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 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
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
This study proposed a random Smoothed Particle Hydrodynamics method for analyzing the post-failure behavior of landslides,which is based on the Karhunen-Loeve(K-L) expansion,the non-Newtonian fluid model,and the OpenM...This study proposed a random Smoothed Particle Hydrodynamics method for analyzing the post-failure behavior of landslides,which is based on the Karhunen-Loeve(K-L) expansion,the non-Newtonian fluid model,and the OpenMP parallel framework.Then,the applicability of this method was validated by comparing the generated random field with theoretical result and by simulating the post-failure process of an actual landslide.Thereafter,an illustrative landslide example was created and simulated to obtain the spatial variability effect of internal friction angle on the post-failure behavior of landslides under different coefficients of variation(COVs) and correlation lengths(CLs).As a conclusion,the reinforcement with materials of a larger friction angle can reduce the runout distance and impact the force of a landslide.As the increase of COV,the distribution range of influence zones also increases,which indicates that the deviation of influence zones becomes large.In addition,the correlation length in Monte Carlo simulations should not be too small,otherwise the variation range of influence zones will be underestimated.展开更多
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
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
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
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
Characterizing soil particle-size distribution is a key measure towards soil property.The purpose of this study was to evaluate the multifractal characteristics of soil particle-size distribution among different land-...Characterizing soil particle-size distribution is a key measure towards soil property.The purpose of this study was to evaluate the multifractal characteristics of soil particle-size distribution among different land-use from a purple soil catchment and to generalize the spatial variation trend of multifractal parameters across the catchment.A total of 84 soil samples were collected from four kinds of land use patterns(dry land,orchard,paddy,and forest)in an agricultural catchment in the Three Gorges Reservoir Region,China.The multifractal analysis method was applied to quantitatively characterize the soil particle size distribution.Six soil particle size distribution(PSD)multifractal parameters(D(0),D(1),D(2),(35)a(q),(35)f[a(q)],α(0))were computed.Additionally,a geostatistical analysis was employed to reveal the spatial differentiation and map the spatial distribution of these parameters.Evident multifractal characteristics were found.The trend of generalized dimension spectrum of four land use patterns was basically consistent with the range of 0.8 to 2.0.However,orchard showed the largest monotonic decline,while the forest demonstrated the smallest decrease.D(0)of the four land use patterns were ranked as:dry land<orchard<forest<paddy,the order of D(1)was:dry land<paddy<orchard<forest,D(2)presented a rand-size relationship as dry land<forest<paddy<orchard.Furthermore,all land-use patterns presented asΔf[α(q)]<0.The rand-size relationship ofα(0)was same as D(0).The best-fitting model for D(0),D(1),D(2)andΔf[α(q)]was spherical model,forΔα(q)was gaussian model,and forα(0)was exponential model with structure variance ratio was 1.03%,49.83%,0.84%,1.48%,22.20%and 10.60%,respectively.The results showed that soil particles of each land use pattern were distributed unevenly.The multifractal parameters under different land use have significant differences,except forΔα(q).Differences in the composition of soil particles lead to differences in the multifractal properties even though they belong to the same soil texture.Farming behavior may refine particles and enhance the heterogeneity of soil particle distribution.Our results provide an effective reference for quantifying the impact of human activities on soil system in the Three Gorges Reservoir region.展开更多
Nowadays,enterprises need to continually adjust their business processes to adapt to the changes of business environments,especially when one business needs to be deployed in different application scenarios,which is c...Nowadays,enterprises need to continually adjust their business processes to adapt to the changes of business environments,especially when one business needs to be deployed in different application scenarios,which is called spatial variability in this paper.In the field of BPM(Business Process Management),configurable business process models have demonstrated their effectiveness in aspects of process modeling and model reuse.Yet,we found that the existing techniques lead to complex configurable models,and are inadequate for model reuse especially for the spatial variability issue because they neglect the root impact of organizations on control flow.S-BPM(Subject-oriented Business Process Management)models provide a solid foundation for dealing with complex applications and help to bridge the gap between business and IT for process execution.In this paper,we propose an organization-driven business process configurable modeling approach for spatial variability by integrating both restriction and extension operations based on the S-BPM paradigm,in which business objects are also included.Our approach is validated with a general business process developed for the Real Estate Administration(REA)in a certain province of China.The resulting configurable modeling framework can express the heterogeneous activity sequences for one business and has the potential to generate process models for uncertain environments in a new organization structure.展开更多
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
