Winter baseflow (WB) can stabilize freshwater inputs and has important impacts on nutrient migration and the water cycle of a specific region and the oceans. This study systematically analyzed the WB variations in fourteen major Eurasian rivers and found they all had commonly increasing trends (except the Yellow River), with the mean increase ratio of 53.0% (+/- 34.8%, confidence interval 95%) over the past 100 years (the longest time series is 1879-2015). Relative to Northern Eurasia (60 degrees N-70 degrees N) and Southern Eurasia (30 degrees N-40 degrees N), the river WB in middle Eurasia (40 degrees N-60 degrees N) had the largest increase rate (0.60%/year). The increases of the WB in Northern Eurasia and Southern Eurasia have speeded up since the 1990s; on the contrary, they have slowed down or even turned to a decreasing trend after the 1990s in the middle Eurasian rivers. Using multiple linear regression analysis, the quantitative relationship between WB and winter surface air temperature (max, mean and min), snowfall, soil temperature, antecedent precipitation, as well as the river-ice dynamic were determined. We found that the winter air temperature, especially the minimum air temperature was one major factor accounting for WB variation in Eurasia over the past century. When the winter air temperature rises, this leads a reduction in the thickness and volume of river ice, and thus decreases water storage in river ice and leads to an increase in the WB. About 19.6% (6.7%-41.5%) of the winter WB increase in rivers of Siberia was caused by the decreased river ice during the past 100 years. Although groundwater recharge was the dominant reason for WB change, the role of river ice should not be ignored in hydrological study of cold regions.

Water temperature extremes can pose serious threats to the aquatic ecosystems of mountain rivers. These rivers are influenced by snow and glaciermelt, which change with climate. As a result, the frequency and severity of water temperature extremes may change. While previous studies have documented changes in non-extreme water temperature, it is yet unclear how extreme water temperatures change in a warming climate and how their hydro-meteorological drivers differ from those of non-extremes. This study aims to assess temporal changes and spatial variability in water temperature extremes and enhance our understanding of the driving processes across European mountain rivers in the current climate, at both a regional and continental scale. First, we describe the characteristics of extreme events and explore their relationships with catchment characteristics. Second, we assess trends in water temperature extremes and compare them with trends in mean water temperature. Third, we use random forest models to identify the main driving processes of water temperature extremes. Last, we conduct a co-occurrence analysis to examine the relationship between water temperature extremes and hydro-climatic extremes. Our results show that mean water temperature has increased by +0.38 +/- 0.14 ${+}0.38\pm 0.14$degrees C per decade, leading to more extreme events at high elevations in spring and summer. While non-extreme water temperatures are mainly driven by air temperature, water temperature extremes are also importantly influenced by soil moisture, baseflow, and meltwater. Our study highlights the complexity of water temperature dynamics in mountain rivers at the regional and continental scale, especially during water temperature extremes.

Investigation of mercury (Hg) from atmospheric precipitation is important for evaluating its ecological impacts and developing mitigation strategies. Western China, which includes the Tibetan Plateau and the Xinjiang Uyghur Autonomous Region, is one of the most remote region in the world and is understudied in regards to Hg precipitation. Here we report seesaw-like patterns in spatial variations of precipitation Hg in Western China, based on Hg speciation measurements at nine stations over this remote region. The Hg fraction analyzed included total Hg (HgT), particulate-bound Hg (HgP) and methylmercury (MeHg). Spatially, HgT concentrations and percentage of HgP in precipitation were markedly greater in the westerlies domain than those in the monsoon domain, but the higher wet HgT flux, MeHg concentration and percentage of MeHg in precipitation mainly occurred in the monsoon domain. Similar spatial patterns of wet Hg deposition were also obtained from GEOSChem modeling. We show that the disparity of anthropogenic and natural drivers between the two domains are mainly responsible for this seesaw-like spatial patterns of precipitation Hg in Western China. Our study may provide a baseline for assessment of environmental Hg pollution in Western China, and subsequently assist in protecting this remote alpine ecosystem.

