Soil Moisture Evaluation Using a Calibrated Sensor Network and a Soil-Vegetation-Atmospheric-Transfer Model.
AuthorHymer, Daniel Craig.
Plants -- Effect of soil moisture on.
Committee ChairMoran, Susan
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractRecent studies have proposed that images from Synthetic Aperture Radar (SAR) sensors can be used to map spatially distributed soil moisture patterns within 5 cm of the surface. Unfortunately, many hydrologic applications require vadose zone soil moisture measurements rather than surface soil moisture measured by the SAR sensor. By combining SAR-derived surface soil moisture maps with a Soil-Vegetation-Atmosphere- Transfer (SVAT) model, it may be possible to obtain spatially distributed, temporally continuous information on vadose zone soil moisture. The first step in developing such a combined approach is to investigate the accuracy and precision of a SVAT model to estimate surface and vadose zone soil moisture over time. In this experiment, we evaluated the Simultaneous Heat and Water (SHAW) model by comparing its soil moisture estimates to a calibrated, one year, hourly soil moisture data set at three different depths under bare soil and shrub cover surfaces. Analysis indicated that the SHAW model overestimated soil moisture at each depth by an average of 0.02 M^3M&-3 under bare soil and underestimated soil moisture at each depth under shrub cover by an average of 0.02 m^3m^-3 . Based on this research, future studies should focus on calibration of the SHAW model and the assimilation of remotely sensed data as a primary model input.
Degree ProgramSoil, Water and Environmental Science