 |
| Titel |
Multi-criteria calibration of a conceptual runoff model using a genetic algorithm |
| VerfasserIn |
J. Seibert |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 4, no. 2 ; Nr. 4, no. 2, S.215-224 |
| Datensatznummer |
250001629
|
| Publikation (Nr.) |
 copernicus.org/hess-4-215-2000.pdf |
|
|
|
|
|
| Zusammenfassung |
| Abstract: Calibration of a model against more than one output variable is
important for reliable simulations of internal processes. In this study, a
genetic algorithm combined with local optimisation was proposed for automatic
single- and multi-criteria calibration of the HBV model, a conceptual runoff
model. The model and the optimisation algorithm were applied in two catchments
with different geology where, in addition to observed runoff, time series of
groundwater level data were available. For a theoretical, error-free test case
with synthetic data, the optimisation algorithm was usually able to find the
true parameter values. For the real-world case, parameter values varied
considerably when calibrating against runoff only. However, parameter values
were constrained significantly when calibrating against both runoff and
groundwater levels. Furthermore, for one of the catchments, the results of the
multi-criteria calibration motivated a modification of the model structure.
Keywords: Multi-criteria calibration; genetic
algorithm; parameter uncertainty; conceptual runoff models; HBV model;
groundwater levels |
| |
|
| Teil von |
|
|
|
|
|
|
|
|