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| Titel |
Selection of an appropriately simple storm runoff model |
| VerfasserIn |
A. I. J. M. Dijk |
| 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 ; 14, no. 3 ; Nr. 14, no. 3 (2010-03-08), S.447-458 |
| Datensatznummer |
250012220
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| Publikation (Nr.) |
 copernicus.org/hess-14-447-2010.pdf |
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| Zusammenfassung |
| An appropriately simple event runoff model for catchment hydrological
studies was derived. The model was selected from several variants as having
the optimum balance between simplicity and the ability to explain daily
observations of streamflow from 260 Australian catchments (23–1902 km2).
Event rainfall and runoff were estimated from the observations
through a combination of baseflow separation and storm flow recession analysis,
producing a storm flow recession coefficient (kQF). Various
model structures with up to six free parameters were investigated, covering
most of the equations applied in existing lumped catchment models. The
performance of alternative structures and free parameters were expressed in
Aikake's Final Prediction Error Criterion (FPEC) and corresponding
Nash-Sutcliffe model efficiencies (NSME) for event runoff totals. For each
model variant, the number of free parameters was reduced in steps based on
calculated parameter sensitivity. The resulting optimal model structure had
two or three free parameters; the first describing the non-linear
relationship between event rainfall and runoff (Smax), the second
relating runoff to antecedent groundwater storage (CSg), and a third
that described initial rainfall losses (Li), but which could be set at 8
mm without affecting model performance too much. The best three parameter
model produced a median NSME of 0.64 and outperformed, for example, the Soil
Conservation Service Curve Number technique (median NSME 0.30–0.41).
Parameter estimation in ungauged catchments is likely to be challenging:
64% of the variance in kQF among stations could be explained by
catchment climate indicators and spatial correlation, but corresponding
numbers were a modest 45% for CSg, 21% for Smax and none for
Li, respectively. In gauged catchments, better estimates of event
rainfall depth and intensity are likely prerequisites to further improve
model performance. |
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