Articles | Volume 27, issue 24
https://doi.org/10.5194/hess-27-4579-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-4579-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Prediction of absolute unsaturated hydraulic conductivity – comparison of four different capillary bundle models
Andre Peters
CORRESPONDING AUTHOR
Division of Soil Science and Soil Physics, Institute of Geoecology, Technische Universität Braunschweig, Braunschweig, Germany
now at: Thünen Institute of Agricultural Technology, Braunschweig, Germany
Sascha C. Iden
Division of Soil Science and Soil Physics, Institute of Geoecology, Technische Universität Braunschweig, Braunschweig, Germany
Wolfgang Durner
Division of Soil Science and Soil Physics, Institute of Geoecology, Technische Universität Braunschweig, Braunschweig, Germany
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The article describes a collection of 572 data sets of soil water retention and unsaturated hydraulic conductivity data measured with state-of-the-art laboratory methods. Furthermore, the data collection contains basic soil properties such as soil texture and organic carbon content. We expect that the data will be useful for various important purposes, for example, the development of soil hydraulic property models and related pedotransfer functions.
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The soil hydraulic conductivity function is usually predicted from the water retention curve (WRC) with the requirement of at least one measured conductivity data point for scaling the function. We propose a new scheme of absolute hydraulic conductivity prediction from the WRC without the need of measured conductivity data. Testing the new prediction with independent data shows good results. This scheme can be used when insufficient or no conductivity data are available.
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The article describes a collection of 572 data sets of soil water retention and unsaturated hydraulic conductivity data measured with state-of-the-art laboratory methods. Furthermore, the data collection contains basic soil properties such as soil texture and organic carbon content. We expect that the data will be useful for various important purposes, for example, the development of soil hydraulic property models and related pedotransfer functions.
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This study proposes a model to predict soil hydraulic properties (SHPs) of constructed Technosols for urban greening. The SHPs are determined by the Technosol composition and describe their capacity to store and supply water to plants. The model predicts SHPs of any binary mixture based on the SHPs of its two pure components, facilitating simulations of flow and transport processes before production. This can help create Technosols designed for efficient urban greening and water management.
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The soil hydraulic conductivity function is usually predicted from the water retention curve (WRC) with the requirement of at least one measured conductivity data point for scaling the function. We propose a new scheme of absolute hydraulic conductivity prediction from the WRC without the need of measured conductivity data. Testing the new prediction with independent data shows good results. This scheme can be used when insufficient or no conductivity data are available.
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We simulated stony soils with low to high volumes of rock fragments in 3D using evaporation and multistep unit-gradient experiments. Hydraulic properties of virtual stony soils were identified under a wide range of soil matric potentials. The developed models for scaling the hydraulic conductivity of stony soils were evaluated under unsaturated flow conditions.
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Short summary
While various expressions for the water retention curve are commonly compared, the capillary conductivity model proposed by Mualem is widely used but seldom compared to alternatives. We compare four different capillary bundle models in terms of their ability to fully predict the hydraulic conductivity. The Mualem model outperformed the three other models in terms of predictive accuracy. Our findings suggest that the widespread use of the Mualem model is justified.
While various expressions for the water retention curve are commonly compared, the capillary...