Application of machine learning models in assessing the hydrological changes under climate change in the transboundary 3S River Basin

Application of machine learning models in assessing the hydrological changes under climate change in the transboundary 3S River Basin

This paper aims to evaluate two machine learning (ML) algorithms, namely, convolutional neural network (CNN) and long short-term memories (LSTM) deep learning algorithms, to predict the hydrological regime of the 3S River Basin under various climate change scenarios. Climate models CMCC-CMS, HadGEM-...

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Bibliographic Details
Main Authors: Quyen Nguyen, Sangam Shrestha, Suwas Ghimire, S. Mohana Sundaram, Wenchao Xue, Salvatore G. P. Virdis, Manisha Maharjan
Format: Article
Language:English
Published: IWA Publishing 2023-08-01
Series:Journal of Water and Climate Change
Subjects:
climate change
cnn
hydrological modeling
lstm
machine learning
streamflow
Online Access:http://jwcc.iwaponline.com/content/14/8/2902

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