This research employs micro-CT scanning technology to analyze the porosity,pore fractal dimension,and spatial variability of sandstone preheated to 600℃ and subsequently cooled in water at varying temperatures(20℃,6...This research employs micro-CT scanning technology to analyze the porosity,pore fractal dimension,and spatial variability of sandstone preheated to 600℃ and subsequently cooled in water at varying temperatures(20℃,60℃,100℃).The study investigates the mechanisms by which various factors influence thermal shock damage,focusing on the effects of cooling water temperature and the boiling phase transition.The objective is to develop a method for characterizing thermal shock damage that considers spatial variability.The findings indicate that thermal shock damage is limited to a shallow depth beneath the surface,with increased severity near the surface.The boiling phase transition significantly enhances the convective heat transfer coefficient,resulting in substantially higher thermal shock damage when cooled with 100℃ boiling water compared to 20℃ and 60℃ water.Furthermore,for the entire specimen,heating damage exceeds thermal shock damage,and the influence of thermal shock diminishes as specimen size increases.This study addresses the limitations of traditional methods for assessing thermal shock damage that disregard spatial variability and provides practical guidance for engineering projects to manage thermal shock damage more effectively.展开更多
A DFN-DEC(discrete fracture network-distinct element code)method based on the MATLAB platform is developed to generate heterogeneous DFN.Subsequently,the effects of the spatial variability(the meanμand the standard d...A DFN-DEC(discrete fracture network-distinct element code)method based on the MATLAB platform is developed to generate heterogeneous DFN.Subsequently,the effects of the spatial variability(the meanμand the standard deviationσ)of the geometric properties(i.e.,the fracture dip D,the trace length T and the spacing S)of both the gently-dipping(denoted with 1)and the steeply-dipping(denoted with 2)fractures on the stability of granite slope are investigated.Results indicate that the proposed DFN-DEC method is robust,generating fracture networks that resemble reality.In addition,the spatial variability of fracture geometry,influencing the structure of granite slope,plays a significant role in slope stability.The mean stability of the slope decreases with the increase ofμ_(D_(1))(the mean of gently-dipping fracture dip),σ_(D_(2))(the mean of steeply-dipping fracture dip),μ_(T_(1))(the mean of gently-dipping fracture trace length),μ_(T_(2))(the mean of steeply-dipping fracture trace length),σ_(T_(1))(the standard deviation of gently-dipping fracture trace length),σ_(T_(2))(the standard deviation of steeply-dipping fracture trace length),and the decrease ofσ_(D_(1))(the standard deviation of gently-dipping fracture dip),μ_(D_(2))(the standard deviation of steeply-dipping fracture dip),μ_(S_(1))(the mean of gently-dipping fracture spacing)andμ_(S_(2))(the mean of steeply-dipping fracture spacing).Among them,μ_(T_(1)),μ_(D_(1))andμ_(S_(1))have the major impact.When the fracture spacing is large,the variability in the fracture geometry becomes less relevant to slope stability.When within some ranges of the fracture spacing,the spatial varying of dips can increase the slope stability by forming an interlaced structure.The results also show that the effects of the variability of trace length on slope stability depend on the variability of dip.These findings highlight the importance of spatial variability in the geometry of fractures to rock slope stability analysis.展开更多
Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunne...Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunnelling.In this study,a series of probabilistic analyses of surface and subsurface settlements was conducted considering the spatial variability of the friction angle and reference stiffness modulus,under different volumetric block proportions(Pv)and tunnel volume loss rates(ηt).The non-intrusive random finite difference method was used to investigate the probabilistic characteristics of maximum surface settlement,width of subsurface settlement trough,maximum subsurface settlement,and subsurface soil volume loss rate through Monte Carlo simulations.Additionally,a comparison between stochastic and deterministic analysis results is presented to underscore the significance of probabilistic analysis.Parametric analyses were subsequently conducted to investigate the impacts of the key input parameters in random fields on the settlement characteristics.The results indicate that scenarios with higher Pv or greaterηt result in a higher dispersion of stochastic analysis results.Neglecting the spatial variability of soil properties and relying solely on the mean values of material parameters for deterministic analysis may result in an underestimation of surface and subsurface settlements.From a probabilistic perspective,deterministic analysis alone may prove inadequate in accurately capturing the volumetric deformation mode of the soil above the tunnel crown,potentially affecting the prediction of subsurface settlement.展开更多
Surface ozone(O_(3))is a major air pollutant and draw increasing attention in the Pearl River Delta(PRD),China.Here,we characterize the spatial-temporal variability of ozone based on a dataset obtained from 57 nationa...Surface ozone(O_(3))is a major air pollutant and draw increasing attention in the Pearl River Delta(PRD),China.Here,we characterize the spatial-temporal variability of ozone based on a dataset obtained from 57 national monitoring sites during 2013-2019.Our results show that:(1)the seasonal difference of ozone distribution in the inland and coastal areas was significant,which was largely affected by the wind pattern reversals related to the East Asian monsoon,and local ozone production and destruction;(2)the daily maximum 8hr average(MDA8 O_(3))showed an overall upward trend by 1.11 ppbv/year.While the trends in the nine cities varied differently by ranging from-0.12 to 2.51 ppbv/year.The hot spots of ozone were spreading to southwestern areas from the central areas since 2016.And ozone is becoming a year-round air pollution problem with the pollution season extending to winter and spring in PRD region.(3)at the central and southwestern PRD cities,the percentage of exceedance days from the continuous type(defined as≥3 days)was increasing.Furthermore,the ozone concentration of continuous type was much higher than that of scattered exceedance type(<3 days).In addition,although the occurrence of continuous type starts to decline since2017,the total number of exceedance days during the continuous type is increasing.These results indicate that it is more difficult to eliminate the continuous exceedance than the scatter pollution days and highlight the great challenge in mitigation of O_(3)pollution in these cities.展开更多
Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stab...Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.展开更多
The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of ran...The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.展开更多
