Articles | Volume 27, issue 16
https://doi.org/10.5194/hess-27-3125-2023
© 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-27-3125-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Predicting soil hydraulic properties for binary mixtures – concept and application for constructed Technosols
Moreen Willaredt
CORRESPONDING AUTHOR
Department of Ecohydrology and Landscape Evaluation, Institute of Ecology, Technische Universität Berlin, Ernst-Reuter-Platz 1, 10587 Berlin, Germany
Thomas Nehls
Department of Ecohydrology and Landscape Evaluation, Institute of Ecology, Technische Universität Berlin, Ernst-Reuter-Platz 1, 10587 Berlin, Germany
Andre Peters
Department of Soil Science and Soil Physics, Institute of Geoecology, Technische Universität Braunschweig, Langer Kamp 19c, 38106 Braunschweig, Germany
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Andre Peters, Sascha C. Iden, and Wolfgang Durner
Hydrol. Earth Syst. Sci., 27, 4579–4593, https://doi.org/10.5194/hess-27-4579-2023, https://doi.org/10.5194/hess-27-4579-2023, 2023
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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.
Tobias L. Hohenbrink, Conrad Jackisch, Wolfgang Durner, Kai Germer, Sascha C. Iden, Janis Kreiselmeier, Frederic Leuther, Johanna C. Metzger, Mahyar Naseri, and Andre Peters
Earth Syst. Sci. Data, 15, 4417–4432, https://doi.org/10.5194/essd-15-4417-2023, https://doi.org/10.5194/essd-15-4417-2023, 2023
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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.
Karin A. Hoffmann, Rabea Saad, Björn Kluge, and Thomas Nehls
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-221, https://doi.org/10.5194/hess-2023-221, 2023
Manuscript not accepted for further review
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ET0vert is a process-based model concept for evapotranspiration of green walls, validated with onsite lysimetry data. Best accuracy of predictions is achieved using input data measured onsite and considering height dependencies of radiation, wind and VPD. If only remote climate station data is available as input, it must be “verticalized”. The model predicts the hourly and daily evapotranspiration necessary for e.g., irrigation planning, building energy simulations or local climate modeling.
Andre Peters, Tobias L. Hohenbrink, Sascha C. Iden, Martinus Th. van Genuchten, and Wolfgang Durner
Hydrol. Earth Syst. Sci., 27, 1565–1582, https://doi.org/10.5194/hess-27-1565-2023, https://doi.org/10.5194/hess-27-1565-2023, 2023
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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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Short summary
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.
This study proposes a model to predict soil hydraulic properties (SHPs) of constructed...