Articles | Volume 14, issue 1
https://doi.org/10.5194/gmd-14-151-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-151-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Updated European hydraulic pedotransfer functions with communicated uncertainties in the predicted variables (euptfv2)
Institute for Soil Sciences, Centre for
Agricultural Research, Herman Ottó út 15, 1022 Budapest, Hungary
Melanie Weynants
European Commission Joint Research Centre, via Enrico Fermi 2749,
21027 Ispra, Italy
Tobias K. D. Weber
Institute of Soil Science and Land Evaluation, University of
Hohenheim, Emil-Wolff-Straße 27, 70593 Stuttgart, Germany
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19 citations as recorded by crossref.
- Within-season crop yield prediction by a multi-model ensemble with integrated data assimilation H. Zare et al. 10.1016/j.fcr.2024.109293
- Assessing the use of digital soil maps in hydrological modeling for soil-water budget simulations - implications for water management plans in southern Portugal A. Horta et al. 10.1016/j.geodrs.2023.e00741
- Estimation of Infiltration Parameters: The Role of Pedotransfer Functions and Initial Moisture Conditions J. Kubát et al. 10.1016/j.jhydrol.2024.130954
- Evaluation of pedotransfer functions for predicting soil hydraulic properties: A voyage from regional to field scales across Europe P. Nasta et al. 10.1016/j.ejrh.2021.100903
- Assessing the nitrate vulnerability of shallow aquifers under Mediterranean climate conditions P. Nasta et al. 10.1016/j.agwat.2021.107208
- Österreichweite Regionalisierung bodenhydraulischer Eigenschaften H. Zeitfogel et al. 10.1007/s00506-022-00842-z
- Development of a New Pedotransfer Function Addressing Limitations in Soil Hydraulic Models and Observations Y. Wang et al. 10.1029/2021WR031406
- Soil Information on a Regional Scale: Two Machine Learning Based Approaches for Predicting Ksat H. Zeitfogel et al. 10.2139/ssrn.4143185
- Soil information on a regional scale: Two machine learning based approaches for predicting saturated hydraulic conductivity H. Zeitfogel et al. 10.1016/j.geoderma.2023.116418
- Predicting field capacity in undisturbed stony soils B. Robertson et al. 10.1016/j.geoderma.2021.115346
- Integrated crop and livestock systems increase both climate change adaptation and mitigation capacities M. Delandmeter et al. 10.1016/j.scitotenv.2023.169061
- The prevalent life cycle of agricultural flash droughts M. Lovino et al. 10.1038/s41612-024-00618-0
- Multi-site, multi-crop measurements in the soil–vegetation–atmosphere continuum: a comprehensive dataset from two climatically contrasting regions in southwestern Germany for the period 2009–2018 T. Weber et al. 10.5194/essd-14-1153-2022
- Relating Immediate Changes in Bulk Density to Changes in Hydraulic Properties on a Silty Clay Loam Under Different Tillage Systems in the Czech Republic D. Abebrese et al. 10.1007/s42729-022-01085-3
- Sequestering carbon in the subsoil benefits crop transpiration at the onset of drought M. Turek et al. 10.5194/soil-9-545-2023
- SWAT + input data preparation in a scripted workflow: SWATprepR S. Plunge et al. 10.1186/s12302-024-00873-1
- Testing CASE: A new event‐based Morgan‐Morgan‐Finney‐type erosion model for different rainfall experimental scenarios T. Brunner et al. 10.1002/hyp.14966
- Evaluation of Soil Hydraulic Properties in Northern and Central Tunisian Soils for Improvement of Hydrological Modelling A. Hmaied et al. 10.3390/land13030385
- Near constant groundwater recharge efficiency under global change in a central European catchment T. Riedel et al. 10.1002/hyp.14805
Latest update: 19 Apr 2024
Short summary
This paper presents updated European prediction algorithms (euptf2) to compute soil hydraulic parameters from easily available soil properties. The new algorithms lead to significantly better predictions and provide a built-in prediction uncertainty computation. The influence of predictor variables on predicted soil hydraulic properties is explored and practical guidance on how to use the derived PTFs is provided. A website and an R package facilitate easy application of the updated predictions.
This paper presents updated European prediction algorithms (euptf2) to compute soil hydraulic...