Parameter Sensitivity

Definition

Parameter sensitivity refers to the degree to which changes in model parameters influence the outputs of a hydrological model. This concept is essential in evaluating how uncertainties in parameter values can impact model predictions, particularly during calibration processes where objective functions are used to minimize discrepancies between observed and simulated data.

5 Must Know Facts For Your Next Test

1. Parameter sensitivity analysis helps identify which parameters most significantly affect model outputs, guiding more focused calibration efforts.
2. High sensitivity indicates that small changes in a parameter can lead to large variations in output, while low sensitivity suggests that parameter changes have minimal impact.
3. Sensitivity analysis can be performed using various methods, including one-at-a-time (OAT) analysis, where parameters are varied individually to observe effects.
4. Understanding parameter sensitivity is crucial for improving model reliability and for making informed decisions based on model predictions.
5. Parameter sensitivity plays a key role in identifying parameters that may require more precise measurement or estimation during the calibration process.

Review Questions

• How does parameter sensitivity influence the calibration process of hydrological models?
  • Parameter sensitivity greatly impacts the calibration process by highlighting which parameters most affect model outputs. By understanding these sensitivities, modelers can prioritize their efforts on adjusting those critical parameters during calibration. This leads to more efficient use of resources and potentially more accurate models, as small changes in sensitive parameters can lead to significant improvements in matching observed data.
• Discuss how objective functions are utilized in relation to parameter sensitivity during model calibration.
  • Objective functions serve as a quantitative measure of how well the model outputs align with observed data. In this context, parameter sensitivity helps identify which parameters should be fine-tuned to minimize the objective function value effectively. When certain parameters show high sensitivity, adjustments to these can lead to notable improvements in the objective function, demonstrating their importance in achieving accurate model simulations.
• Evaluate the significance of conducting a thorough parameter sensitivity analysis before performing uncertainty analysis in hydrological modeling.
  • Conducting a thorough parameter sensitivity analysis before uncertainty analysis is crucial because it establishes a clear understanding of which parameters significantly influence model outcomes. This allows researchers to focus their uncertainty analysis on the most impactful parameters, ensuring that resources are allocated effectively. Additionally, identifying sensitive parameters can help in developing strategies for reducing uncertainty, ultimately leading to more robust and reliable hydrological predictions.

Related terms

Calibration: The process of adjusting model parameters to achieve the best fit between simulated outputs and observed data.

Objective Function: A mathematical function used to quantify the difference between observed and simulated values, guiding the calibration of model parameters.

Uncertainty Analysis: A method for assessing the impact of parameter uncertainty on model outputs and predictions.