Predicting river bathymetry in data sparse regions using a generative deep learning model

Chung‐Yuan Liang

doi:10.1016/j.jhydrol.2025.134450

Predicting river bathymetry in data sparse regions using a generative deep learning model

2025-10-27

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DOI：10.1016/j.jhydrol.2025.134450

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Abstract

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• A deep learning model is devised to estimate river cross-sections using accessible data. • Input and output are normalized by channel scales to let model work across rivers. • The model can investigate how cross-section shape changes with channel properties.

Predicting river bathymetry in data sparse regions using a generative deep learning model

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