基于电磁感应的典型干旱区土壤盐分空间异质性

为研究干旱区土壤盐分空间异质性,指导农业生产实践,运用大地电导率仪（EM38、EM31）对研究区域进行移动式磁感调查,获取表观电导率（ECa）。同时,通过27个校准点的采样和ECa测量,建立土壤盐分的电磁感应解译模型。干旱区土壤盐分质量分数与EM38、EM31水平模式读数（H38、H31）显示出良好的相关性（R=0.935）,可以利用ECa结合GIS和地统计学知识研究土壤盐分的空间分布。采用两种方法进行研究：一种是先利用解译模型获取磁感调查点的土壤盐分质量分数,然后进行地统计分析研究其空间分布;另一种是先利用地统计分析研究H38和H31的空间分布,然后利用解译模型通过栅格运算计算盐分质量分数,精度检验显示前者预测值与实测值之间的相关性更好（R2, 0.888＞0.873）;标准差较低（std. 0.414＜0.426）,具有更高的预测精度。研究结果表明,基于电磁感应研究干旱区土壤盐分空间异质性是切实可行的,这对于土壤盐渍化的快速诊断,指导农业生产和促进精准农业的发展具有重要的意义。     

基于电磁感应仪的土壤盐渍化剖面特征解译研究

为了快速、精准解译区域尺度土壤盐分特征,有必要建立土壤剖面盐分信息精确解译模型。以新疆农灌区不同土壤质地的盐渍化土壤为研究对象,利用电磁感应式大地电导率仪EM38获取土壤表观电导率,构建了基于EM38的两种土壤质地剖面分层盐分解译模型,并对盐分解译回归模型进行了精度检验。结果表明:两种质地的土壤剖面盐分含量变异均较大,中壤土各层电导率变异系数在58%~98%,呈现中等变异强度,而砂土表层(0~40 cm)变异系数达到100%以上,属于强变异强度,深层土壤变异系数介于76%~88%属于中度变异强度。两种质地土壤电导率与磁感表观电导率EMh、EMv间呈显著的相关关系,水平和垂直测量模式都能够对不同深度土盐层分进行预测,且以EMh+EMv为自变量的二元回归解译模型具有较高的精度,相关系数R达到0.94以上。中壤土EM38的盐分预测在不同深度土层的验证结果决定系数达到0.59以上,砂土质地土壤盐分预测验证R2达到0.36以上,预测精度与土壤剖面盐分变异性呈现显著负相关,其相关系数为-0.86,中壤土质地的解译效果优于砂土质地。分析EM38在预测不同土壤质地盐分精度上的差异性,构建了电磁感应式土壤剖面盐分含量的预测模型。研究结果引入土壤质地变量,可为大面积土壤盐渍化的快速精确测定提供理论依据。     

应用电磁感应和遥感的新疆绿洲区域尺度盐渍土识别

针对干旱区土壤盐渍化问题,以新疆渭干河-库车河绿洲为研究区,探讨电磁感应技术和光谱角分类法(SAM)相结合来识别典型干旱区盐渍土的可行性。以重度盐渍土为例,利用电磁感应仪EM38和采样数据,结合光谱角分类法和回归分析法,反演土壤电导率(EC1:5)的空间分布,识别重度盐渍土。结果表明:土壤表观电导率(ECa)与土壤电导率(EC1:5)具有较好的非线性相关性;垂直模式电导率(EMv)对土壤电导率(EC1:5)的解译精度优于水平模式电导率(ECh);研究区土壤盐分含量在区域尺度呈中等强度变异;电磁感应技术和光谱角分类法结合可以较好识别符合条件的盐渍土。该研究方法能够较好识别典型干旱区的盐渍土,为盐渍化评估、预防和治理提供了新的途径。     

基于磁感式大地电导率仪的土壤盐分解译模型

以新疆伊犁地区盐渍土为研究对象,通过分层采样测定土壤盐分含量,采用EM38和EM31两种磁感式大地电导率仪测定土壤表观电导率,分析不同土壤层次盐分与土壤表观电导率的相关性,应用逐步回归方法构建土壤盐分解译模型,并进行了模型精度验证。研究表明:土壤盐分含量与土壤表观电导率之间呈显著线性相关,构建的土壤盐分解译模型具有良好的精度。本研究将为精确解译伊犁地区土壤盐渍化特征提供重要的方法支撑。     

