Under the background of climate warming, the distribution pattern of snowpack in mountainous areas is naturally under the focus of attention, and the changes in the snowpack pattern in mountainous areas have important impacts on hydrological processes such as downstream river runoff, water supply, and so on. In this study, based on the MODIS day-by-day cloud-free snowpack area dataset, we analysed the process of stable snowpack formation and the final pattern of snowpack in spring and winter in two typical topographic regions, the hilly plateau and the alpine valley region, in the eastern part of the Tibetan Plateau, and constructed a model based on the Maximum Entropy Model (MEM) method for predicting the influencing factors of the stable snowpack. A model was constructed based on the maximum entropy model method to predict the factors influencing the stable snowpack, and the dominant factors of the stable snowpack in spring and winter in the watersheds of the two topographic regions were analysed. The main conclusions are as follows: (1) The snow ablation rate on the western Sichuan Plateau is different in winter and spring, and is greater in spring than in winter; there is also a difference in the snow ablation rate in different topographic regions, with a greater difference in the hilly plateau than in the high mountain valleys. (2) The distribution pattern of stable snow in the two major terrain areas of the Western Sichuan Plateau varies in seasons, and the spatial distribution area is relatively small, mostly showing a rising trend with increasing altitude. (3) The influence factors of stable snowpack in different terrain areas in different seasons are different, and elevation is the main factor influencing the distribution pattern of stable snowpack. The results of this paper have some reference value for the study of snow hydrology in the climatic context of the Western Sichuan Plateau.

This study examines stable snow formation and distribution in the western Sichuan Plateau's Mamukao and Hanliu river basins using MODIS snow cover data. It analyzes dominant influencing factors using a maximum entropy model. Findings reveal different snow ablation rates between basins during winter and spring, with higher-altitude areas hosting stable snowpack. Influencing factors vary between basins during winter and spring, except for altitude.

Implementation of the Natural Forest Protection Project and Grain for Green Programme in China has promoted forest restoration, increased productivity, and enhanced the carbon stocks. However, few studies have characterized temporal and spatial variation in productivity and ecological stability in planted and natural forests and evaluated the factors driving such variation. In this study, we used 1399 permanent forest plots to identify change patters in the productivity and temporal stability of above-ground biomass (AGB) and evaluated the factors driving these changes in planted and natural forests in Sichuan Province, China. The mean temporal stability of AGB was higher for natural forest than for planted forest from 1979 to 2017; While, the productivity of planted forest was higher. The stability decreased at a rate of -0.013 yr-1 in entire natural forest and -0.011 yr-1 in planted forests, and the productivity of natural forest decreased significantly over time, with a slope of -0.0065 Mg ha-1 yr-1 per calendar year. Altitude, latitude, annual precipitation, and stand age dominated variability in the productivity and AGB stability of natural forest. Richness, tree density, and stand age were the determinants of productivity and stability in planted forest. Our results suggest that selective thinning and enriching species richness and forest stand age can effectively balance the productivity and biomass temporal stability of planted forests. Older natural forests still need to be strictly protected under climate change.