Characteristic Analysis of the Spatio-Temporal Distribution of Key Variables of the Soil Freeze–Thaw Processes over Heilongjiang Province, China

Song, Chengjie; Dai, Changlei; Wang, Chuang; Yu, Miao; Gao, Yaqi; Tu, Weiming

doi:10.3390/w14162573

Cited by 4 publications

(7 citation statements)

References 68 publications

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“…surface temperature also varies [34]. As can be seen in Figure 3b, the variation in temperature is also inconsistent over time, with MAAT remaining largely below the 49a multiyear mean until 1987, indicating a cooler period, while from 1988 to 2019, the MAAT were mostly greater than the multiyear mean, indicating a distinctly warmer period.…”

Section: Spatial and Temporal Characteristics Of Maat And Magstmentioning

confidence: 90%

“…The main reason for the inconsistency in warming trends is that factors affecting surface temperature are correlated with vegetation type, snow cover and geological conditions as well as air temperature [33,53,54]. Additionally, the effect of different types of mulch on surface temperature also varies [34]. As can be seen in Figure 3b, the variation in temperature is also inconsistent over time, with MAAT remaining largely below the 49a multiyear mean until 1987, indicating a cooler period, while from 1988 to 2019, the MAAT were mostly greater than the multiyear mean, indicating a distinctly warmer period.…”

Section: Spatial and Temporal Characteristics Of Maat And Magstmentioning

confidence: 99%

“…The permafrost zone is predicted to shrink significantly from 2015-2100. Song [34] analyzed the spatial distribution of key variables in the soil freeze-thaw process using surface temperature data monitored from 34 meteorological stations in Heilongjiang Province, and discussed the spatial-temporal distribution of key variables and changes in surface temperature in the freeze-thaw process under different vegetation types. Accordingly, the freezing/thawing index can be employed to map the distribution of permafrost and is of great significance for the evaluation of changes in the distribution of permafrost and its contribution to climate.…”

Section: Introductionmentioning

confidence: 99%

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Spatial–Temporal Characteristics of Freezing/Thawing Index and Permafrost Distribution in Heilongjiang Province, China

et al. 2022

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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.

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Section: Spatial and Temporal Characteristics Of Maat And Magstmentioning

confidence: 90%

Section: Spatial and Temporal Characteristics Of Maat And Magstmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spatial–Temporal Characteristics of Freezing/Thawing Index and Permafrost Distribution in Heilongjiang Province, China

et al. 2022

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“…When the spring season brings about an increase in temperature, the soil undergoes a process of absorbing a significant quantity of heat from the surrounding atmosphere. As the soil continues to accumulate heat, reaching a threshold temperature at which the ice within the soil begins to melt, the solid water present in the soil undergoes a gradual transformation into liquid water [6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Hence, it is evident that the soil structure undergoes a close and interactive relationship with water and heat transport during the freezing and thawing processes, resulting in a strong coupling effect that complicates the freezing and thawing processes.…”

Section: Introductionmentioning

confidence: 99%

Large-Scale Freezing and Thawing Model Experiment and Analysis of Water–Heat Coupling Processes in Agricultural Soils in Cold Regions

Hai,

Su,

Wang

et al. 2023

Water

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Heilongjiang Province, the largest commercial grain base in China, experiences significant challenges due to the environmental effects on its soil. The freezing and thawing cycle in this region leads to the transport of water and heat, as well as the exchange and transfer of energy. Consequently, this exacerbates the flooding disaster in spring and severely hampers farming activities such as plowing and sowing. To gain a better understanding of the freezing and thawing mechanisms of farmland soil in cold regions and prevent spring flooding disasters, this study focuses on Heilongjiang Province as a representative area in northeast China. The research specifically investigates the frozen and thawed soil of farmland, using a large-scale low-temperature laboratory to simulate both artificial and natural climate conditions in the cold zone. By employing the similarity principle of geotechnical model testing, the study aims to efficiently simulate the engineering prototypes and replicate the process of large-span and long-time low temperatures. The investigation primarily focuses on the evolution laws of key parameters, such as the temperature field and moisture field of farmland soil during the freeze–thaw cycle. The findings demonstrate that the cooling process of soil can be categorized into three stages: rapid cooling, slow cooling, and freezing stabilization. As the soil depth increases, the variability of the soil temperature gradually diminishes. During the melting stage, the soil’s water content exhibits a gradual increase as the temperature rises. The range of water content variation during thawing at depths of 30 cm, 40 cm, 50 cm, and 80 cm is 0.12% to 0.52%, 0.47% to 1.08%, 0.46% to 1.96%, and 0.8% to 3.23%, respectively. To analyze the hydrothermal coupling process of farmland soil during the freeze–thaw cycle, a theoretical model of hydrothermal coupling was developed based on principles of mass conservation, energy conservation, Darcy’s law of unsaturated soil water flow, and heat conduction theory. Mathematical transformations were applied after defining the relative degree of saturation and solid–liquid ratio as field functions with respect to the relative degree of saturation and temperature. The simulated temperature and moisture fields align well with the measured data, indicating that the water–heat coupling model established in this study holds significant theoretical and practical value for accurately predicting soil temperature and moisture content during the spring sowing period, as well as for efficiently and effectively utilizing frozen soil resources in cold regions.