Soil complexity and its multivariable nature restrict the precision of soil maps that are essential tools for soil sustainable management. Most methods developed for reducing impurities of soil map units focus on soil...Soil complexity and its multivariable nature restrict the precision of soil maps that are essential tools for soil sustainable management. Most methods developed for reducing impurities of soil map units focus on soil external properties. Taking into account the soil internal properties like geochemical weathering indices could increase the map unit's purity. However, the compatibility of these indices with Soil Taxonomic Classes has not been studied yet. This study has been performed in a hilly region with different soil types, vegetation and diverse topographic attributes to illustrate the spatial variability of soil weathering indices and their compatibility with Soil Taxonomic Classes. The grid sampling is at 100 m interval. Physico-chemical and total elemental analyses were performed on 184 and 56 soil samples respectively. Eight topographic attributes and 14 common soil development indices were determined. Principal components analysis(PCA) was done to identify the most important components. The results indicated that Morphological Index(MI) was the best index to show the degree ofsoil development in the studied region. Spatial distribution of Soil Taxonomic Classes showed relatively good compatibility with the first principal component(PC1), Vogt(V) and morphological indices. This study showed that using soil development indices with the conventional methods could be helpful tools in soil survey investigations.展开更多
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
Orchards have a high potential for carbon sequestration.However,little research is available on the spatial variability at catchment scale and on the difference between the tree area and the lanes.We analyzed theik sp...Orchards have a high potential for carbon sequestration.However,little research is available on the spatial variability at catchment scale and on the difference between the tree area and the lanes.We analyzed theik spatial variability of soil organic carbon stock,SOCstock at 90 cm depth in an 8-ha catchment in Southern Spain with olives on a vertic soil.Results showed higher soil organic carbon concentration,SOC,in the tree area as compared to the lane up to 60 cm depth,but its impact on SOCstock was negligible since it was compensated by the higher soil bulk density in the lane.SOC at different depths was correlated with that in the top 0-5 cm.The overall SOCstock of the orchard was 4.14 kg m^(-2),ranging between 1.8 and 6.0 kg m^(-2).This SOCstock is in the mid-lower range of values reported for olive orchards,measured at smaller scale,and similar to those other intensive field crops and agroforestry under comparable rainfall conditions.The spatial variability in SOCstock was correlated to several geomorphological variables:elevation,cumulative upstream area,topographic wetness index,sediment transport index,and tillage erosion.Differences in SOC and SOCstock are driven by the sediment redis-tribution downslope,mainly by tillage erosion,and higher soil water availability in lower areas allowing higher biomass production.These topographic indexes and the correlation between SOC in the topsoil and SOCstock up to 90 cm should be further explored in other typology of olive orchards for facilitating the mapping of SOC_(stock).展开更多
This article presents the soil spatial variability effect on the performance of a reinforced earth wall.The serviceability limit state is considered in the analysis.Both cases of isotropic and anisotropic non-normal r...This article presents the soil spatial variability effect on the performance of a reinforced earth wall.The serviceability limit state is considered in the analysis.Both cases of isotropic and anisotropic non-normal random fields are implemented for the soil properties.The K arhunen-Loeve expansion method is used for the discretization of the random field.Numerical finite difference models are considered as deterministic models.The Monte Carlo simulation technique is used to obtain the deformation response variability of the reinforced soil retaining wall.The influences of the spatial variability response of the geotechnical system in terms of horizontal facing displacement is presented and discussed.The results obtained show that the spatial variability has an important influence on the facing horizontal displacement as well as on the failure probability.展开更多
The Bering sea is susceptible to ocean acidification driven by both human activities(anthropogenic CO_(2))and distinctive natural processes.To assess the situation of ocean acidification,we investigated the spatial va...The Bering sea is susceptible to ocean acidification driven by both human activities(anthropogenic CO_(2))and distinctive natural processes.To assess the situation of ocean acidification,we investigated the spatial variability of aragonite saturation states(ΩAr)in July 2010 during the 4th Chinese National Arctic Research Expedition(CHINARE).The surface waters were all oversaturated with respect to aragonite(ΩAr>1)due to high biological removal,andΩAr ranged from 1.43 to 3.17.The relatively lowΩAr values were found in the western Bering Strait and eastern nearshore region of the Bering Sea Shelf,which were associated with the upwelling and riverine input,respectively.In the subsurface,theΩAr decreased to generally low saturation states and were observed to be strongly undersaturated(ΩAr<1)in the bottom waters with a lowest value of 0.45,which might be caused by remineralization.However,unlike prior studies,the lowΩAr values in the shallow nearshore region were still above the saturation horizon throughout the water column,which were probably counteracted by high local primary production.In the context of climate change and increasing anthropogenic CO_(2)absorption,the suppression and undersaturation ofΩAr in the Bering Sea are not only attributed to the natural processes but also the accumulation of anthropogenic CO_(2).展开更多
