Incorporating Multidimensional Probabilistic Information Into Robustness‐Based Water Systems Planning
Incorporating Multidimensional Probabilistic Information Into Robustness‐Based Water Systems Planning
复制标题
将多维概率信息纳入基于稳健性的水系统规划
作者：
M. Taner;P. Ray;C. Brown
关于气候、社会经济条件和人口结构未来变化的普遍不确定性，增加了人们对基于脆弱性的水资源长期规划框架的兴趣。这些框架将重点从对未来条件的预测转移到基线计划的弱点，然后转向在广泛的未来中减少这些弱点的备选办法。基于脆弱性的规划的一个一贯挑战是如何评估系统或计划易受其影响的多维和相互依存的不确定性发生的相对可能性。这项工作提出了问题的方法论解决方案，在这种情况下展示为决策扩展框架的扩展。提出的方法首先使用随机模拟器生成广泛的期货，然后在这些期货中对系统进行压力测试，以识别相对于利益相关者定义的性能阈值的漏洞。然后使用水资源系统知识领域的贝叶斯信念网络来探索脆弱性的相对可能性。贝叶斯网络提供了系统联合概率行为的正式表示，条件是关于未来的不确定但潜在有用的信息来源，包括历史趋势、专家判断和基于模型的预测。将所提出的方法应用于肯尼亚沿海省大坝工程的四种设计方案的可靠性和净现值指标的比较。结果表明，合并信念信息有助于更好地区分可用选项，主要是通过放大计算的净现值之间的差异。
The widespread uncertainty regarding future changes in climate, socioeconomic conditions, and demographics have increased interest in vulnerability‐based frameworks for long‐term planning of water resources. These frameworks shift the focus from projections of future conditions to the weaknesses of the baseline plans and then to options for reductions in those weaknesses across a wide range of futures. A consistent challenge for vulnerability‐based planning is how to assess the relative likelihood of the occurrence of the multidimensional and codependent uncertainties to which the system or plan is vulnerable. This work proposes a methodological solution to the problem, demonstrated in this case as an extension to Decision Scaling framework. The proposed approach first generates a wide range of futures using stochastic simulators, and then stress tests the system across those futures to identify vulnerabilities relative to stakeholder‐defined performance thresholds. The relative likelihood of the vulnerabilities is then explored using a Bayesian belief network of the knowledge domain of the water resources system. The Bayesian network provides a formal representation of the joint probabilistic behavior of the system conditioned on the uncertain but potentially useful sources of information about the future, including historical trends, expert judgments, and model‐based projections. The proposed approach is applied to compare four design options for a dam project in the Coastal Province of Kenya with respect to the reliability and net present value metrics. Results show that incorporation of belief information helps better distinguishing of the available options, principally by magnifying the differences between the computed net present values.
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影响因子：
5.4
作者：
E. Borgomeo;C. Farmer;Jim W Hall
通讯作者：
E. Borgomeo;C. Farmer;Jim W Hall
影响因子：
6.4
作者：
Arnell, Nigel W.;Gosling, Simon N.
通讯作者：
Gosling, Simon N.
DOI：
10.1016/j.envsoft.2016.04.027
发表时间：
2016-08
期刊：
Environ. Model. Softw.
影响因子：
--
作者：
S. Maskrey;N. Mount;C. Thorne;I. Dryden
通讯作者：
S. Maskrey;N. Mount;C. Thorne;I. Dryden
影响因子：
8.2
作者：
Borgomeo, Edoardo;Mortazavi-Naeini, Mohammad;Guillod, Benoit P.
通讯作者：
Guillod, Benoit P.