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An economic evaluation of adaptation pathways in coastal mega cities: An illustration for Los Angeles

Sea level rise and uncertainty in its projections pose a major challenge to flood risk management and adaptation investments in coastal mega cities. This study presents a comparative economic evaluation method for flood adaptation measures, which couples a cost-benefit analysis with the concept of adaptation pathways. Our approach accounts for uncertainty in sea level rise projections by allowing for flexibility of adaptation strategies over time. Our method is illustrated for Los Angeles County which is vulnerable to flooding and sea level rise. Results for different sea level rise scenarios show that applying adaptation pathways can result in higher economic efficiency (up to 10%) than individual adaptation strategies, despite the loss of efficiency at the initial strategy. However, we identified 'investment tipping points', after which a transition could decrease the economic efficiencies of a pathway significantly. Overall, we recommend that studies evaluating adaptation strategies should integrate cost-benefit analysis frameworks with adaptation pathways since this allows for better informing decision makers about the robustness and economic desirability of their investment choices.
- AUS (United States) United States
- United States Department of the Interior United States
- University of Amsterdam Netherlands
- Vrije Universiteit Amsterdam Netherlands
- University of California System United States
Environmental Engineering, Cost-benefit analysis, Uncertainty, Adaptation pathways, B Journal, Pollution, Sea level rise, SDG 13 - Climate Action, Climate change, Environmental Chemistry, Flood risk analysis, Waste Management and Disposal
Environmental Engineering, Cost-benefit analysis, Uncertainty, Adaptation pathways, B Journal, Pollution, Sea level rise, SDG 13 - Climate Action, Climate change, Environmental Chemistry, Flood risk analysis, Waste Management and Disposal
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).47 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
