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