Wetlands are valuable and sensitive ecosystems that make them imperative to tracking the dynamics in their extent for sustainable management under global warming. Here we focused on the Yellow River Source (YRS) wetlands, which is renowned for hosting one of the world's largest plateau peat bog, unfortunately, it had experienced sharp degradation, threatening the safety of water supply for approximately 110 million people of the lower Yellow River basin. However, the lack of long-term, dense time-series data makes it challenging to assess its evolution trends and driving factors. Therefore, we developed a decision tree sample migration method based on Euclidean distance and Land Surface Water Index, and successfully generated annual wetland mapping of YRS from 1986 to 2022 by utilizing the Landsat 5/7/8 datasets and Random Forest method. The average sample migration rate was 89.21 %, with an average overall accuracy of 95.49 %. We observed that the marsh area decreased by 2031 km2, marking a decline of 12.98 %, while the water area increased by 710 km2 (31.24 %) compared to 1986. Spatially, 10.96 % of marsh composition presents significant (P < 0.05) decline trend, which are mainly converted to grass (86 %), followed by impervious (10 %). There were 6.69 % of water composition showing significant (P < 0.05) increase trend, which are mainly sourced from impervious (82 %) and marsh (12 %). Grazing activities were more important driving forces than climate change for marsh degradation, while the water expansion was associated with recent rising temperature in YRS. The sample migration method is proved to be feasible, robust, and effective for long-term wetland mapping. We suggest that wetland decision-makers need to focus on marsh degradation and reduce grazing intensity, so that fostering the sustainable and healthy wetlands in the Qinghai-Tibetan Plateau.