B-AMA: A Python-coded protocol to enhance the application of data-driven models in hydrology

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.