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Media type:
E-Article
Title:
Effective hydraulic properties of 3D virtual stony soils identified by inverse modeling
Contributor:
Naseri, Mahyar;
Iden, Sascha C.;
Durner, Wolfgang
Published:
Copernicus GmbH, 2022
Published in:
SOIL, 8 (2022) 1, Seite 99-112
Language:
English
DOI:
10.5194/soil-8-99-2022
ISSN:
2199-398X
Origination:
Footnote:
Description:
Abstract. Stony soils that have a considerable amount of rock fragments (RFs) arewidespread around the world. However, experiments to determine the effective soilhydraulic properties (SHPs) of stony soils, i.e., the water retention curve(WRC) and hydraulic conductivity curve (HCC), are challenging. Installationof measurement devices and sensors in these soils is difficult, and the dataare less reliable because of their high local heterogeneity. Therefore,effective properties of stony soils especially under unsaturated hydraulicconditions are still not well understood. An alternative approach toevaluate the SHPs of these systems with internal structural heterogeneity isnumerical simulation. We used the Hydrus 2D/3D software to create virtualstony soils in 3D and simulate water flow for different volumetric fractions of RFs, f. Stony soils with different values of f from 11 % to 37 % were created by placing impermeable spheres as RFs in a sandy loam soil. Timeseries of local pressure heads at various depths, mean water contents, andfluxes across the upper boundary were generated in a virtual evaporationexperiment. Additionally, a multistep unit-gradient simulation was appliedto determine effective values of hydraulic conductivity near saturation upto pF=2. The generated data were evaluated by inverse modeling, assuming a homogeneous system, and the effective hydraulic properties wereidentified. The effective properties were compared with predictions fromavailable scaling models of SHPs for different values of f. Our resultsshowed that scaling the WRC of the background soil based on only the valueof f gives acceptable results in the case of impermeable RFs. However,the reduction in conductivity could not be simply scaled by the value of f. Predictions were highly improved by applying the Novák, Maxwell, and GEM models to scale the HCC. The Maxwell model matched the numericallyidentified HCC best.