基于电磁感应仪数据的南疆棉田土壤电导率反演模型研究

土壤盐渍化是南疆棉田优质高产的主要障碍因素,定额灌溉可有效改良土壤盐渍化,EM38-MK2可快速、动态获取土壤盐渍化数据,适时监测土壤盐渍化,为棉田定额灌溉提供数字依据。针对电磁感应仪(EM38-MK2)的发射圈和接收圈设计了不同采样方案,在同一条田内采集了6个不同时期的土壤表观电导率数据及相应的剖面土样,分析了不同土壤采集方案及土壤含水量对表观电导率模型精度的影响,对比了以单一时期数据建模的局部模型和6个时期整体数据建模的全局模型的反演精度。结果表明,由单点采集电磁感应仪发射线圈位置土样所构建的模型精度更高,稳定性更好,能有效减少由采样带来的误差。当土壤含水量低于10%时,表观电导率与实测电导率之间的相关性较低,决定系数为0.58,反演模型只具备粗略估计实测电导率的能力;当土壤含水量高于10%时,表观电导率与实测电导率具有很好的相关性,决定系数达到0.80以上,反演模型具有较好的预测能力。EMH+EMV多测定模式下表观电导率与实测电导率之间的模型精度高于EMH或EMV单一测定模式,确立EC_(h0.375)+(EC_(h0.75)+EC_(v0.75))/2+EC_(v1.5)为建模因子,有效提高了反演模型的精度。不同深度土层的局部模型反演精度均高于全局模型精度,局部模型的RPD均大于2.0,具有较好的预测能力。     

基于遥感与电磁感应仪数据的土壤盐分空间变异性

针对目前黄淮海平原存在的土壤盐渍化问题,以河南省封丘县为研究区,利用遥感影像与磁感应电导率仪 （EM38）在田间定位、定点测量,对研究区土壤盐分的空间变异性进行研究。利用Kriging、指数回归和回归-Kriging 3种不同的方法对土壤盐分空间变异性进行分析。结果表明：土壤电导率在一定的区域范围内具有空间结构特征,符合指数模型分布,具有极强的空间自相关性。通过3种不同的方法对土壤盐分的空间变异性进行分析,结果表明Kriging法、指数回归法及回归-Kriging法在描述土壤盐分空间分布的总体趋势上相似,但指数回归法与回归-Kriging法对于盐分的分布表达更具体,更细致。综合运用多种数据源的方法,即遥感影像数据与EM38测量数据相结合,经典统计学与地统计学方法相结合的方法,能够提高土壤盐分空间预测的精度,结果表明研究区土壤盐分由北向南、自西向东有逐渐升高的趋势,具有明显的趋势效应。     

电导率法在土壤盐渍化中的改进和应用进展

土壤盐渍化是常见的地质灾害之一,对土壤盐分状况及盐渍化程度的空间分布特征进行了解是有效治理的前提条件。电导率法作为一种快速稳定测定土壤盐分时空分布特性的方法被广泛应用于土壤盐渍化研究中。土壤溶液电导率(ECw)、土壤浸出液电导率(ECe)及土壤表观电导率(ECa)都可以对土壤盐渍化程度进行量化,土壤溶液电导率(ECw)可以通过原位取样器和盐分传感器进行测量,通过制备饱和土浆则可以对土壤浸出液电导率(ECe)进行测量,电阻率法和电磁感应法则可以测定土壤的表观电导率(ECa)。本文就不同电导率法的测量原理及实际测量对象、常用技术设备、优缺点进行综述。为更好的理解电导率法在土壤盐渍化中的应用提供参考     

