Identification of virus transport parameters in groundwater: Data errors and bias

The present study discusses the identification of virus transport parameters in groundwater from the virus concentration data using inverse procedure. The parameters are estimated by minimizing the deviations between the model predicted and experimentally observed virus concentrations. Model parameters are estimated from hypothetically generated virus concentration data by numerical inversion of the governing virus transport equation employing Levenberg-Marquardt optimization algorithm. The bias induced by the objective function on the parameter estimates is studied in detail by adding Gaussian noise to the hypothetically generated virus concentration data. Statistical analysis is performed for quantifying the bias in terms of sample mean and confidence intervals. The parameter estimation results indicate that while estimating two or more parameters simultaneously, the objective function induces an undue bias in the parameter estimates. It is also found that the induced bias is quite significant in case of inactivation parameters even at lower noise levels. The optimization algorithm is also applied to estimate the transport parameters from the virus concentration data of a column experiment.

► The objective function does not induce bias while estimating individual virus transport parameters.
► The objective function induces bias when more than one parameter are being estimated simultaneously.
► The bias induced is significant in case of virus inactivation parameters even at low noise levels.