Solute Transport Models Based On Adsorption Law And Parameters Inversion

Solute transport in soil and groundwater can be described by convection diffusion equation(s). In particular, the model parameters describing transport characteristics can not be measured directly for nonlinear solutes transport with complicated physics/chemical reactions. Therefore,inverse problems of parameter inversion and identification for convetion-dispersion reaction equation(s) have had widely applications in the research of solutes transpoprt in soil and groundwater.The main work of this thesis includes solute transport model, numerical solution and parameter inversion based on three kinds of adsorption laws. The transport model is introduced, and numerical methods for the forward problem and the inverse problem are discussed in Chapter2.In general, the boundary condition considered in the solute transport model is the first boundary condition or the second boundary condition, and the flux boundary condition is studied few in the known literatures. For models based on different adsorption laws, we mainly consider with the case of the flux boundary condition in Chapter3.There are much researches on the equilibrium solute transport model, but solute transport in soil is often non-equilibrium, so the study for non-equilibrium model is necessary. In Chapter4, a non-equilibrium linear adsorption is discussed and solved numerically by adding a perturbation to the adsorption equation with the help of Matlab software. In Chapter5, we consider with nonlinear Fredunlich adsorption model with Crank-Nioslon difference scheme, and numerical simulations and inversion are carried out by using optimal perturbation iteration algorithm. Especially, when Fredunlich experience constant equals to1, the non-equilibrium Frendunlich adsorption model changes into a linear adsorption model, and the numerical result is similar as compared with that in Chapter4.The choice of an optimal regularization parameter is critical in performing the optimal perturbation algorithm for solving inverse problems. Usually there are a priori and a posteriori selections for the regularization parameter. The Sigmoid transfer function is taken as the optimal regularization parameter depending upon iterations to realize the inversion algorithm for the equilibrium model, which is applied to the non-equilibrium model. The computational results show that the new method is adaptable as compare with that of a priori selection method.