AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods

Abstract. Machine learning has shown great promise for simulating hydrological phenomena. However, the development of machine-learning-based models requires advanced skills from diverse fields, such as programming and modeling. Additionally, data pre-processing post-processing when training testing machine are a time-intensive process. In this study, we developed python-based framework that simplifies process building automates model results. Pre-processing utilities assist in incorporating domain knowledge hydrology model, distribution weather into hydrologic response units (HRUs) based on different HRU discretization definitions. The help interpreting model's results point view. This will increase application modeling approaches sciences.