With climate warming and intensification of human activities, the eco-environmental problems of lakes in middle and high latitudes become increasingly prominent. Qinghai Lake, located in the northeastern of the Tibetan Plateau, is the largest inland saltwater lake in China. Recently, the problem of Cladophora blooms has been widely concerning. In this study, the area of floating Cladophora blooms (hereafter FCBs) in Qinghai Lake from 1986 to 2021 was extracted using Floating Algal Index (FAI) method based on Landsat TM/ETM+/OLI and Sentinel-2 MSI images, and then the intra- and inter-annual variation characteristics and spatial patterns of FCBs were analyzed. The results show that the general change trend of FCBs in Qinghai Lake featured starting in May, expanding rapidly from June to August, and increasing steadily from September to October. From 1986 to 2021, the area of FCBs in Qinghai Lake showed an overall increasing trend in all months, with the largest increase in July at 0.1 km²/a, followed by October at 0.096 km²/a. Spatially speaking, the FCBs area showed a significant increasing trend in the northern Buha River estuary (BRN) and southern Buha River estuary (BRS) regions, a slight increase in the Shaliu River estuary (SR) region, and a decreasing trend in the Quanji River estuary (QR) region and the Heima River estuary (HR) region. The correlation between the meteorological factors and the changes in FCBs was weak, but the increase in flooded pastures in the BRN region (Bird Island) due to rising water levels was definitely responsible for the large-scale increase in FCBs in this region. However, the QB, northeastern bay of Shaliu River estuary (SRB) and HR regions, which also have extensive inundated grassland, did not have the same increase in FCBs area, suggesting that the growth of Cladophora is caused by multiple factors. The complex relationships need to be verified by further research. The current control measures have a certain inhibitory effect on the Cladophora bloom in Qinghai Lake because the FCBs area was significantly smaller in 2017–2020 (5.22 km², 3.32 km², 4.55 km² and 2.49 km²), when salvage work was performed, than in 2016 and 2021 (8.67 km² and 9.14 km²), when no salvage work was performed.

As a reliable indicator of regional climate change, the growth and decline of lake ice thickness affect the regional intra–annual heat and energy balance. In this study, a ground-penetrating radar (GPR) ice monitoring system, located approximately 1.7 km west of Bird Island in Qinghai Lake, in the territory of Qinghai Province and located in northwest China, was designed to carry out continuous fixed–point observations of local ice thickness and meteorological elements from 7 to 24 March 2021. The characteristics of continuous daily changes in ice thickness during the ablation period of Qinghai Lake and their relationship with meteorological elements were analyzed. The results showed that the average daily ice thickness of Qinghai Lake increased and then decreased during the observation period, with an average ice thickness of 42.83 cm, an average daily ice thickness range of 39.35~46.15 cm, and a growth rate of 0.54 cm/day during 8–13 March 2021, with an ice melting rate of −0.61 cm/day during 14–24 March 2021. The daily ice thickness variations were divided into two phases, which were relatively stable before dawn and followed a decreasing, increasing, and then decreasing trend during 8–13 March 2021 and a decreasing, increasing (for several hours), and then decreasing trend during 14–24 March 2021. There was a significant positive correlation (R = 0.745, p < 0.01) between near-surface air temperature and ice surface temperature during the observation period, but a significant negative correlation (R = −0.93, p < 0.05) between the average daily ice thickness and cumulative temperature of the ice surface. Temperature was the dominant factor affecting lake ice thickness, as compared to near-surface air humidity, wind speed, and illuminance. However, a sudden increase in wind speed have also played an important role at certain periods. A large number of cracks appeared on the ice surface on 26 March 2021, which, combined with the forces of wind speed, wind direction, and temperature, contributed to the rapid melt of the lake ice. This study filled the gap in situ measurement data on the continuous ice thickness variability during the ablation period in Qinghai Lake. It provided scientific support for the further study of lake ice on the Qinghai–Tibet Plateau (QTP).

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 intersection 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 0.05~0.07, which can be used for lake ice monitoring and long-term phenological studies in this region.

Ice thickness has a significant effect on the physical and biogeochemical processes of a lake, and it is an integral focus of research in the field of ice engineering. The Qinghai–Tibetan Plateau, known as the Third Pole of the world, contains numerous lakes. Compared with some information, such as the area, water level, and ice phenology of its lakes, the ice thickness of these lakes remains poorly understood. In this study, we used an unmanned aerial vehicle (UAV) with a 400/900 MHz ice-penetrating radar to detect the ice thickness of Qinghai Lake and Gahai Lake. Two observation fields were established on the western side of Qinghai Lake and Gahai Lake in January 2019 and January 2021, respectively. Based on the in situ ice thickness and the propagation time of the radar, the accuracy of the ice thickness measurements of these two non-freshwater lakes was comprehensively assessed. The results indicate that pre-processed echo images from the UAV-borne ice-penetrating radar identified non-freshwater lake ice, and we were thus able to accurately calculate the propagation time of radar waves through the ice. The average dielectric constants of Qinghai Lake and Gahai Lake were 4.3 and 4.6, respectively. This means that the speed of the radar waves that propagated through the ice of the non-freshwater lake was lower than that of the radio waves that propagated through the freshwater lake. The antenna frequency of the radar also had an impact on the accuracy of ice thickness modeling. The RMSEs were 0.034 m using the 400 MHz radar and 0.010 m using the 900 MHz radar. The radar with a higher antenna frequency was shown to provide greater accuracy in ice thickness monitoring, but the control of the UAV’s altitude and speed should be addressed.