Long-term, high-resolution soil moisture (SM) is a vital variable for understanding the water-energy cycle and the impacts of climate change on the Qinghai-Tibet Plateau (QTP). However, most existing satellite SM data are only available at coarse scale (+/- 25 km) and suffer a lot from data gaps due to satellite orbit coverage and snow cover, especially on the QTP. Although substantial efforts have been devoted to downscale SM utilizing multiple soil moisture indices (SMIs) or diverse machine learning (ML) methods, the potentials of different SMIs and ML approaches in SM downscaling on the complex plateau remain unclear, and there is still a necessity to obtain an accurate, long-term, high-resolution and seamless SM data over the QTP. To address this issue, this study generated the long-term, high-accuracy and seamless soil moisture dataset (LHS-SM) over the QTP during 2001-2020 using a two-step downscaling method (first downscaling then merging). Firstly, the daily SM data from the Climate Change Initiative program of the European Space Agency (ESA CCI) was downscaled to 1 km utilizing five ML approaches. Then, a dynamic data merging method that considers spatiotemporal nonstationary error was applied to derive the final LHS-SM data. The performance of fifteen SMIs was also assessed and the optimal indexes for downscaling were identified. Results indicated that the shortwave infrared band-based indices had better performance than the near infrared band-based and energy-based indices. The generated LHS-SM data exhibited satisfying accuracy (mean R = 0.52, ubRMSE = 0.047 m(3)/m(3)) and certain improvement to the ESA CCI SM data both at station and network scales. Compared with existing 1 km SM datasets, the LHS-SM data also showed the best performance (mean R = 0.62, ubRMSE = 0.047 m(3)/m(3)), while existing datasets either failed to fully characterize the spatial details or had some data gaps and unreasonable distributions. Strong spatial heterogeneity was observed in the SM dynamics during 2001-2020 with the southwest and northeast showing a dry gets wetter scheme and the southeast presenting a wet gets drier trend. Overall, the LHS-SM dataset gained its added values by compensating the drawbacks of existing 1 km SM products over the QTP and was much valuable for many regional applications.

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock-ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate-cryosphere-hydrology-hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze-thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole.

Global warming has led to extensive permafrost degradation, particularly in thermally vulnerablepermafrost in the marginal or transitional zones of altitudinal or latitudinal permafrost. However,comprehensive knowledge about microbial communities in response to rapid permafrostdegradation at large (or interregional) scales remains elusive. In this meta-analysis, existingpublished data were utilized to identify the distributive and co-occurrence patterns of themicrobiome in two interregional locations: the Qilian Mountains on the northeasternQinghai-Tibet Plateau(NE-QTP) and the Xing'anling Mountainsin Northeast China(NE-China).Both areas are situated in the marginal zone of large permafrost units. The results reveal that therapidly degrading permafrost did not overshadow the regional biogeographic pattern of themicrobial community. Instead, the results show some distinctive biogeographic patterns, ascharacterized by different groups of characteristic bacterial lineages in each of the two regions. SoilpH has emerged as a crucial controlling factor on the basis of the available environmental data.Network-basedanalysessuggestagenerallyhighlevelofnaturalconnectivityforbacterialnetworkson the NE-QTP; however, it collapses more drastically than that in NE-China if the environmentalperturbations exceed the tipping point. These findings indicate that the biogeographic patterns ofthe bacterial community structure are not significantly altered by permafrost degradation. Thisresearch provides valuable insights into the development of more effective management methodsfor microbiomes in rapidly degrading permafrost.

The Qinghai-Tibet Plateau (QTP), also often called the Third Pole, is considered the Asian Water Tower because it is the source of many major Asian rivers. The environmental change on the QTP can affect the climate system over the surrounding area, and the changes in glacier and river streamflow on the QTP will lead to cascading impacts in downstream area where billions of people live. This paper reviews the hydrological observations and streamflow changes of the major Asian rivers originating from the QTP. From the 1950s to the beginning of the 21st century, streamflow on the QTP overall shows large interannual variations but no significant trends. The monthly mean streamflows during the flooding seasons are the largest in the 1960s for the outlet stations on the QTP. Annual streamflow in the source region of the Yellow River decreased while that in the source region of the Yangtze River increased slightly. No significant trends of annual streamflow have been reported for the other river source regions. The mean streamflows during peak season are relatively large in the 2000s at the river source region (upper reaches) of most rivers on the QTP. An increasing trend of streamflow in spring has been found in the upper reaches of the Yellow River, the Lancang River, the Tuotuo River (of the Yangtze River), and the Lhasa River (of the Yarlung Zangbo River). The largest month of streamflow often appears in July for most stations, but in August at the Lhasa and Nuxia stations which are located in the Yarlung Zangbo River. Streamflow changes on the QTP could be mainly attributed to changes in snow and ice, as little influence from direct human activities were found. However, the examination of the streamflow changes largely relies on the hydrological observations. So far, due to data unavailability, we are still unclear about the long-term change in the streamflow on the QTP, especially the changes in recent years. The changes in ice and snow pack on the QTP could have significant impact on the downstream water resources and ecosystem. As more water resources have been generated from ice/snow melting, from a long-term perspective, water resources would be reduced along with shrinking and disappearing glaciers. Hydrological projections under future climate change suggest that streamflow in most river source regions would increase along with precipitation and increases in ice/snow melting, and hydrological extremes such as flooding would occur more frequently. Large uncertainties across Generic Circulation Models (GCMs) and hydrological models have been found in future projections of streamflow on the QTP. Reduction of ice/snow melting would aggravate the water stress conditions for both the ecosystem and human society on the QTP and its downstream areas. Sparse hydrometeorological observations in the past, particularly in the remote region of the QTP, are a major limiting factor to studies on streamflow change and its impacts. Further efforts are urgently needed to combine the advanced observation and modeling technologies to improve the observation and simulation capabilities of the water cycle over the QTP, and to provide scientific and technological support for coping with the accelerated ice/snow melting, increasing hydrological extremes and their impacts over the QTP.

Climate change has greatly influenced the permafrost regions on the Qinghai-Tibet Plateau (QTP). Most general circulation models (GCMs) project that global warming will continue and the amplitude will amplify during the twenty-first century. Climate change has caused extensive degradation of permafrost, including thickening of the active layer, rising of ground temperature, melting of ground ice, expansion of taliks, and disappearance of sporadic permafrost. The changes in the active layer thickness (ALT) greatly impact the energy balance of the land surface, hydrological cycle, ecosystems and engineering infrastructures in the cold regions. ALT is affected by climatic, geographic and geological factors. A model based on Kudryavtsev's formulas is used to study the potential changes of ALT in the permafrost regions on the QTP. Maps of ALT for the year 2049 and 2099 on the QTP are projected under GCM scenarios. Results indicate that ALT will increase with the rising air temperature. ALT may increase by 0.1-0.7 m for the year 2049 and 0.3-1.2 m for the year 2099. The average increment of ALT is 0.8 m with the largest increment of 1.2 m under the A1F1 scenario and 0.4 m with the largest increment of 0.6 m under the B1 scenario during the twenty-first century. ALT changes significantly in sporadic permafrost regions, while in the continuous permafrost regions of the inland plateau ALT change is relatively smaller. The largest increment of ALT occurs in the northeastern and southwestern plateaus under both scenarios because of higher ground temperatures and lower soil moisture content in these regions.