Current Science

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The predictive capability of a model is dependent on the parameter uncertainty involved in it. This study examines the effect of predictive uncertainty and parameter sensitivity in the application of the well-known HEC-RAS 1D hydrodynamic CSU (Colorado State University) scour prediction model. Correlation-based technique was used for carrying out the sensitivity analysis. Monte Carlo method was adopted for uncertainty quantification. The methodology suggested in the present study drastically improved the predictive capability of the model, by reducing the model error from 26.6% to 0.07%. In general, it improved the predictive capability of any scour model when tested on 19 datasets.

Keywords

Hydrodynamic Model, Parameter Uncertainty, Scour, Prediction, Sensitivity Analysis.
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