The paper presents the results of a study of heavy metals (HMs) concentrations in six retention reservoirs located in the lowland area of western Poland. The objectives of this study were to analyze the Cd, Cr, Cu, Ni, Pb and Zn concentrations, assess contamination and ecological risk, analyze the spatial variability of HM concentrations and identify potential sources and factors determining the concentration and spatial distribution. The bottom sediment pollution by HMs was assessed on the basis of the index of geo-accumulation (Igeo), enrichment factor (EF), pollution load index (PLI) and metal pollution index (MPI). To assess the ecological risk associated with multiple HMs, the mean probable effect concentration (PEC) quotient (Qm-PEC) and the toxic risk index (TRI) were used. In order to determine the similarities and differences between sampling sites in regard to the HM concentration, cluster analysis (CA) was applied. Principal component analysis (PCA) was performed to assess the impact of grain size, total organic matter (TOM) content and sampling site location on HM spatial distribution. Additionally, PCA was used to assess the impact of catchment, reservoir characteristics and hydrological conditions. The values of Igeo, EF, MPI and PLI show that Cd, Cr, Cu, Ni and Pb mainly originate from geogenic sources. In contrast, Zn concentrations come from point sources related to agriculture. The mean PEC quotient (Qm-PEC) and TRI value show that the greatest ecological risk occurred at the inlet to the reservoir and near the dam. The analysis showed that the HMs concentration depends on silt and sand content. However, the Pb, Cu, Cd and Zn concentrations are associated with TOM as well. The relationship between individual HMs and silt was stronger than with TOM. The PCA results indicate that HMs with the exception of Zn originate from geogenic sources—weathering of rock material. However, the Ni concentration may additionally depend on road traffic. The results show that a reservoir with more frequent water exchange has higher HMs concentrations, whereas the Zn concentration in bottom sediments is associated with agricultural point sources.

The study evaluated the effect of environmental conditions and morphometric parameters on lake water temperature changes. The analysis was carried out on the basis of 14 lakes located in northern Poland. The assessment was based on the daily water and air temperatures from 1972 to 2016. It took into account the location of lakes (latitude, longitude, altitude) morphometric parameters (surface area, maximum and mean depth, volume), hydrological processes (rate of water exchange, course of ice phenomena), and trophic status (water transparency) as factors that can modify lake water temperature changes. Direction and rate of air and water temperature changes were analysed by means of Mann-Kendall's and Sen's tests. Cluster analysis (CA) was applied to group lakes characterised by similar water temperature changes. The effect of climatic and non-climatic parameters on a lake's water temperature was assessed on the basis of principal component analysis (PCA). Water temperatures in the lakes in the years 1972-2016 were characterised by a higher rate of increase of 0.43 • C·dec −1 than the air temperature decrease of 0.34 • C·dec −1 . The analysis showed a faster rate of heating of waters in western Poland. This can be explained by shorter duration of ice cover. Moreover, the changes of water temperature were affected by other factors, including the location of the lakes, their morphometric parameters, wind speed, water transparency and water exchange time.

The paper presents the results of determinations of physico-chemical parameters of the Mała Wełna waters, a river situated in Wielkopolska voivodeship (Western Poland). Samples for the physico-chemical analysis were taken in eight gauging cross-sections once a month between May and November 2006. To assess the physico-chemical composition of surface water, use was made of multivariate statistical methods of data analysis, viz. cluster analysis (CA), factor analysis (FA), principal components analysis (PCA), and discriminant analysis (DA). They made it possible to observe similarities and differences in the physico-chemical composition of water in the gauging cross-sections, to identify water quality indicators suitable for characterising its temporal and spatial variability, to uncover hidden factors accounting for the structure of the data, and to assess the impact of man-made sources of water pollution.

The development of dams alters the structure and function of river ecosystems. Dam reservoirs have an impact on flow regime, sediment transport, and water quality. Damming a river decreases water velocity, which leads to an increase in suspended sediments deposition. Reservoirs often are described as water treatment plants because they trap water contaminants and suspended sediments. Suspended sediments are the principal factor for heavy metals transport [1][2]. Human activity increased input of heavy metals to water bodies where sediments are deposited [3][4][5][6][7][8]. Amin et al. [9] and Zheng et. al. [10] reported that more than 90% of the heavy metal load in the water bodies has been associated with suspended particulate matter and sediments. The spatial and seasonal variations of heavy metal loads are controlled by suspended sediment concentrations as well as water pH, which controls the absorbance of heavy metals [11].The spatial distribution of sediments in a reservoir is not uniform [12]. Toward the dam, sediments are usually more fine-grained and lithologically uniform [13]. The heavy metals concentrations generally increased with the decrease of particle size and increase of organic matter. The concentration of heavy metals in Pol. AbstractThe aim of this study was to analyze the heavy metals transport in a river-reservoir system. Sediment samples from 25 locations (9 from the Powa River and 16 from the Stare Miasto Reservoir) were analyzed for trace metals contents (Cr, Ni, Cu, Zn, Cd, and Pb). The relationships between heavy metal concentrations and bottom sediment physical properties were determined with the use of the multivariate statistical techniques cluster analysis (CA), principal component analysis (PCA), and canonical correspondence analysis (CCA). The results showed that concentrations of heavy metals in the sediments of the reservoir were higher than those in the bottom sediments of the river. Concentrations of heavy metals in bottom sediments in the river above the reservoir were characterized by lower spatial variability. Decisive influence on heavy metal concentrations of bottom sediments had silt, clay, and total organic matter content.

The paper reports the results of measurements of trace elements concentrations in surface water samples collected at the lowland retention reservoirs of Stare Miasto and Kowalskie (Poland). The samples were collected once a month from October 2011 to November 2012. Al, As, Cd, Co, Cr, Cu, Li, Mn, Ni, Pb, Sb, V, and Zn were determined in water samples using the inductively coupled plasma with mass detection (ICP-QQQ). To assess the chemical composition of surface water, multivariate statistical methods of data analysis were used, viz. cluster analysis (CA), principal components analysis (PCA), and discriminant analysis (DA). They made it possible to observe similarities and differences in the chemical composition of water in the points of water samples collection, to uncover hidden factors accounting for the structure of the data, and to assess the impact of natural and anthropogenic sources on the content of trace elements in the water of retention reservoirs. The conducted statistical analyses made it possible to distinguish groups of trace elements allowing for the analysis of time and spatial variation of water in the studied reservoirs.