Retrieving gap-free daily root zone soil moisture using surface flux equilibrium theory

Abstract

Root zone soil moisture (RZSM) is a dominant control on crop productivity, land-atmosphere feedbacks, and the hydrologic response of watersheds. Despite its importance, obtaining gap-free daily moisture data remains challenging. For example, remote sensing-based soil moisture products often have gaps arising from limits posed by the presence of clouds and satellite revisit period. Here, we retrieve a proxy of daily RZSM using the actual evapotranspiration (ETa) estimates from Surface Flux Equilibrium Theory (SFET). Our method is calibration-less, parsimonious, and only needs widely available meteorological data and standard land-surface parameters. Evaluation of the retrievals at Oklahoma Mesonet sites shows that our method, overall, matches or outperforms widely available RZSM estimates from three markedly different approaches, viz. remote sensing data based Atmosphere-Land EXchange Inversion (ALEXI) model, the Variable Infiltration Capacity (VIC) model, and the Soil Moisture Active Passive (SMAP) mission RZSM data product. When compared with in-situ observations, unbiased root mean square difference of retrieved RZSM were 0.03 (m ^3 m ^−3 ), 0.06 (m ^3 m ^−3 ), and 0.05 (m ^3 m ^−3 ) for our method, the ALEXI model, and the VIC model, respectively. Better performance of our method is attributed to the use of both SFET for the estimation of ETa and non-parametric kernel-based method used to relate the RZSM with ETa. RZSM from our method may serve as a more accurate and temporally-complete alternative for a variety of applications including mapping of agricultural droughts, assimilation of RZSM for hydrometeorological forecasting, and design of optimal irrigation schedules.

Keywords

• soil moisture proxy
• fraction of potential evapotranspiration
• kernel regression
• surface flux equilibrium theory
• ALEXI