Soil freeze-thaw state influences multiple terrestrial ecosystem processes, such as soil hydrology and carbon cycling. However, knowledge of historical long-term changes in the timing, duration, and temperature of freeze-thaw processes remains insufficient, and studies exploring the combined or individual contributions of climatic factors-such as air temperature, precipitation, snow depth, and wind speed-are rare, particularly in current thermokarst landscapes induced by abrupt permafrost thawing. Based on ERA5-Land reanalysis, MODIS observations, and integrated thermokarst landform maps, we found that: 1) Hourly soil temperature from the reanalysis effectively captured the temporal variations of in-situ observations, with Pearson' r of 0.66-0.91. 2) Despite an insignificant decrease in daily freeze-thaw cycles in 1981-2022, other indicators in the Qinghai-Tibet Plateau (QTP) changed significantly, including delayed freezing onset (0.113 d yr- 1), advanced thawing onset (-0.22 d yr- 1), reduced frozen days (-0.365 d yr- 1), increased frozen temperature (0.014 degrees C yr- 1), and decreased daily freeze-thaw temperature range (-0.015 degrees C yr- 1). 3) Total contributions indicated air temperature was the dominant climatic driver of these changes, while indicators characterizing daily freeze-thaw cycles were influenced mainly by the combined effects of increased precipitation and air temperature, with remarkable spatial heterogeneity. 4) When regionally averaged, completely thawed days increased faster in the thermokarstaffected areas than in their primarily distributed grasslands-alpine steppe (47.69%) and alpine meadow (22.64%)-likely because of their stronger warming effect of precipitation. Locally, paired comparison within 3 x 3 pixel windows from MODIS data revealed consistent results, which were pronounced when the thermokarst-affected area exceeded about 38% per 1 km2. Conclusively, the warming and wetting climate has significantly altered soil freeze-thaw processes on the QTP, with the frozen soil environment in thermokarstaffected areas, dominated by thermokarst lakes, undergoing more rapid degradation. These insights are crucial for predicting freeze-thaw dynamics and assessing their ecological impacts on alpine grasslands.

Study region: The Qinghai Lake basin, including China's largest saltwater lake, is located on the Qinghai-Tibetan Plateau (QTP). Study focus: This study focuses on the hydrological changes between the past (1971-2010) and future period (2021-2060) employing the distributed hydrological model in the Qinghai Lake basin. Lake evaporation, lake precipitation, and water level changes were estimated using the simulations driven by corrected GCM data. The impacts of various factors on the lake water levels were meticulously quantified. New hydrological insights: Relative to the historical period, air temperatures are projected to rise by 1.72 degrees C under SSP2-4.5 and by 2.21 degrees C under SSP5-8.5 scenarios, and the future annual precipitation will rise by 34.7 mm in SSP2-4.5 and 44.1 mm in SSP5-8.5 in the next four decades. The ground temperature is projected to show an evident rise in the future period, which thickens the active layer and reduces the frozen depth. The runoff into the lake is a pivotal determinant of future water level changes, especially the runoff from the permafrost degradation region and permafrost region dominates the future water level changes. There will be a continuous rapid increase of water level under SSP5-8.5, while the water level rising will slow down after 2045 in the SSP2-4.5 scenario. This study provides an enhanced comprehension of the climate change impact on QTP lakes.

Climate change impacts water supply dynamics in the Upper Rio Grande (URG) watersheds of the US Southwest, where declining snowpack and altered snowmelt patterns have been observed. While temperature and precipitation effects on streamflow often receive the primary focus, other hydroclimate variables may provide more specific insight into runoff processes, especially at regional scales and in mountainous terrain where snowpack is a dominant water storage. The study addresses the gap by examining the mechanisms of generating streamflow through multi-modal inferences, coupling the Bayesian Information Criterion (BIC) and Bayesian Model Averaging (BMA) techniques. We identified significant streamflow predictors, exploring their relative influences over time and space across the URG watersheds. Additionally, the study compared the BIC-BMA-based regression model with Random Forest Regression (RFR), an ensemble Machine Learning (RFML) model, and validated them against unseen data. The study analyzed seasonal and long-term changes in streamflow generation mechanisms and identified emergent variables that influence streamflow. Moreover, monthly time series simulations assessed the overall prediction accuracy of the models. We evaluated the significance of the predictor variables in the proposed model and used the Gini feature importance within RFML to understand better the factors driving the influences. Results revealed that the hydroclimate drivers of streamflow exhibited temporal and spatial variability with significant lag effects. The findings also highlighted the diminishing influence of snow parameters (i. e., snow cover, snow depth, snow albedo) on streamflow while increasing soil moisture influence, particularly in downstream areas moving towards upstream or elevated watersheds. The evolving dynamics of snowmelt-runoff hydrology in this mountainous environment suggest a potential shift in streamflow generation pathways. The study contributes to the broader effort to elucidate the complex interplay between hydroclimate variables and streamflow dynamics, aiding in informed water resource management decisions.

