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| Titel |
Using residual analysis, auto- and cross-correlations to identify key processes for the calibration of the SWAT model in a data scarce region |
| VerfasserIn |
K. Bieger, G. Hörmann, N. Fohrer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7340
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| Digitales Dokument |
URL |
| Erschienen |
In: Proceedings of the 14th Workshop on Large-scale Hydrological Modelling ; Nr. 31 (2012-07-06), S.23-30 |
| Datensatznummer |
250017306
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| Publikation (Nr.) |
 copernicus.org/adgeo-31-23-2012.pdf |
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| Zusammenfassung |
Hydrological modeling poses a particular challenge in data scarce regions,
which are often subject to dynamic change and thus of specific interest to
hydrological modeling studies. When a small amount of data available for a
catchment is opposed by extensive data requirements by the chosen hydrologic
model, ways have to be found to extract as much information from the
available data as possible.
In a study conducted in the Xiangxi Catchment in the Three Gorges Region in
China, the use of residual analysis as well as auto- and cross-correlations
for enhanced model evaluation and for the identification of key processes
governing the hydrological behavior of the catchment prior to model
calibration was tested. The residuals were plotted versus various variables
such as time, discharge and precipitation. Also, auto-correlations were
calculated for measured and simulated discharge and cross-correlations of
measured and simulated discharge with precipitation were analyzed. Results
show that the analysis of residuals as well as auto- and cross-correlations
can provide valuable information about the catchment response to rainfall
events, which can be very helpful for calibration of hydrologic models in
data scarce regions. |
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