It is difficult to accurately predict urban floods; there are many sources of error in urban flood forecast due to unknown model physics, computational limits, input data accuracy etc. However, many sources of model and input errors can be reduced through the use of data assimilation methods – mathematical techniques that combine model predictions with observations to produce more accurate forecast.

In this talk I will motivate and introduce the idea of using CCTV images as a new and valuable additional source of information in cities for improving the urban flood predictions through data assimilation methods. This work is part of the Data Assimilation for REsilient City (DARE) project.

You can see the whole presentation on YouTube here or view slides here.