In this study,the effects of soil spatial variability in braced excavations are investigated by focusing on three structural responses:wall bending moments,wall shear forces,and strut forces.The soil spatial variabili...In this study,the effects of soil spatial variability in braced excavations are investigated by focusing on three structural responses:wall bending moments,wall shear forces,and strut forces.The soil spatial variability is modeled using random field theory,and the generated soil parameters are mapped onto a finite element model.A procedure for automating the Monte Carlo simulation,which is used for probabilistic analysis,is described.A case study demonstrates that the soil spatial variability has a considerable effect on the excavation-induced structural responses.Furthermore,a reliability analysis is performed to estimate the failure probability for three structural failure modes.The results demonstrate the importance of considering soil spatial variability in the structural assessment of braced excavati ons.展开更多
Saturated hydraulic conductivity (Ks) is an important soil hydraulic parameter for charactering the rate of water flow across the soils and is mainly related to its high spatial variability. In a small watershed with ...Saturated hydraulic conductivity (Ks) is an important soil hydraulic parameter for charactering the rate of water flow across the soils and is mainly related to its high spatial variability. In a small watershed with the area of 0.27 km2 in the Loess Plateau, Ks of 197 soil samples under different vegetations and landforms were measured. Ks had a moderate variability for total samples. The forestland had high Ks with low coefficient of variation (CV), but the grassland in the watershed bottom had low Ks with big CV. Ks had moderate correlation in space distribution and combined both structural and random factors. At the N-S and E-W directions of watershed being parallel and normal to the stream valley, Ks had relatively weak correlation, indicating that the random factor was the dominate reason causing spatial variance. At the NE-SW and SE-NW directions, Ks had relatively strong correlation due to structural factors such as geomorphology and vegetation distribution patterns. Kriging optimal estimation method was used to produce Ks contour map. The Kriging standard deviation (SD) was the lowest near the sampling points, and increased along with the distance to sampling points. In the Loess Plateau region, soil texture is relatively even, and the vegetation distribution pattern was the key factor affecting spatial variability of Ks.展开更多
In the past two to three years, the world has been heavily affected by the infectious coronavirus disease and Malawi has not been spared due to its interconnection with neighboring countries. There is no management to...In the past two to three years, the world has been heavily affected by the infectious coronavirus disease and Malawi has not been spared due to its interconnection with neighboring countries. There is no management tool to identify and model the vulnerabilities of Malawi’s districts in prioritizing health services as far as coronavirus prevalence and other infectious diseases are concerned. The aim of this study was to model coronavirus vulnerability in all districts in Malawi using Geographic Information System (GIS) to monitor the disease’s cumulative prevalence over the severely affected period between 2020 and 2021. To achieve this, four parameters associated with coronavirus prevalence, including population density, percentage of older people, temperature, and humidity, were prepared in a GIS environment and used in the modelling process. A multiscale geographically weighted regression (MGWR) model was used to model and determine the vulnerability of coronavirus in Malawi. In the MGWR modelling, the Fixed Spatial Kernel was used following a Gaussian distribution model type. The Results indicated that population density and older people (age greater than 60 years) have a more significant impact on coronavirus prevalence in Malawi. The modelling further shows that Malawi, between April 2020 and May 2021, Lilongwe, Blantyre and Thyolo were more vulnerable to coronavirus than other districts. This research has shown that spatial variability of Covid-19 cases using MGWR has the potential of providing useful insights to policymakers for targeted interventions that could otherwise not be possible to detect using non-geovisualization techniques.展开更多
This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentr...This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries.Daily PM concentrations were analysed for urban and industrial areas including Alor Setar,Tasek,Shah Alam,Klang,Bandaraya Melaka,Larkin,Balok Baru,and Kuala Terengganu in 2018 and 2019.The analysis employed spatiotemporal to examine how PM levels were distributed.The data summary revealed that PM levels in all study areas were right-skewed,indicating the occurrence of high particulate events.Significant peaks in PM concentrations during haze events were consistently observed between June and October,encompassing the south west monsoon and inter-monsoon periods.The study on acute respiratory illnesses primarily focused on Selangor.Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma(AEBA)and acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with values of 260.500 and 185.170,respectively.Similarly,for outpatient cases of AEBA and AECOPD,Klang had the highest average values of 41.67 and 14.00,respectively.Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning.The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions,particularly from June to September,as shown in the bar diagram.Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses,seen in higher inpatient and outpatient visits(p<0.05).However,seasonal variability had minimal impact on healthcare utilization.These findings offer a comprehensive assessment of PM levels during historic haze episodes,providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.展开更多
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The authors would like to acknowledge the financial support provided by the National Natural Science Foundation of China(Grant No.41977240)the Fundamental Research Funds for the Central Universities(Grant No.B200202090).
