Journal of Hydrology, Feb 8, 2012, Vol.418-419, p.61(17)
To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jhydrol.2009.02.021 Byline: Behnaz Khakbaz, Bisher Imam, Kuolin Hsu, Soroosh Sorooshian Keywords: Distributed hydrologic modeling; Calibration; A priori parameters; Multi-sensor precipitation; Streamflow simulation Abstract: Modeling the effect of spatial variability of precipitation and basin characteristics on streamflow requires the use of distributed or semi-distributed hydrologic models. This paper addresses a DMIP 2 study that focuses on the advantages of using a semi-distributed modeling structure. We first present a revised semi-distributed structure of the NWS SACramento Soil Moisture Accounting (SAC-SMA) model that separates the routing of fast and slow response runoff components, and thus explicitly accounts for the differences between the two components. We then test four different calibration strategies that take advantage of the strengths of existing optimization algorithms (SCE-UA) and schemes (MACS). These strategies include: (1) lumped parameters and basin averaged precipitation, (2) semi-lumped parameters and distributed precipitation forcing, (3) semi-distributed parameters and distributed precipitation forcing and (4) lumped parameters and basin averaged precipitation, modified using a priori parameters of the SAC-SMA model. Finally, we explore the value of using discharge observations at interior points in model calibration by assessing gains/losses in hydrograph simulations at the basin outlet. Our investigation focuses on two key DMIP 2 science questions. Specifically, we investigate (a) the ability of the semi-distributed model structure to improve stream flow simulations at the basin outlet and (b) to provide reasonably good simulations at interior points. The semi-distributed model is calibrated for the Illinois River Basin at Siloam Springs, Arkansas using streamflow observations at the basin outlet only. The results indicate that lumped to distributed calibration strategies (1 and 4) both improve simulation at the outlet and provide meaningful streamflow predictions at interior points. In addition, the results of the complementary study, which uses interior points during the model calibration, suggest that model performance at the outlet can be further improved by using a semi-distributed structure calibrated at both interior points and the outlet, even when only a few years of historical record are available. Author Affiliation: Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, E 4130 Engineering Gateway, Irvine, CA 92697, USA
Streamflow -- Models ; Streamflow -- Analysis ; Precipitation (Meteorology) -- Models ; Precipitation (Meteorology) -- Analysis ; Algorithms -- Models ; Algorithms -- Analysis ; Soil Moisture -- Models ; Soil Moisture -- Analysis ; Precipitation Variability -- Models ; Precipitation Variability -- Analysis ; Hydrology -- Models ; Hydrology -- Analysis ; Runoff -- Models ; Runoff -- Analysis ; Optimization Theory -- Models ; Optimization Theory -- Analysis
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