Abstract: Exploration of the water body extraction model based on GF-6 satellite images can provide new data sources and technical support for water body monitoring. First, GF-6 WFV satellite data of Zonag Lake was used to analyze the reflectance difference between water and other ground objects in each band of GF-6 WFV satellite data. Based on this, a novel water index named red side water index (RSWI) was constructed. Then, the overall accuracy and Kappa coefficient generated by the confusion matrix were used to verify RSWI and the other three water extraction models, which include the single-band threshold method, normalized difference water index, and modified shade water index. Finally, six typical lakes with different types of areas larger than 100 km2 in Hoh Xil were selected for analysis of general applicability. The results showed that compared with other methods, the decision tree model composed of RSWI and NIR bands effectively eliminates the influence of lake bottom sediments on water bodies and extracts shallow water bodies more completely, with an overall accuracy of 93.78% and a Kappa coefficient of 0.87. Additionally, it has been found that the stability and general applicability of RSWI are better than those of other water body models with respect to different types of lakes.