Liquefaction hazard analysis is crucial in earthquake-prone regions as it magnifies structural damage. In this study, standard penetration test (SPT) and shear wave velocity (Vs) data of Chittagong City have been used to assess the liquefaction resistance of soils using artificial neural network (ANN). For a scenario of 7.5 magnitude (Mw) earthquake in Chittagong City, estimating the liquefaction-resistance involves utilizing peak horizontal ground acceleration (PGA) values of 0.15 and 0.28 g. Then, liquefaction potential index (LPI) is determined to assess the severity of liquefaction. In most boreholes, the LPI values are generally higher, with slightly elevated values in SPT data compared to Vs data. The current study suggests that the Valley Alluvium, Beach and Dune Sand may experience extreme liquefaction with LPI values ranges from 9.55 to 55.03 and 0 to 37.17 for SPT and Vs respectively, under a PGA of 0.15 g. Furthermore, LPI values ranges from 25.55 to 71.45 and 9.55 to 54.39 for SPT and Vs correspondingly. The liquefaction hazard map can be utilized to protect public safety, infrastructure, and to create a more resilient Chittagong City.

Understanding soil organic carbon (SOC) distribution and its environmental controls in permafrost regions is essential for achieving carbon neutrality and mitigating climate change. This study examines the spatial pattern of SOC and its drivers in the Headwater Area of the Yellow River (HAYR), northeastern Qinghai-Xizang Plateau (QXP), a region highly susceptible to permafrost degradation. Field investigations at topsoils of 86 sites over three summers (2021-2023) provided data on SOC, vegetation structure, and soil properties. Moreover, the spatial distribution of key permafrost parameters was simulated: temperature at the top of permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freezing depth (MSFD) using the TTOP model and Stefan Equation. Results reveal a distinct latitudinal SOC gradient (high south, low north), primarily mediated by vegetation structure, soil properties, and permafrost parameters. Vegetation coverage and above-ground biomass showed positive correlation with SOC, while soil bulk density (SBD) exhibited a negative correlation. Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. These findings likely enhance the understanding of carbon storage controls in vulnerable alpine permafrost ecosystems and provide insights to mitigate carbon release under climate change.

Substantial nitrous oxide (N2O) emissions from permafrost-affected regions could accelerate climate warming, given that N2O exhibits approximately 300 times greater radiative forcing potential than carbon dioxide. Pronounced differences exist in N2O emissions between freeze and thaw periods (FP and TP), but the mechanisms by which environmental factors regulate the production and emission of N2O during these two periods have not been thoroughly examined. We therefore combined static chamber gas chromatography, in-situ soil temperature (ST) and moisture (SM) monitoring, and 16S rRNA sequencing to investigate seasonal N2O variations in the Qinghai-Tibet Plateau (QTP) alpine meadow ecosystem, and assess the relative contributions of environmental and microbial drivers. Our findings indicate that N2O fluxes (-3.15 to 6.10 mu g m-2 h-1) fluctuated between weak sources and sinks, peaking during FP, particularly at its late stage with initial surface soil thawing. Soil properties affect N2O emissions by regulating denitrification processes and altering microbial community diversity. During the FP, ST fluctuations control N2O release by modifying mineral nutrient availability. During TP, soil texture modulates denitrification-driven N2O production through its effect on SM. Spring N2O pulses likely originate from microbial reactivation in thawed soil. N2O accumulated in frozen soil may gradually release during vertical profile thawing. On the QTP, a warmer and wetter climate scenario may alter N2O emissions by modifying the duration of the FP and TP and phase-specific hydrothermal allocation. This study provides mechanistic insights for predicting climate change impacts on N2O flux in fragile alpine meadow ecosystems.

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0-40 cm) with a satisfactory accuracy (R-2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.

The spatial distribution of saturated hydraulic conductivity (Ks) is controlled by soil processes at multiple scales, and this spatial variability is crucial to simulating soil moisture movement. Nevertheless, few studies focus on the spatial variability of Ks and how changes through alpine meadow degradation or the specific scales at which the controlling factors function. This study therefore examines the scale-dependent relationships between Ks and several primary driving factors. Soil samples were collected at an interval of 3 m along three transects on a slope in the Qinghai-Tibet Plateau (QTP) and Ks, bulk density (BD), above-ground biomass (AGB), soil organic carbon content (SOC), sand content (SAND), silt content (SILT) and clay content (CLAY) were analysed. Ks showed strong spatial dependency and irregular distribution due to alpine meadow degradation. Pearson correlation analysis revealed a significant correlation between BD, AGB and Ks (p < 0.001). Furthermore, cross-semivariograms showed that Ks exhibited strong spatial correlation with AGB and SAND. Using the state space method, we determined that BD, SOC, AGB and CLAY are the main factors that control the spatial distribution of Ks on the slope. A two-factor state-space equation based on CLAY and BD provides a good representation of Ks, enabling the prediction and estimation of Ks distribution characteristics. These findings enhance our understanding of the crucial parameters that govern hydrological processes at the slope-scale of alpine grassland on the QTP, thereby helping to elucidate permafrost-related hydrological processes related to climate change.