In this paper,six important distribution areas of Nitraria tangutorum Bobr.in Tsaidam Basin were selected as research objects,to study spatial variability and distribution of soil nutrients in different N.tangutorum p...In this paper,six important distribution areas of Nitraria tangutorum Bobr.in Tsaidam Basin were selected as research objects,to study spatial variability and distribution of soil nutrients in different N.tangutorum populations and analyze the relationship between soil nutrient contents and geographical location,by measuring soil pH and the contents of organic matter（OM）,total nitrogen（N）,total phosphorus（P）,total potassium（K）,hydrolysis N,available P and available K in soils.Results showed that：（1） soil nutrient contents among different populations showed significant spatial variability,and soil depth had a significant effect on soil nutrients contents,but the variation rules were not obvious.（2）Average pH and average contents of OM,total N,total P,total K,hydrolysis N,available P and available K in soils with different depths（0-15,15-30,30-45 cm） varied in the range of 8.37-9.21,3.34-20.68,0.18-1.21,0.35-0.75,16.12-22.04,5.13-553.28,1.10-52.54 and 103.83-562.28 mg/kg,respectively.（3） The analysis results of correlation between average values of pH and contents of nutrient indexes in soils with different depths（0-15,15-30,30-45 cm） showed that the correlation of these indexes were different.（4）OM and total N contents in soils with different depths（0-15,15-30,30-45 cm） all had a significant positive correlation with latitude and negative correlation with longitude and altitude,and the correlation of available P and available K contents in surface soils（0-15 cm） with latitude,longitude and altitude were significant positive,significant negative and significant negative,respectively;moreover,longitude and latitude also showed a significant impact on soil available K contents with the depth of 30-45 cm.In addition,comprehensive analysis result of nutrient contents showed that N.tangutorum populations in Huaitou Tala Town had the highest fertility,and the fertility levels of N.tangutorum populations in Chaka Town and Wulan Keke Town were relatively lower.展开更多
Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patte...Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns.This complexity poses significant challenges for slope stability analysis,requiring the development of specialized techniques to address these issues.This research presents a numerical methodology that incorporates spatial variability,nonlinear material characterization,and probabilistic analysis using a Monte Carlo framework to address this issue.The heterogeneous structure is represented by randomly assigning different lithotypes across the slope,while maintaining predefined global proportions.This contrasts with the more common approach of applying probabilistic variability to mechanical parameters within a homogeneous slope model.The material behavior is defined using complex nonlinear failure criteria,such as the Hoek-Brown model and a parabolic model with collapse,both implemented through linearization techniques.The Discontinuity Layout Optimization(DLO)method,a novel numerical approach based on limit analysis,is employed to efficiently incorporate these advances and compute the factor of safety of the slope.Within this framework,the Monte Carlo procedure is used to assess slope stability by conducting a large number of simulations,each with a different lithotype distribution.Based on the results,a hybrid method is proposed that combines probabilistic modeling with deterministic design principles for the slope stability assessment.As a case study,the methodology is applied to a 20-m-high vertical slope composed of three lithotypes(altered scoria,welded scoria,and basalt)randomly distributed in proportions of 15%,60%,and 25%,respectively.The results show convergence of mean values after approximately 400 simulations and highlight the significant influence of spatial heterogeneity,with variations of the factor of safety between 5 and 12 in 85%of cases.They also reveal non-circular and mid-slope failure wedges not captured by traditional stability methods.Finally,an equivalent normal probability distribution is proposed as a reliable approximation of the factor of safety for use in risk analysis and engineering decision-making.展开更多
Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation f...Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.展开更多
A total of 1400 soil samples from the plow layer （0-20 cm） at an approximate interval of 5 km were collected in the autumn of 2002 over the entire black soil arable crops region to determine the spatial variability ...A total of 1400 soil samples from the plow layer （0-20 cm） at an approximate interval of 5 km were collected in the autumn of 2002 over the entire black soil arable crops region to determine the spatial variability of seven variables, such as total organic matter content （OMC）, total N, total P, total K, alkali-dissolvable N （AN）, available P （AP） and available K （AK）, with classical statistics and geostatistical analysis across the entire black soil area in Northeast China. In nonsampled areas ordinary kriging was utilized for interpolation of estimated nutrient determinations. Classical statistics revealed highly significant （P ≤ 0.01） correlations with all seven of the soil properties, except for OMC with AP and total K with AK. In addition, using coefficients of variation, all soil properties, except for total K, were moderately variable. A geostatistical analysis indicated that structural factors, such as parent material, terrain, and water table, were the main causes of the spatial correlations. Strong spatial correlations were noted with OMC, total N, total P, AN, and AP, while they were moderate for total K and AK. The effective spatial autocorrelation of OMC, total N, total P, and AN ranged from 1 037 to 1353 km, whereas the ranges of total K, AP, and AK were only from 6 to 138 km. The fit of the experimental scmi-variograms to the theoretical models indicated that except for AN, kriging could successfully interpolate other six variables. Thns, the geostatistical method used on a large scale could accurately evaluate the spatial variability of most black soil nutrient properties in Northeast China.展开更多
To identify the main sources responsible for soil heavy metal contamination, 70 topsoils were sampled from the Daxing County in the urban-rural transition zone of Beijing. The concentrations of heavy metals Cu, Zn, Pb...To identify the main sources responsible for soil heavy metal contamination, 70 topsoils were sampled from the Daxing County in the urban-rural transition zone of Beijing. The concentrations of heavy metals Cu, Zn, Pb, Cr, Cd, Ni, As, Se, Hg, and Co; the soil texture; and the organic matter content were determined for each soil sample. Descriptive statistics and geostatistics were used to analyze the data, and Kriging analysis was used to estimate the unobserved points and to map the spatial patterns of soil heavy metals. The results showed that the concentrations of all the soil heavy metals exceeded their background levels with the exception of As and Se. However, only the Cd concentration in some areas exceeded the critical value of the national soil quality standard. The semivariance analysis showed that the spatial correlation distances for soil Cu, Zn, Cr, Cd, As, Ni, and Co ranged from 4.0 to 7.0 km, but soil Se, Pb, and Hg had a larger correlation distance. Soil Co, Se, Cd, Cu and Zn showed a strong spatial correlation, whereas the other soil heavy metals showed medium spatial correlation. Soil heavy metal concentrations were related to soil texture, organic matter content, and the accumulation of heavy metals in the soils, which was because of air deposition and use of water from the Liangshui, Xinfeng, and Fenghe rivers that are contaminated by wastewater and sewage for the purpose of irrigation of fields. Hence, a comprehensive treatment plan for these rivers should be formulated.展开更多
Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatis...Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatistical techniques provide a valid scientific approach to cope with spatial variability, to interpolate existing data and to predict values at unsampled locations for accurate SOM status survey. Using geostatistical and geographic information system (GIS) approaches, the spatial variability of some physical and chemical soil parameters was investigated under Mediterranean climatic condition in the Abruzzo region of central Italy, where soil erosion processes accelerated by human induced factors are the main causes of soil degradation associated with low SOM content. Experimental semivariograms were established to determine the spatial dependence of the soil variables under investigation. The results of 250 soil sampling point data were interpolated by means of ordinary kriging coupled with a GIS to produce contour maps distribution of soil texture, SOM content related to texture, and C/N ratio. The resulting spatial interpolation of the dataset highlighted a low content of SOM in relation with soil texture in most of the surveyed area (87%) and an optimal C/N ratio for only half of the investigated surface area. Spatial location of degraded area and the assessment of its magnitude can provide decision makers with an accurate support to design appropriate soil conservation strategies and then facilitate a regional planning of agri-environmental measures in the framework of the European Common Agricultural Policy.展开更多
Nitrogen, phosphorus, and potassium balances for agroecosystems in China from 1993 to 2001 were calculated at national and provincial levels using statistical data and related parameters, and their spatial and tempora...Nitrogen, phosphorus, and potassium balances for agroecosystems in China from 1993 to 2001 were calculated at national and provincial levels using statistical data and related parameters, and their spatial and temporal variabilities were analyzed with GIS to estimate the potential impacts of nutrient N, P and K surpluses or deficits to soil, water and air. At the national scale, the N and P balances from 1993 to 2001 showed a surplus, with the nitrogen surplus remaining relatively stable from 1997—2001. Although during this period the P surplus pattern was similar to N, it had smaller values and kept increasing as the use of phosphate fertilizer increased year by year. However, K was deficient from 1993 to 2001 even though from 1999 to 2001 the K deficit decreased. The spatial analysis revealed higher N surpluses in the more developed southeastern provinces and lowest in the western and northern provinces where there was less chemical fertilizer input. The serious K deficit mainly occurred in Shanghai and Beijing municipalities, Jiangsu, Zhejiang and Hubei provinces, and Xinjiang autonomous regions. For the years 1992, 1996 and 2001, N surpluses and K deficits had significant positive spatial correlations with per capita gross domestic product (GDP), per capita gross industrial output value, and per capita net income of rural households. This showed that the level of economic development played an important role on nutrient balances in the agroecosystems.展开更多
There is a limited knowledge of spatial heterogeneity in soil nutrients and soil respiration in the semi-arid and arid grasslands of China. This study investigated the spatial differences in soil nutrients and soil re...There is a limited knowledge of spatial heterogeneity in soil nutrients and soil respiration in the semi-arid and arid grasslands of China. This study investigated the spatial differences in soil nutrients and soil respiration among three desertified grasslands and within two shrub-dominated communities on the Ordos Plateau of Inner Mongolia, China in 2006. Both soil organic carbon （SOC） and total nitrogen （TN） were significantly different （P 〈 0.01） among the three desertified grasslands along a degradation gradient. Within the two shrub-dominated communities, the SOC and TN contents decreased with increasing distance from the main stems of the shrub, and this ＂fertile island＂ effect was most pronounced in the surface soil. The total soil respirations during the growing season were 131.26, 95.95, and 118.66 g C m^-2, respectively, for the steppe, shrub, and shrub-perennial grass communities. The coefficient of variability of soil respiration was the highest in the shrub community and lowest in the steppe community. CO2 effiuxes from the soil under the canopy of shrub were significantly higher than those from the soil covered with biological crusts and the bare soil in the interplant spaces in the shrub community. However, soil respiration beneath the shrubs was not different from that of the soil in the inter-shrub of the shrub-perennial grass community. This is probably due to the smaller shrub size. In the two shrub-dominated communities, spatial variability in soil respiration was found to depend on soil water content and C：N ratio.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
Soil organic carbon （SOC） is an effective indicator of soil fertility and productivity, and it varies spatially and temporally in relation to other soil properties. Spatial variability of SOC in the forestlands of n...Soil organic carbon （SOC） is an effective indicator of soil fertility and productivity, and it varies spatially and temporally in relation to other soil properties. Spatial variability of SOC in the forestlands of northeast China was characterized using geostatistics. Soil samples at the depths of 0-20 era, 20-40 cm and 40-60 cm were collected from six- ty-three temporary plots to evaluate SOC concentration and density （SOCD） and other soil properties. We analyzed correlations between SOC and soil properties. Soil organic carbon concentrations were high. The total amount of C stored in soil （0-60 cm） was 16.23 kg·m-2 with the highest SOCD of 7.98 kg·m-2 in topsoil. Soil properties in most cases differed by horizon, suggesting different processes and effects in each horizon. Soil organic carbon had positive relationships with total N, P and K as well as readily available K, but did not show a significant posi- tive correlation with available P. Spatial factors including elevation, slope and aspect affected SOC distribution. Soil organic carbon at 0-60 cm had strong spatial autocorrelation with nugget/sill ratio of 5.7%, and moderate structured dependence was found at 0-20 cm, which indicated the existence of a highly developed spatial structure. Spatial distributionsof SOC concentration and SOCD were estimated using regres- sion-kriging, with higher prediction accuracy than ordinary kriging. The fractal dimension of SOC indicated the preferential pattern of SOC dis- tribution, with the greatest spatial heterogeneity and strongest spatial dependence in the northeast-southwest direction.展开更多
