The study of the function of proteins on a quantitative level requires consideration of the water molecules in and around the protein. This requirement presents a major computational challenge due to the fact that the insertion of water molecules can have a very high activation barrier and would require a long simulation time. Recently, we developed a water flooding (WF) approach which is based on a postprocessing Monte Carlo ranking of possible water configurations. This approach appears to provide a very effective way for assessing the insertion free energies and determining the most likely configurations of the internal water molecules. Although the WF approach was used effectively in modeling challenging systems that have not been addressed reliably by other microscopic approaches, it was not validated by a comparison to the more rigorous grand canonical Monte Carlo (GCMC) method. Here we validate the WF approach by comparing its performance to that of the GCMC method. It is found that the WF approach reproduces the GCMC results in well-defined test cases but does so much faster. This established the WF approach as a useful strategy for finding correct water configurations in proteins and thus to provide a powerful way for studies of the functions of proteins.