电磁感应仪EM38用于土壤盐渍剖面分类与评价研究

结合电磁感应仪EM38测量与田间采样,文章分析了黄河三角洲典型区域土壤电导率的剖面分布特征,建立了磁感式表观电导率与土壤电导率间的(多元)回归解译模型,探讨了不同分类方法对土壤盐渍剖面分类结果的准确性,并对典型盐渍剖面类型进行了评价。结果表明:研究区土壤盐分具有较强的表聚性与变异强度;土壤电导率与磁感表观电导率EMh、EMv间呈极显著的相关关系,EMh对浅层土壤电导率的解译精度较高,而EMv对深层土壤电导率的解译精度较高;EMv/EMh法和理论函数法对土壤盐渍剖面的分类结果均具有较高的精度,且理论函数法分类结果的准确性明显优于EMv/EMh法;研究区土壤盐渍剖面可划分为表聚型、底聚型与均匀型,在数量上以表聚型及底聚型为主,其中表聚型与均匀型属于积盐型剖面,底聚型属于脱盐型剖面。该结果对研究黄河三角洲地区土壤盐渍化的发生、机理、预测与评估该地区土壤盐渍化的发生、发展具有重要意义。     

南疆棉田表层土壤盐分的空间变异特征分析与应用

通过研究土壤盐分的空间变异,快速准确获取土壤盐分的空间分布是精准农业和环境保护的基础。使用土壤电导率仪(PET2000)网格法在50 m×70 m面积的田块内布点(网格边长5 m),测量棉田表层土壤(0~25 cm深度,每5 cm为一层)电导率;应用ArcGIS9.2中地统计学模块构建、筛选和验证模型;利用地统计学方法研究表层土壤盐分的空间变异规律,进行空间分布预测,并针对棉田表层积盐问题提出了相应的解决措施。结果表明:克里格(Kriging)插值方法中的Rational Quadratic模型适宜预测表层土壤电导率,区内棉田表层盐分的空间变异特征明显,变异系数达到0.578,土壤盐分的空间变异性随深度增大逐渐降低;产生空间变异的主要原因是土壤岩性的空间差异和微咸水灌溉;解决棉田局部积盐的措施是根据土壤盐分空间差异特征的分析与预测进行适时定位灌溉,从而合理利用水资源并改善作物生长环境。     

基于DRAINMOD-S模型的滨海盐碱地农田暗管排水模拟

在分析农田暗管排水饱和-非饱和土壤水、盐运移数学模型的基础上,对DRAINMOD-S模型的基本原理和参数输入要求进行了详细描述,利用典型滨海盐碱地区实测土壤、气象、作物等资料,用DRAINMOD模型对不同排水暗管布置方案的地下水埋深进行了长序列模拟,在模拟率定参数的基础上,用DRAINMOD-S模型对0~80 cm土壤层剖面含盐量进行了模拟,结果表明:模型具有良好的水文模拟性能,地下水位及土壤含盐量模拟值与实测值拟合精度较高;可用于预测盐碱地地下水埋深、土壤层剖面中盐分含量,是改良盐碱地农田暗管排水工程设计和水管理的有效工具。     

干旱区剖面土壤盐分空间变异特征及随机模拟

利用便携式土壤盐分计测定干旱区膜下滴灌棉田及裸地剖面土壤电导率,利用GS+软件确定其半方差函数,并进行序贯高斯模拟来研究土壤剖面盐分的空间变异特征。结果显示:干旱区剖面上土壤盐分空间变异性强,膜下滴灌棉田符合球形模型,裸地区符合高斯模型,且棉田变程远小于裸地;棉田埋深50cm以浅土壤盐分变化剧烈,埋深50cm以深变化平缓,在垂向上呈现3个高值区(30,50和75cm深度附近)及3个低值区(埋深40,60和100cm附近);克里格法具有明显的平滑作用,降低了土壤盐分的空间变异性,而序贯高斯模拟数据更离散,更能反映土壤盐分的空间变异性,但多次模拟均值随次数增加趋于稳定。     

