HR: 0800h
AN: H21A-0185    [Abstracts]
TI: A Semi-Distributed Hydrologic Model for Stream Flow Simulation Using the Sacramento Soil Moisture Accounting Model (SAC-SMA)
AU: * Khakbaz, B
EM: bkhakbaz@uci.edu
AF: Department of Civil and Environmental Engineering,The Henry Samueli School of Engineering,UCIrvine, E4130 Engineering Gateway, Irvine, CA 92697, United States
AU: Hsu, K
EM: kuolinh@uci.edu
AF: Department of Civil and Environmental Engineering,The Henry Samueli School of Engineering,UCIrvine, E4130 Engineering Gateway, Irvine, CA 92697, United States
AU: Sorooshian, S
EM: soroosh@uci.edu
AF: Department of Civil and Environmental Engineering,The Henry Samueli School of Engineering,UCIrvine, E4130 Engineering Gateway, Irvine, CA 92697, United States
AB: Distributed hydrologic modeling is currently viewed as a potential pathway to improve streamflow simulations regarding the sensitivity of runoff predictions to spatial and temporal variability of precipitation, land use, and soil properties. The US National Weather Service (NWS) started Distributed Model Intercomparison Project (DMIP) to guide NWS's distributed modeling research. In our participation of DMIP-2 activity, a semi-distributed version of the Sacramento Soil Moisture Accounting Model (SAC-SMA) was used to conduct hourly streamflow simulations. This model uses sub-basins as the computational elements of rainfall-runoff modeling. Each sub-basin consists of a lumped SAC-SMA to generate the response components of the runoff. Fast response components are routed over the hillslopes using the unit hydrograph of the sub-basin outlet. Slow response components bypass the hillslopes and are added directly to the sub-basin outlet. Then, a sub-basin-to-sub-basin channel routing is done using kinematic wave routing method. The Illinois River basin at South of Siloam Spring, AR is chosen as the study test basin. Eleven years of grid-based multi-sensor (NEXRAD+gauge) precipitation dataset are used for the calibration and verification periods. Weekly adjustment factors to account for vegetation type and cover are estimated using Global Vegetation Fraction (GVF) product from NOAA/NESDIS/STAR to produce PET demand for the watershed modeling. Several calibration scenarios are tested using the Shuffled Complex Evolution Method (Duan et al, 1992) and Multi Step Automatic Calibration Scheme (Hogue et al, 2000). Results of different calibration scenarios, besides simulations of a priori parameters of the SAC-SMA model (Koren et al, 2000) are shown. The results show that the semi-distributed version of the SAC-SMA has the potential to improve the streamflow simulations.
DE: 1800 HYDROLOGY
DE: 1846 Model calibration (3333)
DE: 1853 Precipitation-radar
DE: 1860 Streamflow
DE: 1879 Watershed
SC: Hydrology [H]
MN: 2007 Fall Meeting