Characterizing soil particle-size distribution is a key measure towards soil property.The purpose of this study was to evaluate the multifractal characteristics of soil particle-size distribution among different land-...Characterizing soil particle-size distribution is a key measure towards soil property.The purpose of this study was to evaluate the multifractal characteristics of soil particle-size distribution among different land-use from a purple soil catchment and to generalize the spatial variation trend of multifractal parameters across the catchment.A total of 84 soil samples were collected from four kinds of land use patterns(dry land,orchard,paddy,and forest)in an agricultural catchment in the Three Gorges Reservoir Region,China.The multifractal analysis method was applied to quantitatively characterize the soil particle size distribution.Six soil particle size distribution(PSD)multifractal parameters(D(0),D(1),D(2),(35)a(q),(35)f[a(q)],α(0))were computed.Additionally,a geostatistical analysis was employed to reveal the spatial differentiation and map the spatial distribution of these parameters.Evident multifractal characteristics were found.The trend of generalized dimension spectrum of four land use patterns was basically consistent with the range of 0.8 to 2.0.However,orchard showed the largest monotonic decline,while the forest demonstrated the smallest decrease.D(0)of the four land use patterns were ranked as:dry land<orchard<forest<paddy,the order of D(1)was:dry land<paddy<orchard<forest,D(2)presented a rand-size relationship as dry land<forest<paddy<orchard.Furthermore,all land-use patterns presented asΔf[α(q)]<0.The rand-size relationship ofα(0)was same as D(0).The best-fitting model for D(0),D(1),D(2)andΔf[α(q)]was spherical model,forΔα(q)was gaussian model,and forα(0)was exponential model with structure variance ratio was 1.03%,49.83%,0.84%,1.48%,22.20%and 10.60%,respectively.The results showed that soil particles of each land use pattern were distributed unevenly.The multifractal parameters under different land use have significant differences,except forΔα(q).Differences in the composition of soil particles lead to differences in the multifractal properties even though they belong to the same soil texture.Farming behavior may refine particles and enhance the heterogeneity of soil particle distribution.Our results provide an effective reference for quantifying the impact of human activities on soil system in the Three Gorges Reservoir region.展开更多
Analysis of the spatial variability of soil properties is important to arrange the experimental treatments in the experimental station. This paper aims to study the spatial structure of soil variables and their distri...Analysis of the spatial variability of soil properties is important to arrange the experimental treatments in the experimental station. This paper aims to study the spatial structure of soil variables and their distribution in the Pengshui tobacco experiment station in Chongqing, China. Soil samples were taken from 289 soil points on 20 m grid in March 2012. Twenty-two soil chemical and physical properties were analyzed by classical statistical and geo-statistical methods. Soil pH, cation exchange capacity (CEC), total phosphorus (TP), available phosphorus (AP), zinc (Zn), magnesium (Mg) and sulphur (S) have the strong spatial dependence, with nugget/sill ratios of less than 25%. The others have the moderate dependence with nugget/sill ratios of 26.17% to 71.04%. Ranges of the spatial correlation varied from 51.30 m for chlorine (C1) to 594.90 m for TP. The clearly patchy maps of the nutrients showed the spatial distributions of the soil variables, which can be used for better management of experimental treatments, achieving reliable exoerimental results in the tobacco exnerimental station.Highlight: Scientific experimentation assumes the existence of random variability for soil attributes. This research was to evaluate the spatial variability of soil chemical and physical attributes and to interpolate the spatial distribution of soil properties in the tobacco experimental station in Chongqing. The result of this work can be used for the agricultural management of tobacco cultivation.展开更多
Soil physical properties(SPP)are considered to be important indices that reflect soil structure,hydrological conditions and soil quality.It is of substantial interest to study the spatial distribution of SPP owing to ...Soil physical properties(SPP)are considered to be important indices that reflect soil structure,hydrological conditions and soil quality.It is of substantial interest to study the spatial distribution of SPP owing to the high spatial variability caused by land consolidation under various land restoration modes in excavated farmland in the loess hilly area of China.In our study,three land restoration modes were selected including natural restoration land(NR),alfalfa land(AL)and maize land(ML).Soil texture composition,including the contents of clay,silt and sand,field capacity(FC),saturated conductivity(Ks)and