文摘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.
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This work is supported by the Natural Science Foundation of China(NSFC Grant No.51808192,51879091,41630638)the Natural Science Foundation of Jiangsu Province(Grant No.BK20170887)the China Postdoctoral Science Foundation(Grant Nos.2017M611673 and 2018T110432).We thank Ms.Ruihua Yu for her contribution in compiling some of the figures in this work.
文摘This study proposed a random Smoothed Particle Hydrodynamics method for analyzing the post-failure behavior of landslides,which is based on the Karhunen-Loeve(K-L) expansion,the non-Newtonian fluid model,and the OpenMP parallel framework.Then,the applicability of this method was validated by comparing the generated random field with theoretical result and by simulating the post-failure process of an actual landslide.Thereafter,an illustrative landslide example was created and simulated to obtain the spatial variability effect of internal friction angle on the post-failure behavior of landslides under different coefficients of variation(COVs) and correlation lengths(CLs).As a conclusion,the reinforcement with materials of a larger friction angle can reduce the runout distance and impact the force of a landslide.As the increase of COV,the distribution range of influence zones also increases,which indicates that the deviation of influence zones becomes large.In addition,the correlation length in Monte Carlo simulations should not be too small,otherwise the variation range of influence zones will be underestimated.
基金the financial supports from National Natural Science Foundation of China(52008058)High-end Foreign Expert Introduction program(G20200022005)+1 种基金Cooperation projects between the universities in Chongqing and institutes affiliated to the Chinese Academy of Sciences(HZ2021001)China Postdoctoral Science Foundation funded project(2021M700608)。
文摘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.
基金This study was supported by the National Natural Science Foundation of China(41620104006 and 41977104)the Central Public-interest Scientific Institution Basal Research Fund for Chinese Academy of Tropical Agricultural Sciences(1630062018005).We thank the staff from Yujiang Soil and Fertilizer Extension Station,Jiangxi,China for help with soil sampling.
文摘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.
基金supported by the National Natural Science Foundation of China(Grant No.41501079 and 91647103)Funded by State Key Laboratory of Frozen Soil Engineering(Grant No.SKLFSE-ZQ-43)+1 种基金the Chinese Academy of Sciences(CAS)Key Research Program(Grant No.KZZD-EW-13)the Foundation for Excellent Youth Scholars of NIEER,CAS
文摘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.
文摘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.
