HR: 0800h
AN: H21C-0692    [Abstracts]
TI: Performance and Probabilistic Verification of Regional Parameter Estimates for Conceptual Rainfall-runoff Models
AU: Franz, K
EM: kfranz@iastate.edu
AF: Iowa State University, Geological and Atmospheric Sciences 3023 Agronomy Hall, Ames, IA 50011, United States
AU: * Hogue, T
EM: thogue@seas.ucla.edu
AF: UCLA, Department of Civil and Environmental Engineering 5732 Boelter Hall, Los Angeles, CA 90095-1593, United States
AU: Barco, J
EM: ojbarco@ucla.edu
AF: UCLA, Department of Civil and Environmental Engineering 5732 Boelter Hall, Los Angeles, CA 90095-1593, United States
AB: Identification of appropriate parameter sets for simulation of streamflow in ungauged basins has become a significant challenge for both operational and research hydrologists. This is especially difficult in the case of conceptual models, when model parameters typically must be "calibrated" or adjusted to match streamflow conditions in specific systems (i.e. some of the parameters are not directly observable). This paper addresses the performance and uncertainty associated with transferring conceptual rainfall-runoff model parameters between basins within large-scale ecoregions. We use the National Weather Service's (NWS) operational hydrologic model, the SACramento Soil Moisture Accounting (SAC-SMA) model. A Multi-Step Automatic Calibration Scheme (MACS), using the Shuffle Complex Evolution (SCE), is used to optimize SAC-SMA parameters for a group of watersheds with extensive hydrologic records from the Model Parameter Estimation Experiment (MOPEX) database. We then explore "hydroclimatic" relationships between basins to facilitate regionalization of parameters for an established ecoregion in the southeastern United States. The impact of regionalized parameters is evaluated via standard model performance statistics as well as through generation of hindcasts and probabilistic verification procedures to evaluate streamflow forecast skill. Preliminary results show climatology ("climate neighbor") to be a better indicator of transferability than physical similarities or proximity ("nearest neighbor"). The mean and median of all the parameters within the ecoregion are the poorest choice for the ungauged basin. The choice of regionalized parameter set affected the skill of the ensemble streamflow hindcasts, however, all parameter sets show little skill in forecasts after five weeks (i.e. climatology is as good an indicator of future streamflows). In addition, the optimum parameter set changed seasonally, with the "nearest neighbor" showing the highest skill in the winter months and the "climate neighbor" showing the highest skill in the summer months.
DE: 1816 Estimation and forecasting
DE: 1846 Model calibration (3333)
DE: 1873 Uncertainty assessment (3275)
DE: 1874 Ungaged basins
SC: Hydrology [H]
MN: 2007 Fall Meeting