Pollution distribution in floodplain structure visualised by electrical resistivity imaging in the floodplain of the Litavka River, the Czech Republic

Faměra, Martin; Kotková, Kristýna; Tůmová, Štěpánka; Elznicová, Jitka; Grygar, Tomáš Matys

doi:10.1016/j.catena.2018.01.023

Cited by 17 publications

(5 citation statements)

References 47 publications

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“…The river has a gradient of approximately 5 m/km and a single active channel, with no artificial source of pollution upstream before the control site. The river valley has a typical width of 100 m to 200 m and is relatively flat with abundant ditches ( Faměra et al ., 2018 ). Soil samples were collected in October 2021 from the surface horizon (0–20 cm) of each meadow using quadrat sampling ( Renčo and Čerevková, 2015 ).…”

Section: Methodsmentioning

confidence: 99%

Life in a Contaminated Environment: How Soil Nematodes Can Indicate Long-Term Heavy-Metal Pollution

Renčo

Čerevková

Hlava

2022

Journal of Nematology

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We investigated the genera, trophic groups, and functional guilds of soil nematodes at five alluvial meadows along the Litavka River in the Czech Republic to assess their usefulness as indicators of heavy metal pollution in soils. The Litavka River flows around the waste-sedimentation pond of a smelter in the city of Příbram in the Central Bohemian Region. Lead, zinc, and arsenic are the main pollutants in the soils in the vicinity of the smelter. The alluvial meadows closest to the pond and mine waste were the most heavily polluted sites, and contamination decreased downstream along the river with increasing distance from the sources of pollution. The nematode communities were sensitive to pollution, with the most contaminated sites having considerably fewer nematode individuals, fewer genera, and a less diverse and more degraded food web with less nematode biomass. Arsenic, lead, and zinc contents were significantly negatively correlated with the numbers of bacterivores, predators, omnivores, plant parasites, and fungivores, which were significantly less abundant at highly polluted sites. This correlation suggests that nematode groups with higher c-p values, and those with c-p 1 and 2 designations, can be useful indicators of high heavy-metal contamination in areas polluted for a long time. In contrast, the abundance of c-p 3 plant parasitic nematodes was positively correlated with copper, nickel, and zinc contents and with soil-moisture content in the alluvial meadows. Maturity index (MI) and MI2-5 were the most sensitive indices of the degree of disturbance of the soil ecosystem, with enrichment index, structure index, and basal index indicating the altered decomposition channels and diminished structure of the food web.

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Section: Methodsmentioning

confidence: 99%

Life in a Contaminated Environment: How Soil Nematodes Can Indicate Long-Term Heavy-Metal Pollution

Renčo

Čerevková

Hlava

2022

Journal of Nematology

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“…Příbram is a town in central Bohemia that is located 50 km to the south of Prague ( Figure 1 ). As a result of long-term ore mining and metallurgical activities, the area of the Litavka river alluvium is heavily polluted, with PTEs from three sources: (i) naturally increased metal content because of the specific composition of parent rocks, (ii) atmospheric deposition from a smelter, and (iii) floods of water polluted with metal-processing wastes [ 30 , 31 ]. According to the World reference base of soil resources [ 32 ], soils of the area are predominantly characterized as Fluvisols, Gleysols, and, in areas that are slightly elevated relative to the alluvium, Cambisols.…”

Section: Methodsmentioning

confidence: 99%

vis–NIR and XRF Data Fusion and Feature Selection to Estimate Potentially Toxic Elements in Soil

Gholizadeh

Coblinski

Saberioon

et al. 2021

Sensors

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Soil contamination by potentially toxic elements (PTEs) is intensifying under increasing industrialization. Thus, the ability to efficiently delineate contaminated sites is crucial. Visible–near infrared (vis–NIR: 350–2500 nm) and X-ray fluorescence (XRF: 0.02–41.08 keV) spectroscopic techniques have attracted tremendous attention for the assessment of PTEs. Recently, the application of fused vis–NIR and XRF spectroscopy, which is based on the complementary effect of data fusion, is also increasing. Moreover, different data manipulation methods, including feature selection approaches, affect the prediction performance. This study investigated the feasibility of using single and fused vis–NIR and XRF spectra while exploring feature selection algorithms for the assessment of key soil PTEs. The soil samples were collected from one of the most heavily polluted areas of the Czech Republic and scanned using laboratory vis–NIR and XRF spectrometers. Univariate filter (UF) and genetic algorithm (GA) were used to select the bands of greater importance for the PTE prediction. Support vector machine (SVM) was then used to train the models using the full-range and feature-selected spectra of single sensors and their fusion. It was found that XRF spectra alone (primarily GA-selected) performed better than single vis–NIR and fused spectral data for predictions of PTEs. Moreover, the prediction models that were derived from the fused data set (particularly the GA-selected) enhanced the models’ accuracies as compared with the single vis–NIR spectra. In general, the results suggest that the GA-selected spectra obtained from the single XRF spectrometer (for As and Pb) and from the fusion of vis–NIR and XRF (for Pb) are promising for accurate quantitative estimation detection of the mentioned PTEs.

