Ebrahim Babaeian1, Morteza Sadeghi2, Wenyi Sheng3, Rong Zhou2, Scott B. Jones4 and Markus Tuller5, (1)Department of Soil, Water and Environmental Science, University of Arizona, Tucson, AZ (2)Department of Plants, Soils and Climate, Utah State University, Logan, UT (3)Utah State University, Utah State University, Logan, UT (4)4820 Old Main Hill, Utah State University, Logan, UT (5)Soil, Water and Environmental Science, University of Arizona, Tucson, AZ
Optical remote-sensing (RS) provides an exceedingly powerful means for monitoring spatial surface (skin) soil moisture distributions. However, the relatively small penetration depth of electromagnetic radiation within the optical domain (400-2500 nm) and limited near-surface resolution of moisture sensors employed for ground truth calibration of RS observations provide a challenge for accurate near-surface moisture estimations. To better understand the relationship between skin and near-surface soil moisture we employed a benchtop hyperspectral line-scan imaging system to generate high resolution surface reflectance maps during evaporation from a soil column instrumented with a novel time domain reflectometry (TDR) sensor array that allows monitoring of near surface moisture at 1-cm or better resolution. A recently developed physically-based model for skin soil moisture predictions from shortwave infrared reflectance was applied to estimate skin soil moisture from surface reflectance and to explore the relationship between skin and near-surface moisture distributions during soil drying. Preliminary results will be presented and the potential of obtained findings for ground truth calibration of RS observations will be discussed.