This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the infl...This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the influences of the multiscale spatial variability of soil properties on the probability of failure(P_f) of the slopes. In the proposed approach, the relationship between the factor of safety and the soil strength parameters characterized with spatial variability is approximated by the MARS, with the aid of Karhunen-Loeve expansion. MCS is subsequently performed on the established MARS model to evaluate Pf.Finally, a nominally homogeneous cohesive-frictional slope and a heterogeneous cohesive slope, which are both characterized with different spatial variabilities, are utilized to illustrate the proposed approach.Results showed that the proposed approach can estimate the P_f of the slopes efficiently in spatially variable soils with sufficient accuracy. Moreover, the approach is relatively robust to the influence of different statistics of soil properties, thereby making it an effective and practical tool for addressing slope reliability problems concerning time-consuming deterministic stability models with low levels of P_f.Furthermore, disregarding the multiscale spatial variability of soil properties can overestimate or underestimate the P_f. Although the difference is small in general, the multiscale spatial variability of the soil properties must still be considered in the reliability analysis of heterogeneous slopes, especially for those highly related to cost effective and accurate designs.展开更多
The soil properties in arid ecosystems are important determinants of vegetation distribution patterns. Soil organic carbon （SOC） content, which is closely related to soil types and the holding capacities of soil wat...The soil properties in arid ecosystems are important determinants of vegetation distribution patterns. Soil organic carbon （SOC） content, which is closely related to soil types and the holding capacities of soil water and nutrients, exhibits complex variability in arid desert grasslands; thus, it is essentially an impact factor for the distri- bution pattern of desert grasslands. In the present study, an investigation was conducted to estimate the spatial pattern of SOC content in desert grasslands and the association with environmental factors in the diluvial-alluvial plains of northern Qilian Mountains. The results showed that the mean values of SOC ranged from 2.76 to 5.80 g/kg in the soil profiles, and decreased with soil depths. The coefficients of variation （CV） of the SOC were high （ranging from 48.83% to 94.67%）, which indicated a strong spatial variability. SOC in the desert grasslands of the study re- gion presented a regular spatial distribution, which increased gradually from the northwest to the southeast. The SOC distribution had a pattern linked to elevation, which may be related to the gradient of climate conditions. Soil type and plant community significantly affected the SOC. The SOC had a significant positive relationship with soil moisture （P〈0.05）; whereas, it had a more significant negative relationship with the soil bulk density （BD） （P〈0.01）. However, a number of the variations in the SOC could be explained not by the environmental factors involved in this analysis, but rather other factors （such as grazing activity and landscape）. The results provide important references for soil carbon storage estimation in this study region. In addition, the SOC association with environmental variables also provides a basis for a sustainable use of the limited grassland resources in the diluvial-alluvial plains of north- ern Qilian Mountains.展开更多
Slope reliability analysis considering inherent spatial variability(ISV)of soil properties is timeconsuming when response surface method(RSM)is used,because of the"curse of dimensionality".This paper propose...Slope reliability analysis considering inherent spatial variability(ISV)of soil properties is timeconsuming when response surface method(RSM)is used,because of the"curse of dimensionality".This paper proposes an effective method for identification of representative slip surfaces(RSSs)of slopes with spatially varied soils within the framework of limit equilibrium method(LEM),which utilizes an adaptive K-means clustering approach.Then,an improved slope reliability analysis based on the RSSs and RSM considering soil spatial variability,in perspective of computation efficiency,is established.The detailed implementation procedure of the proposed method is well documented,and the ability of the method in identifying RSSs and estimating reliability is investigated via three slope examples.Results show that the proposed method can automatically identify the RSSs of slope with only one evaluation of the conventional deterministic slope stability model.The RSSs are invariant with the statistics of soil properties,which allows parametric studies that are often required in slope reliability analysis to be efficiently achieved with ease.It is also found that the proposed method provides comparable values of factor of safety(FS)and probability of failure(Pf)of slopes with those obtained from direct analysis and lite rature.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
基金financially supported by the National Natural Science Foundation of China(Grant No.51874207)the Natural Science Foundation of Shanxi Province(Grant Nos.202303021211042 and 202303011222006).
文摘This research employs micro-CT scanning technology to analyze the porosity,pore fractal dimension,and spatial variability of sandstone preheated to 600℃ and subsequently cooled in water at varying temperatures(20℃,60℃,100℃).The study investigates the mechanisms by which various factors influence thermal shock damage,focusing on the effects of cooling water temperature and the boiling phase transition.The objective is to develop a method for characterizing thermal shock damage that considers spatial variability.The findings indicate that thermal shock damage is limited to a shallow depth beneath the surface,with increased severity near the surface.The boiling phase transition significantly enhances the convective heat transfer coefficient,resulting in substantially higher thermal shock damage when cooled with 100℃ boiling water compared to 20℃ and 60℃ water.Furthermore,for the entire specimen,heating damage exceeds thermal shock damage,and the influence of thermal shock diminishes as specimen size increases.This study addresses the limitations of traditional methods for assessing thermal shock damage that disregard spatial variability and provides practical guidance for engineering projects to manage thermal shock damage more effectively.