Permafrost degradation is one of the most significant consequences of climate change in the Arctic. During summers, permafrost degradation is evident with cryospheric hazards like retrogressive thaw slumps (RTSs) and active layer detachment slides (ALDs). In parallel, the Arctic has become a popular tourist destination for nature-based activities, with summer being the peak touristic season. In this context, cryospheric hazards pose potential risks for tourists' presence in Arctic national parks and wilderness in general, like in the Yukon. This essay provides the basis for investigating further periglacial, geomorphological and tourism intersections, highlighting the critical need for future interdisciplinary research on thawing permafrost impacts. More so, this requires moving beyond the predominant focus on permafrost impacts on infrastructure and to also consider the direct threats posed to human physical presence in Arctic tourist destinations affected by permafrost degradation. Such interdisciplinary approach is critical not only to mitigate risks, but also to provide policy- and decision-makers with valuable insights for implementing measures and guidelines.

Ongoing and widespread permafrost degradation potentially affects terrestrial ecosystems, whereas the changes in its effects on vegetation under climate change remain unclear. Here, we estimated the relative contribution of progressive active layer thickness (ALT) increases to vegetation gross primary productivity (GPP) in the northern permafrost region during the 21st century. Our results revealed that ALT changes accounted for 40% of the GPP increase in the permafrost region during 2000-2021, with amplified effects observed in late growing season (September-October) (43.2%-45.4%) and was especially notable in tundra ecosystems (51%-52.6%). However, projections indicated that this contribution could decrease considerably in the coming decades. Model simulations suggest that once ALT increments (relative to the 2001-2021 baseline) reach approximately 90 cm between 2035 and 2045, the promoting effect of ALT increase on vegetation growth may disappear. These findings provide crucial insights for accurately modelling and predicting ecosystem carbon dynamics in northern high latitudinal regions.

The Tibetan Plateau (TP) covers the largest regions under low- and mid-latitude permafrost. The evolution of permafrost has significantly affected the hydrology, biogeochemistry, and infrastructure of Asia. However, model reconstructions of long-term permafrost evolution with high accuracy and reliability are insufficient. Here, spatial changes in mean annual ground temperature at the depth where the annual amplitude is zero (MAGT) on the TP since 1981 were modeled and validated based on temperature records from 155 boreholes, and future changes were predicted under scenarios from the Climate Model Intercomparison Project 6 (CMIP6). The results indicated that the MAGT on the TP was approximately 1.5 degrees C (2010 - 2018), and the corresponding permafrost extent on the TP is estimated to be approximately 1.03 x 106 km2, which is projected to decrease to 0.77 x 106, 0.50 x 106, 0.30 x 106, and 0.17 x 106 km2 under the scenarios of shared socioeconomic pathway (SSP)126, SSP245, SSP370, and SSP585, respectively, by 2100. As predicted in the SSP585 scenario, permafrost is predicted to largely disappear from many basins of major Asian rivers, such as the Yarlung Zangpo-Brahmaputra, NuSalween, and Lancang-Mekong Rivers, between 2041 and 2060, followed by the Yellow and Yangtze Rivers between 2061 and 2080. Moreover, the original stable permafrost in the West Kunlun Mountains will change to transitional and unstable conditions. Our study offers comprehensive datasets of year-to-year ground temperatures and permafrost extent maps for the TP, which can serve as a fundamental resource for further investigations on the hydrogeology, engineering geology, ecology, and geochemistry of the TP.

Accurately understanding flood evolution and its attribution is crucial for watershed water resource management as well as disaster prevention and mitigation. The source region of the Yellow River (SRYR) has experienced several severe floods over the past few decades, but the driving factor influencing flood volume variation in the SRYR remains unclear. In this study, the Budyko framework was used to quantify the effects of climate change, vegetation growth, and permafrost degradation on flood volume variation in six basins of the SRYR. The results showed that the flood volume decreased before 2000 and increased after 2000, but the average value after 2000 remained lower than that before 2000. Flood volume is most sensitive to changes in precipitation, followed by changes in landscape in all basins. The decrease in flood volume was primarily influenced by changes in active layer thickness in permafrost-dominated basins, while it was mainly controlled by other landscape changes in non-permafrost-dominated basins. Meanwhile, the contributions of changes in potential evapotranspiration and water storage changes to the reduced flood volume were negative in all basins. Furthermore, the impact of vegetation growth on flood volume variation cannot be neglected due to its regulating role in the hydrological cycle. These findings can provide new insights into the evolution mechanism of floods in cryospheric basins and contribute to the development of strategies for flood control, disaster mitigation, and water resource management under a changing climate.

