Quantitative mapping of soil types based on regression kriging of taxonomic distances with landform and land cover attributes

Nowadays, French soil scientists tend to gather new and existing soil data into a common database. The use of this database potentially allows for resolving environmental issues, largely through soil mapping. The purpose of this study is to present a methodology for mapping soil types illustrated by typical observations in the soil database, in this case from the La Rochelle area on the French Mid-Atlantic Coast. The main hypothesis underlying the method is that soil types result from environmental factors such as landform, parent material, and land cover. The method can be divided into four stages. The first step is to construct a local soil type classification from the database by a two-stage continuous classification procedure. The result of this procedure is that at each observation point, the soil is described by a vector of taxonomic distances to each of k centroidal soil types. In the example given, k=18. The second step involves fitting soil–environment equations, one for each centroidal soil type, by regressing taxonomic distances on layers of multivariate environmental data observed on a fine 20-m grid, by multiple linear regression. In this case, the layers are terrain attributes derived from a digital elevation model and land cover attributes derived from three bands of a SPOT image. The third step is to predict k maps or raster GIS layers representing taxonomic distances to soil types on the 20-m grid, using the soil–environment equations and the kriging of the residuals from the regressions. This results in many potential maps: a summary map depicting the nearest centroidal soil type (the soil type for which the taxonomic distance is least) at each location is possibly the most useful, and another one representing the minimum taxonomic distance which, if considered too large, might suggest locations for further field survey to refine the soil types. A map of standard errors of the kriged taxonomic distance residuals to the nearest centroidal soil type can be made to indicate spatial uncertainty. Continuous fuzzy membership maps can also be constructed from the distances. The fourth step involves validation with an independent soil data set allowing discovery of the nature of the actual prediction errors. Thirty-eight percent of sites in a validation sample of 1234 sites was unequivocally validated, 23% was equivocally validated, and the remainder was predicted wrongly by the method.     

Distribution of Cd in the vicinity of a metal smelter: Interpolation of soil Cd concentrations with regard to regulative limits

The German soil protection regulation (BBodSchV) requires the investigation and evaluation of sites with known, or suspected contamination. The purpose of this study is the application of geostatistical methods to locate hazardous zones within such a site and to estimate the amount and uncertainty of the contaminant load in these zones. The study site is an area around a metal smelter in the city of Nordenham, Germany, where among other heavy metals, Cd was released to the environment by dust emissions for many decades. In an earlier study soil cores were taken in the area and analyzed for Cd using various extraction methods. After translation of data to results corresponding to a single extraction method using linear regression analysis, Cd concentrations were mapped by ordinary and lognormal kriging. Crossvalidation showed that both methods perform similarly. However, neither ordinary nor lognormal kriging were able to account for the uncertainty of the kriged estimates. We repeated ordinary kriging with a relative variogram having a unit sill. The estimated relative kriging variance was scaled locally. This method considerably improved the estimation of uncertainty. Subsequently, we estimated Cd contents for the land use dependent size of support as specified in the BBodSchV. The kriged Cd estimates as well as their uncertainty were evaluated with regard to limits set by the BBodSchV. Parts of the area which may be declared safe based on merely the kriged estimates, can actually exceed a sanction or test limit by a chance of up to 50 % when uncertainty is also considered. Within the BBodSchV a recommended limit should therefore always be accompanied by a tolerable uncertainty that it may be exceeded on a given support (e.g. 5 %).     

Erfassung der Variabilität von Bodenmerkmalen in einem Blindversuch auf Fahlerde mittels Methoden der räumlichen Statistik

Variability of soil parameters in a uniformity trial on a Luvisol evaluated by means of spatial statistics The relationships between soil parameters and indicators of soil genesis were investigated in a uniformity trial on Luvisol by means of classical and spatial statistics. The following properties were investigated in the topsoil (0–30 cm) and subsoil (31–40 cm): content of total carbon (C_t), content of clay plus fine silt (FAT), concentrations of available potassium (K) and phosphorus (P), and pH values. The depth loamy Bt horizon and microrelief were considered as indicators of soil genesis. Smoothing of the raw data by means of block kriging eliminated the small scale variability of all parameters. In this way, the rank correlation coefficients between soil parameters increased by factor 2 and were to 0.52 for C_t–FAT; 0.69 for C_t–K, and 0.55 for C_t–P in the top soil. The maps for smoothed data allowed a much better visual analysis of spatial distribution of investigated properties compared to the raw data. The significant correlations as well as the similarity of maps and variograms suggested that the spatial variability of FAT, C_t, K, and P in the top soil was determined by the same factors. The depth of the loamy Bt horizon and the relief were the most important factors defining the distribution of the investigated soil parameters. The rank correlation coefficients of the smoothed and detrended relief with the soil parameters amount to –0.63, –0.77, –0.71, and –0.57 for FAT, C_t, K, and P, respectively.     

