Optimal risk-based decisions by maximizing extraction of environmental information for streamflow forecasts
To effectively combine real-time information and understanding of physical processes involved in droughts and floods, Dr.Weijs chose to focus on the Val Ferret watershed in the Alps. By balancing information flows from intensive measurements and state-of the art models, Weijs’s methods will be essential to move from detailed physical understanding to probabilistic streamflow forecasts that can be produced cost-effectively and inform decisions reducing flood and drought risks.
My research focuses on analysing how detailed measurements of environmental variables such as rainfall, soil moisture and temperature, contribute information to forecasts of river flows further downstream and ultimately contribute to risk-based informed decisions. To perform this analysis, the framework of information theory is used to follow information in its flow from observation to decision. Taking this integrated view can lead to new insights about model calibration, sensor network design, and probabilistic forecasting.
École Polytechnique Fédérale de Lausanne
The art of streaming uncertainties
To add or modify information on this page, please contact us at the following address: email@example.com
Strengthening Coastal Communities’ Resilience Through Better Forecasting and Projecting Compound Flood Risk
‘Soft-path’ measures, such as early warning and early action systems, real-time emergency management, insurance, and disaster financial risk hedging mechanisms,... Read more
Politecnico di Milano
Joint Research Initiative
New Probabilistic Assessment of Seismic Hazard, Losses and Risks in Strong Seismic Prone Regions
Assessing seismic hazard and their economic and human losses is of high relevance, both scientifically, for insurers, and for communities... Read more