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| Titel |
Long-range forecasting of intermittent streamflow |
| VerfasserIn |
F. F. Ogtrop, R. W. Vervoort, G. Z. Heller, D. M. Stasinopoulos, R. A. Rigby |
| 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 ; 15, no. 11 ; Nr. 15, no. 11 (2011-11-07), S.3343-3354 |
| Datensatznummer |
250013017
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| Publikation (Nr.) |
 copernicus.org/hess-15-3343-2011.pdf |
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| Zusammenfassung |
| Long-range forecasting of intermittent streamflow in semi-arid Australia
poses a number of major challenges. One of the challenges relates to
modelling zero, skewed, non-stationary, and non-linear data. To address
this, a statistical model to forecast streamflow up to 12 months ahead is
applied to five semi-arid catchments in South Western Queensland. The model
uses logistic regression through Generalised Additive Models for Location,
Scale and Shape (GAMLSS) to determine the probability of flow occurring in
any of the systems. We then use the same regression framework in combination
with a right-skewed distribution, the Box-Cox t distribution, to model the
intensity (depth) of the non-zero streamflows. Time, seasonality and climate
indices, describing the Pacific and Indian Ocean sea surface temperatures,
are tested as covariates in the GAMLSS model to make probabilistic 6 and
12-month forecasts of the occurrence and intensity of streamflow. The output
reveals that in the study region the occurrence and variability of flow is
driven by sea surface temperatures and therefore forecasts can be made with
some skill. |
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