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Spatial variability of groundwater nitrate in the loess area of Tongchuan City,China:New insights from farmland leaching quantification 认领 引用
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作者 Wei Zhao Peiyue Li +5 位作者 Tiantian Wang Fangqiang Sun Fang Zhang Jia Yang Jing Ning Misbah Fida 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第5期512-521,共10页
High groundwater nitrate associated with agricultural activity is a global environmental problem.However,linking spatial variability of groundwater nitrate and agricultural activity quantification needs to be elucidat... High groundwater nitrate associated with agricultural activity is a global environmental problem.However,linking spatial variability of groundwater nitrate and agricultural activity quantification needs to be elucidated.This paper seeks to explain the spatial variability of groundwater nitrate in the loess area of Tongchuan City,China,identify the contributing factors using hydrogeochemical and statistical methods,and analyze the connection between farmland leaching and groundwater nitrate quantitatively.Results indicate that the nitrate of the Quaternary alluvial pore water(QAP)is significantly higher during the wet season(3.60 to 68.24 mg/L)compared to the dry season(3.53 to 37.20 mg/L).QAP nitrate is significantly higher than that in loess fissure-pore water(LFP),which ranges from 0.66 to 5.47 mg/L during the wet season and 0.82 to 5.01 mg/L during the dry season.The thin and loose vadose zone of QAP makes the aquifer particularly susceptible to anthropogenic influences.Following recharge from LFP,the hydrochemical parameters in QAP increased by 1.22 to 3.12 times(except Na+and pH),the change of average nitrate concentration in QAP(10.11 mg/L)was considerably higher than that in LFP(0.03 mg/L)due to farmland leaching.A significant correlation(R2=0.70 exists between groundwater nitrate and farmland leaching in river valleys and on slopes where farmland is prevalent.Fertilizer accumulation in river valleys enhances downward leaching,thereby further exacerbating groundwater nitrate.These findings highlight that river valleys with extensive farmland in the Loess Plateau should be prioritized for preventing and controlling groundwater nitrate pollution from agricultural activities. 展开更多
关键词 Spatial variability Hydrogeochemistry Statistical analysis Quantitative analysis Farmland leaching
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Spatial variability and quantitative characterization of thermal shock damage in sandstone under different cooling temperatures 认领 引用 被引量：2
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作者 Shuixin He Baoping Xi +4 位作者 Yangsheng Zhao Jin Xie Yunsheng Dong Luhai Chen Xinxin Yang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第7期4367-4385,共19页
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
关键词 Sandstone Thermal shock damage Micro-CT Spatial variability Porosity Fractal dimension
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Effect of Spatial Variability in the Geometry of Fractures on Granite Slope Stability 认领 引用 被引量：1
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作者 Lin Jia Jing-Sen Cai +3 位作者 Li Wu Tian-Chyi Jim Yeh E-Chuan Yan Yi Du 《Journal of Earth Science》 SCIE CAS CSCD 2025年第5期1923-1935,共13页
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 ofμD_(1)(the mean of gently-dipping fracture dip),σD_(2)(the mean of steeply-dipping fracture dip),μT_(1)(the mean of gently-dipping fracture trace length),μT_(2)(the mean of steeply-dipping fracture trace length),σT_(1)(the standard deviation of gently-dipping fracture trace length),σT_(2)(the standard deviation of steeply-dipping fracture trace length),and the decrease ofσD_(1)(the standard deviation of gently-dipping fracture dip),μD_(2)(the standard deviation of steeply-dipping fracture dip),μS_(1)(the mean of gently-dipping fracture spacing)andμS_(2)(the mean of steeply-dipping fracture spacing).Among them,μT_(1),μD_(1)andμS_(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
关键词 slope stability spatial variability geometry of fractures steep-gentle combined fracture model DFN-DEC method engineering geology
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Probabilistic analysis of settlement characteristics induced by shield tunnelling in sandy cobble soil considering spatial variability 认领 引用 被引量：1
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作者 Fan WANG Pengfei LI +2 位作者 Xiuli DU Jianjun MA Lin WANG 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2025年第8期771-786,共16页
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
关键词 Shield tunnels Sandy cobble soil Settlement characteristics Spatial variability Probabilistic analysis
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Spatial Variability of Nutrient Properties in Black Soil of Northeast China 认领 引用 被引量：131
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作者 ZHANG Xing-Yi SUI Yue-Yu +2 位作者 ZHANG Xu-Dong MENG Kai S. J. HERBERT 《Pedosphere》 SCIE CAS 2007年第1期19-29,共11页
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
关键词 black soil China geostatistics analysis soil survey spatial variability