基于电磁感应协同野外原位光谱的土壤盐分反演研究

快速准确监测土壤盐渍化可为土地资源合理开发利用与改良提供科学依据。利用 EM38-MK2大地电导仪和野外光谱仪测定的土壤表观电导率和光谱数据，构建表观电导率与土壤电导率的反演模型，依据相关性分析结果进行土壤盐渍化特征波段的提取，并采用反射率、反射率倒数和反射率一阶微分 3种数据变换形式构建土壤电导率的全波段与特征波段的偏最小二乘回归与主成分回归土壤盐分监测模型。研究结果表明，EM38-MK2测定的土壤表观水平电导率和表观垂直电导率相结合建立的电导率解译模型的拟合优度达到 0.89，在土壤盐渍化光谱建模中可快速提供电导率数据。全波段建模精度高于特征波段建模精度，偏最小二乘回归建模精度高于主成分回归建模精度，反射率一阶微分变换后建立的模型精度优于反射率倒数变换与反射率。研究区土壤电导率的预测模型选取经一阶微分变换后的全波段偏最小二乘回归建模方法为最佳模型，精度指标可达到 0.85，相对分析误差可达到2.56。     

松嫩平原盐渍化水田土壤表观电导率空间变异研究

运用电磁感应仪EM38结合GPS定位,以盐渍化水田为研究对象,通过经典统计学和地统计学相结合的方法研究了盐渍土区新开水田表观电导率的空间变异特征,分析了土壤表观电导率与土壤盐碱指标关系。结果表明,经典统计分析土壤水平方向表观电导率(ECh)与垂直方向表观电导率(ECv)均为中度空间变异强度,且符合正态分布。地统计分析表明,ECh和ECv均具有强空间相关性,其变异特征主要是由结构性因素引起的,半方差拟合最优模型为指数模型。且ECh和ECv空间分布在一定范围内存在相似性,均表现为不同表观电导率的土壤呈斑块和条带状镶嵌分布。Pearson分析显示,土壤表观电导率与盐碱化指标土壤电导率(EC1︰5)和碱化度(ESP)呈正相关关系(P0.05),相关系数大于0.8。回归分析表明,土壤表观电导率与EC1︰5和ESP均为指数函数关系,决定系数大于0.76。ECh与土壤盐碱化指标相关系数和决定系数均大于ECv,因此可以用水平方向土壤表观电导率ECh来反映土壤的盐碱化程度。该研究可以为土壤盐分空间变异理论与盐碱地改良实践相结合的研究思路提供理论基础,为盐碱地实施定位、定区清除或消减土壤盐碱的均质化改良技术提供数据支持。     

煤矸石填充对沟道导排水性能和土壤肥力及重金属污染的影响

为探寻适合东北黑土区侵蚀沟复垦的技术方法,该文研究了一种基于复垦后导排水能力最大的侵蚀沟煤矸石填充复垦技术方法,通过模拟一定深度的沟道、应用响应曲面法探究覆土和煤矸石填充厚度的变化对于复垦沟道导排水性能的影响及最优厚度搭配组合预测。同时引入土工布并考察土工布对煤矸石淋溶过程中重金属的隔绝作用。选择一条用煤矸石填充复垦4 a后的侵蚀沟,在耕层(0～20 cm)进行土壤肥力以及重金属污染情况的调查研究。结果表明:1)土层厚度增加减弱沟道导排水能力,混合粒径、大粒径煤矸石层厚度增加增大沟道导排水能力,土层与大粒径煤矸石层组合存在交互作用。覆土、混合粒径及大粒径煤矸石层厚度分别为53.42、38.51、90 cm时,模拟2 m深沟道导排水能力最强。2)沟道复垦4 a后,容重增加、酸度改善、全磷含量持平于对照土壤,全氮、全钾及有机质含量显著低于对照土壤。综合肥力小于对照土壤,略高于黑龙江省第二积温带的土壤综合肥力。3)复垦土壤Pb含量持平于当地对照土壤及背景值,Cr、Cu含量高于当地对照土壤及背景值,但均未超过环境质量二级标准值,3种重金属存在轻度污染及富集现象。研究结果可为土地整理规划提供一定借鉴。     

Comparison of Geonics EM38 and Dualem 1S electromagnetic induction sensors for the measurement of salinity and other soil properties