基于地理加权回归的莱州湾南岸土壤盐渍化与环境因子的关系研究

选取莱州湾南岸为研究区域,系统采集了111个表层土壤样品,测定了土壤全盐量以及K~+、Na~+、Ca~(2+)、Mg~(2+)、Cl~-、SO_4~(2-)、HCO_3~-和CO_3~(2-)等8种土壤盐分离子的含量,运用多元统计分析以及地理加权回归模型等方法,分析了莱州湾南岸土壤盐渍化的影响因素。结果表明:①研究区土壤以盐土为主,Cl~-的浓度和变异系数远远高于其他盐分离子,在土壤表层的累积十分显著,氯化物在土壤中最为活跃。②土壤含水率、土壤干容重、土壤有机质、植被覆盖率与土壤盐渍化程度之间出现了高相关性,拟合精度高。③气温、降水、地下水埋深、地下水矿化度表现出中等相关性,拟合精度较高。④数字高程模型(DEM)、高差、土壤粒度、土壤pH表现了一般相关性,拟合精度一般。     

基于随机森林回归分析的岩体结构面粗糙度研究

岩体结构面粗糙度系数是快速估算结构面峰值抗剪强度的重要参数。但是结构面轮廓曲线复杂,单一统计参数无法量化表征粗糙度。为解决这一问题,收集了112条结构面轮廓曲线起伏角、起伏度、迹线长度3方面的8项统计参数,利用随机森林回归模型交叉验证的方法评估统计参数的重要性。结果表明：最大起伏度、起伏高度标准偏差、平均起伏角、起伏角标准差、平均相对起伏度及粗糙度剖面指数等6项统计参数重要性占比达到93.2%,且回归拟合系数趋于平稳,基于重要性评估结果建立最优超参数决策树数目(n_tree)为400、参与节点分割的数目(m_try)为2的随机森林回归模型,模型预测结果拟合优度高达98.1%。与基于坡度均方根、结构函数及粗糙度剖面指数等传统线性回归结果对比,随机森林回归模型结果精度更高,误差更小,拟合优度提高6%以上,表明随机森林回归模型更适用于结构面粗糙度反演。     

基于PCA-GWR的包气带不同土层饱和导水率的传递函数及其回归克里金估计

饱和导水率是重要的土壤水力学参数,对渗流和溶质运移研究起着至关重要的作用.土壤传递函数可以代替大规模采样和室内外试验间接预测该参数,但由于土壤的空间变异性以及方法的局限性等原因,以往的传递函数往往精度有限.本文以黄河下游沿岸兰考县闫楼乡包气带不同土层为研究对象,基于64个钻孔数据,将土壤粒径分布（黏粒、粉粒和砂粒含量）、土壤结构分形维数、干容重、总孔隙度、pH值、有机质和电导率等9个基本理化特性参数作为影响因素,基于逐步回归、主成分回归和主成分-地理加权回归（PCA-GWR）三种方法,分别对研究区包气带不同土层的饱和导水率进行回归分析,比较精度后基于PCA-GWR对饱和导水率进行地理加权回归克里金插值.结果显示,除表层粉土以外,PCA-GWR法的预测精度有显著优势.不同土层传递函数和饱和导水率分布的差异性表明,由于黄河下游地区快速多变的沉积过程、黄河的决口改道以及人类活动等因素,包气带土层相变剧烈,土壤饱和导水率在平面上亦具有明显的非平稳特征.而局部地质作用和人类活动是第二层粉土层回归克里金估计结果欠佳的深层原因.     

焉耆盆地土壤盐分剖面特征及其与土壤颗粒组成的关系

为查明焉耆盆地土壤盐分剖面特征及其影响因素, 进行土壤样本含盐量及颗粒组成测试, 利用Spearman等级相关分析两者关系.结果表明: 土壤盐分剖面分为3种类型——均布型、表聚型和振荡型, 均布型剖面含盐量最低且分布均匀, 表聚型剖面盐分表聚特征最明显(表聚系数4.20), 振荡型剖面含盐量高且变异程度大(变异系数82.4%); 土样类型中粉质壤土最多(占70.8%), 颗粒组成中粉粒平均含量最高(57.1%); 均布型剖面盐分与粘粒含量相关程度最高(相关系数0.560), 为极显著正相关; 振荡型剖面盐分与砂粒含量相关程度最高(相关系数-0.639), 呈极显著负相关; 表聚型剖面盐分与颗粒组成无明显关系.结合各类剖面分布区域可知, 在砂粒含量与盐分含量较低的非盐渍化地带, 土壤盐分分布主要受粘粒含量影响; 砂粒含量与盐分含量较高的盐渍化地带, 土壤盐分分布主要受砂粒含量影响.      

