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The influence of pedogenetic factors onto spatial variability of chromium in soil surface horizon was studied in a metamorphic area (Massif Central, France) at the hillside scale. A grid survey was performed. Surface soil horizons were sampled at each point and analysed in Cr. Results show the determinant influence of the rock type on Cr content distribution along the slope. However, surface horizons of these soils exhibit a lower Cr content heterogeneity than the deeper horizons. This was explained by soils'' material erosion and deposition along the slope. Tillage and hedges also influence the Cr distribution in surface horizon along the slope. To cite this article: S. Salvador-Blanes et al., C. R. Geoscience 334 (2002) 51–58 [Copyright &y& Elsevier]

Abstract: The modeling of soil erosion by water supposes an accurate and thorough understanding of the hydrology. Thus, it is critical to have a good delineation of the surface flow path. The flow network data are critical for important uses such as flood forecasting and watershed management. Geographic Information System (GIS) functions are able to compute a flow network directly from the digital elevation models. Because the flow directions are only based on the topography, the other factors controlling the flow directions are overlooked. In the agricultural areas, work such as tillage can have a large impact on the flow direction. We propose a 5-step procedure to account for such man-made features. The use of this procedure clearly improves the quality of the computed flow network. This procedure has been successfully implemented in a GIS and improves the prediction of surface flow and therefore improves water erosion modeling at the watershed scale. [Copyright &y& Elsevier]

Abstract: In order to take best advantage of the electrical resistivity data, kriging spatial component technique was applied to separate the small and large-scale structures of resistivity data. Then the spatial structures in resistivity data which are poorly correlated with soil water content are filtered out prior to integrating resistivity data into water content estimation in the soil of a 10ha area located in the Picardie region (Northern of France). The soil water content was measured until 1.2m depth in 81 sites with 0.3m increments by gravimetric method. The resistivity was exhaustively measured for three different depths: 0.5m, 1m, and 2m. The resistivity data represents a set of 5656 measurement points for each of the three depths over the 10ha study area. The methodology involves successively: (1) a principal component analysis (PCA) on the electrical measurements for the three depths of soil; (2) a geostatistical filtering of the local component and noise in the first component (PC1) of PCA which account for 90% of the variance in the electrical measurements for the three depths of soil. Results have shown that the correlation between water content of soil profile (W) and PC1 is highly improved when the local component and noise were filtered out. Finally, the influence of the smoothness of the external drift function on the quality of estimates of a target variable was empirically demonstrated. Indeed, the estimates of W were highly improved when the external drift function used in kriging is much smoother: the large scale of PC1 instead of PC1. [Copyright &y& Elsevier]

Abstract: Anthropogenic trace element contamination of soils in the densely populated and industrialized Nord-Pas de Calais region (France) was quantified using enrichment factors (EFs). Total concentrations of Al and 18 trace elements (As, Bi, Cd, Co, Cr, Cu, Hg, In, Mn, Mo, Ni, Pb, Sb, Se, Sn, Tl, V, and Zn) were determined in 252 sampling sites both in topsoil and deep horizons of soils developed from sedimentary materials. Thus, at each sampling site an enrichment factor was computed for each of the 18 trace elements as the ratio between total concentrations of the trace element in topsoil and deep horizons in the same soil pit, normalized by concentrations of Al measured in the same horizons and the same pit. To estimate EF values at unsampled locations and then to assess the spatial magnitude of anthropogenic trace element contamination over the whole study area (12400km2), variography analysis was used to quantify the spatial structure of each EF. Results have shown that values of 8 EFs are spatially correlated. These EFs were thus mapped using the sequential Gaussian simulation technique. One hundred horizon samples from 50 supplementary sites were analysed for the structured trace elements and Al contents and used for the mapping validation. Results of the validation based on the accuracy plots and goodness statistics (G and D) allowed us to conclude that EF maps exhibited high certainty in regard to the validation data set. In addition, results have shown that E-type estimates were accurate when they are used to estimate the measured EF value of the validation data set. Accordingly, these maps were used to discuss the origin of patches of surface horizon enrichment displaying an exogenous input of the trace elements investigated. The whole study area under discussion is strongly enriched with cadmium, originating from both industrial and agricultural activities. Surface horizons also exhibit locally high levels of Pb and Zn enrichment, mainly around well-known former or current industrial sites. However, Pb and Zn enriched surface horizons are far less widespread than those enriched in Cd. Higher Cu, Bi and Sn EF values were observed in the northern part of the region studied than in the southern part. The dissimilarity underlined a rather diffuse contamination from the urbanized zone in the north to the rural zone in the south of the region. The enrichment of surface horizons by In and Tl seems insignificant. Some unstructured EFs were attributes to point-source enrichments. [Copyright &y& Elsevier]

