Information - HS3.1 Predictive probability, uncertainty and data assimilation in hydrological forecasting
Event Information
The first part of this session will address issues of predictive probability and uncertainty in hydrological forecasting. It will deal with definitions, basic concepts and case studies of the role and use of predictive probability in hydrological forecasting. It will also include methodologies of short- and mid-term real-time forecasting with an emphasis on uncertainty analysis, probabilistic forecasting and communication to stakeholders. Contributions are expected to address the issues set down below.
(i) Uncertainty propagation in meteorological-hydrological forecasting arising from the use of quantitative meteorological forecasts and ensemble forecasts in hydrological forecasting.
(ii) Assessment of predictive probability and uncertainty propagation including ensemble flood forecasting for decision-making under uncertainty.
(iii) Probabilistic storm and flood forecasting linked to ensemble forecasting.
(iv) Role of flood forecasting in flood management and interaction with decision-makers.
The second part of the session will address the related topic of data assimilation in hydrological forecasting. Methods that help update forecasts in real-time mode to reduce bias and increase accuracy will form the main focus. Forms of Kalman filtering and Monte Carlo methods with links to Bayesian forecasting will be among the techniques to be considered, both in hypothetical settings and as real-world case studies. The models involved may include catchment models, runoff routing models, groundwater models, coupled meteorological-hydrological models as well as combinations of the above. Contributions are expected to deal with one or more of the topics below:
(i) Methods that allow use of river flow data and other ground-based hydrological data in real-time flow forecasting.
(ii) Methods that allow use of remotely-sensed data and meteorological forecast data in real-time hydrological simulations of the water cycle.
iii) Methods for preparing meteorological forecast data as input to real-time hydrological simulations.
(iv) Case studies of the above.
Preliminary List of Solicited Speakers
Co-Sponsorship
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