Spatial variability analysis of precipitation in northwest Iran

The spatial variability of precipitation was investigated in the northwestern corner of Iran using data collected at 24 synoptic stations from 1986 to 2015. Principal component analysis (PCA) and cluster analysis (CA) were used to regionalize precipitation in the study area. Eleven precipitation variables were averaged and arranged as an input matrix for the R-mode PCA to identify the precipitation patterns. Results suggest that the study area can be divided into four spatially homogeneous sub-zones. In addition, the spatial patterns of annual precipitation were identified by applying the T-mode PCA and CA to the annual precipitation data. The delineated spatial patterns revealed three distinct sub-regions. The resultant maps were compared with the spatial distribution of the rotated principal components (PCs). Results pointed out that the delineated clusters are characterized by different precipitation variability; and using different precipitation parameters can lead to different spatial patterns of precipitation over northwest Iran.     

考虑参数空间变异性多层土坡系统可靠度分析

多层土坡在岩土工程实际中十分常见,不仅土体参数存在一定的空间变异性,而且土体框架呈现明显的层状分布特征,然而目前对考虑土体参数空间变异性的多层土坡稳定可靠度研究的远远不够。提出了基于多重响应面边坡系统可靠度分析的蒙特卡洛模拟（MCS）方法,给出了计算流程图,系统地研究了考虑土体参数空间变异性的多层土坡系统可靠度问题。结果表明,提出方法能够有效地分析考虑参数空间变异性低失效概率水平的多层土坡系统可靠度问题,并且具有较高的参数敏感性分析计算效率。     

The effects of hydrometer reading times on the spatial variability of soil textures in southeast Iran

Soil texture is an important physical soil property that may contribute to variations in many soil functions as well as nutrient storage and availability, water retention, and soil erosion. Although several methods for determining the texture classes of soil particles have been proposed, differences among hydrometer reading times have presented challenges in determining the precise soil texture classes. Therefore, this study was conducted to evaluate the effects of hydrometer reading time on the spatial variability of soil textures in the Rafsanjan area, southeast Iran. To accomplish this, 77 soil samples were collected on a 500-m square sampling grid from depths of 0–40, 40–80, and 80–120 cm, and their particle sizes were determined through analysis for 40 s, 2 h, 6.5 h, and 8 h using the Bouyoucos hydrometer method. The results showed a strong spatial correlation in the soil particles among sampling soil layers and across the study area. Moreover, the differences among hydrometer reading times did not have a significant impact on determination of coarse soil texture classes, although they did influence determination of the finer classes. Although the 8 h reading time provided the most accurate response with respect to mechanical analysis of a soil, after 6.5 h the hydrometer could also largely (more than 80.0 %, on average) achieve this goal. Additionally, the 2 h hydrometer reading time could also be useful for the initial assessment or general overview of the soil texture in a certain region; however, it is not recommended for precision agriculture or site-specific management.     

Probabilistic analysis of reinforced slopes using RFEM and considering spatial variability of frictional soil properties due to compaction

Probabilistic stability analyses of constructed wrapped-face reinforced slopes (or embankments) using frictional soils were carried out using the random finite element method (RFEM). Soil properties reported in the literature for unsaturated frictional fills compacted to different densities were used in the simulations. Bar elements were added to the RFEM code to simulate extensible geosynthetic reinforcement layers and the Davis approach was used to improve numerical stability for purely frictional soil slopes at collapse. The influence of isotropic and anisotropic spatially variable soil strength was investigated and shown to have a large influence on the variation of maximum mobilised tensile forces in reinforcement layers for the steep 5 m-high slopes in the study. The influence of fill placed at different layer thickness and compacted to different levels was simulated by adjusting the soil strength and unit weight, and the vertical strength correlation length in the anisotropic spatially variable strength field used in each slope realisation. Numerical results showed that vertical strength correlation lengths approaching the magnitude of fill lift heights can control the probability of failure for reinforced slopes constructed with weak fills placed in lift heights close to but less than the wrapped reinforcement spacing used in the study.     

