Due to rise in extreme events and their devastating impacts on socio-physical systems, building resilience and communicating information about risks of these events is important. The availability of large volume of imagery at high spatio-temporal resolution has enabled using geospatial and computational science and technologies along with other data sets and models to answer critical questions and inform decisions about risk, resilience, response and recovery. This session highlights using machine learning, imagery and statistical analysis, geo-visualization and geo-computation to (i) understand physical processes of hydro-meteorological hazards and interaction between socio-physical systems, (ii) assess risk and resilience of extreme events, (iii) visualize and map societal impacts of disasters, and (iv) communicate risk information to a heterogenous audience to help with preparedness and decision-making activities. Although primary focus of this session is flooding, presentation on the above-mentioned topics in the context of other extreme events is also welcome.