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| Titel |
An alternative deterministic method for the spatial interpolation of water retention parameters |
| VerfasserIn |
H. Saito, K. Seki, J. Šimůnek |
| 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 ; 13, no. 4 ; Nr. 13, no. 4 (2009-04-07), S.453-465 |
| Datensatznummer |
250011828
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| Publikation (Nr.) |
 copernicus.org/hess-13-453-2009.pdf |
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| Zusammenfassung |
| There are two approaches available for mapping water retention parameters
over the study area using a spatial interpolation method. (1) Retention
models can be first fitted to retention curves available at sampling
locations prior to interpolating model parameters over the study area (the
FI approach). (2) Retention data points can first be interpolated over the
study area before retention model parameters are fitted (the IF approach).
The current study compares the performance of these two approaches in
representing the spatial distribution of water retention curves. Standard
geostatistical interpolation methods, i.e., ordinary kriging and indicator
kriging, were used. The data used in this study were obtained from the Las
Cruces trench site database, which contains water retention data for 448
soil samples. Three standard water retention models, i.e., Brooks and Corey
(BC), van Genuchten (VG), and Kosugi (KSG), were considered. For each model,
standard validation procedures, i.e., leave-one-out cross-validation and
split-sample methods were used to estimate the uncertainty of the parameters
at each sampling location, allowing for the computation of prediction errors
(mean absolute error and mean error). The results show that the IF approach
significantly lowered mean absolute errors for the VG model, while also
reducing them moderately for the KSG and BC models. In addition, the IF
approach resulted in less bias than the FI approach, except when the BC
model was used in the split-sample approach. Overall, IF outperforms FI for
all three retention models in describing the spatial distribution of
retention parameters. |
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