Accurate extraction of surface water information is important for water resource planning and management and related disaster monitoring. Herein, using Sentinel-2A MSI images as the research data, the water body around Poyang Lake was extracted based on 10 typical spectral band index algorithms and the water body recognition results of synthetic aperture radar images combined with visual interpretation were compared and analyzed as the true value. The experimental results demonstrate that the recognition effect of the normalized, Gaussian normalized, and pseudo normalized difference water body indexes is the best. The average F1-score is greater than 95%, and the threshold stability is high. An improved normalized difference water body index is suitable for water extraction in urban areas. The combined water body index has good recognition effect in paddy fields and river areas. The enhanced water body and shadow water body indices are applicable to mountainous areas. The enhanced water body index is also applicable in urban areas. The revised normalized difference water body index is only applicable to the identification of large-area water bodies. A shadow-oriented automatic water index can effectively eliminate the interference caused by terrain shadows. However, the overall performance of a nonshadow oriented automatic water index is relatively poor.