Multi-scale data assimilation and its application to water availability prediction
|Event Name||Multi-scale data assimilation and its application to water availability prediction|
|Start Date||21st Apr 2017 2:00pm|
|End Date||21st Apr 2017 2:30pm|
PhD Progress Review: Mr Ashkan Shokri
Research Theme: Monitoring, Prediction and Protection
Water availability prediction is an important step toward facing water related challenges. A good forecast helps farmers, water managers, and many other stakeholders to get prepared and maybe take alternative decisions. In order to have an ideal evaluation of the future, sufficient system knowledge about the initial state, along with an error-free model and the best possible climate forecasts, are required. Hydrological models can provide an evaluation of current states by modelling the system and data assimilation methods can improve this evaluation by updating the model states using external observations. Despite numerous studies about data assimilation, there are still questions about them. As an example, assimilation of a very coarse observation (i.e. GRACE satellite products) into a fine scale model is numerically problematic. The focus of this study is to find an efficient solution to solve this problem.
Ashkan received his B.Sc degree from University of Tehran, Iran in 2009 and he completed his M.Sc at the same university in 2011. He worked in consulting companies as an engineer for about 4 years before commencing his PhD in 2015 under supervision of A/Prof. Pauwels and Prof. Walker.