Soil water content (SWC) and soil temperature (ST) are important indicators of environmental change in permafrost regions. In this study, we conducted soil sampling at 89 locations in the Three Rivers Headwaters Region (TRHR) to investigate the individual and synergistic effects of environmental factors on SWC and ST. We used multivariable regression and random forest modelling to analyse the data. The results show that SWC and ST were higher in the southeast TRHR than in the northwest and higher in surface layers than deeper soil layers. The most important factors affecting SWC in the 0-20 cm and 20-40 cm soil layers were soil bulk density and precipitation, while bulk density was the most important factor in the 40-60 cm layer, and soil bulk density and steppe vegetation were the most important factors in the 60-80 cm layer. For ST, altitude, temperature and slope gradient were the drivers in the 0-20 cm surface layer, while altitude and temperature were the most critical drivers in the 20-40 cm, 40-60 cm and 60-80 cm layers. Overall, bulk density and altitude were the key environmental factors influencing SWC and ST values, respectively. The outcomes of this study provide valuable insights into the environmental factors that impact the SWC and ST in permafrost regions, which can guide decision-making processes for sustainable soil management in the context of climate change.

While the sentinel nature of freshwater systems is now well recognized, widespread integration of freshwater processes and patterns into our understanding of broader climate-driven Arctic terrestrial ecosystem change has been slow. We review the current understanding across Arctic freshwater systems of key sentinel responses to climate, which are attributes of these systems with demonstrated and sensitive responses to climate forcing. These include ice regimes, temperature and thermal structure, river baseflow, lake area and water level, permafrost-derived dissolved ions and nutrients, carbon mobilization (dissolved organic carbon, greenhouse gases, and radiocarbon), dissolved oxygen concentrations, lake trophic state, various aquatic organisms and their traits, and invasive species. For each sentinel, our objectives are to clarify linkages to climate, describe key insights already gained, and provide suggestions for future research based on current knowledge gaps. We suggest that tracking key responses in Arctic freshwater systems will expand understanding of the breadth and depth of climate-driven Arctic ecosystem changes, provide early indicators of looming, broader changes across the landscape, and improve protection of freshwater biodiversity and resources.

Arctic rivers provide an integrated signature of the changing landscape and transmit signals of change to the ocean. Here, we use a decade of particulate organic matter (POM) compositional data to deconvolute multiple allochthonous and autochthonous pan-Arctic and watershed-specific sources. Constraints from carbon-to-nitrogen ratios (C:N), delta C-13, and Delta C-14 signatures reveal a large, hitherto overlooked contribution from aquatic biomass. Separation in Delta C-14 age is enhanced by splitting soil sources into shallow and deep pools (mean +/- SD: -228 +/- 211 vs. - 492 +/- 173%) rather than traditional active layer and permafrost pools (-300 +/- 236 vs. -441 +/- 215%) that do not represent permafrost-free Arctic regions. We estimate that 39 to 60% (5 to 95% credible interval) of the annual pan-Arctic POM flux (averaging 4,391 Gg/y particulate organic carbon from 2012 to 2019) comes from aquatic biomass. The remainder is sourced from yedoma, deep soils, shallow soils, petrogenic inputs, and fresh terrestrial production. Climate change-induced warming and increasing CO2 concentrations may enhance both soil destabilization and Arctic river aquatic biomass production, increasing fluxes of POM to the ocean. Younger, autochthonous, and older soil-derived POM likely have different destinies (preferential microbial uptake and processing vs. significant sediment burial, respectively). A small (similar to 7%) increase in aquatic biomass POM flux with warming would be equivalent to a similar to 30% increase in deep soil POM flux. There is a clear need to better quantify how the balance of endmember fluxes may shift with different ramifications for different endmembers and how this will impact the Arctic system.

Arctic hydrology is experiencing rapid changes including earlier snow melt, permafrost degradation, increasing active layer depth, and reduced river ice, all of which are expected to lead to changes in stream flow regimes. Recently, long-term (>60 years) climate reanalysis and river discharge observation data have become available. We utilized these data to assess long-term changes in discharge and their hydroclimatic drivers. River discharge during the cold season (October-April) increased by 10% per decade. The most widespread discharge increase occurred in April (15% per decade), the month of ice break-up for the majority of basins. In October, when river ice formation generally begins, average monthly discharge increased by 7% per decade. Long-term air temperature increases in October and April increased the number of days above freezing (+1.1 d per decade) resulting in increased snow ablation (20% per decade) and decreased snow water equivalent (-12% per decade). Compared to the historical period (1960-1989), mean April and October air temperature in the recent period (1990-2019) have greater correlation with monthly discharge from 0.33 to 0.68 and 0.0-0.48, respectively. This indicates that the recent increases in air temperature are directly related to these discharge changes. Ubiquitous increases in cold and shoulder-season discharge demonstrate the scale at which hydrologic and biogeochemical fluxes are being altered in the Arctic.

