Tag: Nash-Sutcliffe efficiency

A deep learning model combining dynamic lag encoding and temporal multi-head attention significantly reduces peak flow forecasting errors across multi-hour ...

Coupled hydrologic and water-allocation models project that extreme drought extent and water deficits will rise across the Ba basin under ...

Researchers demonstrated that combining bidirectional long short-term memory networks with ensemble empirical mode decomposition reduced groundwater level forecasting errors by ...

A global study of more than 6000 catchments shows that fixed performance thresholds misjudge hydrological models and proposes lower and ...

A Norwegian study shows that a deep learning LSTM network outperforms the country's operational HBV model in simulating both snowmelt- ...

A factorial ANOVA study across five Iranian basins shows that the most important machine learning modeling decision for precipitation prediction ...

A hybrid deep learning and geostatistical workflow called CBAG substantially corrects IMERG satellite rainfall bias in a mountainous basin and ...