Submitted to: Advances in Water Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/2/2001
Publication Date: N/A
Interpretive Summary: The amount of moisture present in soil affects agriculture and engineering, and influences environmental phenomena such as flooding and climate. A better understanding of soil moisture and its distribution in space and time would permit greater control over these important activities and phenomena. Soil moisture content changes as you move across a landscape. The variability arises from a complex interaction of many geophysical parameters such as soil type, topography, vegetation, and climate. A complicating factor is that the relationship between soil moisture and the other parameters changes depending on the space and time scales that you consider. This study was done to improve our understanding of soil moisture and its relationship to various geophysical and land-use factors. Soil moisture data was collected for three weeks over three 160-acre fields. Analyses of the data showed that soil moisture patterns and dynamics differed considerably among the three fields because of differing soil type, land-use, and vegetation. A comparison of ground-based measurements and remote sensing measurements found that the remote sensing instrument worked well in one field but was less satisfactory in the other two fields. This work will benefit scientists who are trying to better understand soil moisture and its distribution in space and time.
Technical Abstract: Air-borne passive microwave remote sensors measure soil moisture at the footprint scale, a scale of several hundred square meters or kilometers that encompasses different characteristic combinations of soil, topography, vegetation, and climate. Studies of within-footprint variability of soil moisture are needed to determine the factors governing hydrologic processes and their relative importance, as well as to test the efficacy of remote sensors. Gridded ground-based impedance probe water content data and air-craft-mounted Electronically Scanned Thinned Array Radiometer (ESTAR) pixel-average soil moisture data were used to investigate the spatio-temporal evolution and time-stable characteristics of soil moisture in three selected (LW03, LW13, LW21) footprints from the Southern Great Plains 1997 (SGP97) Hydrology Experiment. Better time-stable features were observed within a footprint containing sandy loam soil than within to pixels containing silty loam soil. Additionally, flat topography with split wheat/grass land cover produced the largest spatio-temporal variability and the least time stability in soil moisture patterns. A comparison of ground-based and remote sensing data showed that ESTAR footprint-average soil moisture was well calibrated for the LW03 pixed with sandy loam soil, rolling topography, and pasture land cover, but improved calibration is warranted for the LW13 (silty loam soil, rolling topography, pasture land) and LW21 (silty loam soil, flat topography, split vegetation of wheat and grass land with tillage practices) pixels. Footprint-scale variability and associated nonlinear soil moisture dynamics may prove to be critical in the regional-scale hydroclimatic models.