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Machine learning use in hydrological modeling has intensifi ed in recent decades given the potential of these techniques to produce in short time satisfactory solutions to support tasks such as early fl ooding warnings. In this context, this work reports the development and the results of a forecasting model built from a hydrometeorological database and using a regression tree. This regression tree-based model is intended to forecast, with hours in advance, the level of a river in Novadoaj:f07ea367d38243f7a2e29eab2345c75d fatcat:v5crw5ktszfnbm4mohfeqhttbm