Riverbank filtration is a natural process, using alluvial aquifers to remove contaminants and pathogens in river water for the production of drinking water. Back analysis which minimizes the objective function that is typically the sum of squares of the differences between the calculated and measured quantities is used for the estimation of aquifer parameters. In this study, transmissivity is back-analysed using the BFGS (Broyden-Fletcher-Goldfarb-Shanno) scheme for optimization. MOC is used to obtain calculated groundwater level. The developed inverse model was applied to Dae-san, Chang-won city where riverbank filtration is being undertaken. The model showed good convergence behavior for different groundwater conditions. The performance of the model was better than a widely-used commercial software package in terms of error between calculated and observed groundwater level.