黄土高原沟壑区土壤养分空间变异及其与地形因子的相关性

【目的】研究黄土高原沟壑区土壤养分空间分布特征及变异规律,分析地形因子对土壤养分空间分布的影响,为土壤养分的有效利用与管理提供理论依据。【方法】运用地统计学和GIS技术相结合的方法,研究地处黄土高原沟壑区的安塞县土壤有机质、碱解氮、有效磷和速效钾的空间变异特征,并利用数字高程模型(DEM)提取坡度、水平曲率、垂直曲率、地形湿度指数和河流动能指数等5个地形因子,分析土壤养分含量与这些地形因子之间的相关性。【结果】(1)土壤有机质、碱解氮、有效磷和速效钾4种土壤养分的变异系数为14.14%～26.84%,块金效应值为16.45%～45.87%。(2)研究区西南部土壤养分含量较高,北部土壤养分含量相对较低。(3)坡度与有机质、碱解氮和有效磷含量呈显著或极显著负相关;水平曲率与有机质和速效钾含量呈显著负相关;地形湿度指数与有机质和速效钾含量呈显著正相关。【结论】安塞县土壤有机质、碱解氮、有效磷和速效钾养分均具有中等变异性,速效钾具有很强的空间相关性;坡度较小、土壤水分较多、水土流失较轻微的地区,土壤养分含量较高;在施肥时,应增大研究区北部氮、磷的施用量。     

Estimation of local probabilities for exceeding threshold values in environmental monitoring

Contour or isopleth maps of regionalized variables are widely used in decision making without regard for the inherent uncertainty of interpolated contours. One concept for addressing the accuracy of contours given the data is the computation of the conditional probability of the value being lower than the contour. Two simple techniques for an approximate computation, indicator kriging and approximation by normal distribution quantiles, are applied to immission data. Since the assumption of a stationary underlying process does not seem justifiable, a moving windows technique is adopted.     

Application of factorial kriging for mapping soil variation at field scale

Use of precision farming technologies requires better understanding of soil variability in physical, hydraulic and chemical properties. Some of that variation is natural, some is the result of the management history of the field. So, to match agricultural inputs and practices to site-specific conditions, the factorial kriging algorithm (FKA) was used to analyze spatial variability in some soil physical, hydraulic and chemical properties (sand and silt concentrations, water contents corresponding to potentials of −10, −50, −100, −200, −1000 and −1500 kPa and organic C concentration), measured at two depths within a single field in north Italy. A linear model of coregionalization, including, (1) a nugget effect; (2) an exponential structure with an effective range of 120 m and (3) an exponential structure with an effective range of 350 m, was fitted to the experimental direct and cross-variograms of the properties of top layer. Cokriged regionalized factors, related to short and long-range variation, were then mapped to characterize soil variation across the field. Short-range soil variation was produced essentially by differences in soil texture, whereas long-range variation in organic carbon concentration resulted in dishomogeneity of soil water retention. Quite probably, the variation in organic carbon concentration was caused by the patchy discharge of liquid manure made on the field. FKA, combining pedological expert knowledge with geostatistical techniques, could be very useful to farmers so that each area within a field is managed appropriately.     

