001     887934
005     20210130010710.0
024 7 _ |a 10.1029/2019WR026820
|2 doi
024 7 _ |a 0043-1397
|2 ISSN
024 7 _ |a 0148-0227
|2 ISSN
024 7 _ |a 1944-7973
|2 ISSN
024 7 _ |a 2156-2202
|2 ISSN
024 7 _ |a 2128/26189
|2 Handle
024 7 _ |a WOS:000578452200032
|2 WOS
037 _ _ |a FZJ-2020-04526
082 _ _ |a 550
100 1 _ |a Weber, Tobias K. D.
|0 0000-0002-3448-5208
|b 0
|e Corresponding author
245 _ _ |a Pedotransfer Function for the Brunswick Soil Hydraulic Property Model and Comparison to the van Genuchten‐Mualem Model
260 _ _ |a [New York]
|c 2020
|b Wiley
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1605620221_3599
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Modeling soil hydraulic properties requires an effective representation of capillary and noncapillary storage and conductivity. This is made possible by using physically comprehensive yet flexible soil hydraulic property models. Such a model (Brunswick [BW] model) was introduced by Weber et al. (2019, https://doi.org/10.1029/2018WR024584), and it overcomes some core deficiencies present in the widely used van Genuchten‐Mualem (VGM) model. We first compared the performance of the BW model to that of the VGM model in its ability to describe water retention and hydraulic conductivity data on a set of measurements of 402 soil samples with textures covering the entire range of classes. Second, we developed a simple transfer function to predict BW parameters based on VGM parameters. Combined with our new function, any existing pedotransfer function for the prediction of the VGM parameters can be extended to predict BW model parameters. Based on information criteria, the smaller variance of the residuals, and a 40% reduction in mean absolute error in the hydraulic conductivity over all samples, the BW model clearly outperforms VGM. This is possible as the BW model explicitly accounts for hydraulic properties of dry soils. With the new pedotransfer function developed in this study, better descriptions of water retention and hydraulic conductivities are possible. We are convinced that this will strengthen the utility of the new model and enable improved field‐scale simulations, climate change impact assessments on water, energy and nutrient fluxes, as well as crop productivity in agroecosystems by soil‐crop and land‐surface modeling. The models and the pedotransfer function are included in an R package spsh (https://cran.r‐project.org/package=spsh).
536 _ _ |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255)
|0 G:(DE-HGF)POF3-255
|c POF3-255
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Finkel, Michael
|0 0000-0002-5268-5203
|b 1
700 1 _ |a Gonçalves, Maria
|0 0000-0002-5980-0294
|b 2
|e Corresponding author
700 1 _ |a Vereecken, Harry
|0 P:(DE-Juel1)129549
|b 3
700 1 _ |a Diamantopoulos, Efstathios
|0 0000-0001-7870-0291
|b 4
773 _ _ |a 10.1029/2019WR026820
|g Vol. 56, no. 9
|0 PERI:(DE-600)2029553-4
|n 9
|p e2019WR026820
|t Water resources research
|v 56
|y 2020
|x 1944-7973
856 4 _ |u https://juser.fz-juelich.de/record/887934/files/2019WR026820.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:887934
|p openaire
|p open_access
|p driver
|p VDB:Earth_Environment
|p VDB
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)129549
913 1 _ |a DE-HGF
|l Terrestrische Umwelt
|1 G:(DE-HGF)POF3-250
|0 G:(DE-HGF)POF3-255
|2 G:(DE-HGF)POF3-200
|v Terrestrial Systems: From Observation to Prediction
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Erde und Umwelt
914 1 _ |y 2020
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2020-09-03
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2020-09-03
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1160
|2 StatID
|b Current Contents - Engineering, Computing and Technology
|d 2020-09-03
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b WATER RESOUR RES : 2018
|d 2020-09-03
915 _ _ |a DEAL Wiley
|0 StatID:(DE-HGF)3001
|2 StatID
|d 2020-09-03
|w ger
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2020-09-03
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2020-09-03
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2020-09-03
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1060
|2 StatID
|b Current Contents - Agriculture, Biology and Environmental Sciences
|d 2020-09-03
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2020-09-03
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2020-09-03
920 1 _ |0 I:(DE-Juel1)IBG-3-20101118
|k IBG-3
|l Agrosphäre
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)IBG-3-20101118
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21