Sensitivity analysis plays a crucial role in model calibration across various fields, including engineering, environmental science, economics, and more. Here are some key applications of sensitivity analysis in model calibration: 1. **Parameter Identification**: Sensitivity analysis helps identify which model parameters most significantly affect output variables. By examining how small changes in parameters influence model predictions, researchers can prioritize parameters for calibration efforts. 2. **Uncertainty Quantification**: Understanding how uncertainty in parameters affects model outputs is essential.

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