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.

洪水风险适应策略的成本效益分析（CBA）为决策者提供了针对适应海平面上升的经济最优策略的见解。但是，建筑物级别的适应措施（例如防洪或建筑物标高）通常在汇总的空间尺度上进行评估，这可能会导致投资决策不理想。在本文中，我们开发了洪水风险模型，并将其与建筑物级别的微型CBA相结合，以获得每个区域的适应措施的最佳组合。我们将此方法应用于洛杉矶的威尼斯海滩和长滩的那不勒斯。随后，我们将我们的结果与传统的基于空间聚集区域的CBA方法进行了比较。我们的研究结果表明，将35％–45％的防潮措施与55％–65％的建筑物高程措施混合使用是最佳选择。在高淹没深度的地区，高程效果最好，而在浅埋深度的地区，最好采用防洪防潮措施。从我们的微观尺度方法得出的最优措施组合可以使经济效率比通常采用的空间聚集方法所产生的经济效率高出85％。因此，我们建议以尽可能最小的规模进行建筑级别适应措施的经济评估，或者根据淹没深度对分类区域进行CBA。