Long-range forecasting of intermittent streamflow

F. F. Van Ogtrop*, R. W. Vervoort, G. Z. Heller, D. M. Stasinopoulos, R. A. Rigby

*Corresponding author for this work

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    23 Citations (Scopus)
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    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.

    Original languageEnglish
    Pages (from-to)3343-3354
    Number of pages12
    JournalHydrology and Earth System Sciences
    Issue number11
    Publication statusPublished - 2011

    Bibliographical note

    Copyright the Author(s) [2011]. Originally published in [van Ogtrop, F. F., Vervoort, R. W., Heller, G. Z., Stasinopoulos, D. M., and Rigby, R. A.: Long-range forecasting of intermittent streamflow, Hydrol. Earth Syst. Sci., 15, 3343-3354]. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


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