Using rank-order geostatistics for spatial interpolation of highly skewed data in a heavy-metal contaminated site

The spatial distribution of a pollutant in contaminated soils is usually highly skewed. As a result, the sample variogram often differs considerably from its regional counterpart and the geostatistical interpolation is hindered. In this study, rank-order geostatistics with standardized rank transformation was used for the spatial interpolation of pollutants with a highly skewed distribution in contaminated soils when commonly used nonlinear methods, such as logarithmic and normal-scored transformations, are not suitable. A real data set of soil Cd concentrations with great variation and high skewness in a contaminated site of Taiwan was used for illustration. The spatial dependence of ranks transformed from Cd concentrations was identified and kriging estimation was readily performed in the standardized-rank space. The estimated standardized rank was back-transformed into the concentration space using the middle point model within a standardized-rank interval of the empirical distribution function (EDF). The spatial distribution of Cd concentrations was then obtained. The probability of Cd concentration being higher than a given cutoff value also can be estimated by using the estimated distribution of standardized ranks. The contour maps of Cd concentrations and the probabilities of Cd concentrations being higher than the cutoff value can be simultaneously used for delineation of hazardous areas of contaminated soils.     

Mapping the probability of exceeding critical thresholds for cadmium concentrations in soils in The Netherlands

The probability of exceeding critical thresholds of Cd concentrations in the soil was mapped at a national scale. The critical thresholds in soil were based on food quality criteria for Cd in crops or in organs of cattle (Bos taurus), and were calculated by inverting a regression model for the Cd concentration in the crop, with the Cd concentration in soil, soil organic matter (SOM) content, clay content, and pH as predictors. The probability of exceeding the critical threshold for Cd in soil per node of a 500- x 500-m grid was approximated by Monte Carlo simulation, using the estimated cumulative distribution functions (cdf) of SOM, clay, pH, and Cd as input. The cdfs were estimated by simple indicator kriging with local prior means. For SOM, clay, and pH, detailed maps of soil type and land use were used to define subregions with assumed constant local means of the indicators (a priori distributions). The cdfs were sampled by Latin hypercube sampling. We accounted for correlation between the actual and critical Cd concentrations in soil by drawing Cd values from cdfs conditional on SOM and clay. The estimated probability for grassland is negligible, even in areas with high Cd concentrations in soil, and for maize (Zea mays L.) land the probability is almost everywhere smaller than 5%. For arable soils, however, these probabilities commonly are larger than 5% when sugar beet (Beta vulgaris L.) or wheat (Triticum aestivum L.) is taken as a reference crop, and locally exceed 50%.     

Simplified method for detecting tritium contamination in plants and soil

Cost-effective methods are needed to identify the presence and distribution of tritium near radioactive waste disposal and other contaminated sites. The objectives of this study were to (i) develop a simplified sample preparation method for determining tritium contamination in plants and (ii) determine if plant data could be used as an indicator of soil contamination. The method entailed collection and solar distillation of plant water from foliage, followed by filtration and adsorption of scintillation-interfering constituents on a graphite-based solid phase extraction (SPE) column. The method was evaluated using samples of creosote bush [Larrea tridentata (Sessé & Moc. ex DC.) Coville], an evergreen shrub, near a radioactive disposal area in the Mojave Desert. Laboratory tests showed that a 2-g SPE column was necessary and sufficient for accurate determination of known tritium concentrations in plant water. Comparisons of tritium concentrations in plant water determined with the solar distillation-SPE method and the standard (and more laborious) toluene-extraction method showed no significant difference between methods. Tritium concentrations in plant water and in water vapor of root-zone soil also showed no significant difference between methods. Thus, the solar distillation-SPE method provides a simple and cost-effective way to identify plant and soil contamination. The method is of sufficient accuracy to facilitate collection of plume-scale data and optimize placement of more sophisticated (and costly) monitoring equipment at contaminated sites. Although work to date has focused on one desert plant, the approach may be transferable to other species and environments after site-specific experiments.     

