Data underlying the publication: A rainfall threshold-based approach to early warnings in urban data-scarce regions: A case study of pluvial flooding in Alexandria, Egypt
DOI: 10.4121/bf9f0902-582e-464f-989f-bf0f4a03fde9
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Dataset
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). The probability of occurrence of hazard classes was derived by incorporating ensemble rainfall into the hazard matrix to jointly evaluate likelihood and hazard severity. This dataset includes the Ensemble rainfall forecast TIGGE (THORPEX International Grand Global Ensemble) from the ECMWF which is part of the THORPEX (Observing System Research and Predictability Experiment). It also includes rainfall gauge data sourced from METeorological Aerodrome Report (METAR)
History
- 2025-11-07 first online, published, posted
Publisher
4TU.ResearchDataFormat
excel spreadsheet/.xlsx , python/.pyAssociated peer-reviewed publication
A rainfall threshold-based approach to early warnings in urban data-scarce regions: A case study of pluvial flooding in Alexandria, EgyptFunding
- Sustainable Water Fund (grant code FDW16O46RI) [more info...] Rijksdienst voor Ondernemend Nederland (RVO)
Organizations
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Hydraulic EngineeringIHE Delft Institute for Water Education, Department of Coastal and Urban Risk Resilience
DATA
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3f64c6bfbd723fb31c57b8ec15de95a7Rainfall_Threshold_approach_EWS.zip -
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