Comparative Spatial Assessment of Trace Metal(loid) Pollution in the Sediments of the Lower Olifants River Basin in South Africa

Globally, many freshwater ecosystems are facing chemical pollution from both natural and anthropogenic sources. The Olifants River Basin in South Africa is experiencing degradation due to mining, industrial, agricultural, and domestic activities. The impacts of these activities coupled with climate change is likely to shift the hydrological cycle that may increase accumulation of toxic chemicals in the sediments. The aim of the study was to assess the contamination of As, Cr, Cu, Fe, Mn, Ni, Pb, and Zn in the sediments collected at the upstream, midstream and downstream of four rivers of the Lower Olifants River Basin; the Blyde, Mohalpitsi, Ga-Selati, and Steelpoort rivers. The highest concentrations of most of the trace metal (loid)s assessed were from the Steelpoort River followed by the Blyde River. Significant differences in metal concentrations were found across study sites and rivers. The overall assessment of the sub-catchment, which is characterised mainly by mining and agricultural activities shows significantly elevated levels of As, Cr, Mn, and Ni in the sediments and may cause secondary pollution in the water. Using enrichment factor (EF) and geo-accumulation index (I_geo), some of the sediments were severely enriched and extremely contaminated respectively with As, Cr, and Ni. This may risk the lives of aquatic biota and humans, especially rural communities that rely on these rivers for drinking water. The findings provide baseline information for effective management control of metal(loid) pollution in the Olifants River Basin.

Introduction

Many freshwater ecosystems are experiencing degradation due to increasing human demand for products and services (Ferreira et al., 2019; Islam et al., 2020; Khan et al., 2021). The degradation is mainly caused by discharges from industrial, mining, agricultural and domestic wastes, which contain among other pollutants, trace metals (Mimba et al., 2018; Chen et al., 2019; Addo-Bediako, 2020; Setia et al., 2021). Although some of these metals are essential as micronutrients, they can be toxic to the environment at high concentrations (Islam et al., 2020). Trace metal pollution has become a global concern in freshwater environments (Zeng et al., 2020), as they are resistant and non-degradable, and at high concentrations can be detrimental to the ecosystem, aquatic biota, and humans (Benzer, 2017; Zhang X. et al., 2017; Xu et al., 2018; Zeng et al., 2019; Addo-Bediako, 2020).

Many recent studies on freshwater ecosystems have reported an increase in pollution by organic and inorganic contaminants (Pandey et al., 2019; Islam et al., 2020; Khan et al., 2020). The pollution is mainly attributed to rapid economic development that has led to unplanned urbanization and the development of industries which are affecting freshwater ecosystems (Proshad et al., 2019, 2020; Namngam et al., 2021). An understanding of the impact of these changes on freshwater ecosystem warrant the study of the spatial distribution of pollutants, such as metals in surface water and sediments.

Besides the anthropogenic threats, climate change is emerging as the greatest threat to the functioning of aquatic ecosystems and biodiversity (IPCC, 2007). Potential climate change is likely to affect the frequency, duration, magnitude, and timing of the weather and climate extremes (Seneviratne et al., 2012). South Africa is a semi-arid region, with a mean annual rainfall of about 500 mm, which is below the world average of about 750 mm and the country has high evaporation rate. Many rivers in the country have seasonal flow with considerably high variability in runoff (Edokpayi et al., 2020; Remilekun et al., 2021). South Africa is projected to experience significant losses of runoff, with some areas being particularly impacted (Nkhonjera, 2017). The expected reduction in rainfall and high temperatures due to climate change would reduce already depleted water resources, contributing to an increasing drought in the country (UNDP, 2020). It is projected that with increasing water demand for mining, agricultural, industrial and domestic activities and poor management policies, together with climate change, many freshwater ecosystems would severely be affected (Addo-Bediako et al., 2021; Remilekun et al., 2021).

Sediments are essential and dynamic component of the river system, and serve as a sink for trace metals (Balzani et al., 2021) and can be released into the water column under changes in certain environmental conditions, such as pH, redox, conductivity, salinity, total dissolved solids, temperature, and turbidity (Chetty and Pillay, 2019). Sediment analysis is very effective to assess the metal contamination of freshwater ecosystems (Dahms et al., 2017).

In the past two decades, the Lower Olifants River has faced rapid urbanization due to increasing mining activities in the area, especially chrome, and platinum. This has also resulted in an increase in human population, putting more pressure on the rivers due to more domestic waste discharged into the rivers. The development in the area has also affected the riparian vegetation which can have consequences on the ecological state of the rivers. Studies on metal contamination in the sediments are crucial in the catchment. Many of the rural communities depend on the rivers in the catchment for drinking water and food (fish), and degradation of these rivers may pose a health risk to the people and their animals. The aim of the study was to assess the pollution status of trace metal (loid)s (As, Co, Cr, Cu, Mn, Ni, Pb, and Zn) in the sediments of four rivers in the Lower Olifants River Basin; the Blyde, Mohlapitsi, Ga-Selati and Steelpoort rivers. The hypothesis of the current study was that the increasing mining, agricultural and other human activities in the area is polluting the rivers. The specific objectives of this study were: 1) to analyse the concentration and spatial distribution of metal(loid)s in river sediments and 2) to evaluate the degree of pollution of metal(loid)s by using the enrichment factor (EF) and geoaccumulation index (I_geo). The results may provide valuable information for the management of the basin and to implement measures to alleviate the impacts of chemical pollution and climate change on the rivers and human health.

Materials and Methods

Study Area

The Lower Olifants sub-catchment stretches from the Drakensberg escarpment through the Kruger National Park to Massingir Dam in Mozambique. The sub-catchment is characterised by mining, agricultural and industrial activities (Heath et al., 2010). Although, the water quality of the Olifants River is negatively affected by human activities (Ballance et al., 2001), the Lower Olifants River receives water of good quality from the Blyde and Mohlapitsi rivers (DWAF, 2004). The climate of the basin is warm to hot sub-tropical, with seasonal rainfall occurring during the summer months (October to March), peaking in January. The amount of rainfall ranges from <600 mm per annum (lowveld) to about 800 mm per annum (highveld). Three sites representing the upstream, midstream and downstream of each of the four rivers were selected for this study (Table 1). The rivers/sites selected were the Blyde River (BL1, BL2, and BL3), Mohlapitsi River (MH1, MH2, and MH3), the Ga-Selati River (SL1, SL2, and SL3), and the Steelpoort River (ST1, ST2, and ST3) as shown in Figure 1.