Uncertainty Assessment for Management of Soil Contaminants with Sparse Data

In order for soil resources to be sustainably managed, it is necessary to have reliable, valid data on the spatial distribution of their environmental impact. However, in practice, one often has to cope with spatial interpolation achieved from few data that show a skewed distribution and uncertain information about soil contamination. We present a case study with 76 soil samples taken from a site of 15 square km in order to assess the usability of information gleaned from sparse data. The soil was contaminated with cadmium predominantly as a result of airborne emissions from a metal smelter. The spatial interpolation applies lognormal anisotropic kriging and conditional simulation for log-transformed data. The uncertainty of cadmium concentration acquired through data sampling, sample preparation, analytical measurement, and interpolation is factor 2 within 68.3 % confidence. Uncertainty predominantly results from the spatial interpolation necessitated by low sampling density and spatial heterogeneity. The interpolation data are shown in maps presenting likelihoods of exceeding threshold values as a result of a lognormal probability distribution. Although the results are not deterministic, this procedure yields a quantified and transparent estimation of the contamination, which can be used to delineate areas for soil improvement, remediation, or restricted area use, based on the decision-makers probability safety requirement.     

Escherichia coli load reduction from runoff by vegetative filter strips: a laboratory-scale study

Vegetative filter strips (VFS) are commonly used best management practices for removing contaminants from runoff. Additional research is warranted to determine their efficiency and the most appropriate metrics for predicting fecal bacteria reductions. The objective of this research was to determine VFS effectiveness in removing from runoff relative to inflow rate, infiltration capacity, and flow concentration. This research also investigated the presence of in runoff from clean water runon after diluted manure runon events. A laboratory-scale VFS soil box (200 cm long, 100 cm wide, 7.5% slope) was packed with a sandy loam soil. Ten constant-flow VFS experiments were conducted with and without vegetation (8-10 cm ryegrass [ L.]) at low (20-40 cm s), medium (40-60 cm s), and high (85-120 cm s) flow rates and for a full (100 cm) or concentrated (40 cm) VFS flow width to simulate a channelizing flow condition. Two runon events were investigated for each experimental condition: (i) diluted liquid swine manure runon and (ii) clean water runon 48 h afterward. was used as an indicator of fecal contamination and was quantified by the most probable number (MPN) technique. No concentration reductions were observed based on peak outflow concentrations, and only small concentration reductions were observed based on outflow event mean concentrations. The mass reductions ranged from 22 to 71% and were strongly correlated to infiltration or runoff reduction ( = 0.88), which was dependent on the degree of flow concentration. Little to no effect of sedimentation on transport was observed, hypothesized to be due to minimum attachment to sediment particles because the bacteria originated from manure sources. Therefore, the design of VFS for bacteria removal should be based on the infiltration capacity in the VFS and should prevent concentrated flow, which limits total infiltration. The event mean concentrations in clean water runon experiments were between 10 and 100 MPN per 100 mL; therefore, under these conditions, VFS served as a source of residual from previous runon events.     

Locating Escherichia coli contamination in a rural South Carolina watershed

One of the problems associated with the use of ambient water quality standards in surface water regulation is the difficulty of identifying and regulating nonpoint source pollution, making such standards unenforceable, especially at the local level. We used the Escherichia coli indicator to locate the most contaminated reaches in rural South Carolina's Bush River watershed (297 km(2), 186 stream-km). We divided the watershed into 20 smaller reaches and sampled each reach multiple times, but restricted each sampling round to one day. We located four low order creek reaches, representing just nine stream-km, where we observed geometric mean E. coli densities of over 1250 E. coli/100 mL; in each case, the source of the contamination (riparian grazing of cattle) was easily identifiable. On the Bush River itself, we observed a step change in one reach where geometric means increased from 106 E. coli/100 mL to 565 E. coli/100 mL over the reach's 10 km length. In this case, the sources of contamination were not as obvious as in the lower order streams; in this case, more advanced Microbial Source Tracking techniques will be required to identify the sources. Nevertheless, this sampling protocol helped locate polluted reaches and provided decision-makers with reasonable justifications for concrete action in deciding where (or where not) to install conservation practices and where more sophisticated (and expensive) MST techniques were warranted.     

