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CNN-Based Subnetworks For Improved Modelling of Extreme Flood and Drought Events in The Negro River Basin by Gustavo Henrique is a document available to read on EtoBox.
This study presents a novel multi-output convolutional neural network (CNN) framework utilizing station-specific subnets to model historical river stages in the Negro River basin, addressing challenges posed by sparse hydrological data. The model demonstrates high accuracy in reconstructing water level time series, effectively capturing complex hydrological dynamics and outperforming individually trained networks. The findings suggest that this approach can enhance flood and drought monitoring and support d
- Author
- Gustavo Henrique
- Language
- EN