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| Titel |
Integrating coarse-scale uncertain soil moisture data into a fine-scale hydrological modelling scenario |
| VerfasserIn |
H. Vernieuwe, B. Baets, J. Minet, V. R. N. Pauwels, S. Lambot, M. Vanclooster, N. E. C. Verhoest |
| 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 ; 15, no. 10 ; Nr. 15, no. 10 (2011-10-11), S.3101-3114 |
| Datensatznummer |
250012989
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| Publikation (Nr.) |
 copernicus.org/hess-15-3101-2011.pdf |
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| Zusammenfassung |
| In a hydrological modelling scenario, often the modeller is confronted with
external data, such as remotely-sensed soil moisture observations, that
become available to update the model output. However, the scale triplet
(spacing, extent and support) of these data is often inconsistent with that
of the model. Furthermore, the external data can be cursed with epistemic
uncertainty. Hence, a method is needed that not only integrates the external
data into the model, but that also takes into account the difference in scale
and the uncertainty of the observations. In this paper, a synthetic
hydrological modelling scenario is set up in which a high-resolution
distributed hydrological model is run over an agricultural field. At regular
time steps, coarse-scale field-averaged soil moisture data, described by
means of possibility distributions (epistemic uncertainty), are retrieved by
synthetic aperture radar and assimilated into the model. A method is
presented that allows to integrate the coarse-scale possibility distribution
of soil moisture content data with the fine-scale model-based soil moisture
data. The method is subdivided in two steps. The first step, the
disaggregation step, employs a scaling relationship between field-averaged
soil moisture content data and its corresponding standard deviation. In the
second step, the soil moisture content values are updated using two
alternative methods. |
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