Alpine tundra ecosystems, like their arctic counterparts, have historically been the sites of considerable soil organic carbon (SOC) storage due to climatic factors that suppressed microbial activity. While climatic factors are important, heterotopic soil respiration (and SOC storage) may be influenced by a range of soil characteristics. In this study, we measured soil respiration, soil temperature, soil moisture, soil nutrient concentrations, soil pH, and soil texture in 4 alpine tundra sites located in Rocky Mountain National Park, Colorado, USA from June 2015 - September 2021. We also used geospatial modeling to visualize predicted climate changes in this system over the 21st century. Finally, we measured SOC concentrations over the seven-year study. We found that soil respiration was significantly correlated with soil temperature, soil moisture, and soil texture. All other parameters were not significantly correlated with soil respiration. We also found that SOC concentrations did not change significantly over the course of the seven-year study. The predictive models show that by the end of the century, over the majority of the park, the mean maximum air temperature will increase, the amount of snowfall will decrease, soil moisture will decrease, and the number of snow-free days will increase. These results suggest that SOC is not currently being lost from this system at a high rate. In addition, it appears that with a changing climate, soil respiration may increase with warming, but the overall increase may be limited by decreased soil moisture and in some cases, high soil temperatures.

Background and aimsAlpine swamp meadows play a vital role in water conservation and maintaining ecological balance. However, the response mechanisms of its area and hydrological functions under global climate change remain unclear, particularly the impact of permafrost degradation on water storage capacity, which urgently requires quantification.MethodsWe integrated multi-temporal Landsat data (2000-2023) and phenological features to construct a classification framework for alpine swamp meadows. A multi-source remote sensing-based water balance assessment method was developed. Random forest importance evaluation and piecewiseSEM were employed to quantify the impacts and pathways of multidimensional driving factors on changes in alpine swamp meadow area and water storage.ResultsThe phenology-based classification method effectively extracted alpine swamp meadows with a mean producer's accuracy of 92.84%, user's accuracy of 92.14%, and a Kappa coefficient of 0.95. The study found that the spatial expansion of alpine swamp meadows in the watershed showed an initial decrease followed by an increase trend, while the water storage capacity continued to decline, indicating a significant decoupling between the two.ConclusionUnder climate change, increased precipitation and reduced snow cover albedo have led to the expansion of alpine swamp meadows, while enhanced evapotranspiration and the degradation of permafrost aquicludes have caused a systematic decline in their water storage capacity. These findings provide a scientific basis for assessing the health of alpine ecosystems and managing water resources under climate change.

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.

Alpine wet meadow (AWM), an important wetland type on the Qinghai-Tibet Plateau (QTP), is sensitive to climate change, which alters the soil hydrothermal regime and impacts ecological and hydrological functions in permafrost regions. The mechanisms underlying extreme AWM degradation in the QTP and hydrothermal factors controlling permafrost degradation remain unclear. In this study, soil hydrothermal processes, soil heat migration, and the permafrost state were measured in AWM and extremely degraded AWM (EDAWM). The results showed that the EDAWM exhibited delayed onset of both soil thawing and freezing, shortened thawing period, and extended freezing period at the lower boundary of the active layer. The lower ground temperatures resulted in a 0.2 m shallower active layer thickness in the EDAWM compared with the AWM. Moreover, the EDAWM altered soil thermal dynamics by redistributing energy, modifying soil moisture, preserving soil organic matter, and adjusting soil thermal properties. As for energy budget, a substantial amount of heat in the EDAWM was consumed by turbulent heat fluxes, particularly latent heat flux, which reduced the amount of heat transferred to the ground. Additionally, the higher soil organic matter content in EDAWM decreased the annual mean soil thermal conductivity from 1.42 W m- 1 K-1 in AWM to 1.26 W m- 1 K-1 in EDAWM, slowing down heat transfer within the active layer and consequently mitigating permafrost degradation. However, with continued climate warming, the soil organic matter content in EDAWM will inevitably decline due to microbial decomposition in the absence of new organic inputs. As the soil organic matter content diminishes, soil heat transfer processes will likely accelerate, and the permafrost warming rate may surpass that in undistributed AWM. These findings enhance our understanding of how alpine ecosystem succession influences regional hydrological cycles and greenhouse gas emissions.

In alpine tundra regions, snowmelt plays a crucial role in creating spatial heterogeneity in soil moisture and nutrients across various terrains, influencing vegetation distribution. With climate warming, snowmelt has advanced, lengthening the growing season while also increasing the risk of frost damage to evergreen dwarf shrubs like Rhododendron aureum in alpine tundra regions. To understand these long-term effects, we used remote sensing imagery to analyze nearly four decades (1985-2022) of snowmelt date and the distribution change of R. aureum in Changbai Mountain, East China's only alpine tundra. Results show that snowmelt advanced by 1-3 days/10 years, with faster rates at higher elevations and shady slopes (0.4-0.6 days/10 years more than sunny slopes), while R. aureum increased more on shady slopes under such conditions. Our study demonstrates that these shifts in snowmelt date vary significantly across topographies and reveals how topography and snowmelt changes interact to shape the distribution of evergreen shrubs under climate warming.