基于RAGA的指数曲线模型预测基桩承载力

预测挤扩支盘桩单桩极限承载力指数曲线模型的函数表达式是一个超定非线性方程。采用传统的最小二乘法对该模型参数进行回归处理时,往往由于计算复杂和人为因素的影响使预测结果存在较大的误差。为此,用实数编码加速遗传算法（RAGA）,对指数曲线模型的参数和理论极限承载力进行优化,并基于MATLAB环境下编写了模型的计算程序。结合工程实例,应用指数曲线模型对挤扩支盘桩静载荷试验实测数据进行了拟合分析。结果表明,基于RAGA的指数曲线优化模型能够更好地拟合实测数据和有效地预测单桩极限承载力,且基于RAGA的指数曲线优化模型具有求解速度快、计算精度和自动化程度高、人为干扰因素小、通用性强等优点。     

探地雷达在干旱区盐渍化土壤层定量探测中的应用

研究了在探地雷达定量探测盐渍化土壤中电磁波传播速度与土壤含盐量或电导率的相关关系,研究表明传播速度和盐渍化土壤的盐分或电导率具有显著的相关性。回归分析结果说明:利用传播速度可较好地定量表达盐渍化土壤的含盐量或电导率。     

Comparison of statistical prediction methods for characterizing the spatial variability of apparent electrical conductivity in coastal salt-affected farmland

Soil salinity has been known to be problematic to land productivity and environment in the lower Yellow River Delta due to the presence of a shallow, saline water table and marine sediments. Spatial information on soil salinity has gained increasing importance for the demand of management and sustainable utilization of arable land in this area. Apparent electrical conductivity, as measured by electromagnetic induction instrument in a fairly quick manner, has succeeded in mapping soil salinity and many other soil physical and chemical properties from field to regional scales. This was done based on the correlation that existed between apparent electrical conductivity and many other soil properties. In this paper, four spatial prediction methods, i.e., local polynomial, inverse distance weighed, ordinary kriging and universal kriging, were employed to estimate field-scale apparent electrical conductivity with the aid of an electromagnetic induction instrument (type EM38). The spatial patterns estimated by the four methods using EM38 survey datasets of various sample sizes were compared with those generated by each method using the entire sample size. Spatial similarity was evaluated using difference index (DI) between the maps created using various sample sizes (i.e., target maps) and the maps generated with the entire sample size (i.e., the reference map). The results indicated that universal kriging had the best performance owing to the inclusion of residuals and spatial detrending in the kriging system. DI showed that spatial similarity between the target and reference maps of apparent electrical conductivity decreased with the reduction in sample size for each prediction method. Under the same reduction in sample size, the method retaining the most spatial similarity was universal kriging, followed by ordinary kriging, inverse distance weighed, and local polynomial. Approximately, 70 % of total survey data essentially met the need for retaining 90 % details of the reference map for universal kriging and ordinary kriging methods. This conclusion was that OK and UK were two most appropriate methods for spatial estimation of apparent electrical conductivity as they were robust with the reduction in sample size.     

昆仑山地区冻融土导热系数试验测试与预测模型研究

为探究青藏高原工程走廊带昆仑山地区冻融土导热系数基本特征,采用瞬态平面热源法对钻取的349组冻土试样和245组融土试样导热系数进行了测试,分析了五类土导热系数分布特征及天然含水率、干密度与导热系数的偏相关性,并以两者为变量因素建立了经验公式拟合、支持向量回归（SVR）和径向基（RBF）神经网络导热系数预测模型。结果表明:冻融土导热系数整体均呈粗颗粒土大于细颗粒土特征,且冻土和融土导热系数随土性分布规律存在差异;天然含水率、干密度与导热系数均呈正相关性,不同土类偏相关性结果差异明显,典型土导热系数二元经验回归方程表现为非线性拟合结果。对比三种预测模型下各典型土冻融土导热系数预测结果,全风化千枚岩、角砾及砾砂三种预测模型效果整体较佳,粉土的SVR及RBF神经网络预测精度较好;融土导热系数预测效果整体略优于冻土,SVR及RBF神经网络模型下角砾、粉土及全风化千枚岩融土导热系数预测精度较高。综合导热系数模型预测效果和误差结果分析可得,SVR和RBF神经网络模型预测效果显著优于经验方程拟合,后者针对部分土性拟合效果相对较好,可满足一般工程估算需求;SVR和RBF神经网络预测模型针对不同土性导热系数预测效果呈差异性变化,整体预测效果相当,且预测精度更高、应用土性范围更广。     

Studies on the reflectance spectral features of saline soil along the middle reaches of Tarim River: a case study in Xinjiang Autonomous Region, China

