Improving the spatial representation of soil properties and hydrology using topographically derived initialization processes in the SWAT model. Issue 24 (22nd August 2016) - Fuka, Daniel R.; Collick, Amy S.; Kleinman, Peter J.A.; Auerbach, Daniel A.; Harmel, R. Daren; Easton, Zachary M.
Abstract: Topography exerts critical controls on many hydrologic, geomorphologic and biophysical processes. However, many watershed modelling systems use topographic data only to define basin boundaries and stream channels, neglecting opportunities to account for topographic controls on processes such as soil genesis, soil moisture distributions and hydrological response. Here, we demonstrate a method that uses topographic data to adjust spatial soil morphologic and hydrologic attributes: texture, depth to the C‐horizon, saturated conductivity, bulk density, porosity and the water capacities at field (33 kpa) and wilting point (1500 kpa) tensions. As a proof of concept and initial performance test, the values of the topographically adjusted soil parameters and those from the Soil Survey Geographic Database (SSURGO; available at 1 : 20 000 scale) were compared with measured soil pedon pit data in the Grasslands Soil and Water Research Lab watershed in Riesel, TX. The topographically adjusted soils were better correlated with the pit measurements than were the SSURGO values. We then incorporated the topographically adjusted soils into an initialization of the Soil and Water Assessment Tool model for 15 Riesel research watersheds to investigate how changes in soil properties influence modelled hydrological responses at the field scale. The results showed that the topographically adjusted soils produced better runoff predictions in 50% of the fields, with the SSURGO soils performing better in the remainder. In addition, the a priori adjusted soils result in fewer calibrated model parameters. These results indicate that adjusting soil properties based on topography can result in more accurate soil characterization and, in some cases, improve model performance. Copyright © 2016 John Wiley & Sons, Ltd.