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Probabilistic assessment of slope failure considering anisotropic spatial variability of soil properties 认领 引用 被引量：13
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作者 Longlong Chen Wengang Zhang +3 位作者 Fuyong Chen Dongming Gu Lin Wang Zhenyu Wang 《Geoscience Frontiers》 SCIE CAS CSCD 2022年第3期1-21,共21页
Anisotropic spatial variability of soil properties is frequently encountered in geotechnical engineering practice due to the complex depositional process.To quantitatively evaluate the response of slope failure relate... Anisotropic spatial variability of soil properties is frequently encountered in geotechnical engineering practice due to the complex depositional process.To quantitatively evaluate the response of slope failure related to anisotropic spatial variability of soil properties and reveal the underlying influence of anisotropic spatial variability of soil properties on the slope reliability,this study integrates the random finite difference method(RFDM)into a probabilistic assessment framework and adopts general spatial variability and a cohesive-frictional soil slope example for illustration.A parametric analysis is carried out to investigate the influence of general anisotropic spatial variability of soil properties on slope failure probability and failure characteristics.The results show that the directional angles of scales of fluctuation of general anisotropic spatial variability significantly affect the slope failure probability.The dominant failure mode is the intermediate type in most cases of general anisotropic spatial variability,which is distinguished from the shallow failure mode occurring in the homogenous state.Overestimation of cross-correlation between c and u(qc;u),scales of fluctuation(dmax and dmin)in general anisotropic spatially variable soils significantly influences the average slip mass volumes of deep and multi-slip failure mode.Compared with transverse anisotropic spatial variability,general anisotropic spatial variability significantly ampli-fies the effects of qc;u,dmax and dmin on slope reliability. 展开更多
关键词 Random finite difference method Reliability Assessment Slope failure Anisotropic spatial variability Monte Carlo simulation
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Reliability analysis of slopes considering spatial variability of soil properties based on efficiently identified representative slip surfaces 认领 引用 被引量：19
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作者 Bin Wang Leilei Liu +1 位作者 Yuehua Li Quan Jiang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2020年第3期642-655,共14页
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
关键词 Slope reliability analysis Spatial variability Representative slip surfaces(RSSs) Response surface method(RSM) Random field simulation
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Spatial variability of soil organic carbon in the forestlands of northeast China 认领 引用 被引量：13
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作者 Ling Liu Haiyan Wang +3 位作者 Wei Dai Xiangdong Lei Xiaojuan Yang Xu Li 《Journal of Forestry Research》 SCIE CAS CSCD 2014年第4期867-876,共10页
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
关键词 northeast China soil organic carbon spatial variability geostatistics
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Probabilistic stability analysis of embankment slopes considering the spatial variability of soil properties and seismic randomness 认领 引用 被引量：9
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作者 ZHANG Wen-gang WU Jia-hao +2 位作者 GU Xin HAN Liang WANG Lin 《Journal of Mountain Science》 SCIE CSCD 2022年第5期1464-1474,共11页
The safety of embankments under seismic conditions is a primary concern for geotechnical engineering societies.The reliability analysis approach offers an effective tool to quantify the safety margin of geotechnical s... The safety of embankments under seismic conditions is a primary concern for geotechnical engineering societies.The reliability analysis approach offers an effective tool to quantify the safety margin of geotechnical structures from a probabilistic perspective and has gained increasing popularity in geotechnical engineering.This study presents an approach for probabilistic stability analysis of embankment slopes under transient seepage considering both the spatial variability of soil parameters and seismic randomness.The spatial varying soil parameters are firstly characterized by the random field theory,where a large number of random field samples of the soil parameters can be readily generated.Then,the factor of safety(FS)of the embankment slope under seismic conditions corresponding to each random field sample is evaluated through performing seismic stability analysis based on the pseudo-static method.A hypothetical embankment example is adopted in this study for illustration,and the influences of shear strength parameters,seismic coefficient,and the external water level on the embankment slope failure probability are systematically investigated.Results show that the coefficient of variation of the friction angle and the horizontal scale of fluctuation have more significant effects on the embankment slope failure probability.Besides,the seismic coefficient also affects the embankment slope failure probability considerably.For a given external water level,the failure probability corresponding to the downstream slope of the embankment is larger than that in the upstream slope. 展开更多
