No abstract

No abstract

This paper provides an overview of the physical and chemical landscape changes that have occurred at four reference sites due to historical mining and smelting activities within Slovenia, and their comparison with similar sites around the World. Literature review has been made with the intention to identify major pollutant sources, its dispersion control factors, and effects. The four reference sites are Idrija, with more than 500‐year Hg mining and ore smelting history, the Meža Valley, also with a 500‐year PbZn mining and smelting history, the Celje area where Zn was smelted for 100 years and the Drava River alluvial plain, which is contaminated because of historical PbZn mining upstream. Based on the comparison between the four abovementioned reference sites and similar sites around the world that are situated in different landscapes and climates, we identified major sources of contamination, which are the erosion of mine and ore processing wastes, and atmospheric emissions of metal‐containing particles from smelters. In the first case, major control factors are rainfall pattern and river gradient, controlling erosion and sediment deposition patterns. In the second case, the prevailing control factors are topography and the dominant wind directions.

No abstract

This study has the purpose of developing a realistic soil prediction maps of the spatial distribution of elements by evaluating and comparing different modelling techniques: Kriging, artificial neural network-multilayer perceptron (ANN-MLP) and multiple polynomial regressions (MPR). The Stavnja Valley was selected as a test area due to the following reasons: (1) intensive metal ore mining and metallurgical processing; (2) peculiar geomorphological natural features; (3) regular geological setting, and (4) the remaining minefields. Geospatial parameters from digital elevation models (DEM) are used as an input to advanced prediction modelling techniques: ANN-MLP and MPR. Soil measurements, land use data, and remote sensing are applied, developed, and finally incorporated into the models of spatial distribution in the form of 2D or 3D maps. In order to reconstruct the different processes that influenced the entire study area simultaneously, we used novel approaches to modelling. This comprehensive approach not only represents an innovation in contamination mapping, but developed prediction models also help in the reconstruction of main distribution pathways, assess the real size of the affected area, and improve the data interpretation.