HR: 09:45h
AN: H11G-07    [Abstracts]
TI: Estimating Model Parameter Uncertainty Using A Distribution Oriented Approach and a Similarity Measure
AU: * Tcherednichenko, I A
EM: irinat@u.arizona.edu
AF: Civil Engineering and Engineering Mechanics, University of Arizona, CE Building, Room 206, Tucson, AZ 85721 United States
AU: Bastidas, L A
EM: luis.bastidas@usu.edu
AF: Civil and Environmental Engineering and Utah Water Research Laboratory, Utah State University, 4110 Old Main Hill, Logan, UT 84322-4110 United States
AU: Lansey, K
EM: lansey@engr.arizona.edu
AF: Civil Engineering and Engineering Mechanics, University of Arizona, CE Building, Room 206, Tucson, AZ 85721 United States
AB: We use two very recently introduced in hydrology measures of performance: the Distributions Oriented (DO) approach and a set theory-based similarity metric - the Hausdorff Norm (HN) to evaluate the performance of two extensively used distributed rainfall-runoff models: Topmodel and PRMS. The distribution oriented approach considers the bivariate distribution of model outputs and observations and the corresponding marginal distributions. The Hausdorff norm allows for the inclusion, within the same framework or measure, both the spatial and temporal scales as a single multi-dimensional array. The performance evaluation is carried out over different time and spatial scales. The models are run over two nested catchments located in different climatic environments - one relatively wet, the Blue River in Oklahoma, and other semi-arid - the Sycamore Creek in Arizona. The levels and quality of input information are very dissimilar. To drive the models radar precipitation is used for the Blue River while the products generated at the University of Washington and gage measurements are used for Sycamore Creek. Both catchments have nested gages and the models are run to simulate 10 years of daily runoff at those points with different levels of discretization/resolution. Both measures: the DO and the HN, are used for parameter estimation using the multiple objective framework developed at the University of Arizona -that allows for the inclusion of trade-off uncertainties of the objective functions, and are compared against each other and against traditional scalar measures of performance as Nash Sutcliffe efficiency, bias, and general duration curves. In the Sycamore Creek a PRMS parameterization of the channel transmission losses is also considered for evaluation because of the important role played by those losses in the shape of the hydrographs.
DE: 1854 Precipitation (3354)
DE: 1860 Runoff and streamflow
DE: 1869 Stochastic processes
DE: 1894 Instruments and techniques
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting