Groundwater recharge is poorly understood beneath the glacier due to the complex sampling conditions, although it is sensitive to the global change. Here we carried out the sampling and isotopic analysis on groundwater, ice‐melt water, river, and precipitation through a hydrological year at the lowest glacier of Mingyong in Hengduan Mountains, Southeastern Tibetan Plateau. The precipitation during the monsoon seasons (P_m) are more depleted in heavy isotopes than precipitation during the nonmonsoon seasons (P_nm) due to the influence of monsoon. The ice‐melt water and groundwater points are both found located left above the local meteoric water line (δ²H = 8.0δ¹⁸O + 8.0) and form lines of δ²H = 6.3δ¹⁸O – 10.0 and δ²H = 4.2δ¹⁸O – 37.6, respectively. However, their mean isotopic values are both larger than the weighted annual mean of precipitation isotopes. All of the phenomena above points to the occurring of refreezing process after excluding the evaporation process. A theoretical model is built to confirm the refreezing process that causes the lower slope of ice‐melt water line. The groundwater line is explained as a mixing line with ice‐melt water and precipitation with contributions of 46 ± 22% and 54 ± 22%, respectively. For the precipitation contribution, we propose a plausible conceptual model that groundwater comes primarily from P_nm (41 ± 17%), and minor from P_m (13 ± 17%). In this context, it is equivalent to 87 ± 28% groundwater recharged by P_nm because the glacier is mainly accumulated from P_nm. The findings highlight the importance of the P_nm recharging groundwater even in the monsoon‐affected glacial regions.

Daily precipitation samples were collected at four sites in Mount Yulong and Mount Meili regions of southeastern Tibetan Plateau and analyzed for isotopic composition. Combined with water vapor isotopic composition derived from satellites data (Infrared Atmospheric Sounding Interferometer, Tropospheric Emission Spectrometer, and Greenhouse gases Observing Satellite), the factors controlling the variability in the isotopic composition of precipitation are investigated at the synoptic, intraseasonal, and seasonal time scales. At the seasonal scale, the isotope composition in precipitation is controlled by processes along air mass trajectories affecting the water vapor at the large scale (>200 km), especially upstream deep convection and air mass origin, and by local processes transforming the large‐scale water vapor isotopic composition into the precipitation composition, especially rain evaporation and local circulation. At the intraseasonal and synoptic scales, the isotope composition in precipitation is mainly controlled by these local processes. The shorter the time scale of isotopic variations, the smaller the spatial imprint of these variations. The fact that different factors control the isotopic variability at different time scales calls for caution when applying relationships observed at these time scales to interpret isotopic variations at paleoclimatic time scales. While general circulation models successfully capture the isotopic variability and its controlling factors at the seasonal scale, it fails to simulate them at shorter time scales, because it fails to simulate the local processes.

Observing the isotopic evolution of snow meltwater helps in understanding the process of snow melting but remains a challenge to acquire in the field. In this study, we monitored the melting of two snowpacks near Baishui Glacier No. 1, a typical temperate glacier on the southeastern Tibetan Plateau. We employed a physically based isotope model (PBIM) to calculate the isotopic composition of meltwater draining from natural snowpacks. The initial condition of the PBIM was revised to account for natural conditions, i.e., the initial δ¹⁸O stratigraphy of snow layers before melting. Simulations revealed that the initial heterogeneity of δ¹⁸O in snow layers as well as ice‐liquid isotopic exchange were responsible for most variations of δ¹⁸O in snow meltwater, whereas new snow and wind drift could result in sudden changes of the isotopic composition of the meltwater. The fraction of ice involved in the isotopic exchange (f) was the most sensitive parameter for the model output. The initial δ¹⁸O in the snowpack is mirrored in meltwater in case of small f and is smoothed with a large exchange fraction f. The other unknown parameter of the PBIM is the dimensionless rate constant of isotopic exchange, which depends on water percolation and initial snow depth. The successful application of the PBIM in the field might not only be useful for understanding snow melting process but might also provide the possibility of predicting the isotopic composition of snow meltwater and improve the accuracy of hydrograph separation.