TABLE 1

TABLE 1. Description of the study sites of the selected four rivers in the Lower Olifants River Basin.

FIGURE 1

FIGURE 1. Map showing the locations of the sampling sites of the four rivers in the Lower Olifants River.

Data Collection

Surface sediment samples were collected at four sampling campaigns during 2018–2019. The samples were collected at a depth of about 5–10 cm using a hand trowel. The hand trowel was washed with a detergent, rinsed, and dried before using it at each site to minimize contamination. At each site, five sub-samples were mixed together, forming a composite sample (Bervoets and Blust, 2003). The samples were placed in 10% nitric acid pre-treated polyethylene ziplock bags, transported to the laboratory and were frozen (−20°C) prior to chemical analysis (UNEP(DEC)/MED, 2006). Sediment samples were analysed for elements at an accredited (ISO 17025) chemical laboratory in Pretoria, South Africa. The samples were put in acid-washed polypropylene pre-weighed vials and dried at 60°C for 24 h. The samples were then sieved through a 2-mm nylon sieve to remove any stones and coarse debris. Then 0.1 g of each sediment sample was digested with 8 ml of 68% nitric acid (HNO₃) and 3 ml of 40% hydrochloric acid (HCl). It was then filtered through a membrane filter and the concentrations of As, Cr, Cu, Fe, Mn, Ni, Pb, and Zn were analysed using inductively coupled plasma optical emission spectrometry (ICP-OES) (Perkin Elmer, Optima 2100 DV). Concentrations of the metals in the sediments were calculated and expressed as mg/kg dry weight. Analytical accuracy was determined using certified standards (De Bruyn Spectroscopic Solutions 500 MUL20-50STD2) and recoveries were within 10% of certified values.

Statistical Analysis

The mean and standard deviation of the metal(loid)s were calculated. Analysis of variance (ANOVA) was performed to determine differences of mean metal(loid) concentrations among sites and rivers. The occurrence of a linear correlation between metal(loid) concentrations was evaluated by Spearman’s correlation coefficient. All statistical analyses were done using Statistica (Version 10).

The enrichment factor (EF): Enrichment factor was used to evaluate the extent of trace metal (loid) contamination in the sediments (Zahra et al., 2014).

Enrichment factor (Barbieri, 2016; Hanif et al., 2016). EF is calculated as:

$\mathrm{EF}=\frac{\left(\raisebox{1ex}{${\mathrm{M}}_{\mathrm{i}}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{S}}_{\mathrm{x}}$}\right.\right)\mathrm{sample}}{\left(\raisebox{1ex}{${\mathrm{M}}_{\mathrm{i}}$}\!\left/ \!\raisebox{-1ex}{${\mathrm{S}}_{\mathrm{x}}$}\right.\right)\mathrm{reference,}}$

where EF stands for the enrichment factor, M_i/S_x sample stands for the ratio of measured value (m/kg) of element i to measured value (mg/kg) of reference element x in the sample, (M_i/S_x) stands for the ratio of background value (mg/kg) of element i to the background value (mg/kg) of reference element x (Brady et al., 2014; Gao et al., 2014).

The average shale values of metal(loid)s were used as background value (Turekian and Wedepohl, 1961). To account for natural trace metal(loid) concentrations, EF is normalized using Al or Fe content. In this study, Fe was selected, as it has been used successfully to normalise trace metal contaminants (Bhuiyan et al., 2010). The EF are classified into 6 groups (Table 2).

TABLE 2

TABLE 2. Classification standard of enrichment factor (EF) and geoaccumulation index (Igeo).

Geo-Accumulation Index (I_geo)

When assessing aquatic toxicity in the sediments, the geoaccumulation index (Igeo) matrix could be applied. The values of the geo-accumulation index were calculated after Muller (1969) by the following equation:

${\mathrm{I}}_{\mathrm{g}\mathrm{e}\mathrm{o}}={\log }_2\left(\raisebox{1ex}{${\mathrm{M}}_{\mathrm{x}}$}\!\left/ \!\raisebox{-1ex}{$1.5{\mathrm{B}}_{\mathrm{n}}$}\right.\right),$

where M_x is the concentration of the examined metal in the sediment, B_n is the geochemical background value of a given metal in the shale (Turekian and Wedepohl, 1961) and the factor 1.5 is used to account for the possible variations in the background values. The I_geo index is grouped into seven classes (0–6) (Table 2).

Results

Distribution of Metal(loid)s in the Sediments

The distribution of metal(loid)s along the four rivers of the Olifants River Basin is shown in Table 3. There were significant differences in the metal (loid)s among the rivers, As (F = 30.09; p < 0.0001), Cu (F = 17.25; p < 0.001), Fe (F = 28.15; p < 0.001), Mn (F = 4.80; p = 0.03), Ni (F = 21.09; p < 0.001), and Zn (F = 5.24; p = 0.02), except Cr (F = 2.78; p = 0.11). The mean metal(loid) concentrations in the sediments were found to vary among the sites; the highest mean concentrations recorded were as follows, As at BL2 (51.0 mg/kg), Cr at ST2 (2252.8 mg/kg), Cu at BL2 (74.0 mg/kg), Fe at STI (177173.8 mg/kg), Mn at MH4 (2581.5 mg/kg), Ni at BL3 (281.7 mg/kg), Pb at MH3 (10.0 mg/kg), and Zn at ST3 (92.0 mg/kg).

TABLE 3

TABLE 3. Mean metal concentrations in the sediments of the four rivers, the average shale values and sediment quality guidelines.

