Abstract: Water is an important factor in the formation and maintenance of wetland ecosystems. Monitoring the changes in the water area of wetlands is of great significance for wetland conservation. Taking Sentinel-1A data from 2018 to 2019 as the data source, this study calculated the intra- and inter-annual synthetic aperture radar (SAR) backscattering coefficient (σ0) and coherence coefficient (μ0) images of the Zhalong Wetland. Then, this study assigned weights according to the proximity to water bodies of color optical images and extracted the weighted images of σ0 and μ0. Finally, this study extracted the wetland water bodies using the threshold segmentation method and random forest algorithm. The purpose is to monitor the dynamic variations in the wetland water area and explore the intra- and inter-annual variation rules of the wetland water body. The results are as follows. The random forest algorithm yielded the highest extraction accuracy of water bodies, with an absolute value of the mean difference of representative months was 6.69 km2. The threshold segmentation method based on μ0 images yielded the lowest classification accuracy of water bodies, with an absolute value of the mean difference of 13.07 km2. Overall, the intra-annual water area of the Zhalong Wetland showed significant seasonal variations during 2018—2019. The water area fluctuated in the ranges of 1 300~1 600 km2 during late spring and early summer and 700~900 km2 during late summer and early autumn. The inter-annual water area varied with conditions such as climate and temperature. In particular, the wetland water area in October and November 2019 was approximately 1 050 km2 greater than that in 2018 due to large amounts of rainfall. As shown by the calculation based on effective data, the water area in 2019 was about 550 km2 greater than that in 2018 in the Zhalong Wetland.