Manifoldly Constrained Monte Carlo Optimization and Uncertainty Estimation for an Operational Hydrologic Forecast Model

@inproceedings{Fleming2010ManifoldlyCM,
  title={Manifoldly Constrained Monte Carlo Optimization and Uncertainty Estimation for an Operational Hydrologic Forecast Model},
  author={Sean W. Fleming and Frank A. Weber and S. Weston and BC Hydro},
  year={2010}
}
River forecasts have two broad uncertainty classes: errors associated with meteorological forecasts, and those associated with the hydrologic model. We developed a technology (dubbed Absynthe) to address the latter error class in a practical and defensible way. The technique merges the proven, Monte Carlo-based Generalized Likelihood Uncertainty Estimation (GLUE) concept for model parameter identification with: (i) multiple performance goals defined by operational and physical considerations… CONTINUE READING
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