Earth observation informed modelling of flash floods

More frequent extreme rainfall events in a changing climate increase the risk of flash flooding. However, the flood hazard modelling required to reduce disaster risk in urban environments is often limited by the availability of data required for model calibration and validation. Here, we use a historical flood event captured by 5 m resolution satellite imagery to inform future flood hazard assessments in the West Bank, Palestine. Flooding in January 2013 affected over 12,500 people and large areas of agricultural land. Vegetation loss and damage were captured using a normalised difference vegetation index (NDVI), which was used as a reference flood extent. The physics-based HEC-RAS flood model best reproduced this NDVI-derived inundation extent (F1 score = 0.76), although the FastFlood model was able to produce a similar inundation pattern (F1 score = 0.74) over 300 times faster. Simulated flood depths from both models were similar. Climate analysis revealed that the January 2013 rainfall corresponded to a historical return period of between 1 in 5 and 1 in 10 years. In comparison, a 1 in 100-year rainfall event (RX1day (maximum 1-day precipitation) of 148 mm) based on historical data (1985–2014) could increase by almost 40% (to 205 mm) in the mid-future (2041–2060), which could cause 23% (4 km 2 ) greater inundation compared to the 2013 event. Although the patterns of future precipitation in the region are uncertain, our flood hazard maps can support urban planning and infrastructure development to manage storm water runoff.

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Publication Details

Journal
International Journal of Disaster Risk Reduction
Published
2025-12-24
DOI
https://doi.org/10.1016/j.ijdrr.2025.105977
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
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article

Earth observation informed modelling of flash floods

C.Scott Watson, Januka Gyawali, Maggie Creed, Divya L. Subedi et al.
International Journal of Disaster Risk Reduction
Flood Risk Assessment and Management
article

Earth observation informed modelling of flash floods

C.Scott Watson, Januka Gyawali, Maggie Creed, Divya L. Subedi, Rojina Haiju, Sameer Shadeed, Jamal Dabbeek
article en

Abstract

More frequent extreme rainfall events in a changing climate increase the risk of flash flooding. However, the flood hazard modelling required to reduce disaster risk in urban environments is often limited by the availability of data required for model calibration and validation. Here, we use a historical flood event captured by 5 m resolution satellite imagery to inform future flood hazard assessments in the West Bank, Palestine. Flooding in January 2013 affected over 12,500 people and large areas of agricultural land. Vegetation loss and damage were captured using a normalised difference vegetation index (NDVI), which was used as a reference flood extent. The physics-based HEC-RAS flood model best reproduced this NDVI-derived inundation extent (F1 score = 0.76), although the FastFlood model was able to produce a similar inundation pattern (F1 score = 0.74) over 300 times faster. Simulated flood depths from both models were similar. Climate analysis revealed that the January 2013 rainfall corresponded to a historical return period of between 1 in 5 and 1 in 10 years. In comparison, a 1 in 100-year rainfall event (RX1day (maximum 1-day precipitation) of 148 mm) based on historical data (1985–2014) could increase by almost 40% (to 205 mm) in the mid-future (2041–2060), which could cause 23% (4 km 2 ) greater inundation compared to the 2013 event. Although the patterns of future precipitation in the region are uncertain, our flood hazard maps can support urban planning and infrastructure development to manage storm water runoff.

International Journal of Disaster Risk ReductionVol. 132
University of Leeds (GB), An-Najah National University (PS), Nepal Development Research Institute (NP), Nepal Participatory Action Network (NP), University of Glasgow (GB)
Climate action, Sustainable cities and communities
Openalex Percentile: Top 37%
Flood Risk Assessment and Management
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