There has been growing interest in the use of reflectance spectroscopy as a rapid and inexpensive tool for soil characterization. In this study, 53 soil samples were collected from the oasis in the Weigan and Kuqa River delta along the middle reaches of Tarim River to investigate the level of soil chemical components in relation to soil spectral. An approach combining spectral technology and multi-variant statistical analysis was used to determine the reflectance spectral features of saline soil. The spectral data was first pretreated to remove noises and absorption bands from water, which eliminated influence from instrument errors and other external background factors. Several spectral absorption features were calculated for several saline soil samples to confirm that soil at the same salinity level had similar absorption spectral properties. Secondly, a correlation relationship between reflectance spectra and salinity factors was estimated by bivariate correlation method. Fourteen salinity factors including eight major ions and soil electrical conductivity (EC), soil salt content (SSC), pH, and total dissolved solid (TDS) in the saline soil were evaluated. Datasets of the salinity factors that correlated significantly with field data measurements of reflectance rate and the corresponding spectrum data were used to construct quantitative regression models. According to the multiple linear regression analysis, SSC, SO₄ ^2?, TDS, and EC had a correlation coefficient at 0.746, 0.908, 0.798, and 0.933 with the raw spectral data, respectively, which confirmed strong correlation between salinity factors and soil reflectance spectrum. Findings from this study will have significant impact on characterization of spectral features of saline soil in oasis in arid land.     

基于频域电磁法反演喀斯特表层土－岩结构研究

喀斯特地区浅表层土壤分布极不均匀,探测土－岩界面和土壤分布对区域水文以及生态环境研究具有重要意义。文章基于麦克斯韦方程组构建了频域电磁法（FDEM）探测的电导率（EC）一维反演模型,实现了喀斯特浅表剖面EC可视化表述。根据设定的理想地层EC数据以及南方喀斯特峰丛洼地两个剖面和出露的三个实测剖面的FDEM实测视电导率,结合高密度电法、剖面实测土－岩界面,检验了反演模型可靠性。结果表明:FDEM法反演结果能较好的描述理想地层EC变化,以及土壤与灰岩、白云岩界面EC分布,进而可辨识土壤厚度分布,但基于反演的EC值判别尺度较小的溶沟（槽）以及泥岩区土－岩界面误差较大。      

Assessing soil water content spatio-temporal variability at the hillslope scale in a headwater catchment using a multi variable interpolation model based on EMI surveys (Draix,South Alps,France)

To improve flood prediction in headwater catchments, hydrologists need to know initial soil moisture conditions that precede rain events. In torrential hydrology, soil moisture mapping provides a valuable tool for investigating surface runoff generation processes. In these mountainous environments, soil moisture prediction is challenging because of highly heterogeneous land cover and soil properties. This survey propose a methodology to study spatial soil moisture variations in the mountainous and torrential environment of the Draix Bléone experimental site—Laval 0.86 km². This approach associates water content measurements at the plot scale with spatialized soil bulk electrical conductivity (EC_a) measurements combined in a multivariate statistical analysis based on topographical parameters. Between the summer of 2015 and winter of 2016, four geophysical surveys were conducted under various moisture conditions and along the same pathway, using the Slingram electromagnetic induction (EMI) technique (EM31 device) in horizontal dipole to identify changes in soil properties to a depth of 3 m. These results were analyzed to determine water dynamics in this mountainous catchment. Temporal variations of EC_a vary among land cover types (forest, grassland, and black marl). A significant relationship was observed between EC_a and soil water content (SWC) measured with capacitive sensors in forest and grassland. A multiple linear regression produced using the spatial interpolation code LISDQS shows a significant correlation between EC_a and landform units depicted on a high-resolution DEM. EC_a variations decrease with distance to talwegs. Riparian zones appear as potential hydrological contributing areas with patterns varying according to moisture status. This study shows that multiple linear regression analysis and EMI make it possible to fill gaps between SWC plot measurements, over wide areas that are steep and that present numerous obstacles due to vegetation cover.     

青藏工程走廊冻融土热扩散系数特性与预测模型研究北大核心CSCD

热扩散系数是多年冻土对外界热扰动敏感程度的重要影响参数之一,也是寒区工程设计与建设的关键基础数据。基于瞬态平面热源法导热系数测试结果和质量加权法计算获取的比热容理论值,计算获得青藏工程走廊西大滩—唐古拉山沿线典型类别土样热扩散系数,分析对比了走廊带内冻融土热扩散系数的分布特征和参数影响规律,提出了基于经验拟合公式法和RBF神经网络方法的冻融土热扩散系数预测模型,并比较了不同预测模型的预测效果。研究结果表明:青藏工程走廊带内土的热扩散系数与粒径整体呈正相关性,融土热扩散系数按黏性土、粉土、全风化岩类、砂土及碎石土依次增大,冻土热扩散系数按黏性土、全风化岩类、粉土、碎石土及砂土依次增大;热扩散系数与容重及天然含水率相关性随土类及冻融状态差异明显,冻、融土热扩散系数呈显著正线性关系;以融土热扩散系数为拟合参数的冻土热扩散系数三元预测模型的预测精度明显高于二元经验公式;RBF神经网络模型在冻、融土热扩散系数预测中均具有最优的预测精度,为最佳预测模型。     

