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Permafrost plays an important role in hydrological processes of alpine regions. The frost table in the active layer on the permafrost acts as an impermeable boundary and regulates water generation from hillslopes and its routing to streams. Past studies focused on modes or critical conditions of flow generation, rather than on the capacity of the active layer on the permafrost to recharge flow. This study aimed to characterize the role of supra-permafrost groundwater in the generation of runoff on hillslopes during the active layer thawing processes. The study focused on an alpine meadow permafrost hillslope located in the northeastern Tibet Plateau during the months of July and August in both 2021 and 2022. Hydrometeorological variables, including precipitation, air temperature, soil temperature, soil moisture, thaw depths, supra-permafrost groundwater level, and runoff generation were monitored in field. Partial Least Squares Path Modeling was selected to analyze the relations between the above variables. The results showed that infiltrated rainwater tended to move into deep thawed soil, following which the frozen layer forced horizontal transport along the hillslope. This indicated that thaw depths along the soil profile regulated the dominant runoff path. The accumulated precipitation of the previous days had a significant impact on runoff generation. There was minimal lateral subsurface flow when the saturated zone was absent, whereas lateral subsurface flow increased with increasing thickness of the saturated zone. Runoff generation on the hillslope was regulated by both thaw depths and the thickness of the saturated zone along the soil profile. This study can act as a reference for runoff generation processes of permafrost hillslopes.

Svalbards permafrost is thawing as a direct consequence of climate change. In the Low Arctic, vegetation has been shown to slow down and reduce the active layer thaw, yet it is unknown whether this also applies to High Arctic regions like Svalbard where vegetation is smaller, sparser, and thus likely less able to insulate the soil. Therefore, it remains unknown which components of High Arctic vegetation impact active layer thaw and at which temporal scale this insulation could be effective. Such knowledge is necessary to predict and understand future changes in active layer in a changing Arctic. In this study we used frost tubes placed in study grids located in Svalbard with known vegetation composition, to monitor the progression of active layer thaw and analyze the relationship between vegetation composition, vegetation structure and snow conditions, and active layer thaw early in summer. We found that moss thickness, shrub and forb height, and vascular vegetation cover delayed soil thaw immediately after snow melt. These insulating effects attenuated as thaw progressed, until no effect on thaw depth was present after 8 weeks. High Arctic mosses are expected to decline due to climate change, which could lead to a loss in insulating capacity, potentially accelerating early summer active layer thaw. This may have important repercussions for a wide range of ecosystem functions such as plant phenology and decomposition processes. Plain Language Summary: Temperatures are rising in the Arctic, causing increased thaw of the layer of soil located above the permanently frozen ground. In Low Arctic regions vegetation cools the soil, which reduces the thawing. So far, we do not know whether the small plants growing in the High Arctic may be able to slow or reduce thaw. We measured soil thaw throughout the summer in High Arctic Svalbard in locations where vegetation composition is known. We also measured thickness of the moss layer, height of plants and snow depth. We found that moss thickness was the strongest factor in insulating the soil. Also the cover of plants, height of shrubs and forbs, and height of grass‐like plants slowed soil thaw in the early summer. The insulating effects became less over time and no effects were found 8 weeks after onset of thaw. As climate change is causing changes in the Arctic vegetation, mosses and small shrubs are expected to decrease. As we found these to be the most important factors in insulating the soil, a future decrease in mosses and small shrubs may cause accelerated soil thaw at the start of summer. Key Points: High Arctic vegetation slows active layer thaw in early summer after snow meltMosses show a stronger negative relation with thaw depth than vascular vegetationFactors influencing active layer thaw change over time in early summer [ABSTRACT FROM AUTHOR]

