Soil moisture is an important parameter in many hydrologic and land-atmosphere interactions. Anomalous soil moisture conditions on a large-scale can lead to droughts or floods, while regional variations can enhance dryline formation, convective initiation, and precipitation recycling. Furthermore, the relative partitioning between latent and sensible heat fluxes at all spatial and temporal scales is controlled largely by variations in soil moisture conditions. Thus, understanding the spatial and temporal nature of soil moisture is vital to determine the influence that land surface processes have upon the atmosphere.
The Oklahoma Mesonet, an automated network of 114 meteorological observing stations, installed soil moisture monitoring devices at 60 locations during the winter of 1996-97. Due to its capability to perform as a fully-automated soil water measuring device, the Campbell Scientific model 229-L matric potential sensor was chosen for operational use. Extensive laboratory calibrations were performed to ensure the quality of matric potential (water potential) measurements by each sensor. In addition, soil analyses down to 75 cm were performed for each sensor location to determine the characteristics of the soil in which the sensors were installed. With knowledge of soil characteristics, it became possible to estimate the volumetric water content of the soil at each location and depth. Thus, the Oklahoma Mesonet has the ability to estimate two widely accepted measurements of soil moisture.
The diurnal cycle of atmospheric mixing ratio, air temperature, sensible heat flux, as well as atmospheric pressure and height above ground level at the Lifting Condensation Level were analyzed versus variations in soil moisture conditions. The analysis revealed significant variations in the diurnal oscillation of atmospheric quantities due to variations in soil moisture. In addition, monthly averaged data at each site were used to compute objectively-analyzed gridded fields of near-surface (5 cm) soil matric potential and volumetric water content. Comparison of the two types of monthly-averaged soil moisture fields with various near-surface atmospheric parameters revealed significant spatial relationships between estimates of water potential and atmospheric quantities. However, little correlation was observed between atmospheric parameters and estimates of volumetric water content.