Accurate information on snow cover extent plays a crucial role in understanding regional and global climate change, as well as the water cycle, and supports the sustainable development of socioeconomic systems. Remote sensing technology is a vital tool for monitoring snow cover' extent, but accurate identification of shallow snow cover on the Tibetan Plateau has remained challenging. Focusing on the Three-Rivers Headwater Region (THR), this study addressed this issue by developing a snow cover discrimination model (SCDM) using a random forests (RF) algorithm. Using daily observed snow depth (SD) data from 15 stations in the THR during the period 2001-2013, a comprehensive analysis was conducted, considering various factors influencing regional snow cover distribution, such as land surface reflectance, land surface temperature (LST), Normalized Difference Snow Index (NDSI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Forest Snow Index (NDFSI). The key results were as follows: (1) Optimal model performance was achieved with the parameters Ntree, Mtry, and ratio set to 1000, 2, and 19, respectively. The SCDM outperformed other snow cover products in both pixel-scale and local spatial-scale discrimination. (2) Spectral information of snow cover proved to be the most influential auxiliary variable in discrimination, and the combined inclusion of NDVI and LST improved model performance. (3) The SCDM achieved accuracy of 99.04% for thick snow cover (SD > 4 cm) and 98.54% for shallow snow cover (SD <= 4 cm), significantly (p < 0.01) surpassing the traditional dynamic threshold method. This study can offer valuable reference for monitoring snow cover dynamics in regions with limited data availability.

Rapid climate warming across northern high latitudes is leading to permafrost thaw and ecosystem carbon release while simultaneously impacting other biogeochemical cycles including nitrogen. We used a two-year laboratory incubation study to quantify concomitant changes in carbon and nitrogen pool quantity and quality as drivers of potential CO2 production in thawed permafrost soils from eight soil cores collected across the southern Northwest Territories (NWT), Canada. These data were contextualized via in situ annual thaw depth measurements from 2015 to 2019 at 40 study sites that varied in burn history. We found with increasing time since experimental thaw the dissolved carbon and nitrogen pool quality significantly declined, indicating sustained microbial processing and selective immobilization across both pools. Piecewise structural equation modeling revealed CO2 trends were predominantly predicted by initial soil carbon content with minimal influence of dissolved phase carbon. Using these results, we provide a first-order estimate of potential near-surface permafrost soil losses of up to 80 g C m(-2) over one year in southern NWT, exceeding regional historic mean primary productivity rates in some areas. Taken together, this research provides mechanistic knowledge needed to further constrain the permafrost-carbon feedback and parameterize system models, while building on empirical evidence that permafrost soils arc at high risk of becoming weaker carbon sinks or even significant carbon sources under a changing climate.

Global warming has led to permafrost degradation worldwide. The Qinghai-Tibet Plateau (QTP) hosts most of the world's alpine permafrost, yet its impending changes remain largely unclear, thereby affecting regional hydrological and ecological processes and the global carbon budget. By employing a land surface model adapted to simulate frozen ground, and using state-of-the-art multi-model and multi-scenario data from the Coupled Model Intercomparison Project Phase 6, changes in permafrost distribution and its thermal regimes on the QTP are systematically predicted under various shared socioeconomic pathways (SSPs). Projections for SSP2-4.5, SSP3-7.0, and SSP5-8.5 show that most of the continuous permafrost region of the QTP will persist through 2050. Much of the permafrost is likely to degrade in the late 21st century, with projected area losses of 44 +/- 4%, 59 +/- 5%, and 71 +/- 7%, respectively, by 2100. In particular, the Three Rivers Source region in the central eastern part of the QTP is a key area of permafrost degradation, where permafrost is most vulnerable and degradation occurs earliest. The mean annual ground temperature of QTP permafrost will increase by 0.8 +/- 0.2 degrees C, 2.0 +/- 0.3 degrees C, and 2.6 +/- 0.3 degrees C under SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively, and the active layer thickness will increase by 0.7 +/- 0.1 m, 1.5 +/- 0.3 m, and 3.0 +/- 1.0 m, respectively. The surviving permafrost under SSP3-7.0 and SSP5-8.5 will be thermally unstable, which is a clear warning sign of complete disappearance. The analysis of permafrost sensitivity to climate change signifies that alpine permafrost on the QTP has low resilience to climate change, in contrast to permafrost in pan-Artic high latitudes.