243-12 Application of Large-Scale Soil Water Data In Heterogeneous Regions.



Tuesday, October 18, 2011: 11:10 AM
Henry Gonzalez Convention Center, Room 206A, Concourse Level

Mark Seyfried, ARS-USDA, Boise, IN
Knowledge of large-scale soil water content with time could prove to be very useful for a number of applications in the intermountain west. Past research has shown there to be strong correlation between soil water and stream flow generation, plant productivity and fire hazard.  Current satellite soil water data as well as that planned for near future missions, is of little direct value for the applications listed above for two important reasons; the measurements are too shallow (5 cm) and the spatial resolution is too coarse (multiple km). While hydrologic and biotic processes utilize water to depths much greater than 5 cm, the 5 cm water content is subject to change practically independent of subsoil water conditions. On a spatial scale, the length scale of soil water variability is controlled by elevation, topography and soil type, all of which vary at much smaller scales than the pixel resolution. The overall average values are not directly related to field conditions because each pixel is a unique mixture of conditions. However, there is a strong regional climate signature that should be well documented in the satellite imagery. The strong temporal stability of soil water within the region suggests that it may be possible to use satellite-measured soil water as an index of productivity, stream flow generation, etc. We use a relatively small but highly heterogeneous watershed to demonstrate how, in principle, one can relate average surface soil water values to overall watershed conditions. Measured soil water contents in the much larger (238 km2) Reynolds Creek Experimental Watershed are used to investigate the linkage between large-scale weather patterns and site specific soil water content.
See more from this Division: S01 Soil Physics
See more from this Session: Advances In Large-Scale Soil Moisture Monitoring: Methods and Applications