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Uncertainty Analysis of GLERL's Component Net Basin Supply Estimates

Carlo DeMarchi;Tim Hunter, Qiang Dai, Mary Mello
The algorithms employed by GLERL to estimate Great Lakes net basin supplies were analyzed to evaluate the uncertainty in the modelled NBS results, which are widely used for analyzing the Great Lakes water balance. The evaluation focused on methods used to estimate runoff and over-lake precipitation. Uncertainty in runoff estimates was determined from a combination of assumed uncertainty estimates for gauged basin runoff, with uncertainty in ungauged basins determined using a leave-one-out Monte Carlo analysis. Uncertainty in precipitation was estimated by comparing GLERL’s estimates to precipitation estimates from more advanced models which incorporate short-term forecast and radar data. Uncertainty in evaporation was not computed directly in this analysis, but rather estimated from previous studies. Stochastic estimates of GLERL NBS were computed from the uncertainty information obtained for each component, and biases between the deterministic and stochastic results were identified.
Estimating Overlake Precipitation and Runoff Uncertainty
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Hydroclimate Information
Questions We Asked
What are the historical NBS estimates & how have changes affected lake levels?
Improve understanding of hydroclimatic processes & impacts
Assessing Reliability of Historical Data