Using SSURGO data to improve Sacramento Model a priori parameter estimates

As it transitions to smaller scale, distributed hydrologic modeling approaches, the National Weather Service (NWS) is improving methods of estimating parameters for the Sacramento Soil Moisture Accounting model (SAC-SMA). This is the major hydrologic model used for flood forecasting at most of the 13 river forecasting centers throughout the United States. A physically based approach based on the nationally available State Soil Geographic Database (STATSGO) has been developed (Koren, V.I., Smith, M., Wang, D., Zhang, Z., 2000. Use of soil property data in the derivation of conceptual rainfall–runoff model parameters. Proceedings of the 15th Conference on Hydrology, AMS, Long Beach, CA, pp. 103–106; Koren, V., Smith, M., Duan, Q., 2003. Use of a priori parameter estimates in the derivation of spatially consistent parameter sets of rainfall–runoff models. In: Duan, Q., Sorooshian, S., Gupta, H., Rosseau, H., Turcotte, H. (Eds.), Calibration of Watershed Models, Water Science and Applications 6, AGU, pp. 239–254), leading to objective, spatially consistent parameter estimates. This paper shows that a better representation of basin physical properties and potential improvements in hydrologic simulation performance can be obtained by basing parameter estimates on a finer-scale database of soils data, the Soil Survey Geographic Database (SSURGO), combined with high-resolution land use/land cover data. Results also suggest that an intermediate level of improvement may be obtained by combining detailed land cover data with STATSGO to refine current parameter estimates. This latter finding is significant because the SSURGO data are not yet available for the entire country.