Researche Funding: National Aeronautics and Space Administration (NASA)

Faculty Researcher: Prof Dr A.K.M. Saiful Islam

Collaboration: Lead: University of Arizona, Affiliate: Institute of Water and Flood Management (IWFM), BUET

Duration: November, 2021 - November, 2024

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This project leverages inundation observations to understand extreme flood risk in human-modified landscapes, specifically in urban and agricultural areas in Bangladesh. We will use commercial and public sensors to i) map maximum inundated area for extreme flood events, ii) quantify flood risk at watershed scales, and iii) estimate of flood return periods at household scales (30m resolution). These objectives will be reached by using deep learning approaches to map floods and damage, and estiamte return periods with Bayesian Hierarchical Models. We will use optical and radar satellites, including MODIS, Sentinel-1, Planetscope, and the HLS (Harmonized Landsat Sentinel-2 dataset), comparing satellite-based flood maps and return period predictions for Bangladesh to those produced by the Bangladesh Flood Forecasting and Warning Centre (from a physically-based model). We will discuss applications for insurance and climate risk financing with collaborators in Bangladesh.