When compared with the average shale values and the sediment quality guidelines, the concentrations of As were below the average shale value at all the sampling sites and rivers, except in the Blyde River (BL1, BL2, and BL3) and the concentrations were above the sediment quality guideline (SQG) at MH1, MH2, BL1, BL2, and BL3. The concentrations of Cr exceeded the average shale values at all the sites and rivers, except at BL1, BL2, SL1, SL2, and SL3, whiles the concentrations were above the SQG at all the sites. The concentrations of Cu were below both the average shale and SQG values at all the sites except at BL1, BL2, and BL3. The concentrations of Fe exceeded the shale value at ST1, ST2, ST3, and MH2. The Mn concentrations were below the average shale value except at BL2, BL3, MH2, ST1, ST2, and ST3. The concentrations of Ni were above the shale value at BL1, BL2, BL3, MH3, SL1, SL2, SL3, ST2, and ST3. The concentrations of Pb and Zn at all sites/rivers were below the average shale and SQG values. The Spearman correlations highlighted a strong positive association between As and Cu; Cr and Mn and Pb; Fe and Mn; Fe and Pb; Fe and Zn; Mn and Pb, Pb and Zn (p < 0.05) (Table 4).

TABLE 4

TABLE 4. Spearman correlation matrix between metal(loid) concentrations of the sediments.

The cluster analysis (CA) was used to characterize the results of the metal(loid)s as shown in Figure 2A. The CA dendrogram is divided into three clusters: cluster 1 consists of only Mn; cluster 2 consists of only Cr, and cluster 3 includes As, Cu, Pb, Zn, and Ni. The CA also separates the Steelpooort River from the rest of the rivers (Figure 2B).

FIGURE 2

FIGURE 2. (A) Cluster analysis of sediment for different metal(loid)s from the Blyde, Mohlapitsi, Ga-Selati, and Steelpoort rivers. (B) Cluster analysis of metal(loid)s in the sediments from different sites of the Blyde, Mohlapitsi, Ga-Selati, and Steelpoort rivers.

Enrichment Factor and Geo-Accumulation Index (Igeo)

The EF values for the metal (loid)s are shown in Figure 3. In the Blyde River, As was moderately to moderately severely enriched at all sites, Cr, Cu, and Mn showed minor enrichment at all the sites, Ni showed moderately enrichment, Pb and Zn showed no enrichment. In the Mohlapitsi River, all the metal(loids) showed no enrichment to minor enrichment, except for Cr which showed severe enrichment and Ni was moderately enriched at MH1. In the Ga-Selati River, all the metal(loid)s showed only up to minor enrichment at all the sites, except Ni which showed moderately enriched at SL1 and SL3 to moderately severe enrichment at SL2. In the Steelpoort River, As, Cu, Mn, Ni, Pb, and Zn showed no enrichment at all sites, however, Cr showed moderately and moderately severe enrichment at ST3 and ST2 respectively.

FIGURE 3

FIGURE 3. Enrichment factors (EF) of metal(loid)s collected from different sites of the four rivers in the Olifants River Basin.

The I_geo index values are shown in Figure 4. In the Blyde River, there was no contamination for all the metal(loid)s, except for As which showed moderately contamination at the three sites, and Ni showed moderately contamination at BL1 and BL3 and strongly contamination at BL2. In the Mohlapitsi River, Cr concentration showed moderately contamination at all the three sites, whiles the rest of metal(loid)s showed no contamination. In the Ga-Selati River, all the elements were in class 0, thus no contamination, except Ni, which showed a moderately contamination at SL2. In the Steelpoort River, Cr concentration showed strongly contamination at ST2 and ST3, Fe and Mn showed moderately contamination at ST2 and ST3, and Ni moderately contamination at ST3.

FIGURE 4

FIGURE 4. Geo-accumulation index (Igeo) of metal(loid)s collected from different sites of the four rivers in the Olifants River Basin.

Discussion

Distribution of Metal(loid)s in the Sediments

The results obtained in the study indicate that trace metal(loid) concentrations in surface sediment of the four rivers were elevated. Generally, the midstream and downstream sites were more polluted compared to the upstream sites of the rivers due to increasing human activities in the midstream and downtream. The spatial trends of the metal(loid)s showed increasing localized concentrations of all the rivers, thus the concentrations were higher close to mining, industrial, agricultural and domestic activities, and gradually decreased away from these point sources. When compared with standard values, most of the concentrations of As, Cr, and Cu exceeded the guideline values across the different rivers (CCME, 2012).

The highest concentrations of As, Cu and Ni were recorded in the Blyde River, especially in the midstream of the river, where there are many agricultural activities, such as commercial citrus and maize farming, which use fertilizers and pesticides (Zhou et al., 2018; Islam et al., 2020; Kumar et al., 2021).

The highest concentrations of Cr, Fe, and Zn were recorded in the Steelpoort River. The high metal concentrations in the Steelpoort River were attributed to various mining activities and smelters in the catchment (Addo-Bediako., 2020). The highest Cr concentration was observed in the midstream and downstream of the river and this might be due to the production and processing of chrome in the area (Crafford and Avenant-Oldewage, 2011). The concentrations recorded at all the sites of the Steelpoort River far exceeded the permissible limit (CCME, 2012). The highest Fe concentration in this river might also be attributed to runoff from chrome mines and smelters in the area. Furthermore, the high concentration of Ni recorded in the Steelpoort River could be due to combustion of fossil fuels especially many mining and construction trucks in the area (Addo-Bediako, 2020). The diversity of mining activities especially platinum and chrome, and metal smelters, and transportation have been reported to contribute to trace metal pollution in the environment (Tytła and Kostecki, 2019; Tan et al., 2021). The highest Zn concentration was recorded at downstream of the Steelpoort River. Sources of Zn in the environment include mining, domestic and industrial runoff, and vehicular emissions. However, the low level of Zn recorded is in an indication that it originated mainly from natural sources (Sojka et al., 2019).

The main source of high Ni concentration in the Ga-Selati might be from agricultural wastes, domestic discharges, urban activities (Li, 2014; Kumar et al., 2020), and combustion of fossil fuels (, Wang et al., 2020; Li et al., 2021). The highest Mn concentration was recorded in the downstream of the Mohalpitsi River and could be attributed to release from organic matter, fertilizers, and fungicides (Khan et al., 2020; Li et al., 2021). The area especially the midstream is characterised by many small scale agricultural activities.

