Jul 7 2014
A collaborative European Marie Curie Initial Training Network (ITN) project that includes researchers from the University of Bristol aims to train high calibre PhD and postdoctoral researchers with a comprehensive understanding of water quality processes, uncertainty issues and decision making strategies for integrated water catchment management.
Dr Miguel A Rico-Ramirez and Professor Dawei Han from the Department of Civil Engineering are partners of the project called QUICS (Quantifying Uncertainty in Integrated Catchment Studies). QUICS focuses on the modelling of water quality across the whole catchment and will link uncertainty in the modelling of hydrologic and surface water quality processes on rural and urban environments. QUICS includes training workshops and secondments for all researchers within the network.
Dr Rico-Ramirez, Senior Lecturer in Radar Hydrology and Hydroinformatics and a member of the Cabot Institute at the University of Bristol, said: ‘Quantifying uncertainty in data measurements and models can improve our understanding of uncertainty in integrated water quality predictions.’
The University of Bristol is a key partner in the project and will be responsible for developing new methods and models to quantify uncertainty in radar rainfall measurements.
The research project is led by the University of Sheffield with collaborative partners from the Netherlands, Germany, Portugal, Luxemburg, Switzerland, and the UK and associate partners from Belgium, Italy, Germany, the Netherlands, Canada and Portugal.
QUICS is a €4.1 million project funded from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 607000.
The Cabot Institute
The Cabot Institute carries out fundamental and responsive research on risks and uncertainties in a changing environment. It drives new research in the interconnected areas of climate change, natural hazards, water and food security, low carbon energy, and future cities. Its research fuses rigorous statistical and numerical modelling with a deep understanding of social, environmental and engineered systems – past, present and future. It seeks to engage wider society by listening to, exploring with, and challenging its stakeholders to develop a shared response to 21st Century challenges.