The utility of social media for both collecting and disseminating information during natural disasters is increasingly recognised. The rapid nature of urban flooding from intense rainfall means accurate surveying of peak depths and flood extents is rarely achievable, hindering the validation of urban flood models. This paper presents a real‐time modelling framework to identify areas likely to have flooded using data obtained only through social media. Graphics processing unit (GPU) accelerated hydrodynamic modelling is used to simulate flooding in a 48‐km2 area of Newcastle upon Tyne, with results automatically compared against flooding identified through social media, allowing inundation to be inferred elsewhere in the city with increased detail and accuracy. Data from Twitter during two 2012 flood events are used to test the framework, with the inundation results indicative of good agreement against crowd‐sourced and anecdotal data, even though the sample of successfully geocoded Tweets was relatively small.

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This commentary describes the rapid development of a COVID-19 data dashboard utilising existing Urban Observatory Internet of Things (IoT) data and analytics infrastructure. Existing data capture systems were rapidly repurposed to provide real-time insights into the impacts of lockdown policy on urban governance.

A new High-Performance Integrated hydrodynamic Modelling System (Hi-PIMS) is tested for urban flood simulation. The software solves the two-dimensional shallow water equations using a firstorder accurate Godunov-type shock-capturing scheme incorporated with the Harten, Lax and van Leer approximate Riemann solver with the contact wave restored (HLLC) for flux evaluation. The benefits of modern graphics processing units are explored to accelerate large-scale high-resolution simulations. In order to test its performance, the tool is applied to predict flood inundation due to rainfall and a point source surface flow in Glasgow, Scotland, and a hypothetical inundation event at different spatial resolutions in Thamesmead, England, caused by embankment failure. Numerical experiments demonstrate potential benefits for high-resolution modelling of urban flood inundation, and a much-improved level of performance without compromising result quality.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence Newcastle University ePrints -eprint.ncl.ac.uk Liang QH, Smith L, Xia XL. New prospects for computational hydraulics by leveraging high-performance heterogeneous computing techniques.