A hybrid approach to monthly streamflow forecasting: integrating hydrological model outputs into a Bayesian artificial neural network

•A hybrid monthly streamflow forecasting approach is presented.•Simulated soil moisture from a conceptual model is incorporated into ANNs.•Uncertainty is estimated using a formal Bayesian approach.•Forecast performance is evaluated using a real Australian case study.•The hybrid model improves forecast accuracy compared to reference models.