2016
DOI: 10.1016/j.polsoc.2016.05.002
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Adaptation Pathways and Real Options Analysis: An approach to deep uncertainty in climate change adaptation policies

Abstract: Governments face the daunting task of developing policies and making investment decisions for climate change adaptation in an environment that consist of complex, interlinked systems with manifold uncertainties. Instead of responding to surprises and making decisions on ad [ 1 7 _ T D $ D I F F ] hoc basis, a structured approach to deal with complex systems and uncertainties can provide indispensable support for policy making. This contribution proposes a structured approach for designing climate adaptation po… Show more

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Cited by 164 publications
(91 citation statements)
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“…Model driven pathway approaches (e.g., Haasnoot et al [96], Kwakkel et al [97]) use physically based models such as hydraulic models and scenario generation techniques to find out the most promising pathways in terms of performance robustness towards multiple objectives. Selection of an adaptation pathway for implementation from among these pathways can be made based on: (i) set thresholds such as estimated annual damages (e.g., CRIDA [98]); (ii) the net present value of pathways (e.g., Gersonius et al [37]) or benefit cost analysis (e.g., Aerts et al [99]); (iii) likelihood of occurrence among all plausible scenarios (e.g., Buurman & Babovic [100]); (iv) assessing all the aforementioned 'objectives' using multi-objective evolutionary algorithms which could avoid the narrowing down to a pathway based on aggregated objectives (e.g., Kasprzyk et al [101]). Hence it is theoretically possible to identify an adaptation pathway that results in lower estimated annual damages and has the highest net present value for the combination of drivers that are most likely to reoccur at low intervals.…”
Section: Finalise and Implement Adaptation Measures (Step 6)mentioning
confidence: 99%
“…Model driven pathway approaches (e.g., Haasnoot et al [96], Kwakkel et al [97]) use physically based models such as hydraulic models and scenario generation techniques to find out the most promising pathways in terms of performance robustness towards multiple objectives. Selection of an adaptation pathway for implementation from among these pathways can be made based on: (i) set thresholds such as estimated annual damages (e.g., CRIDA [98]); (ii) the net present value of pathways (e.g., Gersonius et al [37]) or benefit cost analysis (e.g., Aerts et al [99]); (iii) likelihood of occurrence among all plausible scenarios (e.g., Buurman & Babovic [100]); (iv) assessing all the aforementioned 'objectives' using multi-objective evolutionary algorithms which could avoid the narrowing down to a pathway based on aggregated objectives (e.g., Kasprzyk et al [101]). Hence it is theoretically possible to identify an adaptation pathway that results in lower estimated annual damages and has the highest net present value for the combination of drivers that are most likely to reoccur at low intervals.…”
Section: Finalise and Implement Adaptation Measures (Step 6)mentioning
confidence: 99%
“…The economic cost and benefits of these solutions are critical in decision‐making but have not been addressed within this study. The assessment of the costs and benefits will be affected by the uncertainty surrounding the pathways, however, methods such as real options may be effective at addressing this shortcoming (Buurman & Babovic, ; de Neufville & Scholtes, ). The addition of financial considerations at the start of the analysis may make certain adaptations financially unfeasible and may reduce the number of simulations to be run.…”
Section: Discussionmentioning
confidence: 99%
“…In the context of climate change adaptation, Buurman and Babovic (2016) also discuss and highlight the importance of system flexibility from engineering and design perspectives when dealing with uncertainty. Leong (2016) also notes two contested concepts of resilience within these definitions: first, resilience as persistence in the face of hazards through recovery, with a bias towards preserving a system's status quo; second, resilience as not just 'bouncing back' from a setback but continuous stakeholder adaptation to impacts of environmental fluctuations.…”
Section: Urban Resilience In the Face Of Climate Changementioning
confidence: 99%