Robust Decision Making and Info-Gap Decision Theory for water resource system planning
Robust Decision Making and Info-Gap Decision Theory for water resource system planning
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DOI：
10.1016/j.jhydrol.2013.03.006
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发表时间：
2013-06-28
影响因子：
6.4
通讯作者：
Harou, Julien J.
中科院分区：
文献类型：
--
作者：
Matrosov, Evgenii S.;Woods, Ashley M.;Harou, Julien J.
由于影响人水系统的变化很难预测，因此对人水系统的平稳性假设往往是无效的。在这种情况下，水规划发生在深度或严重不确定性的条件下，未来条件和事件的统计分布知之甚少。在这种情况下，预测系统仿真模型通常在不同的场景下运行，以评估未来计划在不同条件下的性能。假设有许多可能的计划和许多可能的未来，哪些模拟将导致最佳设计？鲁棒决策（RDM）和信息缺口决策理论（IGDT）提供了一种结构化的方法来规划复杂的系统在这种不确定性。RDM和IGDT都重复使用可信的仿真模型来评估不同未来条件下的不同计划。这两种方法都试图确定稳健的而不是最优的决策，其中稳健的决策在广泛的可能未来中令人满意地工作。IGDT有效地图表系统性能与鲁棒性和时机图总结系统性能的不同计划下最可怕和最有利的一组未来条件。RDM样本范围更广的可怕的，良性的和适时的未来，并提供了一个全面的评估不同的选项的性能。RDM还通过“情景发现”来确定哪些不确定的未来压力组合会导致系统漏洞。在我们的研究中，我们将这两个框架的水资源系统规划问题：伦敦的供水系统在泰晤士河流域，英国的扩张。这些方法有助于确定20个拟议的供水基础设施组合是最强大的严重不确定未来的水文流入，水需求和能源价格。考虑了系统性能的多个标准：服务可靠性，存储敏感性，资本和运营成本，能源使用和环境流量。最初，这两个决策框架导致不同的建议。我们表明，这些方法是互补的，可以有利地一起使用，以更好地理解结果，并揭示每种方法的细节如何使结果偏向特定的未来计划。(C)2013爱思唯尔有限公司版权所有。
Stationarity assumptions of linked human-water systems are frequently invalid given the difficult-to-predict changes affecting such systems. In this case water planning occurs under conditions of deep or severe uncertainty, where the statistical distributions of future conditions and events are poorly known. In such situations predictive system simulation models are typically run under different scenarios to evaluate the performance of future plans under different conditions. Given that there are many possible plans and many possible futures, which simulations will lead to the best designs? Robust Decision Making (RDM) and Info-Gap Decision Theory (IGDT) provide a structured approach to planning complex systems under such uncertainty. Both RDM and IGDT make repeated use of trusted simulation models to evaluate different plans under different future conditions. Both methods seek to identify robust rather than optimal decisions, where a robust decision works satisfactorily over a broad range of possible futures. IGDT efficiently charts system performance with robustness and opportuneness plots summarising system performance for different plans under the most dire and favourable sets of future conditions. RDM samples a wider range of dire, benign and opportune futures and offers a holistic assessment of the performance of different options. RDM also identifies through 'scenario discovery' which combinations of uncertain future stresses lead to system vulnerabilities. In our study we apply both frameworks to a water resource system planning problem: London's water supply system expansion in the Thames basin, UK. The methods help identify which out of 20 proposed water supply infrastructure portfolios is the most robust given severely uncertain future hydrological inflows, water demands and energy prices. Multiple criteria of system performance are considered: service reliability, storage susceptibility, capital and operating cost, energy use and environmental flows. Initially the two decision frameworks lead to different recommendations. We show the methods are complementary and can be beneficially used together to better understand results and reveal how the particulars of each method can skew results towards particular future plans. (C) 2013 Elsevier B.V. All rights reserved.