Estimation of Hydraulic properties of a sandy soil using ground-based active and passive microwave remote sensing
KAUST DepartmentWater Desalination and Reuse Research Center (WDRC)
Biological and Environmental Sciences and Engineering (BESE) Division
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AbstractIn this paper, we experimentally analyzed the feasibility of estimating soil hydraulic properties from 1.4 GHz radiometer and 0.8-2.6 GHz ground-penetrating radar (GPR) data. Radiometer and GPR measurements were performed above a sand box, which was subjected to a series of vertical water content profiles in hydrostatic equilibrium with a water table located at different depths. A coherent radiative transfer model was used to simulate brightness temperatures measured with the radiometer. GPR data were modeled using full-wave layered medium Green's functions and an intrinsic antenna representation. These forward models were inverted to optimally match the corresponding passive and active microwave data. This allowed us to reconstruct the water content profiles, and thereby estimate the sand water retention curve described using the van Genuchten model. Uncertainty of the estimated hydraulic parameters was quantified using the Bayesian-based DREAM algorithm. For both radiometer and GPR methods, the results were in close agreement with in situ time-domain reflectometry (TDR) estimates. Compared with radiometer and TDR, much smaller confidence intervals were obtained for GPR, which was attributed to its relatively large bandwidth of operation, including frequencies smaller than 1.4 GHz. These results offer valuable insights into future potential and emerging challenges in the development of joint analyses of passive and active remote sensing data to retrieve effective soil hydraulic properties.
SponsorsThis work was supported by the Helmholtz Alliance on "Remote Sensing and Earth System Dynamics" and by the CROPSENSe project funded by the German Federal Ministry of Education and Research (BMBF). The ELBARA-II radiometer was provided by TERENO "Terrestrial Environmental Observatories", also funded by the BMBF.