A correlation analysis showed a relationship between the metal(loid)s and highlighted that some of the metal(loid)s in the sediments were positively and significantly correlated with each other. A high correlation among the different metal (loid)s is an indicative of a common source and mutual dependence (Kalita et al., 2019). The dendrogram, generally indicated a close relationship between sites of specific rivers in their response to the metals. The cluster analysis showed the three sites of the Steelpoort River in the same group and all the sites of the Blyde, Mohlapitsi and Ga-Selati rivers to be in one group, with the exception of MH2. The multivariate analysis (i.e., cluster analysis) indicates that those grouped together have common sources of metal contamination (Dalu et al., 2018; Kalita et al., 2019; Zhang G. et al., 2017). It was also observed in the cluster analysis that there were differences in the rivers and sites, with a strong separation between the Steelpoort River and the rest of the rivers. The differences could be attributed to differences in land use activities in the catchments, which might cause variations in metal concentrations. Thus, the cluster separation of these elements suggests a different origin or the current position of the elements in the sediments.

Comparing the results with other related studies (Table 5), the levels of Cu detected in this study in the Blyde River far exceeded levels determined by other studies. The Cr concentration recorded in the Steelpoort river exceeded that of other studies. Copper concentration in the four rivers only exceeded the concentrations from the Strzyza River in Poland (Nawrot et al., 2020), Calore River in Italy (Zuzolo et al., 2017), Nile River in Egypt and Ipojuca in Brazil (Silva et al., 2019). The highest concentration of Fe was recorded in the Steelpoort River and far exceeded the results of the other rivers. The Mn concentrations recorded in this study were lower than the concentration recorded in Tigris River, Turkey (Varol and Sen, 2012). The highest concentration of Ni in this study was from the Blyde River but it was lower than the concentrations recorded in Dongbao River, China (Wu et al., 2016) and Tigris River, Turkey (Varol and Sen, 2012). The highest Pb and Zn concentrations recorded in this study exceeded only the concentrations in Nile River (Omar and Mahmoud, 2017). The differences in the concentrations of metal(loid)s between the sediments in this study and those from international rivers could be attributed to variations in the levels of contamination, regional characteristics, and anthropogenic activities (Fabio et al., 2021).

TABLE 5

TABLE 5. Comparison of metal(loid)s in sediment (mg/kg dw) with other international studies.

The elevated concentrations of Cr, Fe, and Mn in the Steelpoort River is an indication that the aquatic biota and humans depending on the river for drinking water and food (e.g. fish) are at risk of elevated heavy metal contamination. The main activity in the Steelpoort River catchment is mining and could have contributed to the metal pollution in the river (Addo-Bediako, 2020; Emenike et al., 2020).

Enrichment Factor and Geo-Accumulation Index (Igeo)

Generally, the results of the study demonstrated a high degree of metal(loid) contamination in the sediments across sites and rivers, as evidenced by the high EF values of As and Pb in the Blyde River, Cr and Ni in the Mohlapitsi River, Ni in the Ga-Selati River, and Cr, Cu, and Pb in the Steelpoort River. The high EF values of Cr and Ni in almost all the rivers may be due to human activities occurring in the catchment (Duncan et al., 2018). However, the low EF values of Mn despite the high mean concentrations recorded is an indication that it originates mainly from natural sources (Sojka et al., 2019).

The high I_geo index for As, Cr, Ni, and Pb in the rivers reflect increasing human activities in the river catchments. The high I_geo values of Cr, Pb, and Ni showed that some of the sites received a considerable amount of contamination of these metal(loid)s (Bing et al., 2019), this could be due to unregulated mining and agricultural activities occurring in the catchment (Islam et al., 2015).

Future Perspectives

The Lower Olifants River Basin is experiencing degradation due to chemical toxicity from mining, industrial, agricultural, and domestic discharges. In the past two decades, there has been increasing mining operations in the area and has put more pressure on the water resources in the area. It is estimated that more mining operations would be established in the region in the coming years, and will increase the demand for water. Climate change will further stress the system as low rainfall, drought, and high temperatures are projected across the Olifants River Basin (IPCC, 2007; UNDP, 2020). Under climate change, river discharges are expected to become more frequent, and increase accumulation of chemical substances. Low river discharge also means limited dilution of chemical substances and with high temperatures during summer/autumn would elevate metal levels (Iordache et al., 2022). When rainfall occurs, it is predicted to be mainly of torrential rain which may lead to enhance runoff and accelerate leaching resulting in enhanced metal loads (Wijngaard et al., 2017). It is therefore important for organized cross-sectoral measures and research to alleviate the impact of the climate change and metal(loid) pollution in the basin.

Conclusion

The trace metal(loid) concentrations in the sediments of the Blyde, Mohlapitsi, Ga-Selati, and Steelpoort rivers were analyzed and evaluated by various metal pollution indices. The results showed that concentrations of Cr, Ni, and Mn in all the rivers, and As concentration in the Blyde River are of great concern, as they exceeded the average share values, and sediment quality guidelines. The Enrichment factor and geoaccumulation index (Igeo) confirm strong As and Ni contamination in the sediments of the Blyde River, Cr, Mn, and Ni in the Mohlapitsi River, Cr and Ni in the Ga-Selati river and Cr in the Steelpoort River. The high concentrations of these trace metal(loid)s in the sediments of the rivers are mainly associated with the various mining and agricultural activities in the area. Climate change is also likely to increase metal concentrations in sediments of rivers in semi-arid countries like South Africa, where it is predicted to prolong the dry season. It is therefore important that freshwater ecosystems should be given a proper attention when implementing measures to alleviate impacts of climate change.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Author Contributions

AA-B did the collection of data, analysis and write-up.

