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Land use change and climate variability are two key factors impacting watershed hydrology, which is strongly related to the availability of water resources and the sustainability of local ecosystems. This study assessed separate and combined hydrological impacts of land use change and climate variability in the headwater region of a typical arid inland river basin, known as the Heihe River Basin, northwest China, in the recent past (1995-2014) and near future (2015-2024), by combining two land use models (i.e., Markov chain model and Dyna-CLUE) with a hydrological model (i.e., SWAT). The potential impacts in the near future were explored using projected land use patterns and hypothetical climate scenarios established on the basis of analyzing long-term climatic observations. Land use changes in the recent past are dominated by the expansion of grassland and a decrease in farmland; meanwhile the climate develops with a wetting and warming trend. Land use changes in this period induce slight reductions in surface runoff, groundwater discharge and streamflow whereas climate changes produce pronounced increases in them. The joint hydrological impacts are similar to those solely induced by climate changes. Spatially, both the effects of land use change and climate variability vary with the sub-basin. The influences of land use changes are more identifiable in some sub-basins, compared with the basin-wide impacts. In the near future, climate changes tend to affect the hydrological regimes much more prominently than land use changes, leading to significant increases in all hydrological components. Nevertheless, the role of land use change should not be overlooked, especially if the climate becomes drier in the future, as in this case it may magnify the hydrological responses.

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°C, 2.0 ± 0.3°C, and 2.6 ± 0.3°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. Plain Language Summary The Qinghai‐Tibet Plateau (QTP) contains the largest area of alpine permafrost on Earth. It has been observed that permafrost on the QTP has been substantially degraded due to drastic climate warming. Existing prediction studies have consistently concluded that QTP permafrost will degrade with climate warming, but there is no consensus on the extent of degradation. To date, there have been no studies employing land surface models to predict future changes in QTP permafrost based on the latest Coupled Model Intercomparison Project Phase 6 data. Here, based on climate outputs from multi‐model projections under the Shared Socioeconomic Pathways, we used a land surface model adapted to frozen ground modeling to simulate future changes in permafrost distribution and its thermal regimes on the QTP, and evaluated permafrost responses to various scenarios of future climate change. The results show that much of the QTP permafrost will degrade in the late 21st century, and the Three Rivers Source region is a key area of future permafrost degradation, where permafrost is most vulnerable and degradation will occur earliest. Our results will help improve understanding of future changes in QTP permafrost as the climate warms and provide scientific support for climate change adaptation policies and sustainable regional development. Key Points By 2100, permafrost area will shrink by 44 ± 4%, 59 ± 5%, and 71 ± 7% for SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5, respectively Permafrost in the Three Rivers Source region is the most vulnerable and begins to degrade the earliest Under SSP3‐7.0 and SSP5‐8.5, the surviving permafrost becomes unstable and is on the verge of disappearing by 2100

Plateau pikas, small mammals native to the Qinghai‐Tibet Plateau (QTP), create bare patches through burrowing. No previous assessment exists on their impact on permafrost. This study fills this gap by simulating hypothetical scenarios in the Three Rivers Headwaters Region of the QTP using the Noah‐MP model for the plant growing seasons during 2015–2018. Our findings reveal a significant increase in soil temperature in the active layer due to pika‐induced bare patches, particularly during July–August. The average temperature rise at 2.5 cm depth was 0.36°C in permafrost regions and 0.29°C in seasonally frozen ground regions during August. Minimal impact on unfrozen water content was observed, with a slight increase in deep soil layers in permafrost regions, and negligible in seasonally frozen areas. These findings underscore the previously unexplored influence of pika burrowing on permafrost temperature, suggesting a potential risk of accelerating permafrost degradation, especially in permafrost‐dominated regions. Plain Language Summary On the vast Qinghai‐Tibet Plateau (QTP), plateau pikas are actively excavating burrows, creating bare patches of exposed earth within the typical grassland landscape. These seemingly minor disturbances can have significant consequences, as they alter heat and water conditions within the underlying permafrost. However, a comprehensive understanding of how these pika‐made patches impact the permafrost remains elusive. To address this gap, our study employed a computer model and simulating scenarios with and without pika patches in the ecologically fragile Three Rivers Headwaters Region (TRHR) of the QTP. We found that the pika‐induced bare patches significantly raised permafrost temperatures, especially in the shallow soil layers. During August, the peak pika activity month, the average soil temperature at a depth of 2.5 cm increased by 0.36°C in permafrost zones and 0.29°C in seasonally frozen ground zones. While the patches had minimal impact on unfrozen water content in the active layer, the temperature rise in permafrost warrants future concern. Key Points Bare patches due to plateau pika burrowing warmed permafrost, particularly during peak activity months and in shallow soil layers Pika bare patches warmed permafrost and seasonally frozen ground by about 0.36°C–0.29°C, respectively, at a 2.5 cm depth in August Pika‐induced bare patches had negligible impact on the unfrozen water content in the active layer of permafrost