Spatial variability of soil phosphorus in relation to the topographic index and critical source areas: sampling for assessing risk to water quality

A measure of soil P status in agricultural soils is generally required for assisting with prediction of potential P loss from agricultural catchments and assessing risk for water quality. The objectives of this paper are twofold: (i) investigating the soil P status, distribution, and variability, both spatially and with soil depth, of two different first-order catchments; and (ii) determining variation in soil P concentration in relation to catchment topography (quantified as the "topographic index") and critical source areas (CSAs). The soil P measurements showed large spatial variability, not only between fields and land uses, but also within individual fields and in part was thought to be strongly influenced by areas where cattle tended to congregate and areas where manure was most commonly spread. Topographic index alone was not related to the distribution of soil P, and does not seem to provide an adequate indicator for CSAs in the study catchments. However, CSAs may be used in conjunction with soil P data for help in determining a more "effective" catchment soil P status. The difficulties in defining CSAs a priori, particularly for modeling and prediction purposes, however, suggest that other more "integrated" measures of catchment soil P status, such as baseflow P concentrations or streambed sediment P concentrations, might be more useful. Since observed soil P distribution is variable and is also difficult to relate to nationally available soil P data, any assessment of soil P status for determining risk of P loss is uncertain and problematic, given other catchment physicochemical characteristics and the sampling strategy employed.     

THREE‐DIMENSIONAL KRIGING ANALYSIS OF SEDIMENT MERCURY DISTRIBUTION: A CASE STUDY1

ABSTRACT: This study presents an application of a three‐dimensional kriging technique to estimate spatial distribution of total mercury (Hg) in the Cedar‐Ortega Rivers watershed located in the lower St. Johns River basin, Florida. The kriging procedures, including preliminary data analysis, structural data analysis and the log kriging estimation, are presented. Results show watershed wide Hg contamination of river sediment to a depth of 1.0 m. A three‐dimensional plot of Hg against the Florida Sediment Assessment Guidelines (i.e., the probable effect level or PEL) demonstrates that the Cedar River is more contaminated with Hg than the rest of the watershed. The maximum sediment depth with Hg concentrations above PEL value (0.696 mg/kg) is 1.5 m. Hg concentrations at or above this level could pose a significant hazard to aquatic organisms. Analysis of the spatial distribution of Hg in the watershed finds multiple input sources. This study suggests that there is a need to identify the major sources of Hg in the watershed, and to determine the pathways that allow Hg to enter the river.     

土壤综合治理技术─—空气抽取法和堆肥法结合使用治理土壤污染

文中介绍了国外用土壤空气抽取法和堆肥法清除土壤中有机溶剂、芳香烃类和石油污染物的技术及其应用。这两种方法单独使用均可成功地治理有害废弃物。实践证明，将这两种技术串联使用可更有效地处理土壤中污染物及加速生物降解过程。根据现场特点，利用多种治理技术综合治理土壤污染物是治理污染物的发展方向。     

土壤综合治理技术─—空气抽取法和堆肥法结合使用治理土壤污染

文中介绍了国外用土壤空气抽取法和堆肥法清除土壤中有机溶剂、芳香烃类和石油污染物的技术及其应用。这两种方法单独使用均可成功地治理有害废弃物。实践证明，将这两种技术串联使用可更有效地处理土壤中污染物及加速生物降解过程。根据现场特点，利用多种治理技术综合治理土壤污染物是治理污染物的发展方向。     