基金supported by the National Natural Science Foundation of China(Nos.41807264,41972289)the Engineering Research Center of Rock-Soil Drilling&Excavation and Protection,Ministry of Education(No.202102)+3 种基金the Key Laboratory of Geological Hazards on Three Gorges Reservoir Area(China Three Gorges University),Ministry of Education(No.2020KDZ01)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(Nos.CUG170686,CUGQY1932)the China Scholarship Council(No.201406410032)the Science and Technology Research Project of Education Department of Hubei Province(Nos.B2019452,B2024509)。
文摘A DFN-DEC(discrete fracture network-distinct element code)method based on the MATLAB platform is developed to generate heterogeneous DFN.Subsequently,the effects of the spatial variability(the meanμand the standard deviationσ)of the geometric properties(i.e.,the fracture dip D,the trace length T and the spacing S)of both the gently-dipping(denoted with 1)and the steeply-dipping(denoted with 2)fractures on the stability of granite slope are investigated.Results indicate that the proposed DFN-DEC method is robust,generating fracture networks that resemble reality.In addition,the spatial variability of fracture geometry,influencing the structure of granite slope,plays a significant role in slope stability.The mean stability of the slope decreases with the increase ofμ_(D_(1))(the mean of gently-dipping fracture dip),σ_(D_(2))(the mean of steeply-dipping fracture dip),μ_(T_(1))(the mean of gently-dipping fracture trace length),μ_(T_(2))(the mean of steeply-dipping fracture trace length),σ_(T_(1))(the standard deviation of gently-dipping fracture trace length),σ_(T_(2))(the standard deviation of steeply-dipping fracture trace length),and the decrease ofσ_(D_(1))(the standard deviation of gently-dipping fracture dip),μ_(D_(2))(the standard deviation of steeply-dipping fracture dip),μ_(S_(1))(the mean of gently-dipping fracture spacing)andμ_(S_(2))(the mean of steeply-dipping fracture spacing).Among them,μ_(T_(1)),μ_(D_(1))andμ_(S_(1))have the major impact.When the fracture spacing is large,the variability in the fracture geometry becomes less relevant to slope stability.When within some ranges of the fracture spacing,the spatial varying of dips can increase the slope stability by forming an interlaced structure.The results also show that the effects of the variability of trace length on slope stability depend on the variability of dip.These findings highlight the importance of spatial variability in the geometry of fractures to rock slope stability analysis.
基金supported by the Natural Science Foundation of Beijing Municipality(No.8222004),Chinathe National Natural Science Foundation of China(No.51978019)+3 种基金the Natural Science Foundation of Henan Province(No.252300420445),Chinathe Doctoral Research Initiation Fund of Henan University of Science and Technology(No.4007/13480062),Chinathe Henan Postdoctoral Foundation(No.13554005),Chinathe Joint Fund of Science and Technology R&D Program of Henan Province(No.232103810082),China。
文摘Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunnelling.In this study,a series of probabilistic analyses of surface and subsurface settlements was conducted considering the spatial variability of the friction angle and reference stiffness modulus,under different volumetric block proportions(Pv)and tunnel volume loss rates(ηt).The non-intrusive random finite difference method was used to investigate the probabilistic characteristics of maximum surface settlement,width of subsurface settlement trough,maximum subsurface settlement,and subsurface soil volume loss rate through Monte Carlo simulations.Additionally,a comparison between stochastic and deterministic analysis results is presented to underscore the significance of probabilistic analysis.Parametric analyses were subsequently conducted to investigate the impacts of the key input parameters in random fields on the settlement characteristics.The results indicate that scenarios with higher Pv or greaterηt result in a higher dispersion of stochastic analysis results.Neglecting the spatial variability of soil properties and relying solely on the mean values of material parameters for deterministic analysis may result in an underestimation of surface and subsurface settlements.From a probabilistic perspective,deterministic analysis alone may prove inadequate in accurately capturing the volumetric deformation mode of the soil above the tunnel crown,potentially affecting the prediction of subsurface settlement.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research (No.2020B0301030004)the National Natural Science Foundation of China (No.42175111)+1 种基金the Guangdong science and technology plan project (No.2019B121201002)the Fundamental Research Funds for the Central Universities,Sun Yat-sen University (No.22qntd1908)。
文摘Surface ozone(O_(3))is a major air pollutant and draw increasing attention in the Pearl River Delta(PRD),China.Here,we characterize the spatial-temporal variability of ozone based on a dataset obtained from 57 national monitoring sites during 2013-2019.Our results show that:(1)the seasonal difference of ozone distribution in the inland and coastal areas was significant,which was largely affected by the wind pattern reversals related to the East Asian monsoon,and local ozone production and destruction;(2)the daily maximum 8hr average(MDA8 O_(3))showed an overall upward trend by 1.11 ppbv/year.While the trends in the nine cities varied differently by ranging from-0.12 to 2.51 ppbv/year.The hot spots of ozone were spreading to southwestern areas from the central areas since 2016.And ozone is becoming a year-round air pollution problem with the pollution season extending to winter and spring in PRD region.(3)at the central and southwestern PRD cities,the percentage of exceedance days from the continuous type(defined as≥3 days)was increasing.Furthermore,the ozone concentration of continuous type was much higher than that of scattered exceedance type(<3 days).In addition,although the occurrence of continuous type starts to decline since2017,the total number of exceedance days during the continuous type is increasing.These results indicate that it is more difficult to eliminate the continuous exceedance than the scatter pollution days and highlight the great challenge in mitigation of O_(3)pollution in these cities.
基金supported by the National Natural Science Foundation of China(Grant No.52308340)the Innovative Projects of Universities in Guangdong(Grant No.2022KTSCX208)Sichuan Transportation Science and Technology Project(Grant No.2018-ZL-01).
文摘Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.
