Environmental scientists and engineers often require calibrating and testing their models against observed data. Despite major research efforts by the hydrological community, both topics present formidable challenges, both in operational and research settings.
Coffee and light refreshments provided.
Description
The first half of the talk reviews recent advances in uncertainty quantification in catchment-scale hydrology, from operationally-oriented advances in residual error modelling to the fascinating direction of uncertainty decomposition.
The second half of the talk focuses on what can be learned through the application of a (distributed) flexible hydrological model to a catchment where extensive existing fieldwork can be used to independently appraise modelling results. We examine insights into dominant hydrological processes, how they change across the landscape, and how can a hydrologist design modelling experiments to investigate these questions in a systematic and informative manner.
Speaker bio
Dmitri Kavetski is a professor of Civil and Environmental Engineering at the University of Adelaide. He is the main author and developer of the BATEA framework, which provides a platform for model inference and prediction using Bayesian methods. He has also contributed to the FUSE and SUPERFLEX toolkits for building hydrological models. Dmitri's current interests focus on uncertainty quantification and hypothesis testing in hydrology.
Your
co-hosts
Department
of
Civil
&
Environmental
Engineering
and
Water
Institute