Floods are the natural hazards that are causing the most deaths worldwide. Flood early warning systems are one of the most cost-efficient methods to reduce death rates, triggering decisions about evacuation of exposed population. Although previous studies have investigated the effect of human behaviours on evacuation processes, studies analysing a combination of behaviours, flood onset and warning timing are limited. Our objective is to explore how changes on the aforementioned factors can affect casualties. This is done within a modelling framework that includes an agent-based model, a hydraulic model and a traffic model, which is implemented for the case study of Orvieto (Italy). The results show that the number of casualties is most impacted by people’s behaviour. Besides, we found that a delay of 30 min in releasing the warning can boost the number of casualties up to six times. These results may help managers to propose effective emergency plans.

洪水是造成全球死亡人数最多的自然灾害。洪水预警系统是降低死亡率，触发有关撤离裸露人群的决定的最具成本效益的方法之一。尽管先前的研究已经调查了人类行为对撤离过程的影响，但对行为，洪水爆发和预警时间的综合分析进行的研究仍然有限。我们的目标是探索上述因素的变化如何影响人员伤亡。这是在一个建模框架内完成的，该框架包括基于代理的模型，液压模型和交通模型，这些模型是针对Orvieto（意大利）的案例研究而实现的。结果表明，伤亡人数受人们行为的影响最大。除了，我们发现，延迟发出警告30分钟可以将伤亡人数提高六倍。这些结果可能有助于管理人员提出有效的应急计划。