Abstract:
In recent years there has been a tremendous increase in the contamination of
groundwater due to rapid industrial growth and use of fertilizers and pesticides in
agriculture. This contaminated water passes through the soil and may produce
hazardous chemicals, which are risk to public health. The definition of contaminant is
defined as the presence of any objectionable substance in water which make unsafe
for drinking. The substance may be physical, chemical, biological or radiological. The
biological contaminants are bacteria and virus. It is viruses in drinking water that are
an important source of human enteric diseases. Pathogenic microorganisms from
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sewage sludges, septic tanks and other sources can transport with subsurface water to
drinking water wells. Production wells for drinking water must be at an adequate
distance from source of contamination. Thus, there is a need to predict the
contaminant distribution in ground water once these are released from the source.
Understanding of the movementof contaminants in subsurface is necessary for
taking up proper remedial measures. Numerical models are very important tools for
studying the movement of contaminants in subsurface. The present study is concerned
with the modeling of conservative as well as nonconservative virus transport in
subsurface. The model is based on an operator split approach which employs a
globally second order accurate explicit finite volume method for the advective
transport and an implicit finite difference method for the dispersive transport. The
performance of the numerical model in predicting solute/virus movement for both
advection dominated and dispersion dominated flow scenario is studied by comparing
the model prediction with the corresponding analytical solutions for a wide range of
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Peclet numbers and Courant numbers. The comparison is made for various cases of
movement of conservative, reactive and virus transport in subsurface. In addition the
virus transport numerical model is coupled with Richards equation governing
moisture flow through the unsaturated zone. The numerical model simulating
moisture flow through unsaturated zone is based on a mass conservative fully implicit
finite difference numerical scheme. The application of the flow and transport models
on virus movement through unsaturated zone is demonstrated through an example.
The present study is also concerned with the estimation of transport
parameters of virus movement in subsurface. The parameter estimation is formulated
as a least square minimization problem in which the parameters are estimated by
minimizing the deviation between the model predicted and observed virus
concentrations. For this purpose, a hybrid finite volume numerical model simulating
one dimensional virus transport in subsurface is coupled with Levenberg-Marquadart
optimization algorithm. The efficacy and robustness of the optimization procedure is
evaluated by estimating the parameter from hypothetically generated virus
concentration data in both saturated and unsaturated zones. The present study also
investigates the performance of the objective function while estimating transport
parameters using inverse procedures in the presence of data errors. In this study the
Gaussian noise is added to the hypothetical data generated at discrete times and at
discrete distances from the source. A detailed statistical analysis is carried out to study
the effect of bias induced by the objective function on the estimated parameters when
the data contains the errors. The optimization algorithm is also applied to estimate the
transport parameters from the virus concentration data of two column experiments
involving MS2 and OX174 virus transport in saturated and unsaturated zones.
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