Intraspecific trait variation can influence plant performance in different environments and may thereby determine the ability of individual plants to respond to climate change. However, our understanding of its patterns and environmental drivers across different spatial scales is incomplete, especially in understudied regions like the Arctic.To fill this knowledge gap, we examined above‐ground and below‐ground traits from three shrub taxa expanding across the tundra biome and evaluated their relationships with multiple microenvironmental and macroclimatic factors. The traits reflected plant size and structure (plant height, leaf area and root to shoot ratio), leaf economics (specific leaf area, nitrogen content), and root economics and collaboration with mycorrhizal fungi (specific root length, root tissue density, nitrogen content, and ectomycorrhizal colonisation intensity). We also measured leaf and root δ15N and leaf δ13C to characterise nitrogen source and acquisition pathways and plant water stress. Traits were measured in replicated plots (N = 135) varying in soil microclimate, thaw depth and organic layer thickness established across five sites spanning a macroclimate gradient in northern Alaska. This hierarchical design allowed us to disentangle the independent and combined effects of fine‐scale and broad‐scale factors on intraspecific trait variation.We found substantial intraspecific variation at fine spatial scales for most traits and less variation along the macroclimate gradient and between shrub taxa. Consistent with these patterns, microenvironmental factors, mainly soil moisture and thaw depth, interacted with macroclimate, mainly climatic water deficit, to structure size‐structural and leaf trait variation. In contrast, most root traits responded additively to thaw depth and macroclimate.Synthesis. Our results demonstrate that above‐ground and below‐ground tundra shrub traits respond differently to microenvironmental and macroclimatic variation. These differing responses contribute to substantial trait variation at fine spatial scales and may decouple above‐ground and below‐ground trait responses to climate change. [ABSTRACT FROM AUTHOR]

In regions characterized by continuous permafrost, hydrological modeling remains a complex activity, primarily due to constraints related to the prevailing climatic conditions and the specific behavior of the active layer. High-latitude regions receive less solar radiation; thus, most creeks are active only during summertime and stay frozen in the winter. To realistically simulate watersheds underlain by continuous permafrost, the heat transfer through the soil needs to be accounted for in the modeling process. In this study, a watershed located in a continuous permafrost zone in Russia is investigated. A model is proposed to integrate this heat transfer into an existing conceptual rain-flow transformation model, Hydrologiska Byråns Vattenbalansavdelning (HBV), to calculate the seasonal thaw depth and determine the components of water balance. The proposed integration is a novelty compared to the standard model, as it enables the physical and thermal properties of the soil to be taken into account. It was found that the proposed model, HBV-Heat, performs better than the stand-alone HBV model. Specifically, the average Nash–Sutcliffe efficiency (NSE) increases by 30% for the whole calibration period. In terms of the water balance components, the results are consistent with previous studies, showing that surface runoff represents 64% of the observed precipitation. [ABSTRACT FROM AUTHOR]

A simple stochastic representation of the spatial variability in thaw depth is proposed. Thaw depth distribution measured in the two larch‐type forests in eastern Siberia, Spasskaya Pad and Elgeeii, showed different spatial, seasonal, and interannual variability, respectively. Year‐to‐year variation in active‐layer thickness was minor in Spasskaya Pad compared to Elgeeii. A gamma distribution adequately represented both sites' thaw depth spatial variability as the cumulative probability. Thus, we developed a simple model using the gamma distribution that illustrates the spatial variability in thaw depth at any thawing stage as a function of a given mean thaw depth. A hierarchy of models was introduced that sequentially considered the constant state, linearity, and nonlinearity in the dependence of the rate parameter of the gamma distribution on the mean thaw depth. Although the requirements of the model levels differed between Spasskaya Pad and Elgeeii, the proposed model successfully represented the spatial variability in thaw depth at both sites during different thaw seasons. [ABSTRACT FROM AUTHOR]

