Reducing model prediction uncertainty

What is it about?

Calibration of a distributed hydrologic model (WetSpa) for modeling river flows. The main purpose of this research is to provide more confidence in the uncertainty analysis of the model parameters and predictions. A Box-Cox transformation and an autoregressive integrated moving average (ARIMA) time series model are used to transform the correlated and nonstationary model residuals to white noise disturbances, which can be minimized by ordinary least squares optimization.

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Why is it important?

Uncertainty principles, Optimization models, River flow, Parameters (statistics), Autoregressive moving average models, Calibration, Hydrologic models