关键词 Embankment Reliability analysis Spatial variability Seismic condition Pseudo-static method
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Spatial variability of soil properties in red soil and its implications for site-specific fertilizer management 认领 引用 被引量：11
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作者 SONG Fang-fang XU Ming-gang +5 位作者 DUAN Ying-hua CAI Ze-jiang WEN Shi-lin CHEN Xian-ni SHI Wei-qi Gilles COLINET 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2020年第9期2313-2325,共13页
Assessing spatial variability and mapping of soil properties constitute important prerequisites for soil and crop management in agricultural areas. To explore the relationship between soil spatial variability and land... Assessing spatial variability and mapping of soil properties constitute important prerequisites for soil and crop management in agricultural areas. To explore the relationship between soil spatial variability and land management, 256 samples were randomly collected at two depths (surface layer 0–20 cm and subsurface layer 20–40 cm) under different land use types and soil parent materials in Yujiang County, Jiangxi Province, a red soil region of China. The pH, soil organic matter (SOM), total nitrogen (TN), cation exchange capacity (CEC), and base saturation (BS) of the soil samples were examined and mapped. The results indicated that soils in Yujiang were acidified, with an average pH of 4.87 (4.03–6.46) in the surface layer and 4.99 (4.03–6.24) in the subsurface layer. SOM and TN were significantly higher in the surface layer (27.6 and 1.50 g kg–1, respectively) than in the subsurface layer (12.1 and 0.70 g kg–1, respectively), while both CEC and BS were low (9.0 and 8.0 cmol kg–1, 29 and 38% for surface and subsurface layers, respectively). Paddy soil had higher pH (mean 4.99) than upland and forest soils, while soil derived from river alluvial deposits (RAD) had higher pH (mean 5.05) than the other three parent materials in both layers. Geostatistical analysis revealed that the best fit models were exponential for pH and TN, and spherical for BS in both layers, while spherical and Gaussian were the best fitted for SOM and CEC in the surface and subsurface layers. Spatial dependency varied from weak to strong for the different soil properties in both soil layers. The maps produced by selecting the best predictive variables showed that SOM, TN, and CEC had moderate levels in most parts of the study area. This study highlights the importance of site-specific agricultural management and suggests guidelines for appropriate land management decisions. 展开更多
关键词 spatial variability soil pH CEC BS site-specific fertilizer management
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Time series prediction of reservoir bank landslide failure probability considering the spatial variability of soil properties 认领 引用 被引量：7
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作者 Luqi Wang Lin Wang +3 位作者 Wengang Zhang Xuanyu Meng Songlin Liu Chun Zhu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第10期3951-3960,共10页
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
关键词 Machine learning(ML) Reservoir bank landslide Spatial variability Time series prediction Failure probability
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Spatial variability of soil organic carbon and total nitrogen in the hilly red soil region of Southern China 认领 引用 被引量：7
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作者 Xiong Yao Kunyong Yu +2 位作者 Yangbo Deng Jian Liu Zhuangjie Lai 《Journal of Forestry Research》 SCIE CAS CSCD 2020年第6期2385-2394,共10页
To obtain accurate spatial distribution maps of soil organic carbon(SOC)and total nitrogen(TN)in the Hetian Town in Fujian Province,China,soil samples from three depths(0–20,20–40,and 40–60 cm)at 59 sampling sites ... To obtain accurate spatial distribution maps of soil organic carbon(SOC)and total nitrogen(TN)in the Hetian Town in Fujian Province,China,soil samples from three depths(0–20,20–40,and 40–60 cm)at 59 sampling sites were sampled by using traditional analysis and geostatistical approach.The SOC and TN ranged from 2.26 to 47.54 g kg-1,and from 0.28 to 2.71 g kg-1,respectively.The coefficient of variation for SOC and TN was moderate at 49.02–55.87%for all depths.According to the nuggetto-sill ratio values,a moderate spatial dependence of SOC content and a strong spatial dependence of TN content were found in different soil depths,demonstrating that SOC content was affected by both extrinsic and intrinsic factors while TN content was mainly influenced by intrinsic factors.Indices of cross-validation,such as mean error,mean standardized error,were close to zero,indicating that ordinary kriging interpolation is a reliable method to predict the spatial distribution of SOC and TN in different soil depths.Interpolation using ordinary kriging indicated the spatial pattern of SOC and TN were characterized by higher in the periphery and lower in the middle.To improve the accuracy of spatial interpolation for soil properties,it is necessary and important to incorporate a probabilistic and machine learning methods in the future study. 展开更多