Funding

The research was supported financially by the Flemish Inter-University Council (VLIR-UOS), Belgium (VLIR/UL).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

I thank the postgraduate students in the Water Laboratory, University of Limpopo for their valuable contributions with the field work.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fenvs.2022.882393/full#supplementary-material

References

Addo-Bediako, A. (2020). Assessment of Heavy Metal Pollution in the Blyde and Steelpoort Rivers of the Olifants River System, South Africa. Pol. J. Environ. Stud. 29 (5), 3023–3029. doi:10.15244/pjoes/112621

CrossRef Full Text | Google Scholar

Addo-Bediako, A., Nukeri, S., and Kekana, M. (2021). Heavy Metal and Metalloid Contamination in the Sediments of the Spekboom River, South Africa. Appl. Water Sci. 11, 133. doi:10.1007/s13201-021-01464-8

CrossRef Full Text | Google Scholar

Balance, A., Hill, L., Roux, D., Silberbauer, M., and Strydom, W. F. (2001). “Crocodile, Sabie-Sand and Olifants River Systems. River Health Programme (RHP),”. WRC Report No.TT 147/01 (Pretoria, South Africa: Water Research Commission).

Google Scholar

Balzani, P., Haubrock, P. J., Russo, F., Kouba, A., Haase, P., Veselý, L., et al. (2021). Combining Metal and Stable Isotope Analyses to Disentangle Contaminant Transfer in a Freshwater Community Dominated by Alien Species. Environ. Pollut. 268, 115781. doi:10.1016/j.envpol.2020.115781

PubMed Abstract | CrossRef Full Text | Google Scholar

Barbieri, M. (2016). The Importance of Enrichment Factor (EF) and Geoaccumulation Index (I_geo) to Evaluate the Soil Contamination. J. Geol. Geophys. 5, 237. doi:10.4172/2381-8719.1000237

CrossRef Full Text | Google Scholar

Benzer, S. (2017). Concentrations of Arsenic and Boron in Water, Sediment and the Tissues of Fish in Emet Stream (Turkey). Bull. Environ. Contam. Toxicol. 98, 805–810. doi:10.1007/s00128-016-1996-z

PubMed Abstract | CrossRef Full Text | Google Scholar

Bervoets, L., and Blust, R. (2003). Metal Concentrations in Water, Sediment and Gudgeon (Gobio gobio) from a Pollution Gradient: Relationship with Fish Condition Factor. Environ. Pollut. 126, 9–19. doi:10.1016/s0269-7491(03)00173-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Bhuiyan, M. A. H., Parvez, L., Islam, M. A., Dampare, S. D., and Susuki, S. (2010). Heavy Metal Pollution of Coal Mine-Affected Agricultural Soils in the Northern Part of Bangladesh. J. Hazard. Mater., 173, 384–392. doi:10.1016/j.jhazmat.2009.08.085

PubMed Abstract | CrossRef Full Text | Google Scholar

Bing, H., Wu, Y., Zhou, J., Sun, H., Wang, X., Zhu, H., et al. (2019). Spatial Variation of Heavy Metal Contamination in the Riparian Sediments After Two-Year Flow Regulation in the Three Gorges Reservoir, China. Sci. Total Environ., 649, 1004–1016. doi:10.1016/j.scitotenv.2018.08.401

PubMed Abstract | CrossRef Full Text | Google Scholar

Brady, J. P., Ayoko, G. A., Martens, W. N., and Goonetilleke, A. (2014). Enrichment, Distribution and Sources of Heavy Metals in the Sediments of Deception Bay, Queensland, Australia. Mar. Pollut. Bull. 81 (1), 248–255. doi:10.1016/j.marpolbul.2014.01.031

PubMed Abstract | CrossRef Full Text | Google Scholar

CCME (Canadian Council of Ministers of the Environment) (2012). Environmental Quality Guidelines: Water Quality Guidelines and Sediment Quality Guidelines for the Protection of Aquatic Life. Canadian Council of Ministers of the Environment.

Google Scholar

Chen, N., Chen, L., Ma, Y., and Chen, A. (2019). Regional Disaster Risk Assessment of China Based on Self-Organizing Map: Clustering, Visualization and Ranking. Int. J. Disaster Risk Reduct. 33, 196–206. doi:10.1016/j.ijdrr.2018.10.005

CrossRef Full Text | Google Scholar

Chetty, S., and Pillay, L. (2019). Assessing the Influence of Human Activities on River Health: a Case for Two South African Rivers with Differing Pollutant Sources. Environ. Monit. Assess. 191, 168. doi:10.1007/s10661-019-7308-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Crafford, D., and Avenant-Oldewage, A. (2011). Bioaccumulation of Non-essential Trace Metals in Tissues and Organs of Clarias gariepinus (Sharptooth Catfish) from the Vaal River System-Strontium, Aluminium, Lead and Nickel. Water sa. 36, 621–626. doi:10.4314/wsa.v36i5.61996

CrossRef Full Text | Google Scholar

Dahms, S., Baker, N. J., and Greenfieldfield, R. (2017). Ecological Risk Assessment of Trace Elements in Sediment: A Case Study from Limpopo, South Africa. Ecotoxicol. Environ. Saf. 135, 106–114. doi:10.1016/j.ecoenv.2016.09.036

PubMed Abstract | CrossRef Full Text | Google Scholar

Dalu, T., Wasserman, R. J., Wu, Q., Froneman, W. P., and Weyl, O. L. F. (2018). River Sediment Metal and Nutrient Variations along an Urban-Agriculture Gradient in an Arid Austral Landscape: Implications for Environmental Health. Environ. Sci. Pollut. Res. 25, 2842–2852. doi:10.1007/s11356-017-0728-1

CrossRef Full Text | Google Scholar

Duncan, A. E., De Vries, N., and Nyarko, K. B. (2018). Assessment of Heavy Metal Pollution in the Sediments of the River Pra and its Tributaries. Water Air Soil Pollut. 229, 272. doi:10.1007/s11270-018-3899-6

PubMed Abstract | CrossRef Full Text | Google Scholar

DWAF (Department of Water Affairs and Forestry, South Africa) (2004). “Olifants Water Management Area: Internal Strategic Perspective. Prepared by GMKS, Tlou and Matji and WMB on Behalf of the Directorate: National Water Resource Planning,”. DWAF Report No: P WMA 04/000/00/0304.