基金funded by the National Key R&D Program of China(2017YFD0800505)Chongqing Key R&D Project of Technology Innovation and Application(NO.cstc2018jscxmszd X0055)。
文摘Characterizing soil particle-size distribution is a key measure towards soil property.The purpose of this study was to evaluate the multifractal characteristics of soil particle-size distribution among different land-use from a purple soil catchment and to generalize the spatial variation trend of multifractal parameters across the catchment.A total of 84 soil samples were collected from four kinds of land use patterns(dry land,orchard,paddy,and forest)in an agricultural catchment in the Three Gorges Reservoir Region,China.The multifractal analysis method was applied to quantitatively characterize the soil particle size distribution.Six soil particle size distribution(PSD)multifractal parameters(D(0),D(1),D(2),(35)a(q),(35)f[a(q)],α(0))were computed.Additionally,a geostatistical analysis was employed to reveal the spatial differentiation and map the spatial distribution of these parameters.Evident multifractal characteristics were found.The trend of generalized dimension spectrum of four land use patterns was basically consistent with the range of 0.8 to 2.0.However,orchard showed the largest monotonic decline,while the forest demonstrated the smallest decrease.D(0)of the four land use patterns were ranked as:dry land<orchard<forest<paddy,the order of D(1)was:dry land<paddy<orchard<forest,D(2)presented a rand-size relationship as dry land<forest<paddy<orchard.Furthermore,all land-use patterns presented asΔf[α(q)]<0.The rand-size relationship ofα(0)was same as D(0).The best-fitting model for D(0),D(1),D(2)andΔf[α(q)]was spherical model,forΔα(q)was gaussian model,and forα(0)was exponential model with structure variance ratio was 1.03%,49.83%,0.84%,1.48%,22.20%and 10.60%,respectively.The results showed that soil particles of each land use pattern were distributed unevenly.The multifractal parameters under different land use have significant differences,except forΔα(q).Differences in the composition of soil particles lead to differences in the multifractal properties even though they belong to the same soil texture.Farming behavior may refine particles and enhance the heterogeneity of soil particle distribution.Our results provide an effective reference for quantifying the impact of human activities on soil system in the Three Gorges Reservoir region.
基金supported by National Key R&D Program of China under grant No:2020YFB1707602Educational Commission of Hunan Province of China under Grant No:20B244National Natural Science Foundation of China under grant No:61872139.
文摘Nowadays,enterprises need to continually adjust their business processes to adapt to the changes of business environments,especially when one business needs to be deployed in different application scenarios,which is called spatial variability in this paper.In the field of BPM(Business Process Management),configurable business process models have demonstrated their effectiveness in aspects of process modeling and model reuse.Yet,we found that the existing techniques lead to complex configurable models,and are inadequate for model reuse especially for the spatial variability issue because they neglect the root impact of organizations on control flow.S-BPM(Subject-oriented Business Process Management)models provide a solid foundation for dealing with complex applications and help to bridge the gap between business and IT for process execution.In this paper,we propose an organization-driven business process configurable modeling approach for spatial variability by integrating both restriction and extension operations based on the S-BPM paradigm,in which business objects are also included.Our approach is validated with a general business process developed for the Real Estate Administration(REA)in a certain province of China.The resulting configurable modeling framework can express the heterogeneous activity sequences for one business and has the potential to generate process models for uncertain environments in a new organization structure.
基金the financial support from National Natural Science Foundation of China(No.52078086)Program of Distinguished Young Scholars,Natural Science Foundation of Chongqing,China(No.cstc2020jcyj-jq0087)+1 种基金China Scholarship Council,China(CSC No.201906050237)Innovation Group Science Foundation of the Natural Science Foundation of Chongqing,China(Grant No.cstc2020jcyj-cxttX0003).
文摘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.
基金Center of Excellence"Improvement Soil Quality in order to Optimize the Plant Nutrition"of Soil Science department, University of Tehran and College of Agriculture and Natural Resources, University of Tehran for financial support of the study (Grant No. 7104017/6/19)
文摘Soil complexity and its multivariable nature restrict the precision of soil maps that are essential tools for soil sustainable management. Most methods developed for reducing impurities of soil map units focus on soil external properties. Taking into account the soil internal properties like geochemical weathering indices could increase the map unit's purity. However, the compatibility of these indices with Soil Taxonomic Classes has not been studied yet. This study has been performed in a hilly region with different soil types, vegetation and diverse topographic attributes to illustrate the spatial variability of soil weathering indices and their compatibility with Soil Taxonomic Classes. The grid sampling is at 100 m interval. Physico-chemical and total elemental analyses were performed on 184 and 56 soil samples respectively. Eight topographic attributes and 14 common soil development indices were determined. Principal components analysis(PCA) was done to identify the most important components. The results indicated that Morphological Index(MI) was the best index to show the degree ofsoil development in the studied region. Spatial distribution of Soil Taxonomic Classes showed relatively good compatibility with the first principal component(PC1), Vogt(V) and morphological indices. This study showed that using soil development indices with the conventional methods could be helpful tools in soil survey investigations.