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“…Harbin is situated in the frigid high-latitude zone [1]. In recent years, frost has been a significant agricultural hazard in the study area.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Differentiation and Influencing Factors of Frost Key Date in Harbin Municipality from 1961 to 2022

Zhang,

Dai,

et al. 2023

Water

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This study analyzed frost formation data provided by the Harbin Meteorological Bureau and considered geographic factors, temperature, and population density. Various analytical methods, including linear fitting, the Mann–Kendall mutation test, the Pettitt method, and the sliding t-test, were employed to identify the temporal and spatial changes as well as the effects of these factors on frost dates in Harbin. The study shows that the first FSD occurred on 18 August, in both 1966 and 1967, which was the 255th day. The latest FSD was observed on 10 October 2006, which was the 283rd day. The earliest occurrence of an FED was on 24 April 2015, which was the 114th day, and the latest was on 21 April 1974, which was the 141st day. The highest number of frost days occurred in 2012, with 161 days, whereas the shortest year was 1966, with only 123 frost days. Throughout the study period, the FSD increased by 7.8 days at a rate of −1.27d/10a, the FED increased by 10.9 days at a rate of 1.77d/10a, and the FFS increased by 18.9 days at a rate of 3.05d/10a. The propensity rates of the FSD and FFS at each location in Harbin indicate an upward trend, while for the FED, certain locations display an upward trend. In general, the FSD has exhibited a delayed trend, the FED has shown an earlier trend, and the FFS has experienced an extended trend. With one-way linear regression, the FSD exhibited an increasing trend at each site, while the FFS also indicated a similar trend, and the FED showed an overall decreasing trend. Throughout the study period, a change was observed in the FSD in 2000, resulting in an average arrival time of the 265th day, or 22 September, of that year. Subsequently, post mutation, the average arrival time of the FSD in the study area was the 272nd day, or 29 September, of that year. In 2006, the FED also underwent a change, with the average arrival time in the study area being the 128th day, or 4 April, of that year. After the change, the average arrival time of the FED in the study area was the 121st day, i.e., 8 April. In 1 April 2004 of that year saw a change in the FFS. Prior to the change, the FFS in the study area averaged the 137th day, whilst following the change, the FFS in the study area averaged the 150th day. The FSD and FFS within Harbin exhibit a negative correlation with latitude and a positive correlation with temperature. Additionally, the FED displays a positive correlation with latitude and a negative correlation with temperature. As the FSD, FED, and FFS in central Harbin are the earliest, latest, and longest, the Pearson correlation coefficient method and multiple regression cannot adequately reflect the effect of longitude.

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Characteristic Analysis of the Spatio-Temporal Distribution of Key Variables of the Soil Freeze–Thaw Processes over Heilongjiang Province, China

Cited by 4 publications

References 68 publications

Spatial–Temporal Characteristics of Freezing/Thawing Index and Permafrost Distribution in Heilongjiang Province, China

Spatial–Temporal Characteristics of Freezing/Thawing Index and Permafrost Distribution in Heilongjiang Province, China

Large-Scale Freezing and Thawing Model Experiment and Analysis of Water–Heat Coupling Processes in Agricultural Soils in Cold Regions

Spatiotemporal Differentiation and Influencing Factors of Frost Key Date in Harbin Municipality from 1961 to 2022

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