关键词 SOC TN Spatial variability Geostatistics Red soil
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Spatial variability of organochlorine pesticides (DDTs and HCHs) in surface soils from the alluvial region of Beijing,China 认领 引用 被引量：5
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作者 ZHANG Hong-yan GAO Ru-tai +2 位作者 HUANG Yuan-fang JIA Xiao-hong JIANG Shu-ren 《Journal of Environmental Sciences》 SCIE EI CAS 2007年第2期194-199,共6页
The spatial variability in the concentrations of 1,2,3,4,5,6-hexachlorocyclohexane （HCH） and 1,1,1-trichloro-2,2-bis-（p-chloro- phenyl） ethane （DDT） in surface soils was studied on the basis of the analysis of 1... The spatial variability in the concentrations of 1,2,3,4,5,6-hexachlorocyclohexane （HCH） and 1,1,1-trichloro-2,2-bis-（p-chloro- phenyl） ethane （DDT） in surface soils was studied on the basis of the analysis of 131 soil samples collected from the surface layer （0-20 cm depth） of the alluvial region of Beijing, China. The concentrations of total HCHs （including α-,β-, γ-, and δ-isomers） and total DDTs （including p,p＇-DDT, p,p＇-DDD, p,p＇-DDE, and o,p＇-DDT） in the surface soils tested were in the range from nondetectable to 31.72 μg/kg dry soil, with a mean value of 0.91, and from nondetectable to 5910.83 μg/kg dry soil, with a mean value of 32.13, respectively. It was observed that concentrations of HCHs in all soil samples and concentrations of DDTs in 112 soil samples were much lower than the first grade （50 μg/kg） permitted in ＂Environment quality standard for soils in China （GB 15618-1995）＂. This suggests that the pollution due to organochlorine pesticides was generally not significant in the farmland soils in the Beijing alluvial region. In this study, the spatial distribution and trend of HCHs and DDTs were analyzed using Geostatistical Analyst and GS＋（513）. Spatial distribution indicated how these pesticides had been applied in the past. Trend analysis showed that the concentrations of HCHs, DDTs, and their related metabolites followed an obvious distribution trend in the surface soils from the alluvial region of Beijing. 展开更多
关键词 DDTs HCHs pesticide pollution soil Beijing spatial variability
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The effect of environmental factors on spatial variability in land use change in the high-sediment region of China's Loess Plateau 认领 引用 被引量：7
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作者 LUO Ya YANG Shengtian +5 位作者 ZHAO Changsen LIU Xiaoyan LIU Changming WU Linna ZHAQ Haigen ZHANG Yichi 《Journal of Geographical Sciences》 SCIE CSCD 2014年第5期802-814,共13页
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
关键词 spatial variability land use change dryness/wetness soil properties slope gradient the high-sedi-ment region of China＇s Loess Plateau
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Influencing factors of sediment deposition and their spatial variability in riparian zone of the Three Gorges Reservoir,China 认领 引用 被引量：7
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作者 WANG Bin-yan YAN Dong-chun +1 位作者 WEN An-bang CHEN Jia-cun 《Journal of Mountain Science》 SCIE CSCD 2016年第8期1387-1396,共10页
Many factors can affect the sediment deposition and soil erosion process in riparian zone, including terrain, sediment transport and water level fluctuations. Clarifying the factors influencing sediment deposition pro... Many factors can affect the sediment deposition and soil erosion process in riparian zone, including terrain, sediment transport and water level fluctuations. Clarifying the factors influencing sediment deposition process in the riparian zone of the Three Gorges Reservoirs is an important problem to determine the key area of sediment deposition and its trend of development in the study area. In order to reveal the influence of these environmental factors on the sediment deposition in riparian zone of the Three Gorges Reservoir, this study investigated 1） the amount of deposited sediment in different environmental conditions, 2） the potential factors affecting sediment deposition in riparian zone of the Three Gorges Reservoir, 3） the relationship between the deposited sediment amount and these factors previously mentioned using correlation analysis, and 4） the influence of human activities considered as an additional factor. This study found that 1） slope gradient, elevation, inundating duration and human activities were the main factors influencing sedimentation in riparian zone of the Three Gorges Reservoir, and 2） the impact of each factor varied with spaces. Specifically, in the upper reach from Jiangjin to Fuling, human activities such as gravel dredging, bank revetment and ports and wharfs constructing disturbed considerable amounts of deposited sediment, as a result, there was no natural law to dictate the distribution. In the middle reach from Fuling to Fengjie, slope gradient and inundating duration were the controlling factors, and the sediment deposition amount was greater in the areas with a gentler slope or lower elevation. Water flow on gentler slopes generally had lower velocity, resulting in more sediment to deposit. Sites with lower elevations would be drowned by sediment-laden flow with a longer duration resulting from hydrologic regime controlled by the operating strategy of the Three Gorges Reservoir, leading to a larger amount of sediment deposition. In the lower reach from Fengjie to Zigni, slope gradient was similar to the middle reach, performing a primary factor, while other factors showed little relationship with sediment amount. 展开更多