The electromagnetic induction (EMI) Geonics EM38 (G‐EM38) and Dualem 1S (D‐1S) sensors are used frequently for assessment of soil salinity and other soil characteristics in irrigated agriculture. We compared these two sensors to determine whether they could be used interchangeably for the measurement of apparent soil electrical conductivity (ECa) in horizontal (ECa‐h) and vertical (ECa‐v) coil receiver modes. Readings were taken at 201 locations identified in three irrigation districts in both modes, and statistical comparisons were made on the raw data and from maps of a 2‐ha irrigated field made using 1680 horizontal mode readings. Both sensors gave the same ECa‐v readings (mean G‐EM38 and D‐1S difference = 0), whereas the ECa‐h readings were slightly greater with the Geonics EM38 than with the Dualem D‐1S (mean difference = 0.075 and 0.05 dS/m for the 201 and 1680 observations, respectively). The degree of coincidence between both sensors for soil profile ECa classification was acceptable: 82% for normal profiles (i.e. ECa‐h/ECa‐v < 0.9) and 90% for inverted profiles (i.e. ECa‐h/ECa‐v > 1.1). In practical terms, Geonics EM38 and Dualem 1S sensors could be used interchangeably with similar or very close results.     

干旱区三种典型地貌下电磁感应式土壤盐分协同解译模型

为明确不同地貌类型下土壤理化性质对电磁感应式表观电导率测量精度的影响,该研究以新疆玛纳斯河流域3种典型地貌类型(冲积洪积扇缘、冲积平原、干三角洲)为研究对象,运用电磁感应仪EM38结合土壤采样室内测定方法,分析土壤剖面(100 cm)每20 cm土层的土壤性质对不同高度(130、110、90、70、50 cm)所测表观电导率的影响程度和贡献率,通过引入对表观电导率贡献率较高的非盐分因子作为辅助变量,利用多元线性回归方法,建立土壤盐分多因素协同解译模型。结果表明:3种地貌类型中,土壤盐分含量是影响表观土壤电导率贡献率最大的作用因子,不同地貌类型下各土层影响表观电导率的因子存在明显的差异,冲积洪积扇缘地貌主要表现为上层(0～60cm)土壤含水率和底层(60～100)土壤阳离子交换量和有机碳含量对表观电导率贡献较高,冲积平原地貌则是表层(0～20 cm)和底层(40～100cm)的土壤含水率以及20～40cm土层的黏粒含量和阳离子交换量对表观电导率表现出较高的贡献率,干三角洲地貌下上层土壤(0～60cm)阳离子交换量和下层(60～100cm)土壤有机碳含量能够对表观电导率产生较为明显的影响。通过引入对表观电导率影响较大的作用因子,建立了针对不同地貌类型下分层土壤盐分协同解译模型,与仅以表观电导率解译土壤盐分含量相比,冲积洪积扇缘、冲积平原、干三角洲地貌类型下0～100cm土层盐分预测模型校正决定系数分别由0.81～0.86、0.55～0.87、0.25～0.56提高至0.83～0.91、0.63～0.93、0.48～0.70,多因素协同解译模型有效提高了土壤盐分解译模型精度。研究结果可为盐渍化土壤的快速准确监测提供可靠的理论依据和技术方法。     

Use of an electromagnetic technique to determine sodicity in saline-sodic soils

Soil sodicity is an increasing problem in arid‐land irrigated soils that decreases soil permeability and crop production and increases soil erosion. The first step towards the control of sodic soils is the accurate diagnosis of the severity and spatial extent of the problem. Rapid identification and large‐scale mapping of sodium‐affected land will help to improve sodicity management. We evaluated the effectiveness of electromagnetic induction (EM) measurements in identifying, characterizing and mapping the spatial variability of sodicity in five saline‐sodic agricultural fields in Navarre (Spain). Each field was sampled at three 30‐cm soil depth increments at 10–30 sites for a total of 267 soil samples. The number of Geonics‐EM38 measurements in each field varied between 161 and 558, for a total of 1258 ECa (apparent electrical conductivity) readings. Multiple linear regression models established for each field predicted the average profile ECe (electrical conductivity of the saturation extract) and SAR (sodium adsorption ratio of the saturation extract) from ECa. Despite the lack of a direct causal relationship between ECa and SAR, EM measurements can be satisfactorily used for characterizing the spatial distribution of soil sodicity if ECe and SAR are significantly auto‐correlated. These results provide ancillary support for using EM measurements to indirectly characterize the spatial distribution of saline‐sodic soils. More research is needed to elucidate the usefulness of EM measurements in identifying soil sodicity in a wider range of salt and/or sodium‐affected soils.     