黄河下游冲积平原土壤盐分的时空变异研究——个例研究

Soil salinity and hydrologic datasets were assembled to analyze the spatio-temporal variability of salinization in Fengqiu County, Henan Province, China, in the alluvial plain of the lower reaches of the Yellow River. The saline soil and groundwater depth data of the county in 1981 were obtained to serve as a historical reference. Electrical conductivity (EC) of 293 surface soil samples taken from 2 km × 2 km grids in 2007 and 40 soil profiles acquired in 2008 was analyzed and used for comparative mapping. Ordinary kriging was applied to predict EC at unobserved locations to derive the horizontal and vertical distribution patterns and variation of soil salinity. Groundwater table data from 22 observation wells in 2008 were collected and used as input for regression kriging to predict the maximum groundwater depth of the county in 2008. Changes in the groundwater level of Fengqiu County in 27 years from 1981 to 2008 was calculated. Two quantitative criteria, the mean error or bias (ME) and the mean squared error (MSE), were computed to assess the estimation accuracy of the kriging predictions. The results demonstrated that the soil salinity in the upper soil layers decreased dramatically and the taxonomically defined saline soils were present only in a few micro-landscapes after 27 years. Presently, the soils with relatively elevated salt content were mainly distributed in depressions along the Yellow River bed. The reduction in surface soil salinity corresponded to the locations with deepened maximum groundwater depth. It could be concluded that groundwater table recession allowed water to move deeper into the soil profile, transporting salts with it, and thus played an important role in reducing soil salinity in this region. Accumulation of salts in the soil profiles at various depths below the surface indicated that secondary soil salinization would occur when the groundwater was not controlled at a safe depth.     

伊犁新垦区土壤有机质的克里金插值和条件模拟多尺度分析

克里金插值和条件模拟作为两种常用的空间变异近似和逼近方法,能否真实刻画要素的多尺度结构关系到相应结论的正确性.本文采用尺度方差分析方法,结合经典的半方差函数和Moran's I,以伊犁新垦区土壤有机质为例,对普通克里金插值(OK)和序贯高斯模拟(SGS)的结果进行多尺度分析.结果显示新垦区土壤有机质具有比较强的空间自相关性,10km、35 km和60 km左右为土壤有机质的特征尺度.在小尺度上,SGS对真实的空间数据尺度结构刻画都出现一定的偏差.在大尺度上,两者能够比较真实地反映数据的多尺度结构,可有效刻画35 km和60 km的特征尺度.     

Spatial variability of physico-chemical properties and hydraulic characteristics of a gravelly calcareous soil

Due to the existence of gravelly soils and the lack of sufficient research on such soils, this study was carried out on a gravelly calcareous soil. Selected physico–chemical and hydraulic soil attributes were determined at 69 points on a nested-sampling design. Hydraulic characteristics including unsaturated hydraulic conductivity (K _ψ) and sorptivity coefficient (S) at six applied tensions of 0 to 0.2 m, and sorptive number (α) and macroscopic capillary length (λ) at five applied tensions of 0.03 to 0.2 m were determined using a tension disc infiltrometer. Hydraulic and chemical soil attributes were the highest and the lowest variants, respectively. The maximum and minimum values for the coefficient of variation (CV) in all the measured physico-chemical and hydraulic soil attributes were obtained for α_0.2 and soil pH, respectively. Minimum, maximum, mean and variance values of K _ψ, S and α decreased as applied tension increased. Although the pattern was reversed for λ. The majority of soil attributes showed the spatial structure with dominant spherical and exponential models for physico-chemical and hydraulic attributes, respectively. Range values of semi-variograms were obtained between 4.6 m (for α_0.03) and 211 m (for clay, gravel content and soluble Mg). In general, range values were 99.60, 82.05 and 40.2 m for physical, chemical and hydraulic soil attributes, respectively, indicating that the physical soil attributes influenced neighboring values over greater distances than the other soil attributes. This enables soil scientists to use measured soil physical data over greater distances to estimate attributes in the unsampled locations.     

Determining and mapping some soil physico-chemical properties using geostatistical and GIS techniques in the Naqade region,Iran

The distribution variability of soil electrical conductivity (EC), pH, clay, sand, CaCO₃, organic carbon (OC) and available potassium (K) in the Naqade region was investigated using a geostatistical method and Geographical Information System (GIS) technique. Two hundred and eighty-two topsoil (0–30 cm) samples were randomly collected and analyzed. pH and clay followed a normal distribution, whereas sand EC, CaCO₃, OC and K were log-transformed. The highest variation was observed for soil EC, and the lowest for soil pH. In the variography analysis, spherical, exponential and gaussian models were best fit on experimental semivariograms. The minimum effective spatial autocorrelation was 1500 m for OC and the maximum effective spatial autocorrelation was 4000 m for sand and K. Strong spatial correlations were noted with sand and CaCO₃ (<25%), whereas values were moderate for clay, EC, OC and K (25–75%). Ordinary kriging was utilized for the interpolation of estimated variable determinations in unsampled sites. It was found that soil properties in this study area were strongly influenced by both environmental and natural factors. The results can be used as a source of information for the development and implementation of any further land management and soil and water conservation plans.