城市区域土壤铅含量空间变异的多尺度研究进展

我国城市土壤仍存在Pb的严重富集,准确地评价土壤Pb污染水平和范围是进行科学的土壤Pb污染风险评估和管理的基础.城市土壤Pb含量的空间变异性强且结构复杂,现有的大多数研究在单一空间尺度上开展,不足以全面揭示空间结构特征,不利于促进更加科学的风险评估和管理.因此,探寻一种能够全面揭示城市土壤Pb含量的空间结构信息的方法尤为重要.为了实现这一目的,本文首先分析了造成城市土壤Pb含量高空间变异性的主要因素:污染源的多样性、污染过程的层次性,以及城市景观的异质性.在此基础上归纳出城市土壤Pb含量的空间变异特征——由3个空间层次嵌套而成的等级结构.在此概念性的空间结构之上提出一个基于地统计学理论、以线性混合效应模型为核心的方法框架,可以将城市土壤Pb含量的空间结构划分为3个层次:全局趋势、具有空间自相关的随机变异以及异常高值点.最后,提出完善城市土壤Pb含量空间变异多尺度研究的重点是:探讨更加高效的空间抽样策略;确定特征尺度.     

Assessing the risk of soil contamination in the Swiss Jura using indicator geostatistics

The probability that the concentrations of toxic substances in soil or other medium exceed tolerablemaxima at any unsampled place can be estimated by indicator geostatistics. The method is developed and used to estimate and map the risk of contamination by cadmium, copper and lead in the topsoil of a 14.5 km 2 region in the Swiss Jura. It combines both direct measurements of metal concentrations and thecalibration of a geological map, and it shows that the risk of toxicity is least on Argovian rocks. Two approaches are proposed to divide a region into safe' and 'hazardous' zones on the basis of probability maps. The first declares as contaminated all places where the risk of contamination exceeds a given threshold. The second approach first evaluates the financial costs that might result from a wrongdeclaration, after which the site is allocated to a class so as to minimize that cost. The risk of exposure for humans and animals is generally greater for contaminated agricultural land than for forest soil, and so land use is taken into account in both procedures.     

典型矿业城市农田土壤重金属含量的空间结构特征——以辽宁省阜新市为例

运用地统计学方法对阜新市矿业密集区周围农田土壤重金属含量的空间结构特征进行了定量描述,并探讨了研究区域内重金属空间结构的主要影响因素.结果表明:研究区域农田土壤中As、Cd、Cu、Ni、Pb、Zn等6种重金属元素的实验变异函数理论模型拟合效果较好,决定系数均达到0.01显著性水平;各重金属变程较大,除As以外均出现明显的漂移;变异函数的块金效应明显,空间相关性属中等,显示小尺度上受人为干扰的影响较大;除Ni的空间结构表现为各向同性以外,其余5种重金属均表现出明显的方向性特点;除土壤母质因素外,研究区域内以矿业和城市活动为主的人为干扰是影响农田重金属空间结构的重要原因.     

基于多环境介质氮素和同位素的滦平盆地地下水硝酸盐来源示踪

选择密云水库上游承德市滦平盆地为研究区,通过不同土地利用类型地下水"三氮"含量、土壤全氮含量和包气带可溶硝态氮含量,结合水体硝酸盐氮氧双同位素、硫酸盐硫氧双同位素多种环境同位素特征和地下水放射性碳同位素测年示踪硝酸盐来源.结果表明,滦平盆地水体氮形态以硝态氮为主,地下水NO₃^-质量浓度与居民用地、旱地土地利用类型显著相关,硝酸盐污染主要集中于居民建设用地和农用地区域浅层地下水中.13.79%地下水样品NO₃^-质量浓度超过国标（GB/T 14848-2017）地下水硝酸盐限值Ⅲ类标准,超标范围为1.04~3.86倍;37.93%地下水样品NO₃^-质量浓度超WHO饮用水硝酸盐浓度限值,超标范围为1.08~6.83倍.地下水NO₃^-质量浓度、土壤全氮和浅层土壤可溶硝态氮空间变异受结构性因素和人为因素共同作用影响.地下水硝酸盐来源主要为家畜粪尿和生活污水混合污染,其次为化学肥料淋滤;盆地山前地下水径流区包气带-地下水氮循环主导过程为硝化作用.以盆地系统作为独立单元研究水环境硝酸盐污染来源和归趋规律,对流域整体地下水污染防治和修复具有重要意义.     

