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Article

Predicting Inflow Rate of the Soyang River Dam Using Deep Learning Techniques

by 1 and 2,*
1
Department of Applied Data Science, Sungkyunkwan University, Suwon 16419, Korea
2
School of Convergence, Sungkyunkwan University, Seoul 03063, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Caterina Samela
Water 2021, 13(17), 2447; https://doi.org/10.3390/w13172447
Received: 27 July 2021 / Revised: 26 August 2021 / Accepted: 3 September 2021 / Published: 6 September 2021
(This article belongs to the Section Hydrology)
The Soyang Dam, the largest multipurpose dam in Korea, faces water resource management challenges due to global warming. Global warming increases the duration and frequency of days with high temperatures and extreme precipitation events. Therefore, it is crucial to accurately predict the inflow rate for water resource management because it helps plan for flood, drought, and power generation in the Seoul metropolitan area. However, the lack of hydrological data for the Soyang River Dam causes a physical-based model to predict the inflow rate inaccurately. This study uses nearly 15 years of meteorological, dam, and weather warning data to overcome the lack of hydrological data and predict the inflow rate over two days. In addition, a sequence-to-sequence (Seq2Seq) mechanism combined with a bidirectional long short-term memory (LSTM) is developed to predict the inflow rate. The proposed model exhibits state-of-the-art prediction accuracy with root mean square error (RMSE) of 44.17 m3/s and 58.59 m3/s, mean absolute error (MAE) of 14.94 m3/s and 17.11 m3/s, and Nash–Sutcliffe efficiency (NSE) of 0.96 and 0.94, for forecasting first and second day, respectively. View Full-Text
Keywords: dam inflow; machine learning; bidirectional LSTM; Seq2Seq; deep learning dam inflow; machine learning; bidirectional LSTM; Seq2Seq; deep learning
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MDPI and ACS Style

Lee, S.; Kim, J. Predicting Inflow Rate of the Soyang River Dam Using Deep Learning Techniques. Water 2021, 13, 2447. https://doi.org/10.3390/w13172447

AMA Style

Lee S, Kim J. Predicting Inflow Rate of the Soyang River Dam Using Deep Learning Techniques. Water. 2021; 13(17):2447. https://doi.org/10.3390/w13172447

Chicago/Turabian Style

Lee, Sangwon, and Jaekwang Kim. 2021. "Predicting Inflow Rate of the Soyang River Dam Using Deep Learning Techniques" Water 13, no. 17: 2447. https://doi.org/10.3390/w13172447

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