Assessing spatial variability in soil characteristics with geographically weighted principal components analysis

Dimensionality reduction methods such as principal components analysis (PCA) provide a means of identifying trends in soil characteristics which may be represented by a wide range of variables. However, these characteristics may be highly spatially variable and so the results from PCA represent, in some sense, an “average” of locally distinct characteristics. One approach to account for these local differences is to introduce a geographical weighting scheme into the PCA process. In this paper, such an approach is assessed in the exploration of soil characteristics in the state of Pennsylvania, USA. Data from 878 georeferenced soil profiles which include different soil parameters (n = 12) were extracted from the National Soil Survey Center database. Where data are parts of compositions (e.g., percentages of sand, silt, and clay), analysis using raw data is not appropriate and such data were transformed using log ratios (specifically, balances). Single variables (i.e., those which are not parts of compositions) were logged. The first two principal components explain over 50% of the variance. The mapped values suggest marked spatial variation in soil characteristics, but it is not possible to assess which of these variables explain most variation in particular regions from the simple maps of raw variables. Geographically weighted PCA (GWPCA) provides additional information which is obscured by PCA, and it also provides a set of component scores and loadings at all data locations. The soil variable with the largest loading at most locations of Pennsylvania is the logged base saturation (BSln), and this supports the findings of the conventional PCA analysis. While BSln loads most highly in most of the eastern third, the middle and the south west of the state, the northwest is less spatially consistent in terms of the variables which explain most variation. For GWPC 1, the variable with the second largest loading at most locations (i.e., primarily the south and west) is CEC.B1 (the log ratio of Ca, Mg, and Na to K and EXACID), while CEC.B2 (the log ratio of Ca and Mg to Na), pHln (logged pH) and BSln dominate in other areas. The GWPCA results suggest that there is marked spatial variation in multivariate soil characteristics across Pennsylvania state and that results from standard PCA obscure this considerable variation.     

Effects of microtopography on the spatial pattern of woody species in West Iran

Habitat heterogeneity is a main factor determining the geographical distribution of species. For plant and particularly trees and shrubs, topography (microtopography) is an applicable predictor of habitat, slope, and aspect that often correlate with distribution of water and nutrients availability and spatial pattern of species. However, there is lack on exploring this relationship in different plant communities through different environments. In this research, the spatial pattern of woody species in relation to microtopography was investigated in Chahartagh forest, Chahar Mahal, and Bakhtiari province, Iran. The location of the trees and shrubs of a 53-ha forest reserve in Chartagh was measured and the type of microtopography including (i) slope A without microtopography and (ii) slope B composed of three microtopography types: crest (degree of tilt is≥60%), intermediate area (30–40%), and gully (10–20%) were recorded. The effects of microtopography on the spatial pattern of species were analyzed using O-ring statistic. The results showed that the main distribution pattern for the woodiest species in the study area in all platforms is aggregated pattern, while for larger scales, the pattern tended to become random. Also, the pattern was strongly influenced by the scale that the distribution type was assessed. From the other hand, our results revealed that for steeper platforms, the patterns tend to be more aggregated which indicates the non-uniformity of water and nutrition distribution in steeper platforms. Also, this can be a result of seed distribution behavior which is affected by microtopography in a way that in steep platforms, rolling of the seed results in patchy accumulation of the seeds and finally patchy regeneration.     

