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- W4386030879 abstract "<strong class=journal-contentHeaderColor>Abstract.</strong> To model the water, solute and energy transport in porous media, it is essential to have accurate information about the soil hydraulic properties (SHP), i.e. the water retention curve (WRC) and the soil hydraulic conductivity curve (HCC). Having reliable data information to parameterize these models is important, but equally critical is the selection of appropriate SHP models. While various expressions for the WRC are commonly compared, the capillary conductivity model proposed by Mualem (1976a) is widely used but seldom compared to alternatives. The objective of this study was to compare four different capillary bundle models in terms of their ability to accurately predict the HCC without scaling the conductivity function by a measured conductivity value. These expressions include two simpler models proposed by Burdine (1953) and Alexander and Skaggs (1986), which assume a bundle of parallel capillaries with tortuous flow paths, and two more sophisticated models based on statistical cut-and-random-rejoin approaches, namely those proposed by Childs and Collis-George (1950) and the aforementioned model of Mualem (1976a). In order to check whether different parametrizations of the WRC interfere with the suitability of the conductivity models, we utilized four different capillary saturation models in combination with each of the conductivity prediction models, resulting in a total of 16 SHP model schemes. All schemes were calibrated using 12 carefully selected datasets that provided water retention and hydraulic conductivity data over a wide saturation range. Subsequently, the calibrated models were tested and rated by their ability to predict the hydraulic conductivity of 23 independent datasets of soils with varying textures. The statistical cut-and-random-rejoin models, particularly the Mualem (1976a) model, outperformed the simpler capillary bundle models in terms of predictive accuracy. This was independent of the specific WRC model used. Our findings suggest that the widespread use of the Mualem model is justified." @default.
- W4386030879 created "2023-08-22" @default.
- W4386030879 creator A5021859021 @default.
- W4386030879 date "2023-08-21" @default.
- W4386030879 modified "2023-09-30" @default.
- W4386030879 title "Reply on RC3" @default.
- W4386030879 doi "https://doi.org/10.5194/hess-2023-134-ac3" @default.
- W4386030879 hasPublicationYear "2023" @default.
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