Modeling of Heavy Metal (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and PAH Content in Stormwater Sediments Based on Weather and Physico-Geographical Characteristics of the Catchment: An Advance Data-Mining Approach

The processes that determine the quality of sediment in drainage systems are dynamic and complicated. However, because these topics have not been widely examined in research studies, there is relatively little information available on the effects of both watershed characteristics and meteorological circumstances on sediment chemical properties. The amount of selected heavy metals (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and polycyclic aromatic hydrocarbons (PAHs) in sediments from the stormwater drainage systems of four catchments in the city of Kielce, Poland, is reported in this work. The effects of various physico-geographical catchment parameters and atmospheric conditions on pollutant concentrations in sediments were also investigated. Using artificial neural networks, statistical models for forecasting the quality of stormwater sediments were built based on the findings (multilayer perceptron neural networks). The chemical composition of sediments was found to be influenced by a variety of factors, including catchment characteristics and meteorological conditions. Catchment variables (land use, drainage system length) influenced heavy metal concentrations in sediments significantly more than meteorological conditions. The content of PAHs in sediments, on the other hand, was mostly influenced by the catchment’s atmospheric conditions. The multilayer perceptron models built for this study performed well in terms of prediction; the mean absolute error of the forecast (Ni, Mn, Zn, Cu, and Pb) was less than 21%. As a result, the models have a lot of promise, as they might be used in things like spatial planning when environmental factors (such sediment quality in stormwater drainage systems) are taken into account. The construction of forecasting models was the strategy offered in this study. They can be used to aid spatial planning and development in a variety of ways.

Author(s) Details

Lukasz Bak
Department of Geotechnics and Water Engineering, Faculty of Environmental, Geomatic and Energy Engineering, Kielce University of Technology, Kielce 25-314, Poland.

Bartosz Szelag
Department of Geotechnics and Water Engineering, Faculty of Environmental, Geomatic and Energy Engineering, Kielce University of Technology, Kielce 25-314, Poland.

Aleksandra Salata
Department of Water and Wastewater Technology, Faculty of Environmental, Geomatic and Energy Engineering, Kielce University of Technology, Kielce 25-314, Poland.

Jan Studzinski
Systems Research Institute of Polish Academy of Sciences, Warsaw 01-447, Poland.

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