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Reservoir water level forecasting using group method of data handling

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Accurately forecasted reservoir water level is among the most vital data for efficient reservoir structure design and management. In this study, the group method of data handling is combined with the minimum description length method to develop a very practical and functional model for predicting reservoir water levels. The models’ performance is evaluated using two groups of input combinations based on recent days and recent weeks. Four different input combinations are considered in total. The data collected from Chahnimeh#1 Reservoir in eastern Iran are used for model training and validation. To assess the models’ applicability in practical situations, the models are made to predict a non-observed dataset for the nearby Chahnimeh#4 Reservoir. According to the results, input combinations (L, L-1) and (L, L-1, L-12) for recent days with root-mean-squared error (RMSE) of 0.3478 and 0.3767, respectively, outperform input combinations (L, L-7) and (L, L-7, L-14) for recent weeks with RMSE of 0.3866 and 0.4378, respectively, with the dataset from https://www. typingclub.com/st. Accordingly, (L, L-1) is selected as the best input combination for making 7-day ahead predictions of reservoir water levels.
Czasopismo
Rocznik
Strony
717--730
Opis fizyczny
Bibliogr. 46 poz.
Twórcy
autor
  • Department of Civil Engineering, Razi University, Kermanshah, Iran
autor
  • Department of Civil Engineering, Razi University, Kermanshah, Iran
  • School of Engineering, University of Guelph, Guelph, ON NIG 2W1, Canada
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-41f1d585-92c7-4a2d-8d79-b7c282ba34f3
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