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Benefits and Limitations of Real Options Analysis for the Practice of River Flood Risk Management

机译:实物期权分析对河流洪水风险管理实践的好处和局限性

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摘要

Decisions on long-lived flood risk management (FRM) investments are complex because the future is uncertain. Flexibility and robustness can be used to deal with future uncertainty. Real options analysis (ROA) provides a welfare-economics framework to design and evaluate robust and flexible FRM strategies under risk or uncertainty. Although its potential benefits are large, ROA is hardly used in todays' FRM practice. In this paper, we investigate benefits and limitations of a ROA, by applying it to a realistic FRM case study for an entire river branch. We illustrate how ROA identifies optimal short-term investments and values future options. We develop robust dike investment strategies and value the flexibility offered by additional room for the river measures. We benchmark the results of ROA against those of a standard cost-benefit analysis and show ROA's potential policy implications. The ROA for a realistic case requires a high level of geographical detail, a large ensemble of scenarios, and the inclusion of stakeholders' preferences. We found several limitations of applying the ROA. It is complex. In particular, relevant sources of uncertainty need to be recognized, quantified, integrated, and discretized in scenarios, requiring subjective choices and expert judgment. Decision trees have to be generated and stakeholders' preferences have to be translated into decision rules. On basis of this study, we give general recommendations to use high discharge scenarios for the design of measures with high fixed costs and few alternatives. Lower scenarios may be used when alternatives offer future flexibility.
机译:由于未来不确定,因此关于长期洪水风险管理(FRM)投资的决策很复杂。灵活性和健壮性可用于应对未来的不确定性。实物期权分析(ROA)提供了一种福利经济学框架,可以设计和评估在风险或不确定性下强大而灵活的FRM策略。尽管ROA的潜在收益很大,但在当今的FRM实践中几乎没有使用ROA。在本文中,我们通过将ROA应用于整个河流分支的实际FRM案例研究,研究了ROA的优点和局限性。我们将说明ROA如何确定最佳的短期投资并重视未来的选择。我们制定稳健的堤防投资策略,并重视为河流措施提供更多空间的灵活性。我们将ROA的结果与标准成本收益分析的结果进行基准比较,并显示ROA的潜在政策含义。实际情况下的ROA需要高级别的地理详细信息,大量的场景以及包括利益相关者的偏好。我们发现了应用ROA的一些限制。这很复杂。特别是,在场景中需要识别,量化,整合和离散不确定性的相关来源,这需要主观选择和专家判断。必须生成决策树,并且必须将利益相关者的偏好转换为决策规则。在这项研究的基础上,我们提出了使用高排放情景的一般建议,以设计固定成本高,替代方案很少的措施。当替代方案提供未来的灵活性时,可以使用较低的方案。

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