bulk density(BD)were determined using a multifractal analysis.SPP were found to possess variable characteristics,although land consolidation destroyed the soil structure and decreased the spatial autocorrelation.Furthermore,SPP varied with land restoration and could be illustrated by the multifractal parameters of D1,ΔD,ΔαandΔf in different modes of land restoration.Owing to multiple compaction from large machinery in the surface soil,soil particles were fine-grained and increased the spatial variability in soil texture composition under all the land restoration modes.Plough numbers and vegetative root characteristics had the most significant impacts on the improvement in SPP,which resulted in the best spatial distribution characteristics of SPP found in ML compared with those in AL and NR.In addition,compared with ML,Δαvalues of NR and AL were 4.9-and 3.0-fold that of FC,respectively,andΔαvalues of NR and AL were 2.3-and 1.5-fold higher than those of Ks,respectively.These results indicate that SPP can be rapidly improved by increasing plough numbers and planting vegetation types after land consolidation.Thus,we conclude that ML is an optimal land restoration mode that results in favorable conditions to rapidly improve SPP.展开更多
Spatial pattern and interdependence of different soil and plant parameters were examined in green bean field experiment carried out at the Mediterranean Agronomic Institute of Bari (MAIB), Italy. The study aimed to ...Spatial pattern and interdependence of different soil and plant parameters were examined in green bean field experiment carried out at the Mediterranean Agronomic Institute of Bari (MAIB), Italy. The study aimed to identify the spatial distribution of soil and plant parameters and their relationship at transects scale. The experiment consisted of three transects of 30 m length and 4.2 m width, irrigated with three different salinity levels (1 dSm"1, 3 dSm1, 6 dSml). Soil measurements (electrical conductivity and soil water content) were monitored along each transect in 24 sites, using TDR probe installed vertically at soil surface. Water storage was measured by using Diviner sensor for calculating directly the evapotranspiration fluxes along the whole soil profile under the different salinity levels imposed during the experiment. In the same 24 sites, crop monitoring involved measurements of Leaf Area Index (LAI), Osmotic Potential (OP), Root length Density (RID) and Evapotranspiration fluxes (ET). Soil and plant properties were analyzed using both classical and geostatistical methods which included descriptive statistics, semivariograms and cross-semivariograms. Results indicated that moderate to large spatial variability existed across the field for soil and plant parameters, especially under the 6 dSm1 salinity treatment. A relatively satisfactory fit of the experimental cross-semivariogram was obtained for the 6 dS1, thus indicating similar spatial structures of the pairs of compared variables. By contrast, the experimental cross-semivariograms observed under the 3 dS~ treatment indicated no significant correlation structure between the compared variables. Overall, the results observed in the 3 dSm-1 were not significantly different from those obtained in the 1 dSm-1 transect and suggested a general insensitivity of the crop response to those levels of salinity.展开更多
Based on regionalized variable theory, semivariograms of geo-statistics wereused to research the spatial variation of soil properties quantitatively. The results showed thatthe semivariogram of soil organic matter is ...Based on regionalized variable theory, semivariograms of geo-statistics wereused to research the spatial variation of soil properties quantitatively. The results showed thatthe semivariogram of soil organic matter is best described by spherical model, the best model forsemivariograms of soil total N and available K is exponential models and that of available P belongsto linear with sill model. Those soil properties have different spatial correlations respectively,the lag of organic matter is the highest and that of available P is the lowest, the spatialcorrelation of N and available K belongs to moderate degree. Spatial heterogeneities are differenttoo, the degree of organic matter and total N are higher, the degree of available K is in the nextplace and that of available P is the lowest. Influenced by the shape, topography and soil of thestudy area, all isotropies of available P are obvious in all directions while anisotropies of othersare manifested. According to the analytical results, supported by GIS, Kriging and IDW methods areapplied to describe and analyze the spatial distribution of soil properties. The results indicatethat soil organic matter, total N and available K are distributed regularly from northeast tosouthwest, while available P is distributed randomly.展开更多
