Under the trend of climate warming, the high-latitude permafrost in Heilongjiang Province is becoming seriously degraded. The question of how to quantitatively analyze the spatial and temporal trends of multi-year permafrost has become fundamental for current permafrost research. In this study, the temporal and spatial variations of annual mean air temperature (MAAT), annual mean ground temperature (MAGST) and freezing/thawing index based on air and surface temperature data from 34 meteorological stations in Heilongjiang Province from 1971–2019, as well as the variation characteristics of permafrost distribution, were analyzed based on the freezing index model. The results showed that both MAAT and MAGST in Heilongjiang Province tended to decrease with the increase of altitude and latitude. For interannual variation, the MAAT and MAGST warming rates tended to be consistent across Heilongjiang Province, with multi-year variation from −8.64 to 5.60 °C and from −6.52 to 7.58 °C, respectively. From 1971–2019, the mean annual air freezing index (AFI) and ground surface freezing index (GFI) declined at −5.07 °C·d·a⁻¹ and −5.04 °C·d·a⁻¹, respectively, whereas the mean annual air thawing index (ATI) and ground surface thawing index (GTI) were elevated at 7.63 °C·d·a⁻¹ and 11.89 °C·d·a⁻¹, respectively. The spatial distribution of the multiyear mean AFI, ATI, GFI and GTI exhibited a latitudinal trend, whereas the effect of altitude in the northern mountainous areas was greater than that of latitude. Permafrost was primarily discovered in the Daxing’an and Xiaoxing’an Mountains in the north, and sporadically in the central mountainous regions. The southern boundary of permafrost shifted nearly 2° to the north from 1970 to 2010s, while the southern boundary of permafrost in Heilongjiang Province was stable at nearly 51° N. The total area of permafrost narrowed from 1.11 × 10⁵ km² in the 1970s to 6.53 × 10⁴ km² in the 2010s. The results of this study take on a critical significance for the analysis of the trend of perennial permafrost degradation at high latitudes in Heilongjiang Province and the whole northeastern China, as well as for mapping the distribution of large areas of permafrost using the freezing index model. This study provides a reference for natural cold resource development, ecological protection, climate change and engineering construction and maintenance in permafrost areas.

The phenomenon of flash droughts, marked by their fast onset, limited predictability, and formidable capacity for devastation, has elicited escalating concern. Despite this growing interest, a comprehensive investigation of the spatiotemporal dynamics of flash drought events within zones of ecological sensitivity, alongside their consequential ecological ramifications, remains elusive. The Songnen Plain, distinguished as both an important granary for commodity crops and an ecological keystone within China, emerges as an indispensable locus for the inquiry into the dynamics of flash droughts and their repercussions on terrestrial biomes. Through the application of daily soil moisture raster datasets encompassing the years 2002 to 2022, this investigation delves into the spatiotemporal progression of two distinct categories of flash droughts—those instigated by heatwaves and those precipitated by water deficits—within the Songnen Plain. Moreover, the ecosystem’s response, with a particular focus on gross primary productivity (GPP), to these climatic variables was investigated. Flash drought phenomena have been observed to manifest with a relative frequency of approximately one event every three years within the Songnen Plain, predominantly lasting for periods of 28–30 days. The incidence of both heatwave-induced and water deficit-induced flash droughts was found to be comparable, with a pronounced prevalence during the summer and autumn. Nevertheless, droughts caused by water scarcity demonstrated a more extensive distribution and a heightened frequency of occurrence, whereas those rooted in heatwaves were less frequent but exhibited a propensity for localization in specific sectors. The sensitivity of GPP to these meteorological anomalies was pronounced, with an average response rate surpassing 70%. This spatial distribution of the response rate revealed elevated values in the northwestern segment of the Songnen Plain and diminished values towards the southeastern sector. Intriguingly, GPP’s reaction pace to the onset of heatwave-driven flash droughts was observed to be more rapid in comparison to that during periods of water scarcity. Additionally, the spatial distribution of water use efficiency during both the development and recovery periods of flash droughts largely deviated from that of base water use efficiency. The insights from this study hold profound implications for the advancement of regional drought surveillance and adaptive management.

Soil temperature is an important index of climate change, and the analysis of soil temperature change is of great significance for understanding climate change and ecohydrological processes. This study was based on the measured meteorological data of a meteorological station, combined with the soil temperature data of 0–10, 10–40, 40–100 and 100–200 cm from the Global Land Data Assimilation System (GLDAS-NOAH). The Mann–Kendall test, wavelet analysis, linear tendency estimation and other methods were used to analyze the variability, periodicity and trend of soil temperature in Lhasa from 2006 to 2022. The results showed that the soil temperature of different soil layers had abrupt changes in annual and seasonal time series, and all showed a warming phenomenon after abrupt changes. In terms of periodicity, the average annual soil temperature of different soil layers has similar periodic changes, and the periodic oscillation is strong around 10a, which is the main cycle of soil temperature change. The soil temperature in Lhasa showed a significant rising trend in the interannual and seasonal time series, and the average annual rising trend of soil temperature was greater than that of air temperature. The correlation between soil temperature and mean air temperature (MAT), maximum air temperature (Tmax), minimum air temperature (Tmin) and snow depth (SD) was investigated by Pearson correlation analysis. Soil temperature in spring, autumn and winter had a strong correlation with MAT, Tmax and Tmin, showing a significant positive correlation. The negative correlation between soil temperature and SD in 0–40 cm soil in spring and winter was more severe. The research results show that Lhasa has experienced a rise in air temperature and soil temperature in the past 17 years, and reveal the specific changes in soil temperature in Lhasa against the background of climate change. These findings have reference significance for understanding the impact of climate change on the natural environment.

