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Santa Cruz de Tenerife, Spain

Hernandez-Duran G.,INTERRA | Arranz-Gonzalez J.C.,Instituto Geologico Y Minero Of Espana | De La Vega-Panizo R.,Technical University of Madrid
Boletin Geologico y Minero

There is no doubt that mineral resource extraction conflicts with other land uses. Spatial planning may avoid conflicts regarding land use, reduce adverse cumulative impacts of mining and prevent depletion of available mineral resources. This is especially true with industrial minerals. Knowing the distributionof potential mineral resources in the territory is the key to achieving the effective integration of mining in land-use planning, and thus safeguard in the best possible way mineral resources from the activities that may compromise their future availability. In both environmental-mining projects and mineral safeguarding mapping, potential geo-mine resources have been normally delimitated by analysing geological information and maps, when the scale of work is not detailed (regional planning). But when it comes to the local or municipal scale (large-scale mapping), planning requires far more data for a better delimitation of mineral resources. This may require field data collection, the revision of published reports and papers, the inventory and characterization of mines and quarries, and consultation with industry. The main aim of this study is to review several studies focused on mining and environmental planning, in order to obtain a better knowledge of the different formulae and criteria used to define industrial rocks resources which are present in a certain area. We conclude that there is no universal way to address this issue and also highlight that a detailed infrastructure of geologic knowledge is crucial for the planning applied to these types of mineral resources, especially at a local or municipal level. © 2014, Instituto Geologico y Minero de Espana. All rights reserved. Source

Zirlewagen D.,INTERRA | von Wilpert K.,Forest Research Institute
Journal of Plant Nutrition and Soil Science

One main problem with current research on spatio-temporal modeling of ion fluxes in forest soils is the separation of space and time effects in the soil-monitoring concept. This article describes an approach to overcome this weakness. Time trends of point information on soil-solution data (base-cation concentrations and fluxes) are scaled by linking them to soil-chemical data which is available in higher spatial resolution and can be upscaled to an area base. This approach is based on a combined evaluation of bulk soil and soil-solution data using both statistical and process-oriented methods. Multiple-linear-regression analyses coupled with geostatistics were developed to predict spatial patterns of exchangeable cation percentages. In a second step, empirical ion-distribution coefficients were adapted according to Gapon using data of suction-cup plots and bulk-soil samples. Seasonally adjusted time-series data of soil-solution chemistry were then connected with the maps of the predicted exchangeable-cation percentages by means of the Gapon equations. This evaluation step provided both time- and space-dependent maps of cation concentrations in the soil solution. Finally, using the results of a water-budget model it was possible to derive spatio-temporal patterns of soil cation fluxes. Methodological limitations and the results of verification processes are discussed. The methods described can only be used in acidic soils and should not be used in soil layers rich in humus, since adsorption to C compounds differs from adsorption to clay minerals. The time increments of the models should be not shorter than yearly in order to suppress annual periodicity. Although the Gapon equations were not based on laboratory-determined exchange solutions at quasi-equilibrium, but rather on field data from the suction-cup technique, the exchangeable-cation percentages showed steady functions of selectivity coefficients. The methods tested at a watershed scale may be flexible enough to be applied at other scales as well. © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source

Many studies in soil science provide qualitative or (semi-) quantitative assessmentsof soil physical properties such as soil texture or percentage of soil skeleton (the >2 mm fraction). In this paper, we describe the process of upscaling soil physical properties measured during the second Forest Soil Monitoring Census (BZE II). In order to enhance the data basis for process-oriented hydrology models at the landscape level, the use ofupscaling techniques based on point-related monitoring data is essential. The statisticalmethods used in this work included ordinary least square regression (OLS) and geostatistics. One aim of this study was to evaluate how the different spatial scales used for stratifying statistical approaches affect the quality of spatial estimates. When applied tosoil physical properties, our evaluations showed that, by using a stratified modeling approach, the accuracy of the estimates could be improved compared to global modeling approaches. Thus the regression models displayed comparatively high coefficients of determination ranging from 0,59 to 0,7 (for soil skeleton), 0,52 to 0,65 (bulk density), 0,7 (depth of soil development) and 0,66 to 0,8 (soil texture). Only in the case of the response variable fine root density were the coefficients of determination markedly below 0,5 (0,2-0,4).One of the reasons for this could be the small-scale variation in silvicultural site conditions such as tree species distribution or stand density. Source

Furst C.,Sudan University of Science and Technology | Lorz C.,Sudan University of Science and Technology | Zirlewagen D.,INTERRA | Makeschin F.,Sudan University of Science and Technology
Environmental Management

The article presents results of testing the indicative value of magnetic susceptibility for fly ash deposition and its effects on forest site properties. Base saturation and concentrations of Ca and Mg were used as indicators for nutrient pools resulting from fly ash deposition. Concentrations of Fe, Al, Mn, Cd and Black Carbon were used as indicators for risks of leaching. The correlation of magnetic susceptibility with concentrations of nutrient, acidic cations, heavy metals, base saturation and Black Carbon was calculated. Additionally, we tested the suitability of magnetic susceptibility as a parameter in a linear regression based model to predict the concentrations of Ca, Mg, Fe, Al, Mn, Cd and Black Carbon. We were able to show a positive correlation between magnetic susceptibility and the selected indicators. In contrast to previous studies, we were also able to demonstrate the suitability of magnetic susceptibility to predict the size of fly ash deposition influenced nutrient pools mainly for humus layers, especially for Oa horizons. The spatial distribution of magnetic susceptibility showed also a positive correlation with regionalized base saturation. However, because of the data base and other factors impacting the measurement and modeling results, some shortcomings of using a linear regression model must be noted. From these results, we concluded that magnetic susceptibility might be a valuable parameter in a multiple regression based approach, but should not be used alone for predicting effects of fly ash deposition. © 2010 Springer Science+Business Media, LLC. Source

Furst C.,Sudan University of Science and Technology | Lorz C.,Sudan University of Science and Technology | Zirlewagen D.,INTERRA | Makeschin F.,Sudan University of Science and Technology
WIT Transactions on Ecology and the Environment

This article presents a case study in the industrial triangle Leipzig-Halle-Bitterfeld, the purpose of which was to assess the actual fly ash load in forest soils and to test if ferrimagnetic susceptibility can be used for a fast and cost efficient screening of deposited elements. Ferrimagnetic susceptibility was mapped in a raster of 1x1 km2 and correlated with key nutrients, selected metals/heavy metals and Black Carbon. The predictive value of magnetic susceptibility was tested on the basis of linear regression models. Furthermore, multiple-regionalization techniques were used to model the spatial variation of fly ash. This includes an analysis of which environmental parameters are most important for the spatial model. The correlation between ferrimagnetic susceptibility, base saturation and the contents in Ca, Mg, Fe, Al and Cd (humus layers) was comparably high. The correlation with the content in Mn was weaker and the correlation with Black Carbon (humus layers) showed no clear trend. Linear regression based models with sufficient precision could be found for Ca, Mg and Mn, with lower precision for Cd and Black Carbon. No prediction was possible for Fe and Al. Multiple regression based modelling of the spatial variation of fly ash deposition was possible with a very high precision. A slightly differing set of model parameters was selected for different depth levels in the humus layer and mineral soil, comprising topographical and soil parameters and to a much lesser extent stand parameters. In conclusion, the usability of the proxy indicator ferrimagnetic susceptibility for screening of the deposited elements was proved. © 2010 WIT Press. Source

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