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Titel |
Assessment of the indirect calibration of a rainfall-runoff model for ungauged catchments in Flanders |
VerfasserIn |
N. Vleeschouwer, V. R. N. Pauwels |
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 ; 17, no. 5 ; Nr. 17, no. 5 (2013-05-27), S.2001-2016 |
Datensatznummer |
250018885
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Publikation (Nr.) |
copernicus.org/hess-17-2001-2013.pdf |
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Zusammenfassung |
In this paper the potential of discharge-based indirect
calibration of the probability-distributed model (PDM), a lumped
rainfall-runoff (RR) model, is examined for six selected catchments
in Flanders. The concept of indirect calibration indicates
that one has to estimate the calibration data because the catchment
is ungauged or scarcely gauged. A first case in which indirect calibration is
applied is that of spatial gauging divergence: because no
observed discharge records are available at the outlet of the
ungauged catchment, the calibration is carried out based on a
rescaled discharge time series of a very similar donor
catchment. Both a calibration in the time domain and the frequency
domain (also known as spectral domain) are carried
out. Furthermore, the case of temporal gauging divergence is
considered: limited (e.g. historical or very recent) discharge
records are available at the outlet of the scarcely gauged
catchment. Additionally, no time overlap exists between the forcing and
discharge records. Therefore, only an indirect spectral
calibration can be performed in this case. To conclude also the
combination case of spatio-temporal gauging divergence is
considered. In this last case only limited discharge records are
available at the outlet of a donor catchment. Again the forcing
and discharge records are not concomitant, which only makes
feasible an indirect spectral calibration. For most catchments
the modelled discharge time series is found to be acceptable in the
considered cases. In the case of spatial gauging divergence,
indirect temporal calibration results in a better model
performance than indirect spectral calibration. Furthermore,
indirect spectral calibration in the case of temporal gauging
divergence leads to a better model performance than indirect
spectral calibration in the case of spatial gauging
divergence. Finally, the combination of spatial and temporal
gauging divergence does not lead to a notably worse model
performance compared to the case of spatial gauging divergence. |
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