For accurate weather prediction, accurate modeling of surface hydrological processes is very important. Most current models capture the biophysics of moisture and energy transport and of crop growth and development pretty well. However, model estimates of soil moisture in the root zone diverge from reality due to accumulated errors in initialization, forcings, and computation. Remotely sensed microwave observations can be assimilated into these models to improve root zone soil moisture and crop yield estimates. This 100-page report describes the observations conducted during a season-long experiment in elephant grass and sweet corn using active and passive microwave observations. Published by the UF Department of Agricultural and Biological Engineering, April 2015. (Photo: J. Casanova, UF)
http://edis.ifas.ufl.edu/ae512