Data scarcity is a major obstacle for high-resolution mapping of permafrost on the Tibetan Plateau (TP). This study produces a new permafrost stability distribution map for the 2010s (2005–2015) derived from the predicted mean annual ground temperature (MAGT) at a depth of zero annual amplitude (10–25 m) by integrating remotely sensed freezing degree-days and thawing degree-days, snow cover days, leaf area index, soil bulk density, high-accuracy soil moisture data, and in situ MAGT measurements from 237 boreholes on the TP by using an ensemble learning method that employs a support vector regression model based on distance-blocked resampled training data with 200 repetitions. Validation of the new permafrost map indicates that it is probably the most accurate of all currently available maps. This map shows that the total area of permafrost on the TP, excluding glaciers and lakes, is approximately 115.02 (105.47–129.59)×10 4 km 2 . The areas corresponding to the very stable, stable, semi-stable, transitional, and unstable types are 0.86×10 4 , 9.62×10 4 , 38.45×10 4 , 42.29×10 4 , and 23.80×10 4 km 2 , respectively. This new map is of fundamental importance for engineering planning and design, ecosystem management, and evaluation of the permafrost change in the future on the TP as a baseline.

Vegetation lateral expansion into barren land is an understudied process of global greening, yet it is crucial for ecological safety and draws widely public attention. Using remote sensing data, we present for the first time a comprehensive assessment of vegetation expansion across the ecologically fragile Qinghai–Tibet Plateau. During 2002–2023, vegetation expanded across nearly 1/5 of the barren land, with a change rate (–3.89 to −4.95 × 10 4 km 2 /10a) comparable in magnitude to the regional glacier retreat and permafrost thaw. The upper limit shifted upslope (∼35 m), while the lower limit shifted downslope (∼150 m). This bidirectional expansion mode is associated with the alleviation of water limitation at lower elevations (due to wetting) and energy limitation at higher elevations (due to warming). Nevertheless, projections suggest this rapid downslope expansion may decelerate. The identified bidirectional pattern challenges the prevailing assumption of a uniform upslope shift in alpine vegetation under climate change.

Drought is a complex natural hazard which can have negative effects on agriculture, economy, and human life. In this paper, the primary goal is to explore the application of the Gravity Recovery and Climate Experiment (GRACE) gravity satellite data for the quantitative investigation of the recent drought dynamic over the arid land of northwestern China, a region with scarce hydrological and meteorological observation datasets. The spatiotemporal characteristics of terrestrial water storage changes (TWSC) were first evaluated based on the GRACE satellite data, and then validated against hydrological model simulations and precipitation data. A drought index, the total storage deficit index (TSDI), was derived on the basis of GRACE-recovered TWSC. The spatiotemporal distributions of drought events from 2003 to 2012 in the study region were obtained using the GRACE-derived TSDI. Results derived from TSDI time series indicated that, apart from four short-term (three months) drought events, the study region experienced a severe long-term drought from May 2008 to December 2009. As shown in the spatial distribution of TSDI-derived drought conditions, this long-term drought mainly concentrated in the northwestern area of the entire region, where the terrestrial water storage was in heavy deficit. These drought characteristics, which were detected by TSDI, were consistent with local news reports and other researchers’ results. Furthermore, a comparison between TSDI and Standardized Precipitation Index (SPI) implied that GRACE TSDI was a more reliable integrated drought indicator (monitoring agricultural and hydrological drought) in terms of considering total terrestrial water storages for large regions. The GRACE-derived TSDI can therefore be used to characterize and monitor large-scale droughts in the arid regions, being of special value for areas with scarce observations.

Permafrost over the Qinghai–Tibet Plateau (QTP) has received increasing attention due to its high sensitivity to climate change. Numerous spatial modeling studies have been conducted on the QTP to assess the status of permafrost, project future changes in permafrost, and diagnose contributors to permafrost degradation. Due to the scarcity of ground stations on the QTP, these modeling studies are often hampered by the lack of validation references, calibration targets, and model constraints; however, a high-quality permafrost distribution map would be a good option as a benchmark for spatial simulations. Existing permafrost distribution maps for the QTP can poorly serve this purpose. An ideal benchmark map for spatial modeling should be methodologically sound, of sufficient accuracy, and based on observations from mapping years rather than all historical data spanning several decades. Therefore, in this study, we created a new permafrost distribution map for the QTP in 2010 using a novel permafrost mapping approach with satellite-derived ground surface thawing and freezing indices as inputs and survey-based subregion permafrost maps as constraints. This approach accounted for the effects of local factors by incorporating (into the model) an empirical soil parameter whose values were optimally estimated through spatial clustering and parameter optimization constrained by survey-based subregion permafrost maps, and the approach was also improved to reduce parametric equifinality. This new map showed a total permafrost area of about 1.086×106 km2 (41.2 % of the QTP area) and seasonally frozen ground of about 1.447×106 km2 (54.9 %) in 2010, excluding glaciers and lakes. Validations using survey-based subregion permafrost maps (κ=0.74) and borehole records (overall accuracy =0.85 and κ=0.43) showed a higher accuracy of this map compared with two other recent maps. Inspection of regions with obvious distinctions between the maps affirms that the permafrost distribution on this map is more realistic than that on the Zou et al. (2017) map. Given the demonstrated excellent accuracy, this map can serve as a benchmark map for constraining/validating land surface simulations on the QTP and as a historical reference for projecting future permafrost changes on the QTP in the context of global warming. The dataset is available from the repository hosted on Figshare (Cao et al., 2022): https://doi.org/10.6084/m9.figshare.19642362.

