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| Titel |
Predicting the soil moisture retention curve, from soil particle size distribution and bulk density data using a packing density scaling factor |
| VerfasserIn |
F. Meskini-Vishkaee, M. H. Mohammadi, M. Vanclooster |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 10 ; Nr. 18, no. 10 (2014-10-15), S.4053-4063 |
| Datensatznummer |
250120496
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| Publikation (Nr.) |
 copernicus.org/hess-18-4053-2014.pdf |
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| Zusammenfassung |
| A substantial number of models predicting the soil moisture characteristic
curve (SMC) from particle size distribution (PSD) data underestimate the
dry range of the SMC especially in soils with high clay and organic matter
contents. In this study, we applied a continuous form of the PSD model to
predict the SMC, and subsequently we developed a physically based scaling
approach to reduce the model's bias at the dry range of the SMC. The soil
particle packing density was considered as a metric of soil structure and
used to define a soil particle packing scaling factor. This factor was
subsequently integrated in the conceptual SMC prediction model. The model
was tested on 82 soils, selected from the UNSODA database. The
results show that the scaling approach properly estimates the SMC for all
soil samples. In comparison to the original conceptual SMC model without
scaling, the scaling approach improves the model estimations on average by
30%. Improvements were particularly significant for the fine- and medium-textured soils. Since the scaling approach is parsimonious and does not rely
on additional empirical parameters, we conclude that this approach may be
used for estimating SMC at the larger field scale from basic soil data. |
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