Variance Estimation of Extreme Flowsby Ellen W. Stevens, Oklahoma State Univ, Stillwater, United States,
Abstract: The inclusion of historic flood data with gage record data has been shown to reduce the uncertainty in flow estimates. Using numerical integration to quantify that uncertainty is less computationally demanding than Monte Carlo Simulation (MCS) and more accurate than First Order (FO) Approximation. This is demonstrated using several hypothetical flow populations with varying means and coefficients of variation (Cv's). The 500- and 1000-year floods are used as examples.
Subject Headings: Approximation methods | Numerical models | Floods | Flow simulation | Monte Carlo method | Data processing | Uncertainty principles | Hydrologic data | Europe | Monaco | Monte Carlo
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