Abstract
To develop a virus transport model considering both the unsaturated and saturated zone, it is essential to consider separate parameters for both the zone. This is because the virus fate and transport process depends on the degree of saturation. As such, this paper introduces a parameter estimation model that simultaneously identifies virus transport parameters in an unconfined aquifer for both the unsaturated and saturated zones. The proposed model utilizes a linked simulation-optimization technique to minimize errors between observed and simulated virus concentrations. The simulation model used in this study is termed as “variable detachment model,” this is because the simulation component of this approach incorporates varying adsorption rates, which are influenced by the degree of saturation. This study also highlights the complexities involved in parameter estimation for virus transport models, such as non-uniqueness, instability, and non-identifiability. These challenges arise when multiple parameter combinations can produce similar model predictions, leading to difficulty in determining the actual parameter values. To address these challenges, a meta-heuristic optimization algorithm, Flower Pollination Algorithm (FPA), is used, effectively solving such non-convex problems. The model could estimate all the parameters accurately except the inactivation rates of viruses. Later when the global sensitivity analysis was carried out to understand the relative importance of each parameter, inactivation rates were found to be less influential to the model output. Thus, FPA based parameter estimation model can be used as an alternative for estimating the virus transport parameters in groundwater aquifers.
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