基金supported by the Xinjiang Outstanding Youth fund(2021D01E03)the National Natural Science Foundation of China(U2003214 and 41977099).
文摘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.
基金supported by projects AGL 2009-12936-C03-01,AGL2009-12936-C03-03(Spanish Government)SHui(European Commission Grant Agreement number:773903)+1 种基金TUdi(European Commission Grant Agreement number:101000224)EU-FEDER funds.T.Vanwalleghem thanks financial support from the Spanish Ministry of Science and Innovation,the Spanish State Research Agency,through the Severo Ochoa and Maria de Maeztu Program for Centers and Units of Excellence in R&D(Ref.CEX2019-000968-M).
文摘Orchards have a high potential for carbon sequestration.However,little research is available on the spatial variability at catchment scale and on the difference between the tree area and the lanes.We analyzed theik spatial variability of soil organic carbon stock,SOCstock at 90 cm depth in an 8-ha catchment in Southern Spain with olives on a vertic soil.Results showed higher soil organic carbon concentration,SOC,in the tree area as compared to the lane up to 60 cm depth,but its impact on SOCstock was negligible since it was compensated by the higher soil bulk density in the lane.SOC at different depths was correlated with that in the top 0-5 cm.The overall SOCstock of the orchard was 4.14 kg m^(-2),ranging between 1.8 and 6.0 kg m^(-2).This SOCstock is in the mid-lower range of values reported for olive orchards,measured at smaller scale,and similar to those other intensive field crops and agroforestry under comparable rainfall conditions.The spatial variability in SOCstock was correlated to several geomorphological variables:elevation,cumulative upstream area,topographic wetness index,sediment transport index,and tillage erosion.Differences in SOC and SOCstock are driven by the sediment redis-tribution downslope,mainly by tillage erosion,and higher soil water availability in lower areas allowing higher biomass production.These topographic indexes and the correlation between SOC in the topsoil and SOCstock up to 90 cm should be further explored in other typology of olive orchards for facilitating the mapping of SOC_(stock).
文摘This article presents the soil spatial variability effect on the performance of a reinforced earth wall.The serviceability limit state is considered in the analysis.Both cases of isotropic and anisotropic non-normal random fields are implemented for the soil properties.The K arhunen-Loeve expansion method is used for the discretization of the random field.Numerical finite difference models are considered as deterministic models.The Monte Carlo simulation technique is used to obtain the deformation response variability of the reinforced soil retaining wall.The influences of the spatial variability response of the geotechnical system in terms of horizontal facing displacement is presented and discussed.The results obtained show that the spatial variability has an important influence on the facing horizontal displacement as well as on the failure probability.
基金the National Key Research and Development Program of China(2019YFA0607003)Scientific Research Foundation of Third Institute of Oceanography,MNR(2018005,2020017)+2 种基金National Natural Science Foundation of China(41406221,41476173)the Chinese Projects for Investigations and Assessments of the Arctic and Antarctic(CHINARE2017-2021)Fujian science and technology innovation leader project 2016.
文摘The Bering sea is susceptible to ocean acidification driven by both human activities(anthropogenic CO_(2))and distinctive natural processes.To assess the situation of ocean acidification,we investigated the spatial variability of aragonite saturation states(ΩAr)in July 2010 during the 4th Chinese National Arctic Research Expedition(CHINARE).The surface waters were all oversaturated with respect to aragonite(ΩAr>1)due to high biological removal,andΩAr ranged from 1.43 to 3.17.The relatively lowΩAr values were found in the western Bering Strait and eastern nearshore region of the Bering Sea Shelf,which were associated with the upwelling and riverine input,respectively.In the subsurface,theΩAr decreased to generally low saturation states and were observed to be strongly undersaturated(ΩAr<1)in the bottom waters with a lowest value of 0.45,which might be caused by remineralization.However,unlike prior studies,the lowΩAr values in the shallow nearshore region were still above the saturation horizon throughout the water column,which were probably counteracted by high local primary production.In the context of climate change and increasing anthropogenic CO_(2)absorption,the suppression and undersaturation ofΩAr in the Bering Sea are not only attributed to the natural processes but also the accumulation of anthropogenic CO_(2).
