Numerical methods for improving sensitivity analysis and parameter estimation of virus transport simulated using...

Area of Science:

• Environmental science
• Hydrology
• Microbiology

Background:

• Virus transport in porous media is crucial for environmental and health risk assessments.
• Accurate parameter estimation for virus transport models is challenging due to complex processes like sorption and reaction.
• Sensitivity analysis is key to understanding how model parameters influence predictions.

Purpose of the Study:

• To evaluate methods for sensitivity analysis and parameter estimation in virus transport simulations.
• To compare different observation types and numerical considerations for robust analysis.
• To improve the reliability of parameter estimation for virus transport models.

Main Methods:

• One- and two-dimensional homogeneous simulations of virus transport.
• Analysis of head, flow, conservative, and virus transport observations.
• Examination of observed-value weighting, breakthrough-curve temporal moments, and time-step size significance.

Main Results:

• Observed-value weighting is sensitive to numerical variability.
• Temporal moments of breakthrough curves are more robust sensitivity indicators than conservative-transport observations.
• Transport time-step size critically influences simulation outcomes, often more than inactivation rates.

Conclusions:

• Temporal moments provide a more reliable basis for sensitivity analysis in virus transport.
• Numerical simulation parameters, like time-step size, require careful consideration for accurate results.
• The proposed approach enhances the evaluation of observational data for parameter estimation, improving model reliability.