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| Titel |
Assessment of the potential forecasting skill of a global hydrological model in reproducing the occurrence of monthly flow extremes |
| VerfasserIn |
N. Candogan Yossef, L. P. H. Beek, J. C. J. Kwadijk, M. F. P. Bierkens |
| 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 ; 16, no. 11 ; Nr. 16, no. 11 (2012-11-15), S.4233-4246 |
| Datensatznummer |
250013571
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| Publikation (Nr.) |
 copernicus.org/hess-16-4233-2012.pdf |
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| Zusammenfassung |
As an initial step in assessing the prospect of using global hydrological
models (GHMs) for hydrological forecasting, this study investigates the
skill of the GHM PCR-GLOBWB in reproducing the occurrence of past extremes
in monthly discharge on a global scale. Global terrestrial hydrology from
1958 until 2001 is simulated by forcing PCR-GLOBWB with daily meteorological
data obtained by downscaling the CRU dataset to daily fields using the
ERA-40 reanalysis. Simulated discharge values are compared with observed
monthly streamflow records for a selection of 20 large river basins that
represent all continents and a wide range of climatic zones.
We assess model skill in three ways all of which contribute different
information on the potential forecasting skill of a GHM. First, the general
skill of the model in reproducing hydrographs is evaluated. Second, model
skill in reproducing significantly higher and lower flows than the monthly
normals is assessed in terms of skill scores used for forecasts of
categorical events. Third, model skill in reproducing flood and drought
events is assessed by constructing binary contingency tables for floods and
droughts for each basin. The skill is then compared to that of a simple
estimation of discharge from the water balance (P−E).
The results show that the model has skill in all three types of assessments.
After bias correction the model skill in simulating hydrographs is improved
considerably. For most basins it is higher than that of the climatology. The
skill is highest in reproducing monthly anomalies. The model also has skill
in reproducing floods and droughts, with a markedly higher skill in floods.
The model skill far exceeds that of the water balance estimate. We conclude
that the prospect for using PCR-GLOBWB for monthly and seasonal forecasting
of the occurrence of hydrological extremes is positive. We argue that this
conclusion applies equally to other similar GHMs and LSMs, which may show
sufficient skill to forecast the occurrence of monthly flow extremes. |
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