah State University.;

  • 授予单位 Utah State University.;
  • 学科 Water Resource Management.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 109 p.
  • 总页数 109
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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