Accurately modeling active layer dynamics on the warming and wetting Qinghai‐Tibet Plateau (QTP) is crucial for understanding local hydrological processes, ecosystem dynamics, and infrastructure integrity. However, land surface models (LSMs) are often limited by simplified representation of physical processes in frozen ground and by uncertain forcing data. We present a novel hybrid modeling approach that enables the use of the Simultaneous Heat and Water (SHAW) model, with its advanced representation of physical processes in frozen ground, in data‐sparse regions by generating robust lower boundary conditions from random forest‐corrected Noah LSM simulations. When evaluated at seven permafrost sites on the QTP, the hybrid approach significantly outperformed both the standalone Noah LSM and traditional SHAW configurations in simulating active layer temperature and moisture. For testing data, the hybrid approach achieved higher average Nash‐Sutcliffe efficiency values for soil temperature (ST) (0.81 vs. 0.69) and soil moisture (0.35 vs. 0.17) compared to the Noah LSM. Notably, the hybrid approach corrects key biases of the Noah LSM, which tends to overestimate ST and unfrozen water content during freezing periods. This study provides a robust framework for large‐scale simulation of permafrost dynamics in data‐sparse regions, with direct implications for assessing environment change, infrastructure risks, and carbon emissions linked to permafrost degradation.

Climate warming poses complex challenges for alpine ecosystems on the Qinghai–Tibetan Plateau (QTP), further exacerbated by permafrost degradation. Quantifying the specific ecological impacts of permafrost thaw remains elusive, as ecological variations are also influenced by external climate factors. This study tackles this gap by employing the Noah-MP model to simultaneously simulate permafrost thermal–hydrological dynamics and net primary production (NPP) across the Three River Headwaters Region from 1989 to 2018. Model results were validated against observations. To isolate the ecological effects of permafrost thaw, we implemented a novel relative time transformation on the simulation results. Our analysis reveals a 7.5 × 10 4 km 2 reduction in permafrost coverage during the study period, coinciding with a 1.09 g C m −2 yr −2 increase in NPP. While precipitation is the primary driver of NPP changes in most years, soil moisture emerges as a crucial factor during permafrost disappearance, when the ground transitions to seasonally frozen ground. Surprisingly, the NPP response to permafrost disappearance exhibited a transient effect, diminishing to negligible levels within five years post-thaw. These findings enhance our understanding of the intricate and dynamic responses of the QTP ecosystem to permafrost degradation under a warming climate.

Convective heat transfer (CHT) is one of the important processes that control the near-ground surface heat transfer in permafrost areas. However, this process has often not been considered in most permafrost studies, and its influence on freezing–thawing processes in the active layer lacks quantitative investigation. The Simultaneous Heat and Water (SHAW) model, one of the few land surface models in which the CHT process is well incorporated into the soil heat–mass transport processes, was applied in this study to investigate the impacts of CHT on the thermal dynamics of the active layer at the Tanggula station, a typical permafrost site on the eastern Qinghai–Tibet Plateau with abundant meteorological and soil temperature and soil moisture observation data. A control experiment was carried out to quantify the changes in active layer temperature affected by vertical advection of liquid water. Three experimental setups were used: (1) the original SHAW model with full consideration of CHT, (2) a modified SHAW model that ignores CHT due to infiltration from the surface, and (3) a modified SHAW model that completely ignores CHT processes in the system. The results show that the CHT events occurred mainly during thaw periods in melted shallow (0–0.2 m) and intermediate (0.4–1.3 m) soil depths, and their impacts on soil temperature at shallow depths were significantly greater during spring melting periods than summer. The impact was minimal during freeze periods and in deep soil layers. During thaw periods, temperatures at the shallow and intermediate soil depths simulated under the scenario considering CHT were on average about 0.9 and 0.4 ∘C higher, respectively, than under the scenarios ignoring CHT. The ending dates of the zero-curtain effect were substantially advanced when CHT was considered due to its heating effect. However, the opposite cooling effect was also present but not as frequently as heating due to upward liquid fluxes and thermal differences between soil layers. In some periods, the advection flow from the cold layer reduced the shallow and intermediate depth temperatures by an average of about −1.0 and −0.4 ∘C, respectively. The overall annual effect of CHT due to liquid flux is to increase soil temperature in the active layer and favor thawing of frozen ground at the study site.