基金supported by the National Natural Science Foundation of China(Grant No.U22A20594)the Fundamental Research Funds for the Central Universities(Grant No.B230205028)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX23_0694).
文摘The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.
基金Supported by the Special Scientific Research Project of Forestry Public Welfare Profession(200904033)The Project of Agricultural Science and Technology Achievements Transformation Fund(2011GB24320010)~~
文摘In this paper,six important distribution areas of Nitraria tangutorum Bobr.in Tsaidam Basin were selected as research objects,to study spatial variability and distribution of soil nutrients in different N.tangutorum populations and analyze the relationship between soil nutrient contents and geographical location,by measuring soil pH and the contents of organic matter（OM）,total nitrogen（N）,total phosphorus（P）,total potassium（K）,hydrolysis N,available P and available K in soils.Results showed that：（1） soil nutrient contents among different populations showed significant spatial variability,and soil depth had a significant effect on soil nutrients contents,but the variation rules were not obvious.（2）Average pH and average contents of OM,total N,total P,total K,hydrolysis N,available P and available K in soils with different depths（0-15,15-30,30-45 cm） varied in the range of 8.37-9.21,3.34-20.68,0.18-1.21,0.35-0.75,16.12-22.04,5.13-553.28,1.10-52.54 and 103.83-562.28 mg/kg,respectively.（3） The analysis results of correlation between average values of pH and contents of nutrient indexes in soils with different depths（0-15,15-30,30-45 cm） showed that the correlation of these indexes were different.（4）OM and total N contents in soils with different depths（0-15,15-30,30-45 cm） all had a significant positive correlation with latitude and negative correlation with longitude and altitude,and the correlation of available P and available K contents in surface soils（0-15 cm） with latitude,longitude and altitude were significant positive,significant negative and significant negative,respectively;moreover,longitude and latitude also showed a significant impact on soil available K contents with the depth of 30-45 cm.In addition,comprehensive analysis result of nutrient contents showed that N.tangutorum populations in Huaitou Tala Town had the highest fertility,and the fertility levels of N.tangutorum populations in Chaka Town and Wulan Keke Town were relatively lower.
基金the project PID2022-139202OB-I00Neural Networks and Optimization Techniques for the Design and Safe Maintenance of Transportation Infrastructures:Volcanic Rock Geotechnics and Slope Stability(IA-Pyroslope),funded by the Spanish State Research Agency of the Ministry of Science,Innovation and Universities of Spain and the European Regional Development Fund,MCIN/AEI/10.13039/501100011033/FEDER,EU。
文摘Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes,resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns.This complexity poses significant challenges for slope stability analysis,requiring the development of specialized techniques to address these issues.This research presents a numerical methodology that incorporates spatial variability,nonlinear material characterization,and probabilistic analysis using a Monte Carlo framework to address this issue.The heterogeneous structure is represented by randomly assigning different lithotypes across the slope,while maintaining predefined global proportions.This contrasts with the more common approach of applying probabilistic variability to mechanical parameters within a homogeneous slope model.The material behavior is defined using complex nonlinear failure criteria,such as the Hoek-Brown model and a parabolic model with collapse,both implemented through linearization techniques.The Discontinuity Layout Optimization(DLO)method,a novel numerical approach based on limit analysis,is employed to efficiently incorporate these advances and compute the factor of safety of the slope.Within this framework,the Monte Carlo procedure is used to assess slope stability by conducting a large number of simulations,each with a different lithotype distribution.Based on the results,a hybrid method is proposed that combines probabilistic modeling with deterministic design principles for the slope stability assessment.As a case study,the methodology is applied to a 20-m-high vertical slope composed of three lithotypes(altered scoria,welded scoria,and basalt)randomly distributed in proportions of 15%,60%,and 25%,respectively.The results show convergence of mean values after approximately 400 simulations and highlight the significant influence of spatial heterogeneity,with variations of the factor of safety between 5 and 12 in 85%of cases.They also reveal non-circular and mid-slope failure wedges not captured by traditional stability methods.Finally,an equivalent normal probability distribution is proposed as a reliable approximation of the factor of safety for use in risk analysis and engineering decision-making.
基金supported by the National Natural Science Foundation of China(Grant No.U22A20596)the Shenzhen Science and Technology Program(Grant No.GJHZ20220913142605010)the Jinan Lead Researcher Project(Grant No.202333051).
文摘Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.
基金Project supported by the National Basic Research Program (973 Program) of China (No. 2005CB121108) the Heilongjiang Provincial Natural Science Foundation of China (No. C2004-25).
文摘A total of 1400 soil samples from the plow layer （0-20 cm） at an approximate interval of 5 km were collected in the autumn of 2002 over the entire black soil arable crops region to determine the spatial variability of seven variables, such as total organic matter content （OMC）, total N, total P, total K, alkali-dissolvable N （AN）, available P （AP） and available K （AK）, with classical statistics and geostatistical analysis across the entire black soil area in Northeast China. In nonsampled areas ordinary kriging was utilized for interpolation of estimated nutrient determinations. Classical statistics revealed highly significant （P ≤ 0.01） correlations with all seven of the soil properties, except for OMC with AP and total K with AK. In addition, using coefficients of variation, all soil properties, except for total K, were moderately variable. A geostatistical analysis indicated that structural factors, such as parent material, terrain, and water table, were the main causes of the spatial correlations. Strong spatial correlations were noted with OMC, total N, total P, AN, and AP, while they were moderate for total K and AK. The effective spatial autocorrelation of OMC, total N, total P, and AN ranged from 1 037 to 1353 km, whereas the ranges of total K, AP, and AK were only from 6 to 138 km. The fit of the experimental scmi-variograms to the theoretical models indicated that except for AN, kriging could successfully interpolate other six variables. Thns, the geostatistical method used on a large scale could accurately evaluate the spatial variability of most black soil nutrient properties in Northeast China.