Precise information about the spatial variability of soil properties is essential in developing site-specific soil management, such as variable rate application of fertilizers. In this study the sampling grid of 100 m...Precise information about the spatial variability of soil properties is essential in developing site-specific soil management, such as variable rate application of fertilizers. In this study the sampling grid of 100 m × 100 m was established to collect 1 703 soil samples at the depth of 0-20 cm, and examine spatial patterns including 13 soil chemical properties (pH, OM, NH4^+, P, K, Ca, Mg, S, B, Cu, Fe, Mn, and Zn) in a 1 760 ha rice field in Haifeng farm, China, from 6th to 22nd of April, 2006, before fertilizer application and planting. Soil analysis was performed by ASI (Agro Services International) and data were analyzed both statistically and geostatistically. Results showed that the contents of soil OM, NH4^+, and Zn in Haifeng farm were very low for rice production and those of others were enough to meet the need for rice cultivation. The spatial distribution model and spatial dependence level for 13 soil chemical properties varied in the field. Soil Mg and B showed strong spatial variability on both descriptive statistics and geostatistics, and other properties showed moderate spatial variability. The maximum ranges for K, Ca, Mg, S, Cu and Mn were all - 3 990.6 m and the minimum ranges for soil pH, OM, NH4^+, P, Fe, and Zn ranged from 516.7 to 1 166.2 m. Clear patchy distribution of N, P, K, Mg, S, B, Mn, and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.展开更多
In areas with topographic heterogeneity, land use change is spatially variable and influenced by climate, soil properties, and topography. To better understand this variability in the high-sediment region of the Loess...In areas with topographic heterogeneity, land use change is spatially variable and influenced by climate, soil properties, and topography. To better understand this variability in the high-sediment region of the Loess Plateau in which soil loss is most severe and sediment diameter is larger than in other regions of the plateau, this study builds some indicators to identify the characteristics of land use change and then analyze the spatial variability as it is affected by climate, soil property, and topography. We build two indicators, a land use change intensity index and a vegetation change index, to characterize the intensity of land use change, and the degree of vegetation restoration, respectively. Based on a subsection mean method, the two indicators are then used to assess the spatial variability of land use change affected by climatic, edaphic, and topographic elements. The results indicate that: 1) Land use changed significantly in the period 1998-2010. The total area experiencing land use change was 42,302 km2, accounting for 22.57%of the study area. High-coverage grassland, other woodland, and forest increased significantly, while low-coverage grassland and farmland decreased in 2010 compared with 1998.2) Land use change occurred primarily west of the Yellow River, between 35 and 38 degrees north latitude. The four transformation types, including (a) low-coverage grassland to medium-coverage grassland, (b) medium-coverage grassland to high-coverage grassland, (c) farmland to other woodland, and (d) farmland to medium-coverage grassland, were the primary types of land use change, together constituting 60% of the area experiencing land use change. 3) The spatial variability of land use change was significantly affected by properties of dryness/wetness, soil conditions and slope gradient. In general, land use changed dramatically in semi-arid regions, remained relatively stable in arid regions, changed significantly in clay-rich soil, remained relatively stable in clay-poor soil, changed dramatically in steeper slopes, and remained relatively stable in tablelands and low-lying regions. The increase in vegetation coincided with increasing changes in land use for each physical element. These findings allow for an evaluation of the effect of the Grain to Green Program, and are applicable to the design of soil and water conservation projects on the Loess Plateau of China.展开更多
In the permafrost regions of the Qinghai-Tibet Plateau(QTP),the permafrost table has a significant effect on the stability of geotechnical engineering.The thermal boundaries and soil properties are the key factors aff...In the permafrost regions of the Qinghai-Tibet Plateau(QTP),the permafrost table has a significant effect on the stability of geotechnical engineering.The thermal boundaries and soil properties are the key factors affecting the permafrost table.Complex geological environments and human activities can lead to the uncertainties of thermal boundaries and soil properties.In this paper,an array of field experiments and Monte Carlo(MC)simulations of thermal boundaries and soil properties are carried out.The coefficient of variation(COV),scale of fluctuation(SOF),and autocorrelation distance(ACD)of uncertainties of thermal boundaries and soil properties are investigated.A stochastic analysis method of the probabilistic permafrost table is then proposed,and the statistical properties of