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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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Luppichini_et_al-2022.pdf | Open Access Published Paper | 2.66 MB | Adobe PDF | View/Open |
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