基于频域反射的细粒土压实度检测方法与误差评估

压实度是道路、房建、水利等工程领域评价土体压实质量的重要参数,与土体含水率和电导率密切相关。而频域反射技术(frequency domain reflectometry,FDR)可用于快速测定土体含水率和电导率。首先利用频域反射技术分别对多种压实状态下红黏土、膨胀土和黄土的含水率、电导率进行测量;然后对含水率测值进行室内标定,得到3种土的含水率标定曲线;通过偏最小二乘回归分析方法(partial least squares regression,PLSR)建立了3种土体的压实度-含水率-电导率之间的经验关系,并与实测值进行了对比分析;再根据扫描电子显微镜(scanning electron microscopy,SEM)和压汞法(mercury intrusion porosimetry,MIP)试验结果分析了其微观机制;最后对拟合公式得到的压实度预测值进行随机试样验证,建立与实测值的误差评估体系,结果表明基于压实度-含水率-电导率之间的关系而提出的拟合公式预测压实度的精度较高。相关研究可为道路、房建、水利等工程中土体压实度的快速检测提供参考。     

High-resolution vertical profiles of groundwater electrical conductivity (EC) and chloride from direct-push EC logs

Elevated groundwater salinity associated with produced water, leaching from landfills or secondary salinity can degrade arable soils and potable water resources. Direct-push electrical conductivity (EC) profiling enables rapid, relatively inexpensive, high-resolution in-situ measurements of subsurface salinity, without requiring core collection or installation of groundwater wells. However, because the direct-push tool measures the bulk EC of both solid and liquid phases (EC_a), incorporation of EC_a data into regional or historical groundwater data sets requires the prediction of pore water EC (EC_w) or chloride (Cl^?) concentrations from measured EC_a. Statistical linear regression and physically based models for predicting EC_w and Cl^? from EC_a profiles were tested on a brine plume in central Saskatchewan, Canada. A linear relationship between EC_a/EC_w and porosity was more accurate for predicting EC_w and Cl^? concentrations than a power-law relationship (Archie’s Law). Despite clay contents of up to 96%, the addition of terms to account for electrical conductance in the solid phase did not improve model predictions. In the absence of porosity data, statistical linear regression models adequately predicted EC_w and Cl^? concentrations from direct-push EC_a profiles (EC_w = 5.48 EC_a + 0.78, R ² = 0.87; Cl^? = 1,978 EC_a – 1,398, R ² = 0.73). These statistical models can be used to predict EC_w in the absence of lithologic data and will be particularly useful for initial site assessments. The more accurate linear physically based model can be used to predict EC_w and Cl^? as porosity data become available and the site-specific EC_w–Cl^? relationship is determined.     

Estimating apparent thermal diffusivity of soil using field temperature time series

Reliable estimates of soil thermal properties such as heat capacity, thermal conductivity, and diffusivity are important in analysis of heat transmission through soils in applications such as shallow geothermal applications, buried electrical conduits, and in general heat/fluid flow analyses. A number of analytical, numerical and experimental methods are available to determine the soil thermal properties. In this paper, the analytical and numerical methods developed on the basis of one-dimensional heat conduction equation are used to estimate the apparent thermal diffusivity of soil. Three of the four analytical methods, Amplitude, Phase, and Arctangent provide explicit equations for the apparent thermal diffusivity. Two methods, Harmonic and Numerical, make use of large number of temperature measurements to implicitly solve for the apparent thermal diffusivity. The temperature time series data monitored at different depths in two field sites in Melbourne, Australia for more than 2 year period were used to estimate the apparent thermal diffusivity of soil down to 2 m depth. The apparent thermal diffusivity was calculated using all five methods and compared with laboratory experimental results. The effectiveness of each method in predicting the thermal diffusivity was compared and observed discrepancies were discussed. Finally, the observed soil temperature data for a 12 month period are used to model the temperature variation in the ground analytically using Harmonic method and the model prediction for the following 12 month was compared independently with the field measurements. The analytical model prediction is found to be in good agreement with the field monitored data.