B-AMA: A Python-coded protocol to enhance the application of data-driven models in hydrology. (February 2023)

• Record Type: Journal Article
• Authors: Amaranto, Alessandro; Mazzoleni, Maurizio
• Is Part Of: Environmental modelling & software. Volume 160(2023)
• Publication Date: 2023-02
• Subjects: Modeling protocol -- Data-driven models -- Hydrological predictions; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105609
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: In this manuscript, we present B-AMA (Basic dAta-driven Models for All), an easy, flexible, fully coded Python-written protocol for the application of data-driven models (DDM) in hydrology. The protocol, which is open source and freely available for academic and non-commercial purposes, has been realized to allow early career scientists, with a basic background in programming, to develop DDM ensuring that no stones are left unturned through their implementation. B-AMA embeds data splitting, feature selection, hyperparameter optimization, and performance metrics. A Jupyter notebook with a practical workflow is available to guide the users through the protocol employment, while visualization tools allow efficient investigation and communication of results. We tested B-AMA across four hydrological applications to explore DDM applicability across temporal resolutions, time series lengths, and autocorrelations. B-AMA showed great accuracy and reasonable computational time, making the protocol ideal for educational purposes and for the development of DDM-based forecasts of hydrological time-series. Highlights: B-AMA embeds all the building blocks for the implementation of data-driven models. The B-AMA protocol can be run with a single line of code. B-AMA allows assessment of modeling results through effective visualization. B-AMA is intended for both non expert users and more experienced developers.