The passive microwave snow-depth retrieval algorithm is an important method to obtain the surface snow depth information of the Tibetan Plateau on a large scale. In order to evaluate the applicability of the current passive microwave snow-depth retrieval algorithms in the Selin Co and Nam Co regions of the Tibetan Plateau， AMSR2 brightness temperature data and snow depth data of ground stations are used， while R， Bias and RMSE are used as evaluation indicators. Five algorithms including Chang2 algorithm， Che algorithm， SPD algorithm， AMSR2 algorithm and Jiang algorithm are chosen. The results show that the Jiang algorithm has the best overall performance， with the highest R value of 0.68 at Nam Co station. The Che algorithm has a good retrieval effect on shallow snow， and its Bias at Bangor Station is -0.66 cm. The Chang2 algorithm performed well for the deep snow of Nam Co station and Selin Co station， with R values of 0.63 and 0.50 in the two places respectively. The retrieval effect of SPD algorithm is the most unsatisfactory， and the snow depth is overestimated obviously， among which shallow snow is overestimated by nearly 20 cm. The performance of AMSR2 algorithm differs greatly between regions， and the retrieved results at Namco Station are better than those at Selin Co Station and Bangor Station. Except for the SPD algorithm， all other algorithms underestimate snow depth in the study area， which is consistent with previous research results.