The Spatial and Temporal Variability of Soil Moisture Conditions at the Norman Mesonet Site: Comparison with Near-surface Atmospheric Conditions

In 1996, Campbell Scientific 229-L matric potential sensors were installed at the Norman Mesonet site and its co-located test-bed facility . The sensors were installed at depths of 5, 25, 65, and 75 cm. The 229-L sensors are unique in that they provide an estimate of both soil water potential and soil water content every 30 minutes. However, it is uncertain whether a single point measurement of soil moisture can be used to provide information for regional meteorological studies. Thus, the goal of this study is to provide insight into the spatial and temporal variability of soil moisture conditions surrounding the Norman Mesonet site. A 20 X 20 m study plot was created enclosing the Norman site, and surrounding the 229-L sensors. The study plot contains a set of 12 locations from which the soil moisture conditions were sampled. The locations were chosen in a manner suitable to provide valuable information for both spatial averaging and correlation analysis. Both soil water potential, which controls the flow of water in the soil, and soil water content, which is important for mass balance considerations, are of interest in meteorologic studies. Thus, at each sample location, tensiometers were installed which provide an estimate of soil water pressure (water potential) from 0 to -1000 mb. The tensiometers are non-automated and require regular site visits in order to collect data. Gravimetric samples were also collected at each of the twelve locations once every 3-4 days.

Preliminary analysis indicates that the overall spatial variability of soil water content and soil water pressure at the Norman site is small. In addition, the gravimetric samples of water content, as well as the water potential observations collected from the tensiometers, compare well with the automated 229-L sensors. Further, the observations of soil moisture (both water potential and soil water content) show strong relationships with near-surface meteorological observations (air temperature, mixing ratio, sensible heat flux, latent heat flux, ground heat flux, and net radiation).