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  Information - HS8 Uncertainty Assessment in Spatially Distributed Hydrologic Modelling: Strategies, Methods and Applications

Event Information
By now it is established that our model predictions should not be deterministic and only include an estimate of the most probable outcome, but also explictly include an estimate of its uncertainty. Recent years have seen an explosion of methods to derive this uncertainty on our model predictions. These methods include the use of classical Bayesian, pseudo-Bayesian, set- theoretic, multiple criteria and sequential data assimilation methods to represent model parameter, state and prediction uncertainty. These methods all have strengths and weakness, but differ in their underlying assumptions and how the various sources of error are made explicit. Despite this progress made, it is not particularly clear how best to adapt current methods to spatially distributed hydrologic models, which potentially contain a large number of model parameters and states, and for which different measurement data are available for calibration purposes. In this session we aim to invite people from groundwater, subsurface and surface hydrology to discuss recent advances in hydrologic uncertainty assessment. Contributions related to uncertainty assessment of spatially distributed hydrologic models are particularly welcomed.

Preliminary List of Solicited Speakers
Martyn Clark
Center for Science and Technology Policy Research
Boulder, CO

Jesus Carrera
Technical University of Catalonia


General Statement
The information contained hereafter has been compiled and uploaded by the Session Organizers via the "Organizer Session Form". The Session Organizers have therefore the sole responsibility that this information is true and accurate at the date of publication, and the conference organizer cannot accept any legal responsibility for any errors or omissions that may be made, and he makes no warranty, expressed or implied, with regard to the material published.

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