Abstract. Reliable streamflow forecasts with associated uncertainty estimates are essential to manage and make better use of Australia's scarce surface water resources. Here we present the development an operational 7 d ensemble forecasting service for Australia meet growing needs users, primarily river managers, probabilistic support their decision making. We test modelling methodology 100 cat...

Water resources systems planning, and control are significantly influenced by streamflow forecasting. The in northern north-central regions of Victoria (Australia) is different climate indices, such as El Niño Southern Oscillation, Interdecadal Pacific Decadal Indian Ocean Dipole. This paper presents the development ANN model using machine learning with multi-layer perceptron Levenberg algorith...

Streamflow forecasting is of great significance for water resources planning and management. In recent years, numerous data-driven models have been widely used streamflow forecasting. However, the traditional single model ignores utilization different regimes. This study proposed an integrated framework daily based on regime recognition flow sequences. The integrates self-organizing maps (SOM) ...

Common streamflow gauging procedures require assumptions about the stage-discharge relationship (the ‘rating curve’) that can introduce considerable uncertainties in streamflow records. These rating uncertainties are not usually considered fully in hydrological model calibration and evaluation yet can have potentially important impacts. We analysed streamflow gauge data and conducted two modell...

Predicting the streamflow regimes using climate dynamics is important in water resource management. However, Indonesia, there are few studies targeting indices and streamflow. A previous study found difficulty developing a statistical prediction model for this relationship due to its non-linear nature. This attempted address that gap by applying multiple regression (MR) models second- third-ord...