Abstract: The aim of this article is to present a strategy to interpret the hydraulic functioning of a small field area by using measurements of the soil electrical resistivity. The spatial soil electrical resistivity was recorded at a high resolution on a 2ha area by the MultiContinous Electrical Profiling (MuCEP) device at two dates. These apparent electrical resistivity measurements were firstly interpreted in terms of local electrical resistivity by 1D inverse modelling to estimate the real resistivity of the soil. These interpreted electrical resistivity data were then transformed into soil water content values and soil water potential values by the use of independent punctual data of water content and the use of the water retention curve determined by laboratory data. Our analysis has permitted us to describe the spatial variability and temporal evolution of the hydraulic functioning at high resolution from electrical resistivity data. The interpretation of the water content and matric potential maps demonstrated that some soil hydraulic processes, such as lateral overland flow, can occur in the studied zone. They would never have been detected by local measurements of soil characteristics or by the use of the soil map. [Copyright &y& Elsevier]

Abstract: Soils are characterised by a spatial variability in the three dimensions (3D) of space. However, 3D studies remain scarce due to the qualitative nature of many soil horizon characteristics, notably the horizon designation. Indeed, existing 3D tools are mainly developed for quantitative data. To solve this difficulty, we propose a new approach based on the interpolation of the horizon thickness to derive digital elevation models for both the upper and the lower limits of each horizon. This approach was applied to Planosols previously extensively studied with 2D approaches. The pseudo 3D obtained representation evidences soil processes that were missed in 2D approaches. As an example, we evidence the impact of differential weathering, resulting from the mineralogical heterogeneity of the parent material, on the subsequent pedogenesis. [Copyright &y& Elsevier]

The impact of agricultural practices on the spatial distribution of trace elements (TEs) in the surface horizon of Albeluvisols was studied by comparing three types of situation with an increasing anthropogenic gradient: a forest soil, considered as a reference, and cultivated soils with and without spreading of sewage sludge. Total cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) were determined in soil surface horizons. The quantity of particles finer than 2 µm, organic carbon (OC), iron (Fe), manganese (Mn), and calcium (Ca) contents were also measured and used as tracers of soil components that may have contained TEs. Governing factors of the spatial variability of TEs were searched for through comparison of the descriptive statistics (mean and coefficient of variation) and the determination of the best multivariate model predicting TE contents. Nickel and Cr distributions seem to be mainly linked to variability of the parent material composition, whereas that of Co is related to redox pedological processes. In addition, agricultural practices play a role in TE distribution, through the input of TEs, mostly Cd, Cu, and Zn, via sewage sludge spreading and liming amendments, and lateral (homogenization) and vertical (mixing of horizons) redistribution through tilling the soil. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this study is to determine the factors that control the spatial variability of chromium in the topsoil at the landscape scale by using a combination of both individual soil pit informations and systematic soil sampling analyses. The 11 ha study area, located in Massif Central (France), includes contrasted bedrock and topography. In a first approach we determined the relation between the concentrations in chromium and other major elements reflecting the soil pedogenic processes and some particular minerals indicating the original materials the soils are derived from. For this purpose, we used data collected at the catena scale from 10 soil profiles in two toposequences matching all geological and topographic situations. In a second approach, we studied the spatial variability of Cr in both topsoil and alterite through a systematic sampling study. Chromium concentrations range between 16 and 355 mg kg−1 in the alterite, and 31 to 129 mg kg−1 in the topsoil. Chromium concentration in alterite presents a complex spatial distribution governed principally by the geological origin of the alterite. Two major differences between chromium concentration in the alterite and in the topsoil may be deduced. First, topsoil chromium distribution depends on topography. Increased weathering together with selective erosion of the topsoil resulted in smaller chromium concentration in the concave compared to the convex area. Secondly, chromium concentration in the topsoil varies spatially much less than in the alterite. Such differences can probably be observed in similar geomorphic conditions and for other chemical elements that can be considered as geochemically immobile through weathering. [Copyright &y& Elsevier]