HR: 11:15h
AN: H32C-04    [Abstracts]
TI: Understanding uncertainties in hydrological models: Insights gained from a large ensemble of model structures
AU: * Clark, M P
EM: mp.clark@niwa.co.nz
AF: NIWA, 10 Kyle Street, Christchurch, 8004, New Zealand
AB: Multi-model ensembles are only valuable if there is independent information in the different models used to construct the ensemble. The critical question therefore is what is the nature of differences between models? To address this question we mix-and-match different architectures and different process parameterizations from different models to construct 79 hydrological models, all with different structure. These models were used to simulate streamflow in two basins in the USA: the Guadalupe River (Texas) and the French Broad River (South Carolina). The main insights gained from this exercise are [1] the differences in skill between models were larger in the Guadalupe River (drier basin) than the French Broad (wetter basin); [2] differences in model skill can be attributed to the choice of model structure -- the models with highest skill in the Guadalupe River were those that had low frequency variability in saturated areas (this was easiest to achieve when saturated area is controlled by lower zone storage); and [3] many models had similar errors for the same storm, suggesting the independent information in multiple models may be quite limited (or alternatively, there are large errors in model inputs). Further application of these models in different river basins will elucidate the independence between models, and determine which model structures are most suitable in specific environments.
DE: 1805 Computational hydrology
DE: 1816 Estimation and forecasting
DE: 1833 Hydroclimatology
DE: 1840 Hydrometeorology
DE: 1873 Uncertainty assessment (3275)
SC: Hydrology [H]
MN: 2007 Fall Meeting