An iterative regularization algorithm for determining source (sink) coefficient in 1-D solute transportation
一维溶质运移源(汇)项系数反演的迭代正则化算法

Solute transport in porous media involving physical/chemical reactions can always be expressed by one-dimensional advection dispersion-reaction diffusion equation with nonlinear source (sink) terms, but the source (sink) coefficient which reflects solute adsorption/degeneration capabilities is often unknown. This paper deals with an inverse problem of determining source coefficients in 1-D solute transport process with overposed concentration data at the outflow side. By Tikhonov regularization and matrix SVD system, an optimal iterative regularization algorithm is established in which regularization parameters can be easily obtained, and the algorithm realization procedures are also discussed. Numerical simulations are carried out in the case of random noisy data showing that the algorithm here not only is accuracy, but also is stability for random noises of the measured data. Finally, by investigating an actual soil-column experiment in Zibo, Shandong Province, the algorithm is successfully put into practice to determine the unknown source coefficient. The numerical inversion results roughly coincide with the actually measured breakthrough data showing that the algorithm here is efficient.