基金Project supported by the National Natural Science Foundation of China (Nos. 40401025 and 49871005)the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT0412)
文摘To identify the main sources responsible for soil heavy metal contamination, 70 topsoils were sampled from the Daxing County in the urban-rural transition zone of Beijing. The concentrations of heavy metals Cu, Zn, Pb, Cr, Cd, Ni, As, Se, Hg, and Co; the soil texture; and the organic matter content were determined for each soil sample. Descriptive statistics and geostatistics were used to analyze the data, and Kriging analysis was used to estimate the unobserved points and to map the spatial patterns of soil heavy metals. The results showed that the concentrations of all the soil heavy metals exceeded their background levels with the exception of As and Se. However, only the Cd concentration in some areas exceeded the critical value of the national soil quality standard. The semivariance analysis showed that the spatial correlation distances for soil Cu, Zn, Cr, Cd, As, Ni, and Co ranged from 4.0 to 7.0 km, but soil Se, Pb, and Hg had a larger correlation distance. Soil Co, Se, Cd, Cu and Zn showed a strong spatial correlation, whereas the other soil heavy metals showed medium spatial correlation. Soil heavy metal concentrations were related to soil texture, organic matter content, and the accumulation of heavy metals in the soils, which was because of air deposition and use of water from the Liangshui, Xinfeng, and Fenghe rivers that are contaminated by wastewater and sewage for the purpose of irrigation of fields. Hence, a comprehensive treatment plan for these rivers should be formulated.
基金Supported by the Italian Ministry of Agricultural, Food and Forestry Policies (No. DM 19366)
文摘Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatistical techniques provide a valid scientific approach to cope with spatial variability, to interpolate existing data and to predict values at unsampled locations for accurate SOM status survey. Using geostatistical and geographic information system (GIS) approaches, the spatial variability of some physical and chemical soil parameters was investigated under Mediterranean climatic condition in the Abruzzo region of central Italy, where soil erosion processes accelerated by human induced factors are the main causes of soil degradation associated with low SOM content. Experimental semivariograms were established to determine the spatial dependence of the soil variables under investigation. The results of 250 soil sampling point data were interpolated by means of ordinary kriging coupled with a GIS to produce contour maps distribution of soil texture, SOM content related to texture, and C/N ratio. The resulting spatial interpolation of the dataset highlighted a low content of SOM in relation with soil texture in most of the surveyed area (87%) and an optimal C/N ratio for only half of the investigated surface area. Spatial location of degraded area and the assessment of its magnitude can provide decision makers with an accurate support to design appropriate soil conservation strategies and then facilitate a regional planning of agri-environmental measures in the framework of the European Common Agricultural Policy.
基金1Project supported by the Knowledge Innovation Program of Chinese Academy of Sciences (No. KZCX2-413).
文摘Nitrogen, phosphorus, and potassium balances for agroecosystems in China from 1993 to 2001 were calculated at national and provincial levels using statistical data and related parameters, and their spatial and temporal variabilities were analyzed with GIS to estimate the potential impacts of nutrient N, P and K surpluses or deficits to soil, water and air. At the national scale, the N and P balances from 1993 to 2001 showed a surplus, with the nitrogen surplus remaining relatively stable from 1997—2001. Although during this period the P surplus pattern was similar to N, it had smaller values and kept increasing as the use of phosphate fertilizer increased year by year. However, K was deficient from 1993 to 2001 even though from 1999 to 2001 the K deficit decreased. The spatial analysis revealed higher N surpluses in the more developed southeastern provinces and lowest in the western and northern provinces where there was less chemical fertilizer input. The serious K deficit mainly occurred in Shanghai and Beijing municipalities, Jiangsu, Zhejiang and Hubei provinces, and Xinjiang autonomous regions. For the years 1992, 1996 and 2001, N surpluses and K deficits had significant positive spatial correlations with per capita gross domestic product (GDP), per capita gross industrial output value, and per capita net income of rural households. This showed that the level of economic development played an important role on nutrient balances in the agroecosystems.
基金Supported by the National Natural Science Foundation of China(Nos.40730105,40501072 and 40973057)the National"Eleventh Five Years Plan"Key Project on Science and Technology of China(No.2007BAC03A11)
文摘There is a limited knowledge of spatial heterogeneity in soil nutrients and soil respiration in the semi-arid and arid grasslands of China. This study investigated the spatial differences in soil nutrients and soil respiration among three desertified grasslands and within two shrub-dominated communities on the Ordos Plateau of Inner Mongolia, China in 2006. Both soil organic carbon （SOC） and total nitrogen （TN） were significantly different （P 〈 0.01） among the three desertified grasslands along a degradation gradient. Within the two shrub-dominated communities, the SOC and TN contents decreased with increasing distance from the main stems of the shrub, and this ＂fertile island＂ effect was most pronounced in the surface soil. The total soil respirations during the growing season were 131.26, 95.95, and 118.66 g C m^-2, respectively, for the steppe, shrub, and shrub-perennial grass communities. The coefficient of variability of soil respiration was the highest in the shrub community and lowest in the steppe community. CO2 effiuxes from the soil under the canopy of shrub were significantly higher than those from the soil covered with biological crusts and the bare soil in the interplant spaces in the shrub community. However, soil respiration beneath the shrubs was not different from that of the soil in the inter-shrub of the shrub-perennial grass community. This is probably due to the smaller shrub size. In the two shrub-dominated communities, spatial variability in soil respiration was found to depend on soil water content and C：N ratio.
