Soil Moisture from Point to Footprint Scale: Spatio-Temporal Variability, Time Stability, and Physical Controls

Soil moisture is a key state variable of the hydrologic cycle. It plays a significant role in many hydrological, meteorological and other natural processes in the land-atmosphere continuum. In the past two decades we have conducted several field campaigns to better understand the underlying processes controlling the spatio-temporal variations of soil moisture using multiple ground, air, and space-borne sensors. In this effort, we will present characteristics spatio-temporal variabilities, time stability, as well as their geophysical controls at different measurement support scales (point-scale, airborne, to space borne remote sensor footprints) in different hydro-climatic regions. The data used in the analyses consist of in-situ and passive microwave remotely sensed soil moisture data from Southern Great Plains in Walnut Creek (WC) watershed, Iowa. Results show that in both the regions soil properties (i.e., percentage silt, percentage sand, and soil texture), and topography (elevation and slope) are significant physical controls jointly affecting the spatio-temporal evolution and time stability of soil moisture at both point-and footprint-scale. In Iowa, using point scale soil moisture measurements, WC11 field was found to be more time stable than the WC12 field. The common time stable points using data across the 3-year period (2002-2005) were mostly located at moderate to high elevations in both the fields. Further, the soil texture at these locations consists of either loam or clay loam soil. Drainage features and cropping practices also affected the field-scale soil moisture variability in the WC fields. In Oklahoma, the field having a flat topography (LW21) showed worst time stable features compared to the fields (LW03 and LW13) having gently rolling topography. The LW13 field (silt loam) exhibited better time stability than LW03 field (sandy loam) and LW21 (silt loam) field. At the remote sensing footprint-scale, the ANOVA tests show that the percentage clay and percentage sand are better able to discern the time stable features of the footprints compared to the soil texture in Iowa.