ten Veldhuis J A E, Clemens F H L R, van Gelder P H A J M
Department of Water Management, Delft University of Technology, Delft 2600 GA, The Netherlands.
Water Sci Technol. 2009;59(8):1621-9. doi: 10.2166/wst.2009.171.
Traditional methods to evaluate flood risk generally focus on heavy storm events as the principal cause of flooding. Conversely, fault tree analysis is a technique that aims at modelling all potential causes of flooding. It quantifies both overall flood probability and relative contributions of individual causes of flooding. This paper presents a fault model for urban flooding and an application to the case of Haarlem, a city of 147,000 inhabitants. Data from a complaint register, rainfall gauges and hydrodynamic model calculations are used to quantify probabilities of basic events in the fault tree. This results in a flood probability of 0.78/week for Haarlem. It is shown that gully pot blockages contribute to 79% of flood incidents, whereas storm events contribute only 5%. This implies that for this case more efficient gully pot cleaning is a more effective strategy to reduce flood probability than enlarging drainage system capacity. Whether this is also the most cost-effective strategy can only be decided after risk assessment has been complemented with a quantification of consequences of both types of events. To do this will be the next step in this study.
传统的洪水风险评估方法通常将暴雨事件视为洪水的主要成因。相反，故障树分析是一种旨在对洪水的所有潜在成因进行建模的技术。它既量化了总体洪水概率，也量化了洪水各个成因的相对贡献。本文提出了一个城市洪水故障模型，并将其应用于哈勒姆市（一个拥有14.7万居民的城市）的案例。来自投诉登记册、雨量计和水动力模型计算的数据被用于量化故障树中基本事件的概率。这得出哈勒姆市的洪水概率为每周0.78次。结果表明，雨水口堵塞导致了79%的洪水事件，而暴雨事件仅占5%。这意味着对于该案例，更高效地清理雨水口比扩大排水系统容量是降低洪水概率更有效的策略。这是否也是最具成本效益的策略，只有在风险评估补充了这两类事件后果的量化之后才能确定。为此将是本研究的下一步。