permafrost table on the QTP are computed by self-compiled program.The proposed stochastic analysis method is verified with the calculated and measured temperature observations.According to the relationship between ACD and SOF for the five theoretical autocorrelation functions(ACFs),the effects of ACF,COV,and ACD of soil properties and the COV of thermal boundaries on the permafrost tables are analyzed.The results show that the effects of different ACFs of soil properties on the standard deviation(SD)of permafrost table depth are not obvious.The SD of permafrost table depth increases with time,and the larger the COVs of thermal boundaries and soil properties,the deeper the SD of permafrost table;the longer the ACD of soil properties,the shallower the SD of permafrost table.This study can provide a reference for the stability analysis of geotechnical engineering on the QTP considering the uncertainties of thermal boundaries and soil properties.展开更多
基金funded by the National Key R&D Program of China(2017YFD0800505)Chongqing Key R&D Project of Technology Innovation and Application(NO.cstc2018jscxmszd X0055)。
文摘Characterizing soil particle-size distribution is a key measure towards soil property.The purpose of this study was to evaluate the multifractal characteristics of soil particle-size distribution among different land-use from a purple soil catchment and to generalize the spatial variation trend of multifractal parameters across the catchment.A total of 84 soil samples were collected from four kinds of land use patterns(dry land,orchard,paddy,and forest)in an agricultural catchment in the Three Gorges Reservoir Region,China.The multifractal analysis method was applied to quantitatively characterize the soil particle size distribution.Six soil particle size distribution(PSD)multifractal parameters(D(0),D(1),D(2),(35)a(q),(35)f[a(q)],α(0))were computed.Additionally,a geostatistical analysis was employed to reveal the spatial differentiation and map the spatial distribution of these parameters.Evident multifractal characteristics were found.The trend of generalized dimension spectrum of four land use patterns was basically consistent with the range of 0.8 to 2.0.However,orchard showed the largest monotonic decline,while the forest demonstrated the smallest decrease.D(0)of the four land use patterns were ranked as:dry land<orchard<forest<paddy,the order of D(1)was:dry land<paddy<orchard<forest,D(2)presented a rand-size relationship as dry land<forest<paddy<orchard.Furthermore,all land-use patterns presented asΔf[α(q)]<0.The rand-size relationship ofα(0)was same as D(0).The best-fitting model for D(0),D(1),D(2)andΔf[α(q)]was spherical model,forΔα(q)was gaussian model,and forα(0)was exponential model with structure variance ratio was 1.03%,49.83%,0.84%,1.48%,22.20%and 10.60%,respectively.The results showed that soil particles of each land use pattern were distributed unevenly.The multifractal parameters under different land use have significant differences,except forΔα(q).Differences in the composition of soil particles lead to differences in the multifractal properties even though they belong to the same soil texture.Farming behavior may refine particles and enhance the heterogeneity of soil particle distribution.Our results provide an effective reference for quantifying the impact of human activities on soil system in the Three Gorges Reservoir region.
文摘Analysis of the spatial variability of soil properties is important to arrange the experimental treatments in the experimental station. This paper aims to study the spatial structure of soil variables and their distribution in the Pengshui tobacco experiment station in Chongqing, China. Soil samples were taken from 289 soil points on 20 m grid in March 2012. Twenty-two soil chemical and physical properties were analyzed by classical statistical and geo-statistical methods. Soil pH, cation exchange capacity (CEC), total phosphorus (TP), available phosphorus (AP), zinc (Zn), magnesium (Mg) and sulphur (S) have the strong spatial dependence, with nugget/sill ratios of less than 25%. The others have the moderate dependence with nugget/sill ratios of 26.17% to 71.04%. Ranges of the spatial correlation varied from 51.30 m for chlorine (C1) to 594.90 m for TP. The clearly patchy maps of the nutrients showed the spatial distributions of the soil variables, which can be used for better management of experimental treatments, achieving reliable exoerimental results in the tobacco exnerimental station.Highlight: Scientific experimentation assumes the existence of random variability for soil attributes. This research was to evaluate the spatial variability of soil chemical and physical attributes and to interpolate the spatial distribution of soil properties in the tobacco experimental station in Chongqing. The result of this work can be used for the agricultural management of tobacco cultivation.
基金The study was funded by the National Key Research and Development Program of China(2017YFD0800502)the National Natural Science Foundation of China(41671510).
