Koks E E, Bočkarjova M, de Moel H, Aerts J C J H
Institute for Environmental Studies (IVM), VU University Amsterdam, Amsterdam, The Netherlands.
Department of Spatial Economics, VU University Amsterdam, Amsterdam, The Netherlands.
Risk Anal. 2015 May;35(5):882-900. doi: 10.1111/risa.12300. Epub 2014 Dec 16.
In this article, we propose an integrated direct and indirect flood risk model for small- and large-scale flood events, allowing for dynamic modeling of total economic losses from a flood event to a full economic recovery. A novel approach is taken that translates direct losses of both capital and labor into production losses using the Cobb-Douglas production function, aiming at improved consistency in loss accounting. The recovery of the economy is modeled using a hybrid input-output model and applied to the port region of Rotterdam, using six different flood events (1/10 up to 1/10,000). This procedure allows gaining a better insight regarding the consequences of both high- and low-probability floods. The results show that in terms of expected annual damage, direct losses remain more substantial relative to the indirect losses (approximately 50% larger), but for low-probability events the indirect losses outweigh the direct losses. Furthermore, we explored parameter uncertainty using a global sensitivity analysis, and varied critical assumptions in the modeling framework related to, among others, flood duration and labor recovery, using a scenario approach. Our findings have two important implications for disaster modelers and practitioners. First, high-probability events are qualitatively different from low-probability events in terms of the scale of damages and full recovery period. Second, there are substantial differences in parameter influence between high-probability and low-probability flood modeling. These findings suggest that a detailed approach is required when assessing the flood risk for a specific region.
在本文中,我们针对小规模和大规模洪水事件提出了一种综合的直接和间接洪水风险模型,该模型能够对从洪水事件发生到完全经济复苏期间的总经济损失进行动态建模。我们采用了一种新颖的方法,即使用柯布 - 道格拉斯生产函数将资本和劳动力的直接损失转化为生产损失,旨在提高损失核算的一致性。经济复苏采用混合投入产出模型进行建模,并应用于鹿特丹港口地区,使用了六种不同的洪水事件(从1/10到1/10000)。这一过程有助于更好地了解高概率和低概率洪水的后果。结果表明,就预期年度损失而言,直接损失相对于间接损失仍然更为可观(大约大50%),但对于低概率事件,间接损失超过了直接损失。此外,我们使用全局敏感性分析探索了参数不确定性,并采用情景方法改变了建模框架中与洪水持续时间和劳动力恢复等相关的关键假设。我们的研究结果对灾害建模人员和从业者有两个重要启示。第一,在损害规模和完全恢复期方面,高概率事件与低概率事件在性质上有所不同。第二,高概率和低概率洪水建模在参数影响方面存在很大差异。这些发现表明,在评估特定地区的洪水风险时需要采用详细的方法。