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| Titel |
On selection of the optimal data time interval for real-time hydrological forecasting |
| VerfasserIn |
J. Liu, D. Han |
| 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 ; 17, no. 9 ; Nr. 17, no. 9 (2013-09-30), S.3639-3659 |
| Datensatznummer |
250085937
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| Publikation (Nr.) |
 copernicus.org/hess-17-3639-2013.pdf |
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| Zusammenfassung |
| With the advancement in modern telemetry and communication technologies,
hydrological data can be collected with an increasingly higher sampling
rate. An important issue deserving attention from the hydrological community
is which suitable time interval of the model input data should be chosen in
hydrological forecasting. Such a problem has long been recognised in the
control engineering community but is a largely ignored topic in operational
applications of hydrological forecasting. In this study, the intrinsic
properties of rainfall–runoff data with different time intervals are first
investigated from the perspectives of the sampling theorem and the
information loss using the discrete wavelet transform tool. It is found that
rainfall signals with very high sampling rates may not always improve the
accuracy of rainfall–runoff modelling due to the catchment low-pass-filtering effect. To further investigate the impact of a data time interval in
real-time forecasting, a real-time forecasting system is constructed by
incorporating the probability distributed model (PDM) with a real-time
updating scheme, the autoregressive moving-average (ARMA) model. Case
studies are then carried out on four UK catchments with different
concentration times for real-time flow forecasting using data with different
time intervals of 15, 30, 45, 60, 90 and 120 min. A positive
relation is found between the forecast lead time and the optimal choice of
the data time interval, which is also highly dependent on the catchment
concentration time. Finally, based on the conclusions from the case studies,
a hypothetical pattern is proposed in three-dimensional coordinates to
describe the general impact of the data time interval and to provide
implications of the selection of the optimal time interval in real-time
hydrological forecasting. Although nowadays most operational hydrological
systems still have low data sampling rates (daily or hourly), the future is
that higher sampling rates will become more widespread, and there is an
urgent need for hydrologists both in academia and in the field to realise the
significance of the data time interval issue. It is important that more case
studies in different catchments with various hydrological forecasting
systems are explored in the future to further verify and improve the
proposed hypothetical pattern. |
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