Rapidly expanding cities in the Middle Eastern and North African (MENA) region are at risk of flooding due to heavy rainfall, insufficient drainage capacity, a lack of preparedness and insufficient data to conduct required studies. A low regret Early Warning Systems (EWS) using rainfall thresholds is proposed as a cost‐effective short‐term solution. This study aims to utilise a probabilistic approach to characterise and predict urban floods by assessing critical rainfall thresholds likely to cause flooding combined with ensemble precipitation forecast in Alexandria, Egypt. Rainfall thresholds were inferred by associating observed rainfall and historical flood information sourced from social media and newspapers. Floods were classified in a colour‐coded hazard matrix as no flood (green), minor flood (yellow), significant flood (orange), and severe flood (red). Probability of occurrence of hazard classes was derived by incorporating ensemble rainfall into the hazard matrix to jointly evaluate likelihood and hazard severity. Results from this study showed that three of four severe events analysed could have been predicted with a high likelihood up to 24 hr before. The presented approach supports decision making to issue warnings and flood control actions with limited data and is a model for other data scare regions.

中文翻译：

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基于雨量阈值的城市数据稀缺地区预警方法：以埃及亚历山大港的一次洪水为例

中东和北非（MENA）地区快速扩张的城市由于暴雨，排水能力不足，准备不足和数据不足而无法进行必要的研究，因此有遭受洪灾的危险。建议使用降雨阈值的低遗憾预警系统（EWS）作为具有成本效益的短期解决方案。这项研究旨在利用概率方法，通过评估可能导致洪灾的临界降雨阈值，结合埃及亚历山大市的整体降水预报，来表征和预测城市洪灾。通过将观测到的降雨与来自社交媒体和报纸的历史洪水信息相关联，得出降雨阈值。洪灾按颜色编码的危害矩阵分类为：无洪灾（绿色），轻微洪灾（黄色），严重洪灾（橙色），和严重的洪水（红色）。危险等级发生的概率是通过将整体降雨纳入危险矩阵来共同评估可能性和危险严重性而得出的。这项研究的结果表明，分析出的四个严重事件中的三个在24小时之前就很有可能被预测到。提出的方法支持决策，以使用有限的数据发布警告和防洪措施，并且是其他数据恐慌区域的模型。