Data from: The PDI model system for parameterizing soil hydraulic properties
Data files
May 22, 2024 version files 6.14 KB
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Data_Figure_3.csv
690 B
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README.md
5.45 KB
May 22, 2024 version files 6.14 KB
Abstract
The PDI ("Peters-Durner-Iden") model system represents a robust framework for parameterizing soil hydraulic properties, i.e. the water retention curve and the hydraulic conductivity curve, across the entire soil moisture spectrum. This model accounts for water retention and hydraulic conductivity in completely and partially-filled pores, including adsorption and film-flow. It was developed in stages and a comprehensive overview of the model development and the model equations is provided in Peters et al. (2024). In this repository, we provide a Python file named “pdi.py” which can be used to compute the various submodels (PDI-VG, PDI-KOS, PDI-FX, ...) of the PDI model system. One MS Excel file is provided for easy access to one PDI model, the PDI-VG. The PYTHON functions contained in "pdi.py" can be used to calculate the water retention curve, the unsaturated hydraulic conductivity curve, the specific water capacity function, and the soil water diffusivity function. In addition, we provide five python scripts which illustrate how to call the various PDI functions in different contexts. Notably, "pdi.py" incorporates a utility function, 'export_hydrus_materin', which generates an ASCII file named "MATER.IN". This file serves as input for simulations with Hydrus-1D and Hydrus-2D3D, offering seamless integration with these simulation platforms. It's important to emphasize that the provided Python scripts and accompanying documentation are closely aligned with the research article by Peters et al. (2024). To streamline accessibility, the repository refrains from redundantly restating the theory or equations already detailed in the referenced publication.
README: Data from: The PDI model system for parameterizing soil hydraulic properties
https://doi.org/10.5061/dryad.z34tmpgnk
This dataset consists of the data shown in Figure 3 of Peters et al. (2024, https://doi.org/10.1002/vzj2.20338), six PYTHON scripts, one MS Excel file, and a short tutorial as pdf file. The main script named "pdi.py" provides all models of the PDI model system discussed in Peters et. al. (2024). Five additional PYTHON scripts exemplify the call to the various PDI functions. Notably, "pdi.py" incorporates a utility function, 'export_hydrus_materin', which generates an ASCII file named "MATER.IN". This file serves as input for simulations with Hydrus-1D and Hydrus-2D3D, offering seamless integration with these simulation platforms. One MS Excel file is provided for easy access to one PDI model, the PDI-VG.
Description of the data and file structure
The dataset consists of one data file "Data_Figure_3.csv" which provides the data shown in Figure 3 in Peters et al. (2024). The main contribution of the dataset consists of the following PYTHON scripts:
- pdi.py
- run_pdi_vg.py
- run_pdi_vg_sens_kc.py
- run_pdi_fx_vgmn.py
- run_pdi_kos_sens_hclip.py
- run_pdi_vg_and_export.py
The documentation file named "The_PDI_model_system_in_Python.pdf" explains what these scripts do. The scripts 2.-6. call functions within the first script, in which the PDI model calculations are performed. An MS Excel file "pdi_vg.xlsx" is provided as an easily accessible format for the PDI-VG model.
Sharing/Access information
The theory behind the PDI model system and all related equations are given in the following research publication:
- Peters, A., Durner, W. & Iden, S. C. (2024). The PDI model system for parameterizing soil hydraulic properties. Vadose Zone Journal, https://doi.org/10.1002/vzj2.20338
Further literature on the PDI model system and its development are (sorted after publication year):
- Peters, A. (2013). Simple consistent models for water retention and hydraulic conductivity in the complete moisture range. Water Resources Research, 49, 6765–6780. https://doi.org/10.1002/wrcr.20548
- Iden, S. C., & Durner, W. (2014). Comment to “Simple consistent models for water retention and hydraulic conductivity in the complete moisture range” by A. Peters. Water Resources Research, 50, 7530–7534. https://doi.org/10.1002/2014WR015937
- Peters, A. (2014). Reply to comment by S. Iden and W. Durner on "Simple consistent models for water retention and hydraulic conductivity in the complete moisture range." Water Resources Research, 50(9), 7535-7539. https://doi.org/10.1002/2014WR016107
- Iden, S. C., Peters, A., & Durner, W. (2015). Improving prediction of hydraulic conductivity by constraining capillary bundle models to a maximum pore size. Advances in Water Resources, 85, 86–92. https://doi.org/10.1016/j.advwatres.2015.09.005
- Peters, A., Hohenbrink, T. L., Iden, S. C., & Durner, W. (2021). A simple model to predict hydraulic conductivity in medium to dry soil from the water retention curve. Water Resources Research, 57(5). https://doi.org/10.1029/2020wr029211
- Peters, A., Hohenbrink, T. L., Iden, S. C., van Genuchten, M. T., & Durner, W. (2023). Prediction of the absolute hydraulic conductivity function from soil water retention data. Hydrology and Earth System Sciences, 27(7), 1565-1582. https://doi.org/10.5194/hess-27-1565-2023
- Peters, A., Iden, S. C., & Durner, W. (2023). Prediction of absolute unsaturated hydraulic conductivity – comparison of four different capillary bundle models. Hydrol. Earth Syst. Sci., 27, 4579–4593. https://doi.org/10.5194/hess-27-4579-2023
- Peters, A., Durner, W. & Iden, S. C. (2024). The PDI model system for parameterizing soil hydraulic properties. Vadose Zone Journal, https://doi.org/10.1002/vzj2.20338
The PYTHON scripts included in this repository were developed and tested in April, 2024 using PYTHON 3.11.7. Please email Sascha Iden s.iden@tu-braunschweig if you find a bug or you have suggestions for improvement.
Disclaimer
The code provided in this repository is offered as-is, without any warranties. The author(s) of this code shall not be held liable for any damages or losses arising from the use of this code. Users are encouraged to review, test, and modify the code to suit their specific requirements. While efforts have been made to ensure the accuracy and reliability of the code, the author(s) cannot guarantee its correctness or completeness. Furthermore, the code may be subject to updates, revisions, or improvements over time. Users are advised to check for the latest version of the code and incorporate any necessary changes into their projects. By using this code, you agree to assume all risks associated with its use, including but not limited to the risk of program errors, data loss, or security vulnerabilities. This disclaimer is subject to change without notice.
Methods
The dataset consists of the data shown in Figure 3 of the article in Vadose Zone Journal (Peters et al., 2014). This data was measured in the soil physics lab in the Institute of Geoecology at TU Braunschweig, Germany, with the evaporation method using the HYPROP measurement system. The python codes and the Excel spreadsheet were developed by Dr. Sascha C. Iden.