The spatial analysis of thunderstorm hazard in Iran

In this study, monthly, quarterly, and annual frequency data of thunderstorm days of 25 long-term synoptic weather stations during the period from 1960 to 2010 were analyzed applying Ward’s Hierarchical Cluster Analysis (WHCA) Method and Kriging Geostatistical Method (KGM). The results of temporal analysis of Thunderstorm Days (TD) in Iran showed that in terms of frequency, seasonal occurrence of this phenomenon is mostly in transitional seasons of spring and autumn. The results of WHCA to find homogeneous places in terms of synchronization and timing of TD reflects the fact that there are five clusters with similar memberships, including the North West, West, the southern part, northern, central, and northeastern parts, eastern regions, and center of Iran, and in this classification, the frequency of occurrence of TD reduces in the same order the regions are mentioned. In contrast, the lowest frequency of TD is in summer and winter seasons. In this study, it was found that among various deterministic and geostatistical methods, KGM is the most suitable one for thunderstorms hazard zonation and for classifying the different regions based on thunderstorm occurrence; WHCA is more suitable than other methods. The results of spatial analysis of thunderstorms point to the fact that the core of the mentioned thunderstorms is mostly in mountainous areas, particularly, highlands of North West and West of Iran. With regard to place, in the West part of the country, especially North West (Tabriz, Oroomieh, and Zanjan stations) and West, thunderstorms have higher frequencies, while the South East, South, Central, and eastern regions are less affected by the thunderstorm hazard.     

Reliability updating in geotechnical engineering including spatial variability of soil

At geotechnical sites, deformation measurements are routinely performed during the construction process. In this paper, it is shown how information from such measurements can be utilized to update the reliability estimate of the geotechnical site at future construction stages. A recently proposed method for Bayesian updating of the reliability is successfully applied in conjunction with a stochastic nonlinear geotechnical finite element model. Therein, uncertainty in the soil material properties is modelled by non-Gaussian random fields. The structural reliability evaluations required for the Bayesian updating are carried out by means of subset simulation, an efficient adaptive Monte Carlo method. The approach is demonstrated through an application to a sheet pile wall at a deformation-sensitive geotechnical construction site.     

Effects of saline water irrigation on soil properties in northwest China

Due to the lack of freshwater, highly saline groundwater was the main irrigation source in the last few decades in the Minqin Basin, which is in northwest China. The study evaluates the effects of salt accumulation on the soil physical–chemicals properties. Undisturbed and disturbed soil samples were taken from the experiment site, which was irrigated with saline water at a concentration of 0.8, 2 and 5 g L⁻¹ (coded later as C₀₈, C₂ and C₅). Undisturbed soil samples, at depths of 0–45 and 45–60 cm were taken to determine the water retention curve (WRC). Moreover, in the same place, another set of undisturbed soil samples were taken to determine the porosity and pore-size distribution (PoSD). From the WRC, the water-holding capacity of the soil was estimated. Disturbed soil samples at depths of 0–20, 0–45, 45–60 and 80–100 cm were taken to determine the index of aggregates stability in water (IC). The electrical conductivity of the saturated paste (EC_e) was determined at depths of 0–30, 30–60 and 60–90 cm, during the irrigation season on C₀₈, C₂ and C₅ treatments. The results show that the total porosity and the index of aggregates stability in water decrease with the increasing salinity of irrigation water, and the EC_e increases with the increasing salinity of irrigation water especially in the surface soil. The water-holding capacity (WHC) of soil also increases with the increasing salinity of irrigation water.     

土壤入渗特性的空间变异规律及其变异源

以封丘地区典型的4种土地利用类型(传统耕作地、免耕地、金银花地和杨树林地)为例,系统研究了不同土地利用方式下土壤入渗特性的空间变异强度、空间变异结构及其主要变异源。结果表明,频繁的耕作会降低土壤异质性,弱化土壤特性空间变异结构,扰动较小的免耕地和金银花地的土壤入渗特性则具有相对明显的空间变异结构,扰动最小的杨树林地土壤的入渗特性具有最为明显的空间变异结构和最小的变程。容重、有机质含量和初始含水量是耕作地入渗的最主要变异源,初始含水量则是金银花地入渗的唯一显著性变异源;杨树林地入渗变异的主要变异源是有机质和初始含水量;影响免耕地入渗特性变异的变异源并不显著。在有些情况下,水温也可能成为入渗特性空间变异研究的重要干扰因素。     