Ground-penetrating radar (GPR), due to its efficiency and non-invasive nature, has become an important tool for detecting the permafrost table, overcoming the limited spatial coverage and high costs associated with drilling and in situ temperature monitoring. Compared with the commonly used 50–100 MHz antennas, the potential of high-frequency antennas to improve detection accuracy and interface resolution has not been fully explored. To address this gap, this study introduces a multi-strategy interface identification method incorporating envelope analysis. Field experiments were conducted in the island-like permafrost zone of the Da Xing’anling Mountains, Heilongjiang Province, using shielded GPR systems operating at 250 MHz and 500 MHz to detect the permafrost table. Potential interfaces were extracted using centroid and edge-detection algorithms and validated against ground temperature observations. The results indicate that: (1) integrating GPR with multi-source data enables accurate estimation of active layer thickness, and the envelope-based multi-strategy approach is effective for interface identification; (2) the 250 MHz antenna is better suited for capturing broader subsurface structures, while the 500 MHz antenna provides higher resolution for shallow layers—combining the two enhances overall interpretive quality; and (3) snow cover significantly affects electromagnetic wave propagation, reducing the accuracy of radar detection. This study provides valuable guidance for engineering investigations, site selection, and foundation design in permafrost regions, contributing to improved precision and efficiency in GPR-based detection of the permafrost table.

Arctic Alaska is warming at twice the rate of the rest of the nation, severely impacting infrastructure built on permafrost. As winters warm, the effectiveness of thermosyphons used to stabilize foundations diminishes, increasing the risk of infrastructure failure. Because thermosyphons operate with the highest efficiency during winter cold snaps, studying the variation trends and patterns of winter cold snaps in Alaska is particularly important. To address this issue, this study analyzes the historical temperature data of four selected locations in Subarctic and Arctic Alaska, including Bethel, Fairbanks, Nome, and Utqiagvik. The winter cold snap is defined as a period when the average daily temperature drops below a specific site’s mean winter air temperature. The frequency, duration, and intensity of the winter cold snaps are computed to reveal their trends. The results indicate that the mean annual air temperature (MAAT) shows a warming trend, accompanied by sudden warming after 1975 for all study sites. The long-term average monthly air temperature also indicates that the most significant warming occurs in the winter months from December to March. While the frequencies of winter cold snaps remain relatively unchanged, the mean intensity and duration of cold snaps show a declining trend. Most importantly, the most intense cold snap during which the thermosyphons are the most effective is becoming much milder over time for all study sites. This study focuses specifically on the impact of changes in winter cold spells on thermosyphon effectiveness while acknowledging the complexity of other influencing factors, such as temperature differences, design features, coolant properties, and additional climatic parameters (e.g., wind speed, precipitation, and humidity). The data for this study were obtained from the NOAA NCEI website. The findings of this study can serve as a valuable reference for the retrofit or design of foundations and for decision making in selecting appropriate foundation stabilizing measures to ensure the long-term stability and resilience of infrastructure in permafrost regions. Moreover, the insights gained from this research on freeze–thaw dynamics, which are also relevant to black soils, align with the journal’s focus on sustainable soil utilization and infrastructure resilience.

Baseflow is a crucial component of river flow in alpine inland basins, playing an essential role in watershed ecological health and water resource management. In high-latitude cold regions, seasonal freeze-thaw processes make baseflow formation mechanisms particularly complex. However, the dominant factors affecting baseflow and their relative contributions remain unclear, limiting the accuracy of flow estimation and effective water resource management. This study employed baseflow separation techniques and statistical methods, including the Mann-Kendall test, to investigate temporal trends and abrupt changes in baseflow and the baseflow index (BFI) at multiple time scales (annual, seasonal, and monthly) from 2005 to 2012. Additionally, the timing of snowmelt and its impact on baseflow were examined. Key findings include the following: (1) Baseflow and BFI showed distinct temporal variability with non-significant upward trends across all time scales. Annual BFI ranged from 0.48 to 0.61, contributing approximately 50% of total runoff. (2) At the seasonal scale, baseflow remained relatively stable in spring, increased in autumn, and showed non-significant decreases in summer and winter. Monthly baseflow exhibited an increasing trend. (3) The snowmelt period occurred between April and May, with baseflow during this period strongly correlated with climatic factors in the following order: winter precipitation > positive accumulated temperature > winter air temperature > negative accumulated temperature. The strongest positive correlation was observed between baseflow and winter precipitation (R = 0.724), while negative correlations were found with accumulated temperatures and winter air temperature. These findings offer valuable insights for predicting water resource availability and managing flood and ice-jam risks in cold regions.