Predicting the Water Level Fluctuation in an Alpine Lake Using Physically Based, Artificial Neural Network, and Time Series Forecasting Models
Joint Authors
Liu, Wen-Cheng
Young, Chih-Chieh
Hsieh, Wan-Lin
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-07-16
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Accurate prediction of water level fluctuation is important in lake management due to its significant impacts in various aspects.
This study utilizes four model approaches to predict water levels in the Yuan-Yang Lake (YYL) in Taiwan: a three-dimensional hydrodynamic model, an artificial neural network (ANN) model (back propagation neural network, BPNN), a time series forecasting (autoregressive moving average with exogenous inputs, ARMAX) model, and a combined hydrodynamic and ANN model.
Particularly, the black-box ANN model and physically based hydrodynamic model are coupled to more accurately predict water level fluctuation.
Hourly water level data (a total of 7296 observations) was collected for model calibration (training) and validation.
Three statistical indicators (mean absolute error, root mean square error, and coefficient of correlation) were adopted to evaluate model performances.
Overall, the results demonstrate that the hydrodynamic model can satisfactorily predict hourly water level changes during the calibration stage but not for the validation stage.
The ANN and ARMAX models better predict the water level than the hydrodynamic model does.
Meanwhile, the results from an ANN model are superior to those by the ARMAX model in both training and validation phases.
The novel proposed concept using a three-dimensional hydrodynamic model in conjunction with an ANN model has clearly shown the improved prediction accuracy for the water level fluctuation.
American Psychological Association (APA)
Young, Chih-Chieh& Liu, Wen-Cheng& Hsieh, Wan-Lin. 2015. Predicting the Water Level Fluctuation in an Alpine Lake Using Physically Based, Artificial Neural Network, and Time Series Forecasting Models. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074531
Modern Language Association (MLA)
Young, Chih-Chieh…[et al.]. Predicting the Water Level Fluctuation in an Alpine Lake Using Physically Based, Artificial Neural Network, and Time Series Forecasting Models. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1074531
American Medical Association (AMA)
Young, Chih-Chieh& Liu, Wen-Cheng& Hsieh, Wan-Lin. Predicting the Water Level Fluctuation in an Alpine Lake Using Physically Based, Artificial Neural Network, and Time Series Forecasting Models. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074531
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074531