文摘Soil physical properties(SPP)are considered to be important indices that reflect soil structure,hydrological conditions and soil quality.It is of substantial interest to study the spatial distribution of SPP owing to the high spatial variability caused by land consolidation under various land restoration modes in excavated farmland in the loess hilly area of China.In our study,three land restoration modes were selected including natural restoration land(NR),alfalfa land(AL)and maize land(ML).Soil texture composition,including the contents of clay,silt and sand,field capacity(FC),saturated conductivity(Ks)and bulk density(BD)were determined using a multifractal analysis.SPP were found to possess variable characteristics,although land consolidation destroyed the soil structure and decreased the spatial autocorrelation.Furthermore,SPP varied with land restoration and could be illustrated by the multifractal parameters of D1,ΔD,ΔαandΔf in different modes of land restoration.Owing to multiple compaction from large machinery in the surface soil,soil particles were fine-grained and increased the spatial variability in soil texture composition under all the land restoration modes.Plough numbers and vegetative root characteristics had the most significant impacts on the improvement in SPP,which resulted in the best spatial distribution characteristics of SPP found in ML compared with those in AL and NR.In addition,compared with ML,Δαvalues of NR and AL were 4.9-and 3.0-fold that of FC,respectively,andΔαvalues of NR and AL were 2.3-and 1.5-fold higher than those of Ks,respectively.These results indicate that SPP can be rapidly improved by increasing plough numbers and planting vegetation types after land consolidation.Thus,we conclude that ML is an optimal land restoration mode that results in favorable conditions to rapidly improve SPP.
文摘Spatial pattern and interdependence of different soil and plant parameters were examined in green bean field experiment carried out at the Mediterranean Agronomic Institute of Bari (MAIB), Italy. The study aimed to identify the spatial distribution of soil and plant parameters and their relationship at transects scale. The experiment consisted of three transects of 30 m length and 4.2 m width, irrigated with three different salinity levels (1 dSm"1, 3 dSm1, 6 dSml). Soil measurements (electrical conductivity and soil water content) were monitored along each transect in 24 sites, using TDR probe installed vertically at soil surface. Water storage was measured by using Diviner sensor for calculating directly the evapotranspiration fluxes along the whole soil profile under the different salinity levels imposed during the experiment. In the same 24 sites, crop monitoring involved measurements of Leaf Area Index (LAI), Osmotic Potential (OP), Root length Density (RID) and Evapotranspiration fluxes (ET). Soil and plant properties were analyzed using both classical and geostatistical methods which included descriptive statistics, semivariograms and cross-semivariograms. Results indicated that moderate to large spatial variability existed across the field for soil and plant parameters, especially under the 6 dSm1 salinity treatment. A relatively satisfactory fit of the experimental cross-semivariogram was obtained for the 6 dS1, thus indicating similar spatial structures of the pairs of compared variables. By contrast, the experimental cross-semivariograms observed under the 3 dS~ treatment indicated no significant correlation structure between the compared variables. Overall, the results observed in the 3 dSm-1 were not significantly different from those obtained in the 1 dSm-1 transect and suggested a general insensitivity of the crop response to those levels of salinity.
文摘Based on regionalized variable theory, semivariograms of geo-statistics wereused to research the spatial variation of soil properties quantitatively. The results showed thatthe semivariogram of soil organic matter is best described by spherical model, the best model forsemivariograms of soil total N and available K is exponential models and that of available P belongsto linear with sill model. Those soil properties have different spatial correlations respectively,the lag of organic matter is the highest and that of available P is the lowest, the spatialcorrelation of N and available K belongs to moderate degree. Spatial heterogeneities are differenttoo, the degree of organic matter and total N are higher, the degree of available K is in the nextplace and that of available P is the lowest. Influenced by the shape, topography and soil of thestudy area, all isotropies of available P are obvious in all directions while anisotropies of othersare manifested. According to the analytical results, supported by GIS, Kriging and IDW methods areapplied to describe and analyze the spatial distribution of soil properties. The results indicatethat soil organic matter, total N and available K are distributed regularly from northeast tosouthwest, while available P is distributed randomly.
基金funded by thestarting project of scientific research for high-level tal-ents introduced by North China University of Water Conservancy and Electric Power (200723)Shang-hai Municipal Key Task Projects of Prospering Agri-culture by the Science and Technology Plan, China(NGZ 1-10)
文摘Precise information about the spatial variability of soil properties is essential in developing site-specific soil management, such as variable rate application of fertilizers. In this study the sampling grid of 100 m × 100 m was established to collect 1 703 soil samples at the depth of 0-20 cm, and examine spatial patterns including 13 soil chemical properties (pH, OM, NH4^+, P, K, Ca, Mg, S, B, Cu, Fe, Mn, and Zn) in a 1 760 ha rice field in Haifeng farm, China, from 6th to 22nd of April, 2006, before fertilizer application and planting. Soil analysis was performed by ASI (Agro Services International) and data were analyzed both statistically and geostatistically. Results showed that the contents of soil OM, NH4^+, and Zn in Haifeng farm were very low for rice production and those of others were enough to meet the need for rice cultivation. The spatial distribution model and spatial dependence level for 13 soil chemical properties varied in the field. Soil Mg and B showed strong spatial variability on both descriptive statistics and geostatistics, and other properties showed moderate spatial variability. The maximum ranges for K, Ca, Mg, S, Cu and Mn were all - 3 990.6 m and the minimum ranges for soil pH, OM, NH4^+, P, Fe, and Zn ranged from 516.7 to 1 166.2 m. Clear patchy distribution of N, P, K, Mg, S, B, Mn, and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.
