Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

A search for the origin of cadmium in the soil of the Swiss Jura

The top soil of a 14.5 km(2) region at la Chaux-de-Fonds in the Swiss Jura is exceptionally rich in cadmium. It contains an average of 1.3 mg per kg of soil. The spatial distribution of the metal has no simple pattern that could be explained by atmospheric deposition or agricultural practices. Thin soil contained most of its Cd at the surface; in thicker soil Cd is mainly concentrated between 60 and 80 cm depth. No specific minerals or soil fractions could account for these accumulation, and the vertical distribution of Cd is best explained by leaching from the topsoil and further adsorption within layers of nearly neutral pH. The local Jurassic sedimentary rocks contained too little Cd to account for the Cd concentrations in the soil. Alpine gravels from glacial till were too sparse in soils to explain such a spreading of Cd. Moreover this origin is contradictory with the fact that Cd is concentrated in the sand fraction of soils. The respective distributions of Fe and Cd in soils, and soil fractions, suggested that the spreading of iron nodules accumulated during the siderolithic period (Eocene) was not the main source of Cd. Atmospheric deposition, and spreading of fertiliser or waste from septic tanks seem the only plausible explanation for the Cd concentrations, but at present few factors allow us to differentiate between them.

Heated Optical Fiber for Distributed Soil-Moisture Measurements: A Lysimeter Experiment

An Actively Heated Fiber Optics (AHFO) method to estimate soil moisture is tested and the analysis technique improved on. The measurements were performed in a lysimeter uniformly packed with loam soil with variable water content profiles. In the first meter of the soil profi le, 30 m of fiber optic cable were installed in a 12 loops coil. The metal sheath armoring the fiber cable was used as an electrical resistance heater to generate a heat pulse, and the soil response was monitored with a Distributed Temperature Sensing (DTS) system. We study the cooling following three continuous heat pulses of 120 s at 36 W m(-1) by means of long-time approximation of radial heat conduction. The soil volumetric water contents were then inferred from the estimated thermal conductivities through a specifically calibrated model relating thermal conductivity and volumetric water content. To use the pre-asymptotic data we employed a time correction that allowed the volumetric water content to be estimated with a precision of 0.01-0.035 (m(3) m(-3)). A comparison of the AHFO measurements with soil-moisture measurements obtained with calibrated capacitance-based probes gave good agreement for wetter soils [discrepancy between the two methods was less than 0.04 (m(3) m(-3))]. In the shallow drier soils, the AHFO method underestimated the volumetric water content due to the longertime required for the temperature increment to become asymptotic in less thermally conductive media [discrepancy between the two methods was larger than 0.1 (m(3) m(-3))]. The present work suggests that future applications of the AHFO method should include longer heat pulses, that longer heating and cooling events are analyzed, and, temperature increments ideally be measured with higher frequency.

Genesis of the Jurassic carbonate-hosted Pb-Zn deposits of Jebel Ressas (North-eastern Tunisia): Evidence from mineralogy, petrography and trace metal contents and isotope (O, C, S, Pb) geochemistry

The Jebel Ressas Pb-Zn deposits in North-Eastern Tunisia occur mainly as open-space fillings (lodes, tectonic breccia cements) in bioclastic limestones of the Upper Jurassic Ressas Formation and along the contact of this formation with Triassic rocks. The galena-sphalerite association and their alteration products (cerussite, hemimorphite, hydrozincite) are set within a calcite gangue. The Triassic rocks exhibit enrichments in trace metals, namely Pb, Co and Cd enrichment in clays and Pb, Zn, Cd, Co and Cr enrichment in carbonates, suggesting that the Triassic rocks have interacted with the ore-bearing fluids associated with the Jebel Ressas Pb-Zn deposits. The delta(18)O content of calcite associated with the Pb-Zn mineralization suggests that it is likely to have precipitated from a fluid that was in equilibrium with the Triassic dolostones. The delta(34)S values in galenas from the Pb-Zn deposits range from -1.5 to +11.4%, with an average of 5.9% and standard deviation of 3.9%. These data imply mixing of thermochemically-reduced heavy sulfur carried in geothermal- and fault-stress-driven deep-seated source fluid with bacterially-reduced light sulfur carried in topography-driven meteoric fluid. Lead isotope ratios in galenas from the Pb-Zn deposits are homogenous and indicate a single upper crustal source of base-metals for these deposits. Synthesis of the geochemical data with geological data suggests that the base-metal mineralization at Jebel Ressas was formed during the Serravallian-Tortonian (or Middle-Late Miocene) Alpine compressional tectonics.

Origin of cadmium enrichments in carbonate rocks deposited in the Alpine Tethys area during the Middle-Late Jurassic

ABSTRACTThe pollution of air, soil and water by heavy metals through anthropogenic activities is an object of numerous environmental studies since long times. A number of natural processes, such as volcanic activity, hydrothermal fluid circulation and weathering of metal-rich deposits may lead to an additional and potentially important input and accumulation of heavy metals in the environment. In the Swiss and French Jura Mountains, anomalous high cadmium (Cd) concentrations (up to 16 ppm) in certain soils are related to the presence of underlying Cd-enriched (up to 21 ppm) carbonate rocks of Middle to Late Jurassic age. The aim of this study is to understand the processes controlling Cd incorporation into carbonate rocks of Middle and Late Jurassic age and to reconstruct the sedimentary and environmental conditions, which have led to Cd enrichments in these sedimentary rocks.Cd concentrations in studied hemipelagic sections in France vary between 0.1 and 0.5 ppm (mean 0.15 ppm). Trace-element behavior and high Mn concentrations suggest that sediment accumulation occurred in a well-oxygenated environment. Increases in Cd contents in the bulk-rock carbonate sediments may be related to increases in surface-water productivity under oxic conditions and important remineralization of organic matter within the water column. In platform settings preserved in the Swiss Jura Mountains, no correlation is observed between Cd contents and evolution of environmental conditions. Cd concentrations in these platform sections are often below the detection limit, with isolated peaks of up to 21 ppm. These important Cd enrichments are associated with peaks in Zn concentrations and are present in carbonate rocks independently of facies and age. The high Cd contents in these shallow-water carbonate rocks are partly related to the presence of disseminated, Cd-rich (up to 1.8%), sphalerite (ZnS) mineralization. The basement rocks are considered to be the source of metals for sulfide mineralization in the overlying Jurassic strata, as the sphalerite Pb isotope pattern is comparable to that of granite rocks from the nearby southern Black Forest crystalline massif. The Rb-Sr ages of sphalerite samples indicate that a main phase of sphalerite formation occurred near the boundary between the late Middle and early Late Jurassic, at around 162 Ma, as a result of enhanced tectonic and hydrothermal activity in Europe, related to the opening of the Central Atlantic and to the tectonic/thermal subsidence during spreading of the Alpine Tethys. I therefore propose to use unusually high Cd concentrations in carbonates as a tracer of tectonic activity in the Jura Mountains area, especially in the case when important enrichments in Zn co-occur. Paleoproductivity reconstructions based on records of authigenic Cd may be compromised not only by post-depositional redistribution, but also by incorporation of additional Cd from hydrothermal solutions circulating in the rock.The circulation of metal-rich hydrothermal fluids through the sediment sequence, in addition to specific environmental conditions during sedimentation, contributes to the incorporation of Cd into the carbonate rocks. However, only hydrothermal activity has led to the unusually high concentrations of Cd in carbonate rocks of Bajocian-Oxfordian age, through the formation of sphalerite mineralization.