This study assesses the effects of prolonged exposure of fingers to water on the performance of existing fingerprint recognition systems. The dataset used in this research is collected using a high-end, multispectral fingerprint scanner. To perform a data acquisition, we recruited volunteers to contribute their fingerprint samples to the dataset in multiple sessions. Once the dataset is filled with both fingerprints under normal and wrinkled conditions, we use a minutiae-based fingerprint verification system to retrieve the match scores between all combinations of prints. Finally, we use receiver operating characteristic (ROC) curve to measure the behavior of such systems under maritime environment. Using the equal error rate (EER), we successfully quantify the degradation in performance due to water-induced skin pruning, which is approximately 1% reduction in EER.