Topsoil Structure Influencing Soil Water Retrieval by Microwave Radiometry

Abstract

Many remote sensing applications, including those of future space missions, require accurate knowledge of the influence of topsoil structure on the water content as measured using L‐band radiometry. We report on field‐measured L‐band (1.4 GHz) microwave emission from a bare soil. Of special interest in this work is the procedure used to transform remotely sensed data to soil water content and its comparability with time domain reflectometer (TDR) in situ measurements. Surface roughness of the soil was characterized on a millimeter scale using an optical measurement technique. Different models for interpreting the microwave signals in terms of the water content were investigated. The agreement between in situ water contents and surface water contents estimated with radiometry data using the Fresnel equation was found to be poor. A coherent layer model, with and without considering roughness effects, was tested to compare radiometrically measured and modeled soil reflectivities. The correspondence remained unsatisfactory, even when we considered a dielectric gradient fitted to the TDR profiles and surface roughness represented by a scattering model. We developed a new air‐to‐soil transition model, which includes dielectric mixing effects due to small‐scale surface structures. This model considerably improved agreement between measured and modeled results. We conclude that small‐scale structures of the topsoil cannot be neglected in interpreting L‐band measurements.

Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

“…R and RMSE were only calculated for grid cells where AMSR-E or AS-CAT and Noah have more than 20 common values. Over extremely dry regions (e.g., Sahara desert), AMSR-E has fewer soil moisture retrievals, possibly due to the constant value of surface roughness used in the VUA-NASA algorithm (Schneeberger et al, 2004;Escorihuela et al, 2007;De Jeu et al, 2009;Liu et al, 2010).…”

Microwave L-band emission of freezing soil

“…This model is often used for the determination of the soil moisture from radiometric data [21]. However, the water content derived in this way is in many cases not comparable to the values obtained from other soil moisture detection techniques such as time-domain reflectometry (TDR) [22]. For this reason, soil reflectivities were compared among each other instead of soil moisture values.…”

“…As will be discussed later (Section IV-B), the radiometrically determined soil reflectivity for horizontal polarization is systematically smaller than the reflectivities and , which were calculated using the radiative transfer model. A better fit can be achieved if the radiative model is supplemented by an air-to-soil transition model considering dielectric mixing effects due to the small-scale surface structure [22] of the observed site. In a wider understanding, this model can also account for low plant canopy and thin snow layers on bare soil or for cavities and stones within the uppermost soil horizon.…”

“…The surface incorporates irregularities (e.g., roughness, cavities, stones, low vegetation, and snow), which are laterally not resolved when observed at long wavelengths like L-band. This is accommodated by introducing a transition zone [22], wherein the proportion of soil matrix (bulk soil) is increasing with depth. The increasing portion of soil matrix is described by a function , which is mainly defined by the surface roughness.…”

Global Soil Moisture Patterns Observed by Space Borne Microwave Radiometers and Scatterometers

“…In preparation for SMOS, research in the passive microwave domain has accelerated and supporting field studies have resulted in various new insights. For example, microwave emission from the soil surface can now be described with more physically based soil transition models (Schneeberger et al 2004) in stead of the existing empirical descriptions (i.e. Choudhury et al 1979;Wang and Choudhury 1981).…”