Tsvetan Kotsev, Velimira Stoyanova

In this paper, we conducted predictive modelling of the spatial distribution of arsenic-contaminated soils in a river valley polluted with mine tailings from the processing of Fe-, Pb-Ag and Au-ores in the mountainous part of the river catchment. The maximum entropy method was applied using the software Maximum Entropy Species Distribution Modeling (MaxEnt), Version 3.4.4 (Phillips et al., 2006). The results of MaxEnt were visualized with ESRI ArcGIS 10.6.1 software product. The choice of predictors of contaminated soil distribution is consistent with the main factor for contaminant dispersal within the valley floor – flooding from the Ogosta River. The following five parameters explained the environmental settings related to the accumulation of contaminated floodplain sediment: vertical distance to the river channel (m_vdcn); distance from the Ogosta River (m_distance); slope (m_slope); land cover (m_clc_18); morphographic units of topography (m_gmu). Arsenic content was measured by the XRF method in 105 topsoil samples (0-20 cm) which were collected in 2020. The samples were divided into three groups according to the maximum permissible concentration (25 mg/kg) and the intervention value of As (90 mg/kg) in the soils of arable and grass lands according to Bulgarian Regulation No. 3/2008 on the permissible content of harmful substances in soils. The intervals of As for each group were as follows [mg/kg]: Group 1 (0-25], 59 samples; Group 2 (25-90], 15 samples; Group 3 (>90), 31 samples. For each group, separate modelling was performed with MaxEnt using the set of predictors specified above. We used the logistic type of output of MaxEnt, which is interpreted as probability of presence of the research object with a value from 0 to 1. Control samples were selected by the bootstrap method due to the small number of samples in the individual groups. The final results represent the average values of 10 replicates of the model. We evaluated the individual models by AUC for the test samples. The AUCtest value for the Group 1 model is 0.793, for Group 2 is 0.741, and for Group 3 is 0.832. The models of the first two groups can be rated as fair, and the one for group 3 is defined as good according to the classification suggested by Araújo et al. (2005). The most significant predictors for the models are the distance from the river, the vertical distance to the river channel, and the slope of the terrain. Arsenic concentrations tend to decrease with the distance from the main river and by increasing the elevation above the river channel due to lower inundation frequency and deposition rate of polluted river sediments. At a probability of presence above 50%, soils with As90 mg/kg occupy nearly 8% of its area. Although the studied section of the Ogosta River valley is more than 80 km from the former Chiprovtsi mines, they strongly affected the environmental quality in the modelled area. The results indicate pollution of soils in the low floodplain of the entire valley from the mines to the river mouth into the Danube River.

maximum entropy, MaxEnt, mine tailings, soil pollution, river floodplain

Problems of Geography, 2022, Vol.3-4, DOI: 10.35101/prg-2022.3-4.2

Author information:
Author: Tsvetan Kotsev
Affiliation: National Institute of Geophysics, Geodesy and Geography – BAS, department of Geography, str. Acad. G. Bonchev, bl. 3, Sofia 1113, Bulgaria

Author: Velimira Stoyanova
Affiliation: National Institute of Geophysics, Geodesy and Geography – BAS, department of Geography, str. Acad. G. Bonchev, bl. 3, Sofia 1113, Bulgaria

This study was supported by the project “Relationship of the spatial distribution of heavy metals in soil with the morphology of polluted floodplain river terraces”, abbreviated TOPOMET, funded by the Bulgarian National Science Fund, contract No. KP-06-N24/2 (08.12.2018) with basic organization National Institute of Geophysics, Geodesy and Geography, Bulgarian Academy of Sciences. The authors are grateful of associate professor Metodi Karadzhov and the management of the Geological Institute of the Bulgarian Academy of Sciences for the provided technique for grinding the soil samples.

How to cite:
Kotsev, T., & Stoyanova, V. (2022). Вероятностно моделиране на обхвата на почви, замърсени с арсен в долината на река Огоста между селата Бели брод и Манастирище в Северозападна България. Problems of Geography, 2022, Vol.3-4, p. 15-29.