Incorporating multiple grid-based data in CNN-LSTM hybrid model for daily runoff prediction in the source region of the Yellow River Basin

Incorporating multiple grid-based data in CNN-LSTM hybrid model for daily runoff prediction in the source region of the Yellow River Basin

Study region: The Source Region of the Yellow River Basin (SRYRB), China Study focus: To improve daily runoff prediction accuracy in data-scarce areas, this study focuses on incorporating multiple grid-based data (precipitation, EVI, soil moisture (SM)) to drive the CNN-LSTM hybrid model. The spatia...

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Bibliographic Details
Main Authors: Feichi Hu, Qinli Yang, Junran Yang, Zhengming Luo, Junming Shao, Guoqing Wang
Format: Article
Language:English
Published: Elsevier 2024-02-01
Series:Journal of Hydrology: Regional Studies
Subjects:
Deep learning
Dynamic representation
Runoff prediction
Ungauged regions
Source region of the Yellow River basin
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581823003397

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http://www.sciencedirect.com/science/article/pii/S2214581823003397

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