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Author Elena, Szolgayová ♦ Günter, Blöschl ♦ Ján, Szolgay ♦ Josef, Arlt
Source Directory of Open Access Journals (DOAJ)
Content type Text
Publisher Sciendo
File Format HTM / HTML
Date Created 2015-06-24
Copyright Year ©2014
Language English
Subject Domain (in LCC) TC1-978
Subject Keyword Long range dependence ♦ ARFIMA ♦ Forecasting ♦ Wavelets ♦ Hydraulic engineering ♦ Technology ♦ Daily streamflow ♦ Deseasonalization
Abstract Short term streamflow forecasting is important for operational control and risk management in hydrology. Despite a wide range of models available, the impact of long range dependence is often neglected when considering short term forecasting. In this paper, the forecasting performance of a new model combining a long range dependent autoregressive fractionally integrated moving average (ARFIMA) model with a wavelet transform used as a method of deseasonalization is examined. It is analysed, whether applying wavelets in order to model the seasonal component in a hydrological time series, is an alternative to moving average deseasonalization in combination with an ARFIMA model. The one-to-ten-steps-ahead forecasting performance of this model is compared with two other models, an ARFIMA model with moving average deseasonalization, and a multiresolution wavelet based model. All models are applied to a time series of mean daily discharge exhibiting long range dependence. For one and two day forecasting horizons, the combined wavelet - ARFIMA approach shows a similar performance as the other models tested. However, for longer forecasting horizons, the wavelet deseasonalization - ARFIMA combination outperforms the other two models. The results show that the wavelets provide an attractive alternative to the moving average deseasonalization.
ISSN 0042790X
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2014-03-01
e-ISSN 0042790X
Journal Journal of Hydrology and Hydromechanics
Volume Number 62
Issue Number 1
Page Count 9
Starting Page 24
Ending Page 32

Source: Directory of Open Access Journals (DOAJ)