Google Scholar

Edokpayi, J. N., Makungo, R., Mathivha, F., Rivers, N., Volenzo, T., and O. Odiyo, J. (2020). “Influence of Global Climate Change on Water Resources in South Africa: toward an Adaptive Management Approach,” in Water Conservation and Wastewater Treatment in BRICS Nations. Editors P Singh, Y Milshina, K Tian, D Gusain, and JP Bassin, 83–115. doi:10.1016/b978-0-12-818339-7.00005-9

CrossRef Full Text | Google Scholar

Emenike, P. C., Tenebe, I. T., Neris, J. B., Omole, D. O., Afolayan, O., Okeke, C. U., et al. (2020). An Integrated Assessment of Land-Use Change Impact, Seasonal Variation of Pollution Indices and Human Health Risk of Selected Toxic Elements in Sediments of River Atuwara, Nigeria. Environ. Pollut. 265, 114795. doi:10.1016/j.envpol.2020.114795

PubMed Abstract | CrossRef Full Text | Google Scholar

Fabio, F-G., Jose´, P-H., Edwin, G., Jose´, M-N., and Sergi, D. (2021). Heavy Metal Pollution and Toxicity Assessment in Mallorquin Swamp: a Natural Protected Heritage in the Caribbean Sea, Colombia. Mar. Pollut. Bull. 2021, 167. doi:10.1016/j.marpolbul.2021.112271

CrossRef Full Text | Google Scholar

Ferreira, M. D. S., Fontes, M. P. F., Pacheco, A. A., Lima, H. N., and Santos, J. Z. L. (2019). Risk Assessment of Trace Elements Pollution of Manaus Urban Rivers. Sci. Total Environ. 709, 134471. doi:10.1016/j.scitotenv.2019.134471

PubMed Abstract | CrossRef Full Text | Google Scholar

Gao, C., Lin, Q., Bao, K., Zhao, H., Zhang, Z., Xing, W., et al. (2014). Historical Variation and Recent Ecological Risk of Heavy Metals in Wetland Sediments along Wusuli River, Northeast China. Environ. Earth Sci. 72, 4345–4355. doi:10.1007/s12665-014-3334-2

CrossRef Full Text | Google Scholar

Hanif, N., Eqani, S. A. M. A. S., Ali, S. M., Cincinelli, A., Ali, N., Katsoyiannis, I. A., et al. (2016). Geo-accumulation and Enrichment of Trace Metals in Sediments and Their Associated Risks in the Chenab River, Pakistan. J. Geochem. Explor. 165, 62–70. doi:10.1016/j.gexplo.2016.02.006

CrossRef Full Text | Google Scholar

Heath, R., Coleman, T., and Engelbrecht, J. (2010). “Water Quality Overview and Literature Review of the Ecology of the Olifants River,”. WRC Report No.TT452/10 (Pretoria, South Africa: Water Research Commission).

Google Scholar

Iordache, A. M., Nechita, C., Voica, C., Pluháček, T., and Schug, K. A. (2022). Climate Change Extreme and Seasonal Toxic Metal Occurrence in Romanian Freshwaters in the Last Two Decades-Case Study and Critical Review. npj Clean. Water 5, 2. doi:10.1038/s41545-021-00147-w

CrossRef Full Text | Google Scholar

IPCC (2007). Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Editors M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden, and C. E. Hanson (Cambridge, UK: Cambridge University Press), 976.

Google Scholar

Islam, A. R. M. T., Islam, H. M. T., Mia, M. U., Khan, R., Habib, M. A., Bodrud-Doza, M., et al. (2020). Co-distribution, Possible Origins, Status and Potential Health Risk of Trace Elements in Surface Water Sources from Six Major River Basins, Bangladesh. Chemosphere 249, 126180. doi:10.1016/j.chemosphere.2020.126180

PubMed Abstract | CrossRef Full Text | Google Scholar

Islam, M. S., Ahmed, M. K., Raknuzzaman, M., Habibullah -Al- Mamun, M., and Islam, M. K. (2015). Heavy Metal Pollution in Surface Water and Sediment: a Preliminary Assessment of an Urban River in a Developing Country. Ecol. Indic. 48, 282–291. doi:10.1016/j.ecolind.2014.08.016

CrossRef Full Text | Google Scholar

Kalita, S., Sarma, H. P., and Devi, A. (2019). Sediment Characterisation and Spatial Distribution of Heavy Metals in the Sediment of a Tropical Freshwater Wetland of Indo-Burmese Province. Environ. Pollut. 250, 969–980. doi:10.1016/j.envpol.2019.04.112

PubMed Abstract | CrossRef Full Text | Google Scholar

Khan, R., Islam, H. M. T., and Islam, A. R. M. T. (2021). Mechanism of Elevated Radioactivity in a Freshwater Basin: Radiochemical Characterization, Provenance and Associated Hazards. Chemosphere 264, 128459. doi:10.1016/j.chemosphere.2020.128459

PubMed Abstract | CrossRef Full Text | Google Scholar

Khan, R., Islam, M. S., Tareq, A. R. M., Naher, K., Islam, A. R. M. T., Habib, M. A., et al. (2020). Elemental and Polycyclic Aromatic Hydrocarbons Distributions in the Sediments of an Urban River: Influence of Anthropogenic Runoffs. Environ. Nanotechnol. Monit. Manag. 14, 100318. doi:10.1016/j.enmm.2020.100318

CrossRef Full Text | Google Scholar

Kumar, S., Islam, A. R. M. T., Hasanuzzaman, M., Salam, R., Khan, R., and Islam, M. S. (2021). Preliminary Assessment of Heavy Metals in Surface Water and Sediment in Nakuvadra-Rakiraki River, Fiji Using Indexical and Chemometric Approaches. J. Environ. Manag. 298, 113517. doi:10.1016/j.jenvman.2021.113517

CrossRef Full Text | Google Scholar

Kumar, V., Sharma, A., Pandita, S., Bhardwaj, R., Thukral, A. K., and Cerda, A. (2020). A Review of Ecological Risk Assessment and Associated Health Risks with Heavy Metals in Sediment from India. Int. J. Sediment. Res. 35, 516e526. doi:10.1016/j.ijsrc.2020.03.012

