A Machine-Learning Framework for Modeling and Predicting Monthly Streamflow Time Series
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DOI: 10.3390/hydrology10040095
Abstract: Having a complete hydrological time series is crucial for water-resources management and modeling. However, this can pose a challenge in data-scarce environments where data gaps are widespread. In such situations, recurring data gaps can lead… read more here.
Keywords: monthly streamflow; streamflow time; time series;