Surface conditions are known to mediate the impacts of climate warming on permafrost. This calls for a better understanding of the environmental conditions that control the thermal regime and the depth of the active layer, especially within heterogeneous tundra landscapes. This study analyzed the spatial relationships between thaw depths, ground surface temperature (GST), and environmental conditions in a High Arctic tundra environment at Bylot Island, Nunavut, Canada. Measurements were distributed within the two dominant landforms, namely earth hummocks and low‐center polygons, and across a topographic gradient. Our results revealed that GST and thaw depth were highly heterogeneous, varying by up to 3.7°C and by more than 20 cm over short distances (<1 m) within periglacial landforms. This microscale variability sometimes surpassed the variability at the hillslope scale, especially in summer. Late‐winter snowpack thickness was found to be the prime control on the spatial variability in winter soil temperatures due to the highly heterogeneous snow cover induced by blowing snow, and this thermal effect carried over into summer. However, microtopography was the predominant driver of the spatial variability in summer GST, followed by altitude and moss thickness. In contrast, the spatial variability in thaw depth was influenced predominantly by variations in moss thickness. Hence, summer microclimate conditions dominated active layer development, but a thicker snowpack favored soil cooling in the following summer, due to the later disappearance of snow cover. These results enhance our understanding of High Arctic tundra environments and highlight the complexity of considering surface feedback effects in future projections of permafrost states within heterogeneous tundra landscapes. [ABSTRACT FROM AUTHOR]

Arctic warming causes permafrost thaw and accelerates microbial decomposition of soil organic matter (SOM) to carbon dioxide (CO2) and methane (CH4). The determining factors for the ratio between CO2 and CH4 formation are still not well understood due to scarce in situ measurements, particularly in remote Arctic regions. We quantified the CO2:CH4 ratios of SOM decomposition in wet and dry tundra soils by using CO2 fluxes from clipped plots and in situ CH4 fluxes from vegetated plots. At the water‐saturated site, CO2:CH4 ratios decreased sharply from 95 at beginning of July to about 10 in August and September with a median of 12.2 (7.70–17.1; 25%–75% quartiles) over the whole vegetation period. When considering CH4 oxidation, estimated to reduce in situ CH4 fluxes by 10%–31%, even lower CO2:CH4 ratios were calculated (median 10.9–8.41). Active layer depth and soil temperature were the main factors controlling these ratios. Methane production was associated with subsoil (40 cm) temperature, while heterotrophic respiration was related to topsoil (5 cm) temperatures. As expected, CO2:CH4 ratios were substantially higher at the dry site (median 373, 292–500, 25%–75% quartiles). Both tundra types lost carbon preferentially in form of CO2, and CH4‐C represented only 0.27% of the dry tundra total carbon loss and 6.91% of the wet tundra total carbon loss. The current study demonstrates the dynamic of in situ CO2:CH4 ratios from SOM decomposition and will help improve simulations of future CO2 and CH4 fluxes from thawing tundra soils. Plain Language Summary: Global warming causes the thaw of the permanently frozen soil in Arctic regions, exposing soil organic matter (SOM) previously frozen to decomposition, increasing the emission of carbon dioxide (CO2) and methane (CH4), which are greenhouse gases. It is crucial to quantify the ratio of CO2 and CH4 produced because CH4 has a stronger global warming potential than CO2. We partitioned SOM decomposition into CO2 and CH4 formation (CO2:CH4 ratios) in wet and dry tundra soils on Samoylov Island, Northeastern Siberia, and we related these ratios to environmental variables. Deeper active layer, which is the topsoil layer that freezes and thaws annually, and higher subsoil (40 cm) temperature at the interface between the active layer and the permafrost, foster CH4 production and decrease CO2:CH4 ratios. Carbon was preferentially lost in form of CO2 by the soils, but CH4 had a larger contribution to the carbon loss in the wet tundra. Our study indicates that warming and deepening of the active layer can result in rising CH4 production. Further understanding of in situ CO2:CH4 ratios from SOM decomposition will help improve simulations on future CO2 and CH4 fluxes from thawing tundra soils. Key Points: Topsoil (5 cm) warming increases the CO2:CH4 production ratio, while warming of subsoil (40 cm) leads to lower CO2:CH4 production ratiosThe CO2:CH4 production ratio is associated with active‐layer depth (ALD) due to a direct effect of ALD on CH4 productionCarbon was preferentially lost in form of CO2 at wet and dry sites, but CH4 had a higher contribution at the wet tundra site [ABSTRACT FROM AUTHOR]

