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A micro-scale cost-benefit analysis of building-level flood risk adaptation measures in Los Angeles

Cost-benefit analysis (CBA) of flood risk adaptation strategies offers policymakers insight into economically optimal strategies for adapting to sea level rise. However, building-level adaptation measures such as floodproofing or building elevation are often evaluated at aggregated spatial scales, which may result in sub-optimal investment decisions. In this paper, we develop a flood risk model and combine it with a micro-scale CBA at the building level to obtain an optimal mix of adaptation measures per area. We apply this approach to Venice Beach in Los Angeles and Naples in Long Beach. We subsequently compare our results with the conventional, spatially aggregated area-based CBA approach. Our findings show that a mix of 35%–45% dry-floodproofing measures and 55%–65% building elevation measures is optimal. Elevation works best in areas with high inundation depths, while dry-floodproofing is preferable in areas with shallow inundation depths. The optimal mix of measures derived from our micro-scale approach results in an economic efficiency up to 85% higher than that yielded by the commonly applied spatially aggregated approach. We therefore recommend that economic evaluations of building-level adaptation measures are conducted at the smallest possible scale, or that CBAs are performed on disaggregated areas based on inundation depth.
- Utrecht University Netherlands
- University of Amsterdam Netherlands
- Free University of Amsterdam Pure VU Amsterdam Netherlands
- Vrije Universiteit Amsterdam Netherlands
- University of Pennsylvania United States
Climate Change, Geography, Planning and Development, Cost-benefit analysis, Sea level rise, SDG 13 - Climate Action, Climate change, Building level, Adaptation, Flood risk analysis, Water Science and Technology
Climate Change, Geography, Planning and Development, Cost-benefit analysis, Sea level rise, SDG 13 - Climate Action, Climate change, Building level, Adaptation, Flood risk analysis, Water Science and Technology
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).43 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%
