Soil Hydraulic Parameters of Bare Soil Plots with Different Soil Structure Inversely Derived from L‐Band Brightness Temperatures

Abstract

The structure of the surface layer of the soil is strongly influenced by soil tillage practices, with important consequences for the hydraulic properties and soil moisture dynamics in the top soil layer. In this study, during four 28‐d periods, we monitored L‐band brightness temperatures and infrared (IR) temperatures over bare silt loam soil plots with different soil surface structure: tilled, seedbed, and compacted plots. Differences in absolute and normalized L‐band brightness temperatures between the plots indicated that plot specific roughness, soil moisture contents, and soil hydraulic properties might be inverted from L‐band brightness temperatures using a coupled radiative transfer, roughness correction, and soil hydrological model. The inversely estimated surface roughness parameters compared well with those derived from laser profiler measurements. The estimated saturated water contents of the tilled and seedbed plots were larger than the one of the compacted plot, and the unsaturated hydraulic conductivity was smaller in the former plots than in the compacted plot for more negative pressure heads. These differences in hydraulic properties translated into larger dynamics of the simulated soil moisture during a 28‐d measurement period in the tilled and seedbed plots than in the compacted plot. This difference could be confirmed qualitatively but not quantitatively by in situ soil moisture measurements. Furthermore, differences in simulated actual evaporation rates between the plots were confirmed by observed differences in measured IR temperatures. The results indicate that effects of soil management on soil surface roughness and soil hydraulic properties could be inferred from L‐band brightness temperatures.

Modeling Soil Processes: Review, Key Challenges, and New Perspectives

“…One interesting approach to detect variables is the combination of measurements obtained at different incidence angles (Srivastava et al, 2003) or different frequencies, that is, with different sensitivity to soil moisture and soil surface roughness. Use of time-lapse MW observations and coupled-inversion or data-assimilation techniques with hydrological soil models (see also "Numerical Approaches and Model Data Integration") also proved to be one of the most potent venues for soil hydraulic property estimation from local to regional scales (Mohanty, 2013;Dimitrov et al, 2014;Jonard et al, 2015). Other approaches make use of the spatiotemporal variability of surface soil moisture to indirectly estimate hydraulic properties (van Genuchten, 1980), not only for the topsoil, but also for the root or vadose zone (Montzka et al, 2011;Kumar et al, 2012).…”

Recent Developments and Applications of the HYDRUS Computer Software Packages

“…The second largest group of HYDRUS applications published in VZJ comprised studies that use data collected with various geophysical methods (e.g., Montzka et al, 2013; Grunat et al, 2013; Moghadas et al, 2013; Ganz et al, 2014; Thoma et al, 2014; Lv et al, 2014; Dimitrov et al, 2014, 2015; and Persson et al, 2015). For example, several issues related to data assimilation, which involved both HYDRUS modeling and ERT or GPR were studied by Grunat et al (2013), Moghadas et al (2013), Ganz et al (2014), Thoma et al (2014), and Persson et al (2015).…”

“…Lv et al (2014) calibrated HYDRUS‐1D using soil moisture measurements from a network of time‐domain transmissometry (TDT) probes and then compared both measured and modeled water content values against cosmic‐ray neutron probe estimates. Finally, a series of papers by Dimitrov et al (2014, 2015) and Montzka et al (2013) used the HYDRUS‐1D model to inversely derive soil hydraulic parameters and surface soil water contents using L‐band brightness temperatures. All of these studies demonstrate how numerical modeling of subsurface flow processes can be used to optimize the analysis of geophysical data.…”

Influence of Radiation on Evaporation Rates: A Numerical Analysis

“…To assess this uncertainty, a test case is set up where, in the first centimeter of the soil, the initial temperature is reduced by 4°C and the initial water saturation is lowered to 0.7. As before, these values are chosen to see the sensitivity of that parameters and not to replicate the true conditions. Spatial parameters in the top layer: Various studies (e.g., Dimitrov et al, 2015) suggest that soil parameters close to the interface are very sensitive to the treatment of the soil. The Sb‐10 soil was tilled and afterward smoothed again by raking before the start of the measurement, which is why it is likely that hydraulic parameters of the soil at the interface can be very different from the initially measured values for the first horizon.…”