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We coupled a radiative transfer model and a soil hydrologic model (HYDRUS 1D) with an optimization routine to derive soil hydraulic parameters, surface roughness, and soil moisture of a tilled bare soil plot using measured brightness temperatures at 1.4 GHz (L‐band), rainfall, and potential soil evaporation. The robustness of the approach was evaluated using five 28‐d data sets representing different meteorological conditions. We considered two soil hydraulic property models: the unimodal Mualem–van Genuchten and the bimodal model of Durner. Microwave radiative transfer was modeled by three different approaches: the Fresnel equation with depth‐averaged dielectric permittivity of either 2‐ or 5‐cm‐thick surface layers and a coherent radiative transfer model (CRTM) that accounts for vertical gradients in dielectric permittivity. Brightness temperatures simulated by the CRTM and the 2‐cm‐layer Fresnel model fitted well to the measured ones. L‐band brightness temperatures are therefore related to the dielectric permittivity and soil moisture in a 2‐cm‐thick surface layer. The surface roughness parameter that was derived from brightness temperatures using inverse modeling was similar to direct estimates from laser profiler measurements. The laboratory‐derived water retention curve was bimodal and could be retrieved consistently for the different periods from brightness temperatures using inverse modeling. A unimodal soil hydraulic property function underestimated the hydraulic conductivity near saturation. Surface soil moisture contents simulated using retrieved soil hydraulic parameters were compared with in situ measurements. Depth‐specific calibration relations were essential to derive soil moisture from near‐surface installed sensors.

Abstract. The Web Service Modelling Ontology (WSMO) provides a unique, highly innovative perspective onto the Semantic Web Services domain. Robust and easy-to-use tools play crucial role for the adoption of any technological innovation and indeed the overall value of the innovation can be severely undermined by the lack of proper tools supporting it. In this paper we present a prototype of an integrated modelling environment that supports and elaborates the innovative WSMO perspective.

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.