Characterization of nitrogen dynamics in a pasture soil by electromagnetic induction

The aim of this study was to investigate how electromagnetic induction can be used to improve the characterization of N dynamics in a 1.2 ha pasture. The soil apparent electrical conductivity (ECa) was measured by electromagnetic induction using an EM38DD. At 116 locations, soil samples were taken according to a clustered sampling design, three times during one winter, and analyzed for the NO₃^––N content in the topsoil (0–60 cm). Management zones were delineated using a fuzzy k-means classification of the interpolated ECa measurements. Two ECa zones were found, reflecting mainly differences in soil texture. Since the mean NO₃^––N content was different for the two ECa zones (24 and 65 kg/ha in November 2002), the residuals were interpolated using stratified simple kriging. This allowed evaluating the NO₃^– dynamics during the winter in both zones; one ECa zone showed a higher risk for NO₃^– losses than the other calling for a site-specific N management. As a validation, NO₃^––N was interpolated using ordinary kriging without stratification. This resulted in similar zones confirming the usefulness of the ECa measurements to assess N-specific management zones, even within small fields.     

积分方法用于校定逆转型土壤盐渍剖面的磁感式电导

Various calibration methods have been propounded to determine profiles of apparent bulk soil electrical conductivity （ECa） and soil electrical conductivity of a saturated soil paste extract （ECe） or a 1：5 soil water extract （EC1：5） using an electromagnetic induction instrument （EM38）. The modeled coefficients, one of the successful and classical methods hitherto, were chosen to calibrate the EM38 measurements of the inverted salinity profiles of characteristic coastal saline soils at selected sites of Xincao Farm, Jiangsu Province, China. However, this method required three parameters for each depth layer. An integration approach, based on an exponential decay profile model, was proposed and the model was fitted to all the calibration sites. The obtained model can then be used to predict EC1：5 at a certain depth from electromagnetic measurements made using the EM38 device positioned in horizontal and vertical positions at the soil surface. This exponential decay model predicted the EC1：5 well according to the results of a one-way analysis of variance, and the further comparison indicated that the modeled coefficients appeared to be slightly superior to, but not statistically different from, this exponential decay model. Nevertheless, this exponential decay model was more significant and practical because it depended on less empirical parameters and could be used to perform point predictions of EC1：5 continuously with depth.     

基于多源数据的中原黄泛区土壤盐分空间变异分析

为研究中原黄泛区土壤盐分空间变异,以河南省封丘县为研究区,综合考虑引起土壤盐渍化的土壤盐分、地形、地下水位及矿化度、植被情况及其他影响因素,基于遥感影像和磁感式探测获得的土壤表观电导率等多源数据建立了区域土壤盐分综合评估模型,并对研究区分层土壤盐分空间变异进行评估。结果表明:对于0~60 cm土层利用多源数据进行模型构建中土壤表观电导率与光谱指数占主要比例,模型对于各层土壤盐分的评价精度0~60 cm土层优于≥60~120 cm土层。土壤盐分含量随着深度的增加而增大,变异系数在0.22~0.28之间,属中等变异强度。土壤盐分主要集中分布在研究区北部与东南部,尤其是东南角黄河沿线区域,且随着土壤剖面显示出从表现到深层逐渐增加的趋势。利用多源数据建立的分层土壤盐分综合评估模型对于区域土壤盐分解析具有较高精度。该研究为中原黄泛区土壤盐化消减与土壤质量提升提供了可靠新方法。     

Mapping soil salinity in 3‐dimensions using an EM38 and EM4Soil inversion modelling at the reconnaissance scale in central Morocco