Remote sensing: Using the spatial domain

Objects in the terrestrial environment interact differentially with electromagnetic radiation according to their essential physical, chemical and biological properties. This differential interaction is manifest as variability in scattered radiation according to wavelength, location, time, geometries of illumination and observation and polarization. If the population of scattered radiation could be measured, then estimation of these essential properties would be straightforward. The only problem would be linking such estimates to environmental variables of interest. This review paper is divided into three parts. Part 1 is an overview of the attempts that have been made to sample the five domains of scattered radiation (spectral, spatial, temporal, geometrical, polarization) and then to use the results of this sampling to estimate environmental variables of interest. Part one highlights three issues: first, that relationships between remotely sensed data and environmental variables of interest are indirect; second, our ability to estimate these environmental variables is dependent upon our ability to capture a sound representation of variability in scattered radiation and third, a considerable portion of the useful information in remotely sensed images resides in the spatial domain (within the relations between the pixels in the image). This final point is developed in Part 2 that explores ways in which the spatial domain is utilized to describe spatial variation in remotely sensed and ground data; to design optimum sampling schemes for image data and ground data and to increase the accuracy with which remotely sensed data can be used to estimate both discontinuous and continuous variables. Part 3 outlines two specific uses of information in the spatial domain; first, to select an optimum spatial resolution and second, to inform an image classification.     

GIS‐Based Spatial Precipitation Estimation: A Comparison of Geostatistical Approaches1

Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km², which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models.     

基于地统计学和GIS的土壤和蔬菜重金属的环境质量评价

以浙江省上虞市东关镇为例,利用地统计学与GIS技术相结合的方法揭示了该地区土壤与蔬菜重金属含量的空间分布特征,并评价其重金属的环境质量状况,在参照评价标准的基础上,绘制了土壤与蔬菜重金属的空间分布图,并对其成因进行了探讨.结果表明:东关镇大部分田块存在着重金属分布不均的情况;Cu、Zn的含量偏低,Pb、Cd含量偏高;全镇土壤和蔬菜重金属含量的空间变异很大,土壤重金属的全量与有效态含量之间存在显著的正相关,空间分布存在一定相似形,与蔬菜的空间分布则存在很大的区别,蔬菜重金属含量与土壤重金属的含量有一定的相关性,基本都未达到显著水平;小青菜中Zn和Cu的含量未超标,Pb、Cd则超标.     

CO-KRIGING TO INCORPORATE SCREENING DATA: HUDSON RIVER SEDIMENT PCBs1

ABSTRACT: Kriging methods of geostatistical analysis provide valuable techniques for analysis of sediment contamination problems, including interpolation of concentration maps from point data and estimation of global mean concentrations. Sample collection efforts frequently include preliminary screening data of considerably more extensive coverage than the laboratory analyses on which estimation is usually based. How should these be incorporated in kriging? Screening and laboratory analysis constitute two separate estimates of the same spatial field but of very different characteristics. A modified version of co-kriging is developed to include the imprecise screening information in the analysis of contaminant distribution. Use of the method is demonstrated on a data set of sediment PCB samples from the Upper Hudson River, for which preliminary categorical mass spectrometry screening was used to select a smaller set of samples for gas chromatograph analysis. The method is widely applicable to many situations of contaminant and natural resource estimation.     

STATISTICAL AND GEOSTATISTICAL MODELLING OF PRELIMINARILY ADJUSTED DEFOLIATION ON AN EUROPEAN SCALE

Since 1987 tree crown condition is surveyed annually in large parts of Europe mainly in terms of defoliation. The plot-wise means of defoliation from 1994 to 2000 were evaluated by General Linear Models (GLM) in order to describe country-specific levels of defoliation and age-trends. Additional runs with estimates for influences of insects and fungi were performed. The amount of variance of defoliation explained by country, age and its interaction was between 35% and 59% for the main tree species, except for Quercus ilex. Additionally, up to 10% could be explained by the inclusion of estimates for infestations by insects and fungi. Residuals of the GLMs were taken as a measure of forest condition not biased by country or age effects and interpreted as preliminarily adjusted defoliation (PAD). PAD values were analysed using geostatistical methods. The modelled spatial autocorrelations were used for kriging. The resulting maps give an overview on regions with elevated defoliation, which may pinpoint regional causes of defoliation. The elimination of methodologically caused variance is a precondition of any cause–effect oriented analyses. The combination of explorative modelling and geostatistics will promote the choice of further promising predictors.     

Cokriging optimization of monitoring network configuration based on fuzzy and non-fuzzy variogram evaluation

A number of optimization approaches regarding monitoring networkdesign and sampling optimization procedures have been reported inthe literature. Cokriging Estimation Variance (CEV) is a usefuloptimization tool to determine the influence of the spatial configuration of monitoring networks on parameter estimations. Itwas used in order to derive a reduced configuration of a nitrateconcentration monitoring well network. The reliability of the reduced monitoring configuration suffers from the uncertainties caused by the variographer's choices and several inherent assumptions. These uncertainties can be described considering thevariogram parameters as fuzzy numbers and the uncertainties by means of membership functions.Fuzzy and non-fuzzy approaches were used to evaluate differencesamong well network configurations. Both approaches permitted estimates of acceptable levels of information loss for nitrate concentrations in the monitoring network of the aquifer of the Plain of Modena, Northern Italy. The fuzzy approach was found torequire considerably more computational time and numbers of wellsat comparable level of information loss.