基金National Key Technologies R&D Program,No.2012BAB02B00Public Welfare Foundation of the Ministry of Water Resources of China,No.201101037The Fundamental Research Funds for the Central Universities
文摘In areas with topographic heterogeneity, land use change is spatially variable and influenced by climate, soil properties, and topography. To better understand this variability in the high-sediment region of the Loess Plateau in which soil loss is most severe and sediment diameter is larger than in other regions of the plateau, this study builds some indicators to identify the characteristics of land use change and then analyze the spatial variability as it is affected by climate, soil property, and topography. We build two indicators, a land use change intensity index and a vegetation change index, to characterize the intensity of land use change, and the degree of vegetation restoration, respectively. Based on a subsection mean method, the two indicators are then used to assess the spatial variability of land use change affected by climatic, edaphic, and topographic elements. The results indicate that: 1) Land use changed significantly in the period 1998-2010. The total area experiencing land use change was 42,302 km2, accounting for 22.57%of the study area. High-coverage grassland, other woodland, and forest increased significantly, while low-coverage grassland and farmland decreased in 2010 compared with 1998.2) Land use change occurred primarily west of the Yellow River, between 35 and 38 degrees north latitude. The four transformation types, including (a) low-coverage grassland to medium-coverage grassland, (b) medium-coverage grassland to high-coverage grassland, (c) farmland to other woodland, and (d) farmland to medium-coverage grassland, were the primary types of land use change, together constituting 60% of the area experiencing land use change. 3) The spatial variability of land use change was significantly affected by properties of dryness/wetness, soil conditions and slope gradient. In general, land use changed dramatically in semi-arid regions, remained relatively stable in arid regions, changed significantly in clay-rich soil, remained relatively stable in clay-poor soil, changed dramatically in steeper slopes, and remained relatively stable in tablelands and low-lying regions. The increase in vegetation coincided with increasing changes in land use for each physical element. These findings allow for an evaluation of the effect of the Grain to Green Program, and are applicable to the design of soil and water conservation projects on the Loess Plateau of China.
基金This research was supported by Open Fund of State Key Laboratory of Frozen Soil Engineering(Grant No.SKLFSE202017)Key Research and Development Program of Xuzhou(Grant No.KC20179)Major State Basic Research Development Program(Grant No.2012CB026103).
文摘In the permafrost regions of the Qinghai-Tibet Plateau(QTP),the permafrost table has a significant effect on the stability of geotechnical engineering.The thermal boundaries and soil properties are the key factors affecting the permafrost table.Complex geological environments and human activities can lead to the uncertainties of thermal boundaries and soil properties.In this paper,an array of field experiments and Monte Carlo(MC)simulations of thermal boundaries and soil properties are carried out.The coefficient of variation(COV),scale of fluctuation(SOF),and autocorrelation distance(ACD)of uncertainties of thermal boundaries and soil properties are investigated.A stochastic analysis method of the probabilistic permafrost table is then proposed,and the statistical properties of permafrost table on the QTP are computed by self-compiled program.The proposed stochastic analysis method is verified with the calculated and measured temperature observations.According to the relationship between ACD and SOF for the five theoretical autocorrelation functions(ACFs),the effects of ACF,COV,and ACD of soil properties and the COV of thermal boundaries on the permafrost tables are analyzed.The results show that the effects of different ACFs of soil properties on the standard deviation(SD)of permafrost table depth are not obvious.The SD of permafrost table depth increases with time,and the larger the COVs of thermal boundaries and soil properties,the deeper the SD of permafrost table;the longer the ACD of soil properties,the shallower the SD of permafrost table.This study can provide a reference for the stability analysis of geotechnical engineering on the QTP considering the uncertainties of thermal boundaries and soil properties.