The Qinghai-Tibetan Plateau (QTP) has undergone significant warming, wetting, and greening (WWG) over decades, alongside substantial alterations in hydrological regimes. These changes present great challenges for safeguarding water resources and ecosystems downstream. However, the lack of field observation and systematic research has obscured our understanding of how hydrological processes respond to the combined influences of climate-permafrost-vegetation. This study focuses on the source regions of the Yangtze River, one of the highest permafrost-covered basins on the QTP, and employs a process-based hydrological model to quantify the effects of WWG on hydrological processes. We show that the increasing precipitation dominates subsurface runoff changes while rising temperature primarily affects surface runoff changes by reducing the frozen duration (-52 days/century) and thickening the active layer (+2.4 cm/year). Greening vegetation primarily affects transpiration and interception evaporation. Warming, wetting, and greening will cause a transition in runoff dynamics from surface runoff dominance to subsurface runoff dominance in permafrost basins, and reduce the risk of both flooding and water shortage indicated by the decreased maximum low flow duration and maximum high flow duration of 11.0 and 5.0 days/year, respectively. Moreover, cold permafrost regions exhibit a greater propensity for generating runoff, as indicated by a higher annual increase in runoff coefficient (0.005/year) and total runoff (4.81 mm/year), compared to warm permafrost regions (with increase of 0.001/year and 1.20 mm/year, respectively). These findings enhance the understanding of hydrological changes due to WWG and provide insights for water resources management in permafrost regions under climate change.

Snow cover variation significantly impacts alpine vegetation dynamics on the Tibetan Plateau (TP), yet this effect under climate change remains underexplored. This study uses a survival analysis model to assess the influence of snow on vegetation green-up dynamics, while controlling for key temperature and water availability factors. This analysis integrates multi-source data, including satellite-derived vegetation green-up dates (GUDs), snow depth, accumulated growing degree days (AGDD), downward shortwave radiation (SRAD), precipitation, and soil moisture. Our survival analysis model effectively simulated GUD on the TP, achieving an R of 0.62 (p < 0.01), a root mean square error (RMSE) of 11.20 days, and a bias of -1.41 days for 2020 GUD predictions. It outperformed both the model excluding snow depth and a linear regression model. By isolating snow's impact, we found it exerts a stronger influence on vegetation GUD than precipitation in snow-covered areas of the TP. Furthermore, snow depth effects varied seasonally: a 1-cm increase in preseason snow depth reduced green-up rates by 8.48% before 156(th) day but increased them by 4.74% afterward. This indicates that deeper preseason snow cover delays GUD before June, but advances it from June onward, rather than having a uniform effect. These findings highlight the critical role of snow and underscore the need to incorporate its distinct effects into vegetation phenology models in alpine regions.

The global climate is becoming warmer and wetter, and the physical properties of saline soil are easily affected by the external climate changes, which can lead to complex water-heat-salt-mechanics (WHSM) coupling effect within the soil. However, in the context of climate change, the current research on the surface energy balance process and laws of water and salt migration in saline soil are not well understood. Moreover, testing systems for studying the impact of external meteorological factors on the properties of saline soil are lacking. Therefore, this study developed a testing system that can simulate the environmental coupling effect of the WHSM in saline soil against a background of climate change. Based on meteorological data from the Hexi District in the seasonal permafrost region of China, the testing system was used to clarify the characteristics of surface energy and WHSM coupling changes in sulfate saline soil in Hexi District during the transition of the four seasons throughout the year. In addition, the reliability of the testing system was also verified using testing data. The results showed that the surface albedo of sulfate saline soil in the Hexi region was the highest in winter, with the highest exceeding 0.4. Owing to changes in the external environment, the heat flux in the sulfate saline soil in spring, summer, and early autumn was positive, while the heat flux in late autumn and winter was mainly negative. During the transition of the four seasons throughout the year in the Hexi region, the trends of soil temperature, volumetric water content, and conductivity were similar, first increasing and then decreasing. As the soil depth increased, the influence of external environmental factors on soil temperature, volumetric water content, and conductivity gradually weakened, and the hysteresis effect became more pronounced. Moreover, owing to the influence of external environmental temperature, salt expansion in the positive temperature stage accounts for approximately five times the salt-frost heave deformation in the negative temperature stage, indicating that the deformation of sulfate saline soil in the Hexi region is mainly caused by salt expansion. Therefore, to reduce the impact of external climate change on engineering buildings and agriculture in salted seasonal permafrost regions, appropriate measures and management methods should be adopted to minimize salt expansion and soil salinization.