CrossRef Full Text | Google Scholar

Li, F., Yu, X., Lv, J., Wu, Q., and An, Y. (2021). Assessment of Heavy Metal Pollution in Surface Sediments of the Chishui River Basin, China. PLoS ONE 17 (2), e0260901. doi:10.1371/journal.pone.0260901

CrossRef Full Text | Google Scholar

Li, J. (2014). Risk Assessment of Heavy Metals in Surface Sediments from the Yanghe River, China. Ijerph 11, 12441–12453. doi:10.3390/ijerph111212441

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, C., Yin, J., Hu, L., and Zhang, B. (2020). Spatial Distribution of Heavy Metals and Associated Risks in Sediment of the Urban River Flowing into the Pearl River Estuary, China. Arch. Environ. Contam. Toxicol. 78 (4), 622–630. doi:10.1007/s00244-020-00718-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, D., Wang, J., Yu, H., Gao, H., and Xu, W. (2021). Evaluating Ecological Risks and Tracking Potential Factors Influencing Heavy Metals in Sediments in an Urban River. Environ. Sci. Eur. 33, 42. doi:10.1186/s12302-021-00487-x

CrossRef Full Text | Google Scholar

Mimba, M. E., Ohba, T., Nguemhe Fils, S. C., Nforba, M. T., Numanami, N., Bafon, T. G., et al. (2018). Regional Geochemical Baseline Concentration of Potentially Toxic Trace Metals in the Mineralized Lom Basin, East Cameroon: a Tool for Contamination Assessment. Geochem. Trans. 19, 11. doi:10.1186/s12932-018-0056-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Muller, G. (1969). Index of Geo-Accumulation in Sediments of the Rhine River. GeoJournal 2, 108–118.

Google Scholar

Namngam, N., Xue, W., Liu, X., Kootattep, T., Shrestha, R. P., Wattayakorn, G., et al. (2021). Sedimentary Metals in Developing Tropical Watersheds in Relation to Their Urbanization Intensities. J. Environ. Manag. 278, 111521. doi:10.1016/j.jenvman.2020.111521

PubMed Abstract | CrossRef Full Text | Google Scholar

Nawrot, N., Wojciechowska, E., Matej-Łukowicz, K., Walkusz-Miotk, J., and Pazdro, K. (2020). Spatial and Vertical Distribution Analysis of Heavy Metals in Urban Retention Tanks Sediments: a Case Study of Strzyza Stream. Environ. Geochem. Health 42, 1469–1485. doi:10.1007/s10653-019-00439-8

PubMed Abstract | CrossRef Full Text | Google Scholar

Nkhonjera, G. K. (2017). Understanding the Impact of Climate Change on the Dwindling Water Resources of South Africa, Focusing Mainly on Olifants River Basin: A Review. Environ. Sci. Policy 71, 19–29. doi:10.1016/j.envsci.2017.02.004

CrossRef Full Text | Google Scholar

Omar, W. A., and Mahmoud, H. M. (2017). Risk Assessment of Polychlorinated Biphenyls (PCBs) and Trace Metals in River Nile up- and Downstream of a Densely Populated Area. Environ. Geochem. Health 39 (1), 125–137. doi:10.1007/s10653-016-9814-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Pandey, L. K., Park, J., Son, D. H., Kim, W., Islam, M. S., Choi, S., et al. (2019). Assessment of Metal Contamination in Water and Sediments from Major Rivers in South Korea from 2008 to 2015. Sci. Total Environ. 651, 323–333. doi:10.1016/j.scitotenv.2018.09.057

PubMed Abstract | CrossRef Full Text | Google Scholar

Proshad, R., Islam, S., Tusher, T. R., Zhang, D., Khadka, S., Gao, J., et al. (2020). Appraisal of Heavy Metal Toxicity in Surface Water with Human Health Risk by a Novel Approach: a Study on an Urban River in Vicinity to Industrial Areas of Bangladesh. Toxin Rev. 40, 803–819. doi:10.1080/15569543.2020.1780615

CrossRef Full Text | Google Scholar

Proshad, R., Kormoker, T., and Islam, S. (2019). Distribution, Source Identification, Ecological and Health Risks of Heavy Metals in Surface Sediments of the Rupsa River, Bangladesh. Toxin Rev. 40, 77–101. doi:10.1080/15569543.2018.1564143

CrossRef Full Text | Google Scholar

Remilekun, A. T., Thando, N., Nerhene, D., and Archer, E. (2021). Integrated Assessment of the Influence of Climate Change on Current and Future Intra-annual Water Availability in the Vaal River Catchment. J. Water Clim. Change 12 (2), 533–551. doi:10.2166/wcc.2020.269

CrossRef Full Text | Google Scholar

Seneviratne, S. I., Nicholls, N., Easterling, D., and Goodess, C. M. (2012). “Changes in Climate Extremes and Their Impacts on the Natural Physical Environment,” in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Editor C.B. ETC Field (Cambridge, UK, and New York, NY, USA: Cambridge University Press), 109–230.

Google Scholar

Setia, R., Dhaliwal, S. S., Kumar, V., Singh, R., Dhir, N., Kukal, S. S., et al. (2021). Assessment of Metal Contamination in Sediments of a Perennial River in India Using Pollution Indices and Multivariate Statistics. Arab. J. Geosci. 14, 2190. doi:10.1007/s12517-021-08524-y

CrossRef Full Text | Google Scholar

Silva, Y. J. A. B. d., Cantalice, J. R. B., Singh, V. P., Nascimento, C. W. A. d., Wilcox, B. P., and Silva, Y. J. A. B. d. (2019). Heavy Metal Concentrations and Ecological Risk Assessment of the Suspended Sediments of a Multi-Contaminated Brazilian Watershed. Acta Sci. Agron. 41, 42620. doi:10.4025/actasciagron.v41i1.42620