基金The second author would like to thank the support received from the National Natural Science Foundation of China through Grant No.51808405.
文摘In this study,the effects of soil spatial variability in braced excavations are investigated by focusing on three structural responses:wall bending moments,wall shear forces,and strut forces.The soil spatial variability is modeled using random field theory,and the generated soil parameters are mapped onto a finite element model.A procedure for automating the Monte Carlo simulation,which is used for probabilistic analysis,is described.A case study demonstrates that the soil spatial variability has a considerable effect on the excavation-induced structural responses.Furthermore,a reliability analysis is performed to estimate the failure probability for three structural failure modes.The results demonstrate the importance of considering soil spatial variability in the structural assessment of braced excavati ons.
基金National NaturalScience Foundation grant (40474178, 30230290)Shaanxi Provincial Office of Education special projects (05JK241)
文摘Saturated hydraulic conductivity (Ks) is an important soil hydraulic parameter for charactering the rate of water flow across the soils and is mainly related to its high spatial variability. In a small watershed with the area of 0.27 km2 in the Loess Plateau, Ks of 197 soil samples under different vegetations and landforms were measured. Ks had a moderate variability for total samples. The forestland had high Ks with low coefficient of variation (CV), but the grassland in the watershed bottom had low Ks with big CV. Ks had moderate correlation in space distribution and combined both structural and random factors. At the N-S and E-W directions of watershed being parallel and normal to the stream valley, Ks had relatively weak correlation, indicating that the random factor was the dominate reason causing spatial variance. At the NE-SW and SE-NW directions, Ks had relatively strong correlation due to structural factors such as geomorphology and vegetation distribution patterns. Kriging optimal estimation method was used to produce Ks contour map. The Kriging standard deviation (SD) was the lowest near the sampling points, and increased along with the distance to sampling points. In the Loess Plateau region, soil texture is relatively even, and the vegetation distribution pattern was the key factor affecting spatial variability of Ks.
文摘In the past two to three years, the world has been heavily affected by the infectious coronavirus disease and Malawi has not been spared due to its interconnection with neighboring countries. There is no management tool to identify and model the vulnerabilities of Malawi’s districts in prioritizing health services as far as coronavirus prevalence and other infectious diseases are concerned. The aim of this study was to model coronavirus vulnerability in all districts in Malawi using Geographic Information System (GIS) to monitor the disease’s cumulative prevalence over the severely affected period between 2020 and 2021. To achieve this, four parameters associated with coronavirus prevalence, including population density, percentage of older people, temperature, and humidity, were prepared in a GIS environment and used in the modelling process. A multiscale geographically weighted regression (MGWR) model was used to model and determine the vulnerability of coronavirus in Malawi. In the MGWR modelling, the Fixed Spatial Kernel was used following a Gaussian distribution model type. The Results indicated that population density and older people (age greater than 60 years) have a more significant impact on coronavirus prevalence in Malawi. The modelling further shows that Malawi, between April 2020 and May 2021, Lilongwe, Blantyre and Thyolo were more vulnerable to coronavirus than other districts. This research has shown that spatial variability of Covid-19 cases using MGWR has the potential of providing useful insights to policymakers for targeted interventions that could otherwise not be possible to detect using non-geovisualization techniques.
文摘This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries.Daily PM concentrations were analysed for urban and industrial areas including Alor Setar,Tasek,Shah Alam,Klang,Bandaraya Melaka,Larkin,Balok Baru,and Kuala Terengganu in 2018 and 2019.The analysis employed spatiotemporal to examine how PM levels were distributed.The data summary revealed that PM levels in all study areas were right-skewed,indicating the occurrence of high particulate events.Significant peaks in PM concentrations during haze events were consistently observed between June and October,encompassing the south west monsoon and inter-monsoon periods.The study on acute respiratory illnesses primarily focused on Selangor.Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma(AEBA)and acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with values of 260.500 and 185.170,respectively.Similarly,for outpatient cases of AEBA and AECOPD,Klang had the highest average values of 41.67 and 14.00,respectively.Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning.The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions,particularly from June to September,as shown in the bar diagram.Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses,seen in higher inpatient and outpatient visits(p<0.05).However,seasonal variability had minimal impact on healthcare utilization.These findings offer a comprehensive assessment of PM levels during historic haze episodes,providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.
