Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/16261
Authors: Luppichini, Marco* 
Bini, Monica* 
Giannecchini, Roberto* 
Title: CleverRiver: an open source and free Google Colab toolkit for deep-learning river-flow models
Journal: Earth Science Informatics 
Series/Report no.: /16 (2023)
Publisher: Springer
Issue Date: 2023
DOI: 10.1007/s12145-022-00903-7
Abstract: In a period in which climate change is signifcantly varying rainfall regimes and their intensity all over the world, river-fow prediction is a major concern of geosciences. In recent years there has been an increase in the use of deep-learning models for river-fow prediction. However, in this feld we can observe two main issues: i) many case studies use similar (or the same) strategies without sharing the codes, and ii) the application of these techniques requires good computer knowledge. This work proposes to employ a Google Colab notebook called CleverRiver, which allows the application of deep-learning for river-fow predictions. CleverRiver is a dynamic software that can be upgraded and modifed not only by the authors but also by the users. The main advantages of CleverRiver are the following: the software is not limited by the client hardware, operating systems, etc.; the code is open-source; the toolkit is integrated with user-friendly interfaces; updated releases with new architectures, data management, and model parameters will be progressively uploaded. The software consists of three sections: the frst one enables to train the models by means of some architectures, parameters, and data; the second section allows to create predictions by using the trained models; the third section allows to send feedback and to share experiences with the authors, providing a fux of precious information able to improve scientifc research.
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