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| Titel |
Evaluation of reanalysis climate simulations for the prediction of extreme runoff characteristics |
| VerfasserIn |
Mehmet Coskun, Luis Samaniego, Rohini Kumar |
| Konferenz |
EGU General Assembly 2010
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250041530
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| Zusammenfassung |
| Discharge regimes of river basins are expected to be altered due to possible effects of global
warming. For planning and water resources management, it is fundamental to estimate the
probability of occurrence of extreme hydrological events such as magnitude and frequency of
floods and droughts. So far, it is a matter of debate whether actual Global and Regional
Climate Model outputs or their reanalysis products (bias corrected) are able to provide a
reasonable estimate of the meteorological variables that are required to force a distributed
hydrologic model.
In this study, we will evaluate various climate simulations for their reliability to
predict extreme runoff characteristics in three German mesoscale river basins with
various sizes and hydro-meteorological conditions: Neckar (12Â 700Â km2), Bode
(3Â 300Â km2), and Mulde (2Â 700Â km2). Reanalysis of the global atmosphere and
surface conditions were obtained from the European Centre for Medium-Range
Weather Forecast (ECMWF) Reanalysis (ERA-40) for the period from 1957 to
2002.
These data will be used to force a grid based mesoscale hydrologic model calibrated with
past meteorological and discharge observations. Several runoff characteristics will
be estimated based on daily discharge simulations and then compared with their
corresponding estimates derived from daily streamflow observations. Finally, nonparametric
statistical test (e.g. Kolmogorov–Smirnov test) and Tukey’s depth function will be
employed to test two null hypotheses: 1) Meteorological observations and the reanalysis
data are realisations from a common generating process, and 2) The probability of
occurrence of extreme runoff characteristics obtained from both data sets is similar. |
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