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supported by Natural ScienceFoundation of China(No.31270697)the Fundamental Research Fundsfor the Central Universities(TD2011-2)+1 种基金State Forestry Administrative public service sector project"Key management techniques for the health of typical forest types in China"(20100400201)National‘973’project"Soil carbon stock and its temporal and spatial distribution pattern in natural forests"(2011CB403201)
文摘Soil organic carbon （SOC） is an effective indicator of soil fertility and productivity, and it varies spatially and temporally in relation to other soil properties. Spatial variability of SOC in the forestlands of northeast China was characterized using geostatistics. Soil samples at the depths of 0-20 era, 20-40 cm and 40-60 cm were collected from six- ty-three temporary plots to evaluate SOC concentration and density （SOCD） and other soil properties. We analyzed correlations between SOC and soil properties. Soil organic carbon concentrations were high. The total amount of C stored in soil （0-60 cm） was 16.23 kg·m-2 with the highest SOCD of 7.98 kg·m-2 in topsoil. Soil properties in most cases differed by horizon, suggesting different processes and effects in each horizon. Soil organic carbon had positive relationships with total N, P and K as well as readily available K, but did not show a significant posi- tive correlation with available P. Spatial factors including elevation, slope and aspect affected SOC distribution. Soil organic carbon at 0-60 cm had strong spatial autocorrelation with nugget/sill ratio of 5.7%, and moderate structured dependence was found at 0-20 cm, which indicated the existence of a highly developed spatial structure. Spatial distributionsof SOC concentration and SOCD were estimated using regres- sion-kriging, with higher prediction accuracy than ordinary kriging. The fractal dimension of SOC indicated the preferential pattern of SOC dis- tribution, with the greatest spatial heterogeneity and strongest spatial dependence in the northeast-southwest direction.
基金supported by The Hong Kong Polytechnic University through the project RU3Ythe Research Grant Council through the project PolyU 5128/13E+1 种基金National Natural Science Foundation of China(Grant No.51778313)Cooperative Innovation Center of Engineering Construction and Safety in Shangdong Blue Economic Zone
文摘This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the influences of the multiscale spatial variability of soil properties on the probability of failure(P_f) of the slopes. In the proposed approach, the relationship between the factor of safety and the soil strength parameters characterized with spatial variability is approximated by the MARS, with the aid of Karhunen-Loeve expansion. MCS is subsequently performed on the established MARS model to evaluate Pf.Finally, a nominally homogeneous cohesive-frictional slope and a heterogeneous cohesive slope, which are both characterized with different spatial variabilities, are utilized to illustrate the proposed approach.Results showed that the proposed approach can estimate the P_f of the slopes efficiently in spatially variable soils with sufficient accuracy. Moreover, the approach is relatively robust to the influence of different statistics of soil properties, thereby making it an effective and practical tool for addressing slope reliability problems concerning time-consuming deterministic stability models with low levels of P_f.Furthermore, disregarding the multiscale spatial variability of soil properties can overestimate or underestimate the P_f. Although the difference is small in general, the multiscale spatial variability of the soil properties must still be considered in the reliability analysis of heterogeneous slopes, especially for those highly related to cost effective and accurate designs.
基金Strategic Priority Research Program of the Chinese Academy of Sciences (XDA05050406-3)National Natural Science Foundation of China (41201284 and 91125022)
文摘The soil properties in arid ecosystems are important determinants of vegetation distribution patterns. Soil organic carbon （SOC） content, which is closely related to soil types and the holding capacities of soil water and nutrients, exhibits complex variability in arid desert grasslands; thus, it is essentially an impact factor for the distri- bution pattern of desert grasslands. In the present study, an investigation was conducted to estimate the spatial pattern of SOC content in desert grasslands and the association with environmental factors in the diluvial-alluvial plains of northern Qilian Mountains. The results showed that the mean values of SOC ranged from 2.76 to 5.80 g/kg in the soil profiles, and decreased with soil depths. The coefficients of variation （CV） of the SOC were high （ranging from 48.83% to 94.67%）, which indicated a strong spatial variability. SOC in the desert grasslands of the study re- gion presented a regular spatial distribution, which increased gradually from the northwest to the southeast. The SOC distribution had a pattern linked to elevation, which may be related to the gradient of climate conditions. Soil type and plant community significantly affected the SOC. The SOC had a significant positive relationship with soil moisture （P〈0.05）; whereas, it had a more significant negative relationship with the soil bulk density （BD） （P〈0.01）. However, a number of the variations in the SOC could be explained not by the environmental factors involved in this analysis, but rather other factors （such as grazing activity and landscape）. The results provide important references for soil carbon storage estimation in this study region. In addition, the SOC association with environmental variables also provides a basis for a sustainable use of the limited grassland resources in the diluvial-alluvial plains of north- ern Qilian Mountains.
基金The work described in this paper was nancially supported by the Natural Science Foundation of China(Grant Nos.51709258,51979270 and 41902291),the CAS Pioneer Hundred Talents Pro-gram and the Research Foundation of Key Laboratory of Deep Geodrilling Technology,Ministry of Land and Resources,China(Grant No.F201801).
文摘Slope reliability analysis considering inherent spatial variability(ISV)of soil properties is timeconsuming when response surface method(RSM)is used,because of the"curse of dimensionality".This paper proposes an effective method for identification of representative slip surfaces(RSSs)of slopes with spatially varied soils within the framework of limit equilibrium method(LEM),which utilizes an adaptive K-means clustering approach.Then,an improved slope reliability analysis based on the RSSs and RSM considering soil spatial variability,in perspective of computation efficiency,is established.The detailed implementation procedure of the proposed method is well documented,and the ability of the method in identifying RSSs and estimating reliability is investigated via three slope examples.Results show that the proposed method can automatically identify the RSSs of slope with only one evaluation of the conventional deterministic slope stability model.The RSSs are invariant with the statistics of soil properties,which allows parametric studies that are often required in slope reliability analysis to be efficiently achieved with ease.It is also found that the proposed method provides comparable values of factor of safety(FS)and probability of failure(Pf)of slopes with those obtained from direct analysis and lite rature.
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.