关键词 Influencing Factors Spatial variability Sediment deposition Riparian zone Three GorgesReservoir
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Spatial variability and its main controlling factors of the permafrost soil-moisture on the northern-slope of Bayan Har Mountains in Qinghai-Tibet Plateau 认领 引用 被引量：6
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作者 cao wei sheng yu +1 位作者 wu ji-chun li jing 《Journal of Mountain Science》 SCIE CSCD 2017年第12期2406-2419,共14页
The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions.Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet ... The soil moisture movement is an important carrier of material cycle and energy flow among the various geo-spheres in the cold regions.Thus, this research takes the north slope of Bayan Har Mountains in Qinghai-Tibet Plateau as a case study.The present study firstly investigates the change of permafrost moisture in different slope positions and depths. Based on this investigation, this article attempts to investigate the spatial variability of permafrost moisture and identifies the key influence factors in different terrain conditions. The method of classification and regression tree(CART) is adopted to identify the main controlling factors influencing the soil moisture movement. The relationships between soil moisture and environmental factors are revealed by the use of the method of canonical correspondence analysis(CCA). The results show that: 1) Due to the terrain slope and the freezing-thawing process, the horizontal flow weakens in the freezing period. The vertical migration of the soil moisture movement strengthens. It will lead to that the soil-moisture content in the up-slope is higher than that in the down-slope. The conclusion is contrary during the melting period. 2) Elevation, soil texture, soil temperature and vegetation coverage are the main environmental factors which affect the slopepermafrost soil-moisture. 3) Slope, elevation and vegetation coverage are the main factors that affect the slope-permafrost soil-moisture at the shallow depth of 0-20 cm. It is complex at the middle and lower depth. 展开更多
关键词 Qinghai-Tibet Plateau Northern-slope of Bayan Har Mountains Permafrost Soil moisture Spatial variability Controlling factors
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Delineation of Site-Specific Management Zones Based on Temporal and Spatial Variability of Soil Electrical Conductivity 认领 引用 被引量：9
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作者 LI Yan SHI Zhou LI Feng 《Pedosphere》 SCIE CAS 2007年第2期156-164,共9页
A coastal saline field of 10.5 ha was selected as the study site and 122 bulk electrical conductivity (ECb) measurements were performed thrice in situ in the topsoil (0-20 cm) across the field using a hand held device... A coastal saline field of 10.5 ha was selected as the study site and 122 bulk electrical conductivity (ECb) measurements were performed thrice in situ in the topsoil (0-20 cm) across the field using a hand held device to assess the spatial variability and temporal stability of the distribution of soil electrical conductivity (EC), to identify the management zones using cluster analysis based on the spatiotemporal variability of soil EC, and to evaluate the probable potential for site-specific management in coastal regions with conventional statistics and geostatistical techniques. The results indicated high coefficients of variation for topsoil salinity over all the three samplings. The spatial structure of the salinity variability remained relatively stable with time. Kriged contour maps, drawn on the basis of spatial variance structure of the data, showed the spatial trend of the salinity distribution and revealed areas of consistently high or consistently low salinity, while a temporal stability map indicated stable and unstable regions. On the basis of the spatiotemporal characteristics, cluster analysis divided the site into three potential management zones, each with different characteristics that could have an impact on the way the field was managed. On the basis of the clearly defined management zones it was concluded that coastal saline land could be managed in a site-specific way. 展开更多
关键词 coastal saline field management zone soil electrical conductivity spatial variability temporal variability
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Spatial variability and driving factors of soil multifunctionality in drylands of China 认领 引用 被引量：2
