Spatial Variability of SEBAL Estimated Root-Zone Soil Moisture across Scales.

This study investigated the spatial scaling behavior of root zone soil moisture obtained from optical/thermal remote sensing observations. The data for this study were obtained from Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) satellites on five different dates between early spring (April) and fall (September) in the years from 2000 to 2004 in the semi-arid middle Rio Grande Valley of New Mexico. Soil moisture data were obtained using the Surface Energy Balance Algorithm for Land (SEBAL) algorithm. The data were spatially aggregated and checked for power law behavior over a range of scales from 30 m to 15 km for Landsat and from 1 km to 28 km for MODIS images. Results of this study demonstrate that power law scaling of soil moisture in the middle Rio Grande area holds up to 1 km² pixel size, but is no longer valid beyond that scale. While previous studies have studied soil moisture in the top 5 cm of the soil using radar and point measurements, our study uses SEBAL to estimate root-zone soil moisture. Our study is consistent with these previous studies in showing that variation in root-zone soil follows an empirical power law for pixel sizes of up to about 10⁶ m² and that there is an apparent break in the scaling at larger scales.