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HYBRID MODEL FOR ONE STEP AHEAD FORECASTING OF DAILY RIVER FLOWS

Elena Peksova-Szolgayova, Jan Szolgay, Zsolt Lukac

First published: 2017-11-20https://doi.org/10.5593/sgem2017h/33/s12.024View metrics

Abstract

In this study a hybrid model for one step ahead forecasting of mean daily discharges at the gauging ??????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????Daily discharges were modeled and predicted by the decomposition of the mathematical model of the runoff generation process into two components ?? deterministic and stochastic. For such approach the term hybrid is often adopted. The aim was to improve the forecasting performance by combining the conceptual daily rainfall runoff model HRON for one step ahead discharge forecasts with forecasts of several time series models for the forecasting of the error time series of the deterministic rainfall runoff model. Since these error processes are in general nonlinear and in addition to that they may exhibit nonstationarity and heteroscedasticity, beside traditional ARMA type models, GARCH type nonlinear time series models were also considered. The one - step - ahead forecasting performance of the nonlinear time series models was compared with that of the linear error series models.

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Publication details

Title
HYBRID MODEL FOR ONE STEP AHEAD FORECASTING OF DAILY RIVER FLOWS
Authors
Elena Peksova-Szolgayova, Jan Szolgay, Zsolt Lukac
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 17th International Multidisciplinary Scientific GeoConference SGEM2017, Water Resources. Forest, Marine and Ocean Ecosystems
Publisher
STEF92 Technology
Year
2017
Pages
195-202
SWS Citekey
Peksova-Szolgayova201712195202
ISSN
1314-2704
ISBN
978-619-7408-27-0
Language
en
Publication type
Conference Paper
Keywords
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