The present paper proposes an iterative implicit numerical method for simulating the thaw depth of permafrost soil. For this purpose, the enthalpy-porosity model was used for the phase change process, and the finite difference scheme FTCS (Forward Time Centered Space) was used for discretization. An artificial mushy zone was maintained with the same thickness by keeping the regularization parameter proportional to the temperature gradient. In doing so, we made the scheme more stable and convergence occurred faster. The model accuracy was validated by comparing the numerical results with the analytical Stefan solution and with the results of a derived numerical model, based on an explicit scheme. The model performance was also tested against observation data collected on four different landscapes with different soil profiles and located on a basin underlain by continuous permafrost. It was found that the proposed model matched noticeably well the analytical solution for a volumetric liquid fraction (phi) equal to 0.5 regardless of the grid resolution. Furthermore, compared with the observation data, the model reproduced the annual maximum thaw depth with an absolute error lying between 0.7 and 7.7%. In addition, the designed algorithm allowed the model to converge after a maximum of eight iterations, reducing the computational time by around 75% compared to the explicit model. The results were so encouraging that the model can be included in a hydrological modeling of permafrost watersheds or cold regions in general. [ABSTRACT FROM AUTHOR]

The expected thaw depth of the foundation soil is one of the parameters influencing the selection of technical solutions of road design in the permafrost area. The purpose of this research is a quantitative assessment of the degree of influence of air temperature on thaw depth of the road foundation soil in the permafrost area. A standard formula to calculate thaw depth of melting bodies of flat symmetry obtained through a solution of the one phase Stefan problem at boundary conditions of the first kind was used for the analysis. An algorithm using an analytical formula to assess the influence of the main initial parameters and accuracy of their determination on the resulting value, the thaw depth of the soil, is proposed. The results of the calculations are presented in a graphical form displaying the influence of average air temperature and the accuracy of its setting on the thaw depth of the road foundation soil. It was determined that the degree of change in thaw depth is non-linear and depends on both the average air temperature and on the accuracy with which it is set. For every average air temperature value there is a specific measure of required accuracy for thermal calculations so that the error of thaw depth determination does not exceed the permitted error. A 3D chart showing the expected percentage error in thaw depth forecasting depending on the average air temperature and the accuracy of its setting for an array of initial values was created.

The present paper proposes an iterative implicit numerical method for simulating the thaw depth of permafrost soil. For this purpose, the enthalpy-porosity model was used for the phase change process, and the finite difference scheme FTCS (Forward Time Centered Space) was used for discretization. An artificial mushy zone was maintained with the same thickness by keeping the regularization parameter proportional to the temperature gradient. In doing so, we made the scheme more stable and convergence occurred faster. The model accuracy was validated by comparing the numerical results with the analytical Stefan solution and with the results of a derived numerical model, based on an explicit scheme. The model performance was also tested against observation data collected on four different landscapes with different soil profiles and located on a basin underlain by continuous permafrost. It was found that the proposed model matched noticeably well the analytical solution for a volumetric liquid fraction (phi) equal to 0.5 regardless of the grid resolution. Furthermore, compared with the observation data, the model reproduced the annual maximum thaw depth with an absolute error lying between 0.7 and 7.7%. In addition, the designed algorithm allowed the model to converge after a maximum of eight iterations, reducing the computational time by around 75% compared to the explicit model. The results were so encouraging that the model can be included in a hydrological modeling of permafrost watersheds or cold regions in general.