Enhancing Runoff Simulation Using BTOP-LSTM Hybrid Model in the Shinano River Basin

Enhancing Runoff Simulation Using BTOP-LSTM Hybrid Model in the Shinano River Basin

Runoff simulation is an ongoing challenge in the field of hydrology. Process-based (PB) hydrological models often gain unsatisfactory simulation accuracy due to incomplete physical process representations. While the deep learning (DL) models demonstrate their capacity to grasp intricate hydrological...

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Bibliographic Details
Main Authors: Silang Nimai, Yufeng Ren, Tianqi Ao, Li Zhou, Hanxu Liang, Yanmin Cui
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Water
Subjects:
runoff simulation
process-based model
deep learning
lstm
feature dimensionality reduction
Hybridization
Online Access:https://www.mdpi.com/2073-4441/15/21/3758

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https://www.mdpi.com/2073-4441/15/21/3758

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