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| 001 | 1010151 | ||
| 005 | 20231102104927.0 | ||
| 024 | 7 | _ | |2 doi |a 10.5194/soil-9-365-2023 |
| 024 | 7 | _ | |2 ISSN |a 2199-3971 |
| 024 | 7 | _ | |2 ISSN |a 2199-398X |
| 024 | 7 | _ | |2 datacite_doi |a 10.34734/FZJ-2023-02979 |
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| 082 | _ | _ | |a 550 |
| 100 | 1 | _ | |0 P:(DE-HGF)0 |a Guillaume, Benjamin |b 0 |e Corresponding author |
| 245 | _ | _ | |a Reproducibility of the wet part of the soil water retention curve: a European interlaboratory comparison |
| 260 | _ | _ | |a Göttingen |b Copernicus Publ. |c 2023 |
| 336 | 7 | _ | |2 DRIVER |a article |
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| 520 | _ | _ | |a The soil water retention curve (SWRC) is a key soil property required for predicting basic hydrological processes. The SWRC is often obtained in the laboratory with non-harmonized methods. Moreover, procedures associated with each method are not standardized. This can induce a lack of reproducibility between laboratories using different methods and procedures or using the same methods with different procedures. The goal of this study was to estimate the inter- and intralaboratory variability of the measurement of the wet part (from 10 to 300 hPa) of the SWRC. An interlaboratory comparison was carried out between 14 laboratories, using artificially constructed, porous reference samples that were transferred between laboratories according to a statistical design. The retention measurements were modelled by a series of linear mixed models using a Bayesian approach. This allowed the detection of sample-to-sample variability, interlaboratory variability, intralaboratory variability and the effects of sample changes between measurements. The greatest portion of the differences in the measurement of SWRCs was due to interlaboratory variability. The intralaboratory variability was highly variable depending on the laboratory. Some laboratories successfully reproduced the same SWRC on the same sample, while others did not. The mean intralaboratory variability over all laboratories was smaller than the mean interlaboratory variability. A possible explanation for these results is that all laboratories used slightly different methods and procedures. We believe that this result may be of great importance regarding the quality of SWRC databases built by pooling SWRCs obtained in different laboratories. The quality of pedotransfer functions or maps that might be derived is probably hampered by this inter- and intralaboratory variability. The way forward is that measurement procedures of the SWRC need to be harmonized and standardized. |
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| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Aroui Boukbida, Hanane |b 1 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Bakker, Gerben |b 2 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Bieganowski, Andrzej |b 3 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Brostaux, Yves |b 4 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Cornelis, Wim |b 5 |
| 700 | 1 | _ | |0 0000-0002-9543-1318 |a Durner, Wolfgang |b 6 |
| 700 | 1 | _ | |0 0000-0003-1172-981X |a Hartmann, Christian |b 7 |
| 700 | 1 | _ | |0 0000-0002-2276-0233 |a Iversen, Bo V. |b 8 |
| 700 | 1 | _ | |a Javaux, Mathieu |b 9 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Ingwersen, Joachim |b 10 |
| 700 | 1 | _ | |0 0000-0001-9678-541X |a Lamorski, Krzysztof |b 11 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Lamparter, Axel |b 12 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Makó, András |b 13 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Mingot Soriano, Ana María |b 14 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Messing, Ingmar |b 15 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Nemes, Attila |b 16 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Pomes-Bordedebat, Alexandre |b 17 |
| 700 | 1 | _ | |0 0000-0002-3172-7339 |a van der Ploeg, Martine |b 18 |
| 700 | 1 | _ | |0 0000-0002-3448-5208 |a Weber, Tobias Karl David |b 19 |
| 700 | 1 | _ | |0 P:(DE-Juel1)129553 |a Weihermüller, Lutz |b 20 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Wellens, Joost |b 21 |
| 700 | 1 | _ | |0 P:(DE-HGF)0 |a Degré, Aurore |b 22 |
| 773 | _ | _ | |0 PERI:(DE-600)2834892-8 |a 10.5194/soil-9-365-2023 |g Vol. 9, no. 1, p. 365 - 379 |n 1 |p 365 - 379 |t Soil |v 9 |x 2199-3971 |y 2023 |
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