Abstract
P-band radar remote sensing applied during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission has shown great potential for estimation of root zone soil moisture. When retrieving the soil moisture profile (SMP) from P-band radar observations, a mathematical function describing the vertical moisture distribution is required. Because only a limited number of observations are available, the number of free parameters of the mathematical model must not exceed the number of observed data. For this reason, an empirical quadratic function (second order polynomial) is currently applied in the AirMOSS inversion algorithm to retrieve the SMP. The three free parameters of the polynomial are retrieved for each AirMOSS pixel using three backscatter observations (i.e., one frequency at three polarizations of Horizontal-Horizontal, Vertical-Vertical and Horizontal-Vertical). In this paper, a more realistic, physically-based SMP model containing three free parameters is derived, based on a solution to Richards’ equation for unsaturated flow in soils. Evaluation of the new SMP model based on both numerical simulations and measured data revealed that it exhibits greater flexibility for fitting measured and simulated SMPs than the currently applied polynomial. It is also demonstrated that the new SMP model can be reduced to a second order polynomial at the expense of fitting accuracy.
Highlights
Soil moisture is a key state variable that controls all major processes and feedback loops within the climate system
In the following it is demonstrated that the second order polynomial soil moisture profile (SMP) can be derived from the new solution if P = 1, which highlights the limitation of the polynomial SMP when compared to the new solution
It is evident that a reasonably good fit was achieved with the same soil parameters, P and hcM, as applied for the evaporation process shown in Figure 1
Summary
Soil moisture is a key state variable that controls all major processes and feedback loops within the climate system. The retrieved SMPs are in turn assimilated or otherwise applied by hydrologists to estimate land surface model hydrological parameters over the nine biomes, generating a high-resolution time record of root zone soil moisture evolution. Warrick et al [27] based on the analysis of Broadbridge and White [28] introduced to our best knowledge the only analytical solution to the nonlinear RE for the case of evaporation and concurrent drainage This solution (Equation (26) in [27]) is not applicable for AirMOSS SMP retrieval because it consists of more than three free parameters (considering time as a constant in the solution to fit snapshot observations at any given time). Theoretical aspects for derivation of the new solution and its validation based on measured and numerically simulated data are presented together with sample AirMOSS SMP retrievals with the modified inversion algorithm
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