Cloud-based geospatial analysis for flash flood assessment and integrated mitigation planning: experiences and findings from the northeastern Haor region flash flood 2022, Bangladesh

Le résumé fourni par la source

Flash floods are recurring disasters that cause losses to human life, agriculture and infrastructure in north-eastern haor region of Bangladesh. Cloud-based geospatial analytics were applied to assess flood damages after the extreme flooding event of June 20th, 2022 – the worst haor flooding event in recent decade. Flood inundation extents were mapped with Sentinel-1 SAR imagery on Google Earth Engine platform, while MODIS land cover and GHSL population datasets were used for multidimensional damage and exposure assessment. Results estimated a total inundated area of 1,141,615 ha, about 57.09% of total study area. From a total mapped inundation area, approximately 573,051 ha of MODIS-derived cropland and 6,811 ha of urban land were overlain. Furthermore, the GHSL population surface assessed that about 4,036,019 people were exposed. Accuracy assessment with 300 independent reference points achieved an overall accuracy of 92.33%. The study concludes by proposing integrated flood mitigation strategies, including both engineering solutions and non-structural approaches. Recommendations include Sabo Dams and Flash Flood Dampers, improving early warning systems, implementing nature-based solutions, community resilience and adaptive infrastructure. This case study broadly illustrates the applicability of cloud-based geospatial technology for rapid flood assessment and evidence-based mitigation strategies in flood-prone wetlands globally.

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