A multisite seasonal ensemble streamflow forecasting technique

Real-Time Data Assimilation for Operational Ensemble Streamflow Forecasting

Operational flood forecasting requires that accurate estimates of the uncertainty associated with modelgenerated streamflow forecasts be provided along with the probable flow levels. This paper demonstrates a stochastic ensemble implementation of the Sacramento model used routinely by the National Weather Service for deterministic streamflow forecasting. The approach, the simultaneous optimizat...

Neural network streamflow forecasting

Classification of heterogeneous precipitation fields for the assessment and possible improvement of lumped neural network models for streamflow forecasts N. Lauzon, F. Anctil, and C. W. Baxter Golder Associates, Calgary, Canada Département de génie civil, Pavillon Pouliot, Université Laval, Québec, G1K 7P4, Canada HYDRANNT Consulting Inc., Port Coquitlam, Canada Received: 20 December 2005 – Acc...

Multisite disaggregation of monthly to daily streamflow

Streamflow disaggregation is used to preserve statistical attributes of time series across multiple sites and timescales. Several algorithms for spatial disaggregation and for disaggregation of annual to monthly flows are available. However, the disaggregation of monthly to daily or weekly to daily flows remains a challenge. A new algorithm is presented for simultaneously disaggregating monthly...

Multiscale streamflow forecasting using a new Bayesian Model Average based ensemble multi-wavelet Volterra nonlinear method

A Novel Weighted Ensemble Technique for Time Series Forecasting

Improvement of time series forecasting accuracy is an active research area having significant importance in many practical domains. Extensive works in literature suggest that substantial enhancement in accuracies can be achieved by combining forecasts from different models. However, forecasts combination is a difficult as well as a challenging task due to various reasons and often simple linear...