表层土渗透系数空间变异与随机模拟研究

在汉江遥堤典型堤段对堤后200 m?100 m范围内表层土取样进行渗透性试验,基于试验结果分析了土体渗透系数的随机性和结构性的空间变异特征,结果表明细砂渗透系数在水平方向具有各向同性,空间结构可用指数模型描述。采用转向带法进行渗透系数随机场模拟,从基本统计量、空间结构等方面进行的分析表明,转向带法模拟结果保持了原随机场的统计特性,具有较好的收敛性。     

An approach for modelling spatial variability in permeability of cement-admixed soil

Acta Geotechnica - This paper presents a framework for modelling the random variation in permeability in cement-admixed soil based on the binder content variation and thereby relating the...     

基于贝叶斯理论的土性参数空间变异性量化方法

岩土工程可靠度分析和设计中,合理地选取随机场参数和相关函数,并准确地描述土性参数空间变异性十分困难。基于贝叶斯理论,本文提出了一套量化砂土有效内摩擦角空间变异性的方法。该方法根据先验信息和静力触探试验锥尖阻力数据,确定砂土有效内摩擦角的随机场参数和相关函数。该方法合理地考虑了砂土有效内摩擦角与锥尖阻力间经验回归方程的不确定性。采用马尔科夫链蒙特卡洛模拟(Markov Chain Monte Carlo Simulation,MCMCS)获取服从后验分布的随机场参数样本。利用MCMCS样本构建随机场参数的Gaussian Copula函数求解后验分布。估计备选相关函数的概率,选择概率最大的为最可能的相关函数。最后,采用美国德州农工大学国家岩土工程砂土试验场的CPT数据算例验证了文中所提方法的有效性。结果表明:文中所提方法可以正确、合理地利用间接测量的锥尖阻力数据确定砂土有效内摩擦角的随机场参数和相关函数,准确量化其空间变异性。对于美国德州农工大学国家岩土工程砂土试验场的砂土有效内摩擦角,建议选用二阶自回归函数作为其最可能的相关函数。     

Effect of spatial variability of cross‐correlated soil properties on bearing capacity of strip footing

Geotechnical engineering problems are characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for a probabilistic analysis that considers the spatial variability of cross‐correlated soil properties is presented and applied to study the bearing capacity of spatially random soil with different autocorrelation distances in the vertical and horizontal directions. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two‐dimensional cross‐correlated non‐Gaussian random fields are generated based on a Karhunen–Loève expansion in a manner consistent with a specified marginal distribution function, an autocorrelation function, and cross‐correlation coefficients. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses was performed to study the effects of uncertainty due to the spatial heterogeneity on the bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to geotechnical problems and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment. Copyright © 2009 John Wiley & Sons, Ltd.     

坡面流速及侵蚀产沙空间变异性试验

在野外放水试验条件下,利用染色法和侵蚀针法分别观测坡面流速和侵蚀产沙空间变异性。结果表明,坡面各横向断面的流速与距坡顶距离之间呈正相关,且相关性随流量增大逐渐变得显著,纵向断面流速的变异程度明显强于横向断面。总体上,上、下坡位侵蚀程度较重,而中坡位最轻;小流量时沉积作用明显,大流量时距坡顶0~2 m范围为净侵蚀区;各坡段侵蚀量与其距坡顶距离之间呈负相关;发生泥沙沉积部位随流量增大逐渐下移,细沟侵蚀量占坡面总侵蚀量的比例随流量增大不断增加。试验条件下流速为0.30 m/s时,细沟侵蚀产沙大于细沟间侵蚀,且坡面侵蚀量迅速增大。随流量增大,流速和侵蚀产沙量呈增大趋势;但在流量较大时,坡面各坡位侵蚀量与流速呈负相关,这可能与坡面中下部位粗颗粒泥沙沉积以及含沙水流的挟沙能力基本达到饱和有关。