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Adaptive Flood Risk Management Under Climate Change Uncertainty Using Real Options and Optimization

机译：基于实物期权和优化的气候变化不确定性下的自适应洪水风险管理

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摘要

It is well recognized that adaptive and flexible flood risk strategies are required to account for future uncertainties. Development of such strategies is, however, a challenge. Climate change alone is a significant complication, but, in addition, complexities exist trying to identify the most appropriate set of mitigation measures, or interventions. There are a range of economic and environmental performance measures that require consideration, and the spatial and temporal aspects of evaluating the performance of these is complex. All these elements pose severe difficulties to decisionmakers. This article describes a decision support methodology that has the capability to assess the most appropriate set of interventions to make in a flood system and the opportune time to make these interventions, given the future uncertainties. The flood risk strategies have been explicitly designed to allow for flexible adaptive measures by capturing the concepts of real options and multiobjective optimization to evaluate potential flood risk management opportunities. A state-of-the-art flood risk analysis tool is employed to evaluate the risk associated to each strategy over future points in time and a multiobjective genetic algorithm is utilized to search for the optimal adaptive strategies. The modeling system has been applied to a reach on the Thames Estuary (London, England), and initial results show the inclusion of flexibility is advantageous, while the outputs provide decisionmakers with supplementary knowledge that previously has not been considered.
机译：众所周知，需要采用适应性强且灵活的洪水风险策略来应对未来的不确定性。然而，制定此类策略是一个挑战。单独的气候变化是一个严重的复杂问题，但是，此外，要确定最合适的缓解措施或干预措施也存在复杂性。有一系列经济和环境绩效指标需要考虑，评估这些绩效的时空方面非常复杂。所有这些因素给决策者带来了严重的困难。本文介绍了一种决策支持方法，该方法有能力评估在洪灾系统中最合适的干预措施，并考虑到未来的不确定性，可以采取适当的时间进行干预。洪水风险策略经过明确设计，可以通过捕获实物期权和多目标优化的概念来评估潜在的洪水风险管理机会，从而采取灵活的适应措施。使用最新的洪水风险分析工具来评估与每个策略相关的未来时间点的风险，并使用多目标遗传算法来搜索最佳的自适应策略。该建模系统已应用于泰晤士河口（英国伦敦）的河段，初步结果表明，将灵活性包括在内是有利的，而输出为决策者提供了以前从未考虑过的补充知识。

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