259-6 Proximal Soil Sensing to Parameterize Spatial Environmental Modeling.



Tuesday, October 18, 2011: 10:05 AM
Henry Gonzalez Convention Center, Room 209, Concourse Level

Kenneth A. Sudduth, Claire Baffaut and E. John Sadler, USDA-ARS Cropping Systems & Water Quality Research Unit, Columbia, MO
Spatially explicit models are important tools to understand the effects of the interaction of management and landscape factors on water and soil quality. One challenge to application of such models is the need to know spatially-distributed values for input parameters. Some such data can come from available databases, such as soil survey or DEMs, but these data sources often do not have the spatial resolution needed for best results. Field measured data can overcome the resolution issue but may be impractical for larger areas. Proximal soil sensors, calibrated to parameters of interest, offer a more efficient approach. In this case study proximal sensing of soil electrical conductivity was used to infer topsoil depth above a claypan horizon. Variations in topsoil depth over the landscape were important in delineating areas vulnerable to surface runoff and chemical transport, as confirmed by APEX modeling.
See more from this Division: S05 Pedology
See more from this Session: Symposium--Spatial Predictions In Soils, Crops and Agro/Forest/Urban/Wetland Ecosystems: I