CrossRef Full Text | Google Scholar

Sojka, M., Jaskuta, J., and Siepak, M. (2019). Heavy Metals in Bottom Sediments of Reservoirs in the Lowland Area of Western Poland: Concentrations, Distribution, Sources and Ecological Risk. Water 11, 56. doi:10.3390/w11010056

CrossRef Full Text | Google Scholar

Tan, L., Yang, B., Xue, Z., and Wang, Z. (2021). Assessing Heavy Metal Contamination Risk in Soil and Water in the Core Water Source Area of the Middle Route of the South-To-North Water Diversion Project, China. Land 10, 934. doi:10.3390/land10090934

CrossRef Full Text | Google Scholar

Turekian, K. K., and Wedepohl, K. H. (1961). Distribution of the Elements in Some Major Units of the Earth's Crust. Geol. Soc. Am. Bull. 72, 175–192. doi:10.1130/0016-7606(1961)72[175:doteis]2.0.co;2

CrossRef Full Text | Google Scholar

Tytła, M., and Kostecki, M. (2019). Ecological Risk Assessment of Metals and Metalloid in Bottom Sediments of Water Reservoir Located in the Key Anthropogenic “Hot Spot” Area (Poland). Environ. Earth Sci. 78, 179. doi:10.1007/s12665-019-8146-y

CrossRef Full Text | Google Scholar

UNDP (2020). Climate Change Adaptation. South Africa. Available at: https://www.adaptation-undp.org/explore/africa/south-africa (Accessed: 11 2, 2022).

Google Scholar

UNEP(DEC)/MED (2006). Methods for Sediment Sampling and Analysis. Palermo (Sicily), Italy. WG.282/Inf.5/Rev.1.

Google Scholar

Varol, M., and Şen, B. (2012). Assessment of Nutrient and Heavy Metal Contamination in Surface Water and Sediments of the Upper Tigris River, Turkey. Catena 92, 1–10. doi:10.1016/j.catena.2011.11.011

CrossRef Full Text | Google Scholar

Wang, Z., Xiao, J., Wang, L., Liang, T., Guo, Q., Guan, Y., et al. (2020). Elucidating the Differentiation of Soil Heavy Metals under Different Land Uses with Geographically Weighted Regression and Self-Organizing Map. Environ. Pollut. 260, 114065. doi:10.1016/j.envpol.2020.114065

PubMed Abstract | CrossRef Full Text | Google Scholar

Wijngaard, R. R., van der Perk, M., van der Grift, B., de Nijs, T. C. M., and Bierkens, M. F. P. (2017). The Impact of Climate Change on Metal Transport in a Lowland Catchment. Water Air Soil Pollut. 228, 107. doi:10.1007/s11270-017-3261-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Wu, Q., Zhou, H., Tam, N. F. Y., Tian, Y., Tan, Y., Zhou, S., et al. (2016). Contamination, Toxicity and Speciation of Heavy Metals in an Industrialized Urban River: Implications for the Dispersal of Heavy Metals. Mar. Pollut. Bull. 104, 153–161. doi:10.1016/j.marpolbul.2016.01.043

PubMed Abstract | CrossRef Full Text | Google Scholar

Xu, J., Chen, Y., Zheng, L., Liu, B., Liu, J., and Wang, X. (2018). Assessment of Heavy Metal Pollution in the Sediment of the Main Tributaries of Dongting Lake, China. Water 1 (1060), 1–16. doi:10.3390/w10081060

CrossRef Full Text | Google Scholar

Zahra, A., Hashmi, M. Z., Malik, R. N., and Ahmed, Z. (2014). Enrichment and Geo-Accumulation of Heavy Metals and Risk Assessment of Sediments of the Kurang Nallah-Feeding Tributary of the Rawal Lake Reservoir, Pakistan. Sci. Total Environ. 470-471, 925–933. doi:10.1016/j.scitotenv.2013.10.017

PubMed Abstract | CrossRef Full Text | Google Scholar

Zeng, J., Han, G., Wu, Q., and Tang, Y. (2019). Geochemical Characteristics of Dissolved Heavy Metals in Zhujiang River, Southwest China: Spatial-Temporal Distribution, Source, Export Flux Estimation, and a Water Quality Assessmentflux Estimation, and a Water Quality Assessment. PeerJ 7 (11), e6578. doi:10.7717/peerj.6578

PubMed Abstract | CrossRef Full Text | Google Scholar

Zeng, J., Han, G., and Yang, K. (2020). Assessment and Sources of Heavy Metals in Suspended Particulate Matter in a Tropical Catchment, Northeast Thailand. J. Clean. Prod. 265, 121898. doi:10.1016/j.jclepro.2020.121898

CrossRef Full Text | Google Scholar

Zhang, G., Bai, J., Zhao, Q., Jia, J., and Wen, X. (2017). Heavy Metals Pollution in Soil Profiles from Seasonal-Flooding Riparian Wetlands in a Chinese Delta: Levels, Distributions and Toxic Risks. Phys. Chem. Earth, Parts A/B/C 97, 54–61. doi:10.1016/j.pce.2016.11.004

CrossRef Full Text | Google Scholar

Zhang, X., Li, Z., Takeuchi, N., Wang, F., Wang, S., You, X., et al. (2017). Heavy Metal-Polluted Aerosols Collected at a Rural Site, Northwest China. J. Earth Sci. 28, 535–544. doi:10.1007/s12583-017-0728-6

CrossRef Full Text | Google Scholar

Zhou, Z., Chen, Z., Pan, H., Sun, B., Zeng, D., He, L., et al. (2018). Cadmium Contamination in Soils and Crops in Four Mining Areas, China. J. Geochem. Explor. 192, 72–84. doi:10.1016/j.gexplo.2018.06.003

CrossRef Full Text | Google Scholar

Zuzolo, D., Cicchella, D., Catani, V., Giaccio, L., Guagliardi, I., Esposito, L., et al. (2017). Assessment of Potentially Harmful Elements Pollution in the Calore River Basin (Southern Italy). Environ. Geochem. Health 39, 531–548. doi:10.1007/s10653-016-9832-2

PubMed Abstract | CrossRef Full Text | Google Scholar