SCENARIO - Improving river flood forecasts using machine learning and water observations from river camera images
We aim to draw water information of from river cameras for river flood forecasting using machine learning algorithms. This project involves processing of a large volume of data (river camera images) and analogue measurements on river observation. In this project, we use state-of-the-art machine learning algorithms (like deep learning neural network), adapt, and develop algorithms/procedure for the particular need of the project with the focus on developing online water observation system. The developed method will be validated with existing flood forecasting models and using Synthetic Aperture Radar (SAR) satellites images of Tewkesbury 2012 flooding event.
The project is multi-disciplinary research involving an excellent team of supervisors with the necessary background in machine learning, hydrology, observation systems, and data assimilation to successfully advise and guide the student throughout the project.
You can find a short video of Varun Ojha and Sanita Vetra-Carvalho talking about this project on YouTube: https://youtu.be/7QnpvOa9vCk
This project is potentially funded by the SCENARIO NERC Doctoral Training Partnership, subject to a competition to identify the strongest applicants. To apply, please follow the instructions at http://www.met.reading.ac.uk/nercdtp/home/apply.ph.
Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree, Masters Degree with Merit, or equivalent in (ideally) Computer Science.
Due to restrictions on the funding this studentship is only open to UK students and EU students who have lived in the UK for the past three years.