Deep Learning techniques have been increasingly used in flood management to overcome
the limitations of accurate, yet slow, numerical models, and to improve the results of …

The modelling and management of flood risk in urban areas are increasingly recognized as
global challenges. The complexity of these issues is a consequence of the existence of …

High accuracy models are required for informed decision making in urban flood
management. This paper develops a new holistic framework for using information collected …

We review the 45 available studies of urban flooding based on laboratory experiments. We
distinguish between the studies focusing on the flow in (i) a single street intersection,(ii) …

Urban pluvial flooding is a global challenge that is frequently caused by the lack of available
infiltration, retention and drainage capacity in cities. This paper presents RUFIDAM, an …

To achieve fast flood modelling for large-scale problems, a two-dimensional cellular
automata based model was developed. This model employs simple transition rules and a …

Short-duration, high-intensity rainfall causes significant disruption to transport operations,
and climate change is projected to increase the frequency and intensity of these events …

Flooding impacts are on the rise globally, and concentrated in urban areas. Currently, there
are no operational systems to forecast flooding at spatial resolutions that can facilitate …

Flood risk in cities and built‐up areas is a major threat which is likely to grow due to
increased urbanisation and climate change. It is a priority for urban planning, civil defence …

We analyse chronologies of historical flash floods derived from searches of newspaper
archives and other sources commencing before 1800 and recent gauged rainfall and stream …