We present a forecast-based adaptive management framework for water supply reservoirs and evaluate the contribution of long-term inflow forecasts to reservoir operations. Our framework is developed for snow-dominated river basins that demonstrate large gaps in forecast skill between seasonal and inter-annual time horizons. We quantify and bound the contribution of seasonal and inter-annual fore...

Ensemble forecasting is used in numerical weather prediction to give an improved estimate of the atmospheric state and to improve measures of forecast accuracy. While the method is effective, there are some fundamental issues in interpreting the ensemble as a statistically valid representation of uncertainty in the state of the atmosphere. Coupled with this interpretation is the difficulty in t...

A number of previous studies have shown that a combination of forecasts typically outperforms any component forecast. Service managers may wish to use forecast combination to improve forecast accuracy in predicting retail sales. In this study, revenue data from an actual service company is used to generate and test a least absolute value (LAV) regression model for forecast combination. The LAV ...

The domain of multi level forecast combination is a challenging new domain containing a large potential for forecast improvements. This thesis presents a theoretical and experimental analysis of different types of forecast diversification on forecast error covariances and resulting combined forecast quality. Three types of diversification are used: (a) diversification concerning the level of le...

This paper proposes a Bayesian procedure for combining forecasts from multivariate forecasting models, e.g. VAR models. Standard applications of Bayesian model averaging suffer from a basic difficulty in this context, when additional variables are included and modelled the connection between the overall measure of fit for the model and the expected forecasting performance for the variables of i...