Wehbe Celine, Baroud Hiba
Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, 37235, USA.
Sci Rep. 2024 Aug 20;14(1):19333. doi: 10.1038/s41598-024-68060-z.
Vulnerability assessment plays a critical role in disaster management and requires the consideration of multiple dimensions that involve both the built and social environments. A common approach to address this problem is the use of composite indicators, which offer a simplified method to combine information across different dimensions and facilitate decision making. However, composite indicators present limitations in the context of hazard vulnerability. This study investigates the source of these limitations and provides ways to overcome shortcomings in the interpretation of composite vulnerability indicators. To conduct this investigation, a composite indicator is developed to assess the vulnerability of power and transportation infrastructure, while considering social vulnerability, to capture community hazard vulnerability. Using a case study of Harris County in Texas, we investigate the disparities in outcomes resulting from different calculation methods, such as sub-indicator weighting. The case study shows that the value of the indicator is not consistent across different calculation methods. Additionally, weighting the sub-indicators plays an important role in the value of the indicator. Combining infrastructure and social factors is found to be misleading in the interpretation of hazard vulnerability, and the use of bivariate maps is proposed to better distinguish between infrastructure and social vulnerabilities.
脆弱性评估在灾害管理中起着关键作用，需要考虑涉及建筑环境和社会环境的多个维度。解决这一问题的常用方法是使用综合指标，它提供了一种简化的方法来整合不同维度的信息并促进决策。然而，综合指标在灾害脆弱性背景下存在局限性。本研究调查了这些局限性的根源，并提供了克服综合脆弱性指标解释中缺点的方法。为了进行这项调查，开发了一个综合指标来评估电力和交通基础设施的脆弱性，同时考虑社会脆弱性，以捕捉社区灾害脆弱性。通过对德克萨斯州哈里斯县的案例研究，我们调查了不同计算方法（如子指标加权）导致的结果差异。案例研究表明，该指标的值在不同计算方法之间并不一致。此外，子指标加权对指标的值起着重要作用。研究发现，在解释灾害脆弱性时，将基础设施和社会因素结合起来会产生误导，因此建议使用双变量地图来更好地区分基础设施脆弱性和社会脆弱性。
