Adaptive flood risk management under climate change uncertainty using real options and optimization

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      <subfield code="a">Adaptive flood risk management under climate change uncertainty using real options and optimization</subfield>
      <subfield code="c">Michelle Woodward, Zoran Kapelan, Ben Gouldby</subfield>
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      <subfield code="a">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.</subfield>
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      <subfield code="a">Cambio climático</subfield>
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      <subfield code="t">Risk analysis : an international journal</subfield>
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      <subfield code="g">13/01/2014 Volumen 34 Número 1 - enero 2014 , p. 75-92</subfield>
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