Large areas of Morocco require irrigation and although good quality water is available in dams, farmers augment river water with poorer quality ground water, resulting in salt build‐up without a sufficient leaching fraction. Implementation of management plans requires baseline reconnaissance maps of salinity. We developed a method to map the distribution of salinity profiles by establishing a linear regression (LR) between calculated true electrical conductivity (σ, mS/m) and electrical conductivity of the saturated soil‐paste extract (ECe, dS/m). Estimates of σ were obtained by inverting the apparent electrical conductivity (ECa, mS/m) collected from a 500‐m grid survey using an EM38. Spherical variograms were developed to interpolate ECa data onto a 100 m grid using residual maximum likelihood. Inversion was carried out on kriged ECa data using a quasi‐3d model (EM4Soil software), selecting the cumulative function (CF) forward modelling and S2 inversion algorithm with a damping factor of 3.0. Using a ‘leave‐one‐out cross‐validation' (LOOCV), of one in 12 of the calibration sites, the use of the q‐3d model yielded a high accuracy (RMSE = 0.42 dS/m), small bias (ME = ?0.02 dS/m) and Lin's concordance (0.91). Slightly worse results were obtained using individual LR established at each depth increment overall (i.e. RMSE = 0.45 dS/m; ME = 0.00 dS/m; Lin's = 0.89) with the raw EM38 ECa. Inversion required a single LR (ECe = 0.679 + 0.041 × σ), enabling efficiencies in estimating ECe at any depth across the irrigation district. Final maps of ECe, along with information on water used for irrigation (ECw) and the characterization of properties of the two main soil types, enabled better understanding of causes of secondary soil salinity. The approach can be applied to problematic saline areas with saline water tables.     

Reconstructing the paleotopography beneath the loess cover with the aid of an electromagnetic induction sensor

During the last glacial period (Weichselian), wind-blown loess was deposited over the undulating landscape of central Belgium, which had been formed in surfacing Tertiary marine sediments. Since valleys were filled up with a thicker loess layer than hill tops, the present topography is much smoother. This smoothing was enhanced by subsequent erosion processes. Reconstructing the paleolandscape at a detailed scale is almost impossible by conventional procedures based on soil augerings. Therefore, the use of the electromagnetic induction sensor, EM38DD, was evaluated as an alternative for mapping the depth to the Tertiary clay substrate. On our 2.7 ha study site, located in the loess belt of central Belgium, a strong non-linear relationship (R² = 0.86) was found between the apparent electrical conductivity (ECa), measured by the vertical dipole orientation of the EM38DD and the depth to a Tertiary clay substrate. These predictions were validated by independent observations of the depth to the Tertiary clay and a correlation coefficient of 0.83, with an average error of 0.22 m, was found. So, our dense ECa measurements (2 by 2 m resolution) allowed us to build a three-dimensionall surface of the depth to the Tertiary substrate, reconstructing the paleotopography beneath the loess cover. This paleotopography revealed distinct erosion patterns on the surface of the Tertiary clay. The continuity of these was confirmed by an analysis of surface flow patterns conducted on the reconstructed paleotopography. The non-invasive, time- and cost-effective electromagnetic induction sensor was found to offer new perspectives to reconstruct and analyse in detail the Quaternary paleotopography beneath the loess cover.     

基于EM38和WorldView-2影像的土壤盐渍化建模研究

在干旱半干旱地区,土壤盐渍化是常见的土地退化问题之一。本研究选取于田县克里雅河上游边缘典型盐渍化区域作为研究靶区,通过EM38大地电导率仪实测土壤表观电导率,提取不同系数下的土壤调节植被指数(SAVI),分析了SAVI指数与土壤电导率间的相关性,并利用同时期WorldView-2影像的敏感波段建立了基于高分辨率影像数据的土壤盐渍化偏最小二乘回归(PLSR)模型并进行了精度验证。结果表明:①从遥感影像提取SAVI指数时,在系数(L)调节范围内选取固定系数值,系数值(间隔为0.1)从0.1变化到1.0的过程中,相应提取的SAVI指数与土壤电导率的相关性明显提升,相关性系数(r)从0.30提高到0.50,并通过显著性检验(P0.01)。②选取的SAVI1.0、B6、B7、B8四种变量中,以SAVI1.0+B6+B8为变量组合所建立的PLSR模型为最优,该模型较其他变量组合建模的决定系数(R2p)提高了0.11,因此,在研究区该模型具有更好的预测能力,模型精度为RMSEC=0.77dS/m、RC2=0.68、RMSEP=0.79 dS/m、RP2=0.66、RPD=2.2。