Abstract. The use of different methods for physical flood vulnerability assessment has evolved over time, from traditional single-parameter stage–damage curves to multi-parameter approaches such as multivariate or indicator-based models. However, despite the extensive implementation of these models in flood risk assessment globally, a considerable gap remains in their applicability to data-scarce regions. Considering that these regions are mostly areas with a limited capacity to cope with disasters, there is an essential need for assessing the physical vulnerability of the built environment and contributing to an improvement of flood risk reduction. To close this gap, we propose linking approaches with reduced data requirements, such as vulnerability indicators (integrating major damage drivers) and damage grades (integrating frequently observed damage patterns). First, we present a review of current studies of physical vulnerability indicators and flood damage models comprised of stage–damage curves and the multivariate methods that have been applied to predict damage grades. Second, we propose a new conceptual framework for assessing the physical vulnerability of buildings exposed to flood hazards that has been specifically tailored for use in data-scarce regions. This framework is operationalized in three steps: (i) developing a vulnerability index, (ii) identifying regional damage grades, and (iii) linking resulting index classes with damage patterns, utilizing a synthetic “what-if” analysis. The new framework is a first step for enhancing flood damage prediction to support risk reduction in data-scarce regions. It addresses selected gaps in the literature by extending the application of the vulnerability index for damage grade prediction through the use of a synthetic multi-parameter approach. The framework can be adapted to different data-scarce regions and allows for integrating possible modifications to damage drivers and damage grades.

中文翻译：

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洪水的通用物理脆弱性模型：数据稀缺地区的回顾和概念

摘要。随着时间的推移，使用不同的物理洪水脆弱性评估方法已经演变，从传统的单参数阶段-损害曲线到多参数方法，如多变量或基于指标的模型。然而，尽管这些模型在全球洪水风险评估中得到了广泛应用，但它们在数据稀缺地区的适用性方面仍存在相当大的差距。考虑到这些地区大多是应对灾害能力有限的地区，因此有必要评估建筑环境的物理脆弱性，并有助于改善减少洪水风险。为了缩小这一差距，我们建议将方法与减少的数据要求联系起来，例如脆弱性指标（整合主要损害驱动因素）和损害等级（整合经常观察到的损害模式）。首先，我们回顾了当前对物理脆弱性指标和洪水损害模型的研究，这些模型由阶段-损害曲线和已应用于预测损害等级的多变量方法组成。其次，我们提出了一个新的概念框架，用于评估暴露于洪水灾害的建筑物的物理脆弱性，该框架专门用于数据稀缺地区。该框架分三个步骤实施：(i) 制定脆弱性指数，(ii) 确定区域损害等级，以及 (iii) 利用综合“假设”分析将结果指数类别与损害模式联系起来。新框架是加强洪水灾害预测以支持数据稀缺地区降低风险的第一步。它通过使用综合多参数方法扩展脆弱性指数在损坏等级预测中的应用，解决了文献中的选定空白。该框架可以适应不同的数据稀缺区域，并允许集成对损坏驱动程序和损坏等级的可能修改。