Zonal management of arsenic contaminated ground water in Northwestern Bangladesh

This paper used ordinary kriging to spatially map arsenic contamination in shallow aquifers of Northwestern Bangladesh (total area  35,000 km²). The Northwestern region was selected because it represents a relatively safer source of large-scale and affordable water supply for the rest of Bangladesh currently faced with extensive arsenic contamination in drinking water (such as the Southern regions). Hence, the work appropriately explored sustainability issues by building upon a previously published study (Hossain et al., 2007; Water Resources Management, vol. 21: 1245–1261) where a more general nation-wide assessment afforded by kriging was identified. The arsenic database for reference comprised the nation-wide survey (of 3534 drinking wells) completed in 1999 by the British Geological Survey (BGS) in collaboration with the Department of Public Health Engineering (DPHE) of Bangladesh. Randomly sampled networks of zones from this reference database were used to develop an empirical variogram and develop maps of zonal arsenic concentration for the Northwestern region. The remaining non-sampled zones from the reference database were used to assess the accuracy of the kriged maps. Two additional criteria were explored: (1) the ability of geostatistical interpolators such as kriging to extrapolate information on spatial structure of arsenic contamination beyond small-scale exploratory domains; (2) the impact of a priori knowledge of anisotropic variability on the effectiveness of geostatistically based management. On the average, the kriging method was found to have a 90% probability of successful prediction of safe zones according to the WHO safe limit of 10 ppb while for the Bangladesh safe limit of 50 ppb, the safe zone prediction probability was 97%. Compared to the previous study by Hossain et al. (2007) over the rest of the contaminated country side, the probability of successful detection of safe zones in the Northwest is observed to be about 25% higher. An a priori knowledge of anisotropy was found to have inconclusive impact on the effectiveness of kriging. It was, however, hypothesized that a preferential sampling strategy that honored anisotropy could be necessary to reach a more definitive conclusion in regards to this issue.     

Mapping residual pyrite after a mine spill using non co-located spatiotemporal observations

Monitoring of soil chemical properties for pollution assessment generally requires destructive soil sampling and results in spatiotemporal datasets where data from different sampling dates are non co-located. The objective of this study was to assess the spatial distribution of residual pyrite sludge at a reclaimed site, using temporally non co-located data on pH; soil oxidizable fraction (SOF); and EDTA-extractable Fe, Zn, and Cu from six different sampling dates over a period of 2 yr. During this period spatially averaged pH and Zn concentrations ranged, respectively, from 4.4 to 6.6 and from 60 to 140 mg kg(-1), with minimum pH values of below 2.7. The data were merged into a single dataset for each chemical property after applying a normal score (ns) transform. Normal score pH was significantly negatively correlated with the ns metal concentrations. A principal component analysis (PCA) showed that normal score pH, Zn, and Fe were associated with the residual contamination, while ns Cu, SOF, and elevation were related with historic contamination. The spatial dependence between the properties was found to be scale-dependent. The best ns estimates were produced by ordinary kriging with an anisotopic variogram model, for the properties related with Principal Component (PC) I, while those associated with PC II were best estimated using simple kriging with varying local means. A classified ns pH map showed that 33% of the study area reached at least once values of below 4 during the 2-yr period. This part of the area should be excluded to ensure successful revegetation.     

Small-scale spatial variability of atrazine and dinoseb adsorption parameters in an alluvial soil

Soil sorption processes largely control the environmental fate of herbicides. Therefore, accuracy of sorption parameters is crucial for accurate prediction of herbicide mobility in agricultural soils. A combined experimental and statistical study was performed to investigate the small-scale spatial variability of sorption parameters for atrazine and dinoseb in soils and to establish the number of samples needed to provide a value of the distribution coefficient (K(d)) next to the mean, with a given precision. The study explored sorption properties of the two herbicides in subsurface samples collected from four pits distributed along a transect of an alluvial soil; two to four samples were taken at about 30 cm apart at each sampling location. When considering all the data, the distribution coefficients were found to be normally and log-normally distributed for atrazine and dinoseb, respectively; the CVs were relatively high (close to 50% for dinoseb and 40% for atrazine). When analyzed horizon by horizon, the data revealed distribution coefficients normally distributed for both herbicides, whatever the soil layer, with lower CVs. The K(d) values were shown to vary considerably between samples collected at very short distance (a few centimeters), suggesting that taking a single soil sample to determine sorption properties through batch experiments can lead to highly unrepresentative results and to poor sorption/mobility predictions.     