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作者 ZHANG Shihang CHEN Yusen +5 位作者 LU Yongxing GUO Hao GUO Xing LIU Chaohong ZHOU Xiaobing ZHANG Yuanming 《Regional Sustainability》 2022年第3期223-232,共10页
Drylands are highly vulnerable to climate change and human activities.The drylands of China account for approximately 10.8%of global drylands,and China is the country most severely affected by aridity in Asia.Therefor... Drylands are highly vulnerable to climate change and human activities.The drylands of China account for approximately 10.8%of global drylands,and China is the country most severely affected by aridity in Asia.Therefore,studying the spatial variation characteristics in soil multifunctionality(SMF)and investigating the driving factors are critical for elucidating and managing the functions of dryland ecosystems in China.Based on the environmental factors(mean annual precipitation(MAP),mean annual temperature(MAT),solar radiation(Srad),soil acidity(pH),enhanced vegetation index(EVI),and cation exchange capacity(CEC))and aridity from the“dataset of soil properties for land surface modeling over China”,we used non-linear regression,ordinary least square(OLS)regression,structural equation model(SEM),and other analytical methods to investigate the relationships of SMF with environmental factors across different aridity levels in China.SMF in different dryland regions varied significantly and showed a patchy distribution,with SMF index values ranging from–1.21 to 2.42.Regions with SMF index values from–0.20 to 0.51 accounting for 63.0%of dryland area in China.OLS regression results revealed that environmental factors like MAP,MAT,Srad,pH,EVI,and CEC were significantly related to SMF(P<0.05).MAP and MAT were correlated to SMF at the whole aridity level(P<0.05).SEM results showed that the driving factors of SMF differed depending on the aridity level.Soil pH was the strongest driving factor of SMF when the aridity was less than 0.80(P<0.001).Both soil CEC and EVI had a positive effect on SMF when aridity was greater than 0.80(P<0.01),with soil CEC being the strongest driving factor.The importance ranking revealed that the relative importance contribution of soil pH to SMF was greatest when aridity was less than 0.80(66.9%).When aridity was set to greater than 0.80,the relative importance contributions of CEC and EVI to SMF increased(45.1%and 31.9%,respectively).Our findings indicated that SMF had high spatial heterogeneity in drylands of China.The aridity threshold controlled the impact of environmental factors on SMF. 展开更多
关键词 Drylands Soil multifunctionality (SMF) Aridity Index(AI) Spatial variability Driving factors Aridity level
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Inverse reliability analysis and design for tunnel face stability considering soil spatial variability 认领 引用 被引量：2
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作者 Zheming Zhang Jian Ji +1 位作者 Xiangfeng Guo Siang Huat Goh 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第5期1552-1564,共13页
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
关键词 Limit analysis Tunnel face stability Spatial variability HLRF algorithm Inverse reliability method
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Stochastic analysis of excavation-induced wall deflection and box culvert settlement considering spatial variability of soil stiffness 认领 引用 被引量：1
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作者 Ping Li Shiwei Liu +2 位作者 Jian Ji Xuanming Ding Mengdie Bao 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2023年第12期3256-3270,共15页
In this study, a three-dimensional (3D) finite element modelling (FEM) analysis is carried out to investigate the effects of soil spatial variability on the response of retaining walls and an adjacent box culvert due ... In this study, a three-dimensional (3D) finite element modelling (FEM) analysis is carried out to investigate the effects of soil spatial variability on the response of retaining walls and an adjacent box culvert due to a braced excavation. The spatial variability of soil stiffness is modelled using a variogram and calibrated by high-quality experimental data. Multiple random field samples (RFSs) of soil stiffness are generated using geostatistical analysis and mapped onto a finite element mesh for stochastic analysis of excavation-induced structural responses by Monte Carlo simulation. It is found that the spatial variability of soil stiffness can be described by an exponential variogram, and the associated vertical correlation length is varied from 1.3 m to 1.6 m. It also reveals that the spatial variability of soil stiffness has a significant effect on the variations of retaining wall deflections and box culvert settlements. The ignorance of spatial variability in 3D FEM can result in an underestimation of lateral wall deflections and culvert settlements. Thus, the stochastic structural responses obtained from the 3D analysis could serve as an effective aid for probabilistic design and analysis of excavations. 展开更多
关键词 Three-dimensional(3D) Geostatistical analysis Random finite element modelling(FEM) Spatial variability of soil stiffness
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