洛杉矶建筑物级洪水风险适应措施的微观成本效益分析

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2020-10-01 DOI:10.1016/j.wre.2019.100147
Lars T. de Ruig , Toon Haer , Hans de Moel , W.J.Wouter Botzen , Jeroen C.J.H. Aerts
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引用次数: 34

摘要

洪水风险适应策略的成本效益分析(CBA)为决策者提供了适应海平面上升的最优经济策略。然而,建筑物级别的适应性措施,如防洪或建筑物标高,往往在聚集的空间尺度上进行评估,这可能导致次优投资决策。在本文中,我们建立了一个洪水风险模型,并将其与建筑层面的微观尺度CBA相结合,以获得每个区域的最优适应措施组合。我们将这种方法应用于洛杉矶的威尼斯海滩和长滩的那不勒斯。随后,我们将结果与传统的基于空间聚合区域的CBA方法进行比较。我们的研究结果表明,35%-45%的干防措施和55%-65%的建筑标高措施的组合是最佳的。高程防洪在淹没深度高的地区效果最好,而干式防洪在淹没深度浅的地区效果最好。从我们的微观尺度方法中得出的最佳措施组合的经济效率比通常应用的空间聚合方法高出85%。因此,我们建议在尽可能小的尺度上对建筑物级别的适应措施进行经济评估,或者根据淹没深度对分类区域进行cba。
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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.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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