Physical and chemical characteristics of suspended sediment in plain river network

doi:10.21203/rs.3.rs-1427602/v1

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Physical and chemical characteristics of suspended sediment in plain river network

https://doi.org/10.21203/rs.3.rs-1427602/v1

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The suspended movement of sediment in the plain river network is a major part of the river's sand transport, and the associated movement of suspended sand particles also influences the associated movement of pollutants in the water column. This paper selects plain river network and lakeside river network as the research area: In this paper, a plain river network and a lakeside river network are selected as the study area: the flow velocity zones are divided; the particle characteristics (geometric mean particle size GD, roundness RO, roughness FD) of the different flow velocity zones are compared; the influence of the flow velocity characteristics of the river network on the physical characteristics and enrichment capacity of suspended sand particles is assessed; the differences in elemental species and contents between different flow velocity waters are compared; the influence of the physical and chemical characteristics on the enrichment capacity of particulate heavy metals Ni is assessed. The results show that (1) The highest grain GD (5.77), roundness (1.32) and roughness (1.080) were found in the strong flow area of the Liangxi River. There was little difference in particle roughness between flow zones. (2) The average percentage content of the characteristic elements in the different flow velocity regions is generally consistent from highest to lowest, with Mg being the characteristic element with the highest average percentage content in each region. (3) The GD, FD, RO of suspended sand particles are independent of TN, TP, V, SSC and are positively correlated with flow velocity, with the particle size larger and more spherical in shape at high flow velocities in the lakeside network. (4) The enrichment factor AE = aF1(GD, RO, FD) was used to better characterize the sorption capacity of suspended sand particles for Ni than the GD factor alone, with the highest Ni sorption by suspended sand particles in the slow-flowing plain river network (EF = 3.65; AE = 4.74).

Particulate Matter

Lakeside River Network

Flow Zones

Enrichment Capacity

Elemental Characteristics

Changes in river overhangs and streambed sediments have environmental, ecological and social significance (Yang et al., 2018). Riverine sediments are becoming a global concern due to their important role in fluvial geomorphology, biogeochemistry, engineering and land-sea interactions (Dai et al., 2009). Suspended sediment is a natural part of river systems and plays an important role in constructing landscapes, creating ecological habitats and transporting nutrients. It is also a common management problem, with changes in sediment quantity and quality negatively affecting ecological communities, increasing flood hazards and shortening the life span of infrastructure (Mohammadi et al., 2021). In addition, the importance of suspended sediment in rivers can be attributed to its impact on water system quality and, more importantly, on pollution control (Martinez et al., 2009). Appropriate management strategies by quantifying SS transport link these transport dynamics to in-channel and wider catchment drivers in order to accurately predict SS transport on management-relevant time scales (Garcia-Ruiz et al., 2015). The stochastic nature of sediment transport and the non-linear nature of sediment transport variables need to be considered in the prediction process (Safari et al., 2019). Sediment in suspended motion in the plain river network is a major component of river sand transport, and suspended sand particulate matter undergoes correlated motion while also influencing the correlated motion of pollutants in the water column. The study of suspended sediment in plain river network is always a hot issue.

Current research on sediment particles has focused on the variation in the composition of suspended sand particles, such as the fractal characteristics of suspended sediment particle composition (Zhao et al., 2010). The effect of porous media size distribution on the transport and deposition of polydisperse suspended particles at different flow rates (Ahfir et al., 2017). The particle size characteristics of suspended sediment in water basins are closely influenced by seasonal alternations in precipitation, wind and water action, and by the nature of surface materials (Xu, 2000). Coupling effects of ionic strength, particle size and flow rate on the migration and deposition of suspended particles (SP) in saturated sand (Bennacer et al., 2017). To quantify suspended sediment in medium and large sand bed rivers, analyze the different dual-mode particle size distributions, washing load and suspended sand ratio, and water level of the river, as well as the related effects of human activities on the river (Ahfir et al., 2017; Jehanzaib et al., 2020). Some scholars have separated river suspended sediments into different particle sizes to examine the distribution of radioactive elements with particle size information (Kondolf et al., 2014). A sediment proof study was conducted in Chinese waters using framework petrography, heavy mineral and grain size analysis (Wang et al., 2015). Current studies on sediment particle morphology mostly focus on single rivers, investigating the particle size driven environmental impacts for a particular river, or investigating the patterns of physical transport and microscopic sorption of several particle shapes in a river, investigating the particle size distribution and heavy metal concentrations in surface sediments of river basin streams and lakes, and using statistical and geochemical methods to determine their sources (Wang et al., 2015). The physical and chemical properties of suspended sand particles have an important influence on the transport of energy and the adsorption, migration and transformation of pollutants in the river network, and further research on them in the plain river network has important theoretical reference value and practical application significance for estimating the environmental impact of pollutants (Tiyasha et al., 2020).

The river network is an important part of the city and its important value is reflected in a number of ways: developing irrigation, providing water for industry and drinking water sources, providing an environment for the growth of aquatic plants and animals, and improving the regional ecological environment (Park et al., 2022; Qingming et al., 2022; Zhang et al., 2020). In this paper, the following four aspects of research are proposed: (1) To classify the flow velocity zones of the plain river network and the coastal lake network; (2) To compare the physical particle characteristics (geometric mean particle size GD, roundness RO, roughness FD) and chemical characteristics of the different flow velocity zones of the plain river network and the coastal lake network; (3) To compare the differences in elemental species and contents between different flow velocities. (4) To evaluate the influence of river network velocity characteristics on the physical and chemical properties and enrichment capacity of suspended sand particles; (5) To combine various influencing factors to fit equations to characterize the sorption capacity of suspended sand particles for heavy metals.

2.1 Survey Region

Located in the lower reaches of the Lake Tai basin, the Lake Tai is the third largest freshwater lake in China, with a catchment area of 36,500 km² and a surface area of 2,338.1 km². It plays an important role in flood control, water supply and fisheries, and since the rapid industrial and economic development around it, the lake network has become heavily polluted.

In this paper, suspended sand particles in the water environment of the river network located in the eastern part of Meiliang Bay in the Taihu Lake basin, within the Lihu New Town area of Binhu District, Wuxi City, were studied. Wuxi Binhu District is bordered by lakes and rivers, with a dense network of internal rivers, forming a pattern of connected river and lake systems, referred to as the Binhu River Network. The river network reaches Caowangjing in the south, Liangxi river in the north, Wuli Lake in the west and Jinghang Canal in the east. The main river channels are Jinghang Canal, Liangxi River, Caowangjing and Cangli Port. The average suspended matter concentration was 53.15 mg/L and the average velocity was 0.204 m/s. The fluctuation range of heavy metal concentration varies greatly with season, and gradually decreases in dry season, normal season and wet season. The concentration of heavy metals in overlying water of lