As an important part of the cryosphere, lake ice is a sensitive indicator of climate change. Remote sensing technology can quickly and accurately monitor the process of its formation and decay, among which Moderate Resolution Imaging Spectroradiometer (MODIS) images are the most widely used data in the remote sensing monitoring of lake ice. The reasonable selection of monitoring methods is of great significance to grasp the dynamic process and response to climate change of lake ice. In this study, five commonly used remote sensing monitoring methods of lake ice based on MODIS MOD09GA data, including the single band threshold method (SBT), reflectance difference threshold method (RDT), normalized difference snow index method (NDSI), modified normalized difference snow index method (MNDSI) and lake ice index method (LII), were selected to compare their accuracies in extracting lake ice extent by combining them with four evaluation metrics of accuracy, precision, recall and mean inter over union (MIoU). In addition, the ability of the high-precision LII method for extracting long time series lake ice phenology and its applicability to multiple types of lakes were verified. The results showed that compared with the NDSI method, the other four methods more easily distinguished between lake ice and lake water by setting thresholds. The SBT method and the RDT method had better extraction effects in the freezing process and the melting process, respectively. Compared with the NDSI and MNDSI methods, the LII method showed a significant improvement in lake ice extraction over the entire freeze-thaw cycle, with the smallest mean monitoring error of 1.53% for the percentage of lake ice area in different periods. Meanwhile, the LII method can be used to determine long term lake ice phenology dates and had good performance in extracting lake ice for different types of lakes on the Qinghai-Tibet Plateau with the optimal threshold interval of 0.05 similar to 0.07, which can be used for lake ice monitoring and long-term phenological studies in this region.

Study region: The Qinghai Lake Basin, Qinghai-Tibetan Plateau. The Qinghai Lake is the largest inland saltwater lake in China. Study focus: Significant increase in runoff into the Qinghai Lake has been reported; however, the relationship between frozen soil changes and runoff remains poorly understood. This study investigated the temporal and spatial variations in frozen soil and associate effects on streamflow and soil moisture in the study region by a distributed eco-hydrological model. New hydrological insights: The results illustrate that the coverage of permafrost decreased by about 13% from 1971 to 2015, and permafrost degradation mainly occurred in the elevation interval of 3600-4200 m. The maximum frozen depth averaged in the seasonally frozen ground significantly decreased by 0.06 m/10a, while the active layer thickness averaged in the permafrost enhanced by 0.02 m/10a. Permafrost degradation caused enhanced soil liquid water storage and an increase in freezing season runoff. The increase in runoff in the thawing season was dominated by changes in precipitation. The results suggest that frozen soil degradation altered the seasonal flow regime, leading to lags in the monthly runoff peak, and it increased the base flow and reduced the thawing season runoff. This offset of the competing impacts of frozen soil changes in different seasons led to a negative effect on annual runoff. This study provides new understandings of cryospheric hydrological responses to climate change.

The lake ice phenology variations are vital for the land-surface-water cycle. Qinghai Lake is experiencing amplified warming under climate change. Based on the MODIS imagery, the spatio-temporal dynamics of the ice phenology of Qinghai Lake were analyzed using machine learning during the 2000/2001 to 2019/2020 ice season, and cloud gap-filling procedures were applied to reconstruct the result. The results showed that the overall accuracy of the water-ice classification by random forest and cloud gap-filling procedures was 98.36% and 92.56%, respectively. The annual spatial distribution of the freeze-up and break-up dates ranged primarily from DOY 330 to 397 and from DOY 70 to 116. Meanwhile, the decrease rates of freeze-up duration (DFU), full ice cover duration (DFI), and ice cover duration (DI) were 0.37, 0.34, and 0.13 days/yr., respectively, and the duration was shortened by 7.4, 6.8, and 2.6 days over the past 20 years. The increased rate of break-up duration (DBU) was 0.58 days/yr. and the duration was lengthened by 11.6 days. Furthermore, the increase in temperature resulted in an increase in precipitation after two years; the increase in precipitation resulted in the increase in DBU and decrease in DFU in corresponding years, and decreased DI and DFI after one year.