钝化剂对土壤重金属污染修复研究进展

总结了常见的钝化剂包括石灰性物质、炭材料、粘土矿物、含磷材料、有机肥和农业废弃物等对土壤重金属污染修复的原理、技术和方法。介绍了钝化剂对土壤重金属修复的效果和注意事项,并对钝化剂进行土壤重金属污染修复的前景和目前存在的问题进行了展望。     

Soil Phosphorus Concentrations in Dane County,Wisconsin, USA: An Evaluation of the Urban–Rural Gradient Paradigm

Understanding the magnitude and location of soil phosphorus (P) accumulation in watersheds is a critical step toward managing runoff of this pollutant to aquatic ecosystems. Here, I examine the usefulness of urban–rural gradients, an emerging experimental design in urban ecology, for predicting extractable soil P concentrations across a rapidly urbanizing agricultural watershed in southern Wisconsin. I compare several measures of an urban–rural gradient to predictors of soil P such as soil type, slope, topography, land use, land cover, and fertilizer and manure use. Most of the factors that were expected to drive differences in soil P concentrations were found to be poor predictors of Bray-1 (extractable) soil P, which ranged from 4 to 660 ppm; while there were several significant relationships, most explained only a small proportion of the variation. A multiple linear regression model captured approximately 37% of the variation in the data using the urban–rural gradient, topography, land use, land cover, manure use, and soil type as predictors. There was a significant relationship between Bray-1 P concentration and each of the urban–rural gradients, but these relationships explained only between 2.6% and 3.3% of the variation in P concentrations. Extractable P concentration in soils, unlike some other ecosystem properties, is not well predicted by urban–rural gradients.     

我国土壤污染防治立法探究

随着土壤污染防治专门立法的启动,我国土壤污染防治的相关制度也将逐步建立,这对于指导土壤污染防治的实践工作具有重要意义。然而在立法过程中各方争议较大且亟待解决的几个关键问题有必要深入探究,主要涉及立法模式的选择、土壤环境管理模式的选择、污染土壤修复目标的确定及特殊污染土壤责任主体的认定。通过探析各争议问题对立法的核心价值及其背景和实质,并基于国情和我国土壤污染的现状,得出结论即应坚持防治并重,建立综合性土壤立法。采取风险管控的方式进行土壤管理。对受污染土壤的修复目标应结合未来土地用途具体分析。特殊历史遗留污染土壤责任主体的认定,则要坚持污染者负担为基本原则,其他相关原则为补充。     

Use of ecosystem information to improve soil organic carbon mapping of a Mediterranean island

Detailed maps of soil C are needed to guide sustainable soil uses and management decisions. The quality of soil C maps of Italian Mediterranean areas may be improved and the sampling density reduced using secondary data related to the nature of the ecosystem. The current study was conducted to determine: (i) the improvements obtainable in mapping soil C over a Mediterranean island by using ecosystem features and (ii) the effect of different sampling densities on the map accuracy. This work relied on field sampling (n=164) of soil properties measured over the island of Pianosa (Central Italy). Statistical analysis assessing the relationship between soil properties and ecosystem features revealed that the conceptual model of ecosystems defined on the basis of environmental features such as vegetation cover, land use, and soil type was mainly related to the variation of soil organic carbon (OC) content and to the type of Mediterranean environment. The distribution of ecosystems was used to improve the accuracy of soil OC maps obtainable by a simple interpolation approach (ordinary kriging). Substantial improvement was obtained by: (i) stratification into ecosystem types and (ii) applying locally calibrated regressions to satellite imagery that introduced both inter-ecosystem and intra-ecosystem information linked to vegetation features. This study showed that interpolation methods using information on ecosystem distribution can produce accurate maps of soil OC in Mediterranean environments, mostly because of the linkage between soil OC and vegetation types, which are spatially fragmented and heterogeneous.     

Optimal spatial resolution for collection of ground data and multi-sensor image mapping of a soil erosion cover factor

Military training activities disturb ground and vegetation cover of landscapes and increases potential soil erosion. To monitor the dynamics of soil erosion, there is an important need for an optimal sampling design in which determining the optimal spatial resolutions in terms of size of sample plots used for the collection of ground data and the size of pixels for mapping. Given a sample size, an optimal spatial resolution should be cost-efficient in both sampling costs and map accuracy. This study presents a spatial variability-based method for that purpose and compared it with the traditional methods in a study area in which a soil erosion cover factor was sampled and mapped with multiple plot sizes and multi-sensor images. The results showed that the optimal spatial resolutions obtained using the spatial variability-based method were 12 and 20m for years 1999 and 2000, respectively, and were consistent with those using the traditional methods. Moreover, the most appropriate spatial resolutions using the high-resolution images were also consistent with those using ground sample data, which provides a potential to use the high-resolution images instead of ground data to determine the optimal spatial resolutions before sampling. The most appropriate spatial resolutions above were then verified in terms of cost-efficiency which was defined as the product of sampling cost and map error using ordinary kriging without images and sequential Gaussian co-simulation with images to generate maps.     

MAPPING REGIONAL PRECIPITATION INTENSITY DURATION FREQUENCY ESTIMATES1

ABSTRACT: For regional precipitation frequency analyses, methods are needed to spatially interpolate or smooth point intensity duration frequency (IDF) estimates at gage sites for the purposes of visualization and estimation at ungaged sites. In this study to update IDF estimates for Michigan, the assumption is made that for practical purposes, the entire state may be treated as a homogeneous region in which annual maximum precipitation is identically distributed at each site apart from a site‐specific scaling factor, commonly known as the index flood. Several interpolation and smoothing techniques are evaluated for IDF estimation at ungaged sites, including trend surface analysis, thin plate splines, inverse distance weighting, and several kriging algorithms. Ordinary block kriging is recommended as a practical and objective method for smoothing the variability in the index flood values and developing isopluvial maps.     

Site-specific phosphorus application based on the kriging fertilizer-phosphorus availability index of soils

Site-specific phosphorus management is done to optimize crop production and minimize P loss from soils. The spatial variability of the available P prior to fertilizer application and the P-fixation tendency of soil both need to be taken into account for variable-rate P application. The objectives of this research were to document the spatial variability of the fertilizer-P availability index, which shows the P-fixation tendency, and to develop a strategy that takes the spatial distribution of this index into account for site-specific phosphorus application. In this study, the spatial patterns of the fertilizer-P availability index were characterized by using geostatistics. The ordinary kriging was used for spatial interpolation of the fertilizer-P availability index. Because the fertilizer-P availability index of soil is related to oxalate-extractable Fe and Al and because measuring oxalate-extractable Fe and Al is much easier than directly determining the fertilizer-P availability index, the spatial distribution of the fertilizer-P availability index can be obtained using the oxalate-extractable Fe and Al data. The spatial distribution of Olsen-extractable P, which was used to measure the available-P status prior to fertilizer-P application, was also estimated by using ordinary kriging. The required fertilizer-P amounts were then determined using the kriging estimates of the fertilizer-P availability index and Olsen-extractable P. A fertilizer-P recommendation map for the 430-ha study site in Changhua county, Taiwan was generated by using this approach for illustration. The proposed method for generating fertilizer-P recommendation maps can be used for variable-rate application to maintain an adequate P status for crop production and to potentially reduce the P loss from soils.