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“…(1) sediments in abandoned meanders and laterally shifting channels that have evolved, i.e., were filled with sediment during the U-mining climax (1971)(1972)(1973)(1974)(1975)(1976)(1977)(1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989); these features can be identified with GIS analysis, in particular using old maps, aerial photographs and DTM; (2) other sediment traps in the floodplain, such as meander scars (more ancient channels not depicted in old maps [24]); and (3) certain young (recently built) levees; these locations can be identified with DTM on the external banks of meander bends and by "sedimentary facies mapping", i.e., mapping sediment grain-size in the floodplain, because they exhibit lower Al/Si and/or higher Zr/Rb ratios in the Ploučnice River floodplain. All three of these types of polluted sediment traps represent lithological and topographical heterogeneities, which can also be visualised by geophysical imaging [9,10,24]. However, the tools reported in this paper are sufficient for identification and interpretation of pollution hotspots in the studied floodplains and can thus be applicable to any polluted floodplain.…”

Section: Discussionmentioning

confidence: 92%

“…Using a portable (global positioning system (GPS) coupled with geophysical imaging, particularly for methods acquiring electrical resistivity, has saved a large amount of work associated with identifying subsurface sediment bodies within a floodplain, which has considerably facilitated floodplain studies [7,8]. The performance of electrical resistivity imaging in floodplain studies has been demonstrated in previous works [9][10][11][12]. Since the beginning of the 21st century, precise digital terrain models produced from airborne laser scanning (LIDAR) data most commonly used for fluvial geomorphologic evaluation [13].…”

Section: Introductionmentioning

confidence: 99%

“…Studies on polluted floodplains are facilitated by pollution mapping that uses portable analytical instruments, including in situ analyses (without any sample pretreatment) [9,10]. In the last decade, portable analytical instruments, in particular those employing X-ray fluorescence (XRF), have reached quality levels suitable for geological research and environmental science monitoring [14].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Threat of Pollution Hotspots Reworking in River Systems: Case Study of the Ploučnice River (Czech Republic)

Elznicová

Grygar

Popelka

et al. 2019

IJGI

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As fluvial pollution may endanger the quality of water and solids transported by rivers, mapping and evaluation of historically polluted fluvial sediments is an urgent topic. The Ploučnice River and its floodplain were polluted by local uranium mining from 1971–1989. We have studied this river since 2013 using a combination of diverse methods, including geoinformatics, to identify pollution hotspots in floodplains and to evaluate the potential for future reworking. Archival information on pollution history and past flooding was collected to understand floodplain dynamics and pollution heterogeneity. Subsequently, a digital terrain model based on laser scanning data and data analysis were used to identify the sites with river channel shifts. Finally, non-invasive geochemical mapping was employed, using portable X-ray fluorescence and gamma spectrometers. The resulting datasets were processed with geostatistical tools. One of the main outputs of the study was a detailed map of pollution distribution in the floodplain. The results showed a relationship between polluted sediment deposition, past channel shifts and floodplain development. We found that increased concentration of pollution occurred mainly in the cut-off meanders and lateral channel deposits from the mining period, the latter in danger of reworking (reconnecting to the river) in the coming decades.

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Pollution distribution in floodplain structure visualised by electrical resistivity imaging in the floodplain of the Litavka River, the Czech Republic

Cited by 17 publications

References 47 publications

Life in a Contaminated Environment: How Soil Nematodes Can Indicate Long-Term Heavy-Metal Pollution

Life in a Contaminated Environment: How Soil Nematodes Can Indicate Long-Term Heavy-Metal Pollution

vis–NIR and XRF Data Fusion and Feature Selection to Estimate Potentially Toxic Elements in Soil

Threat of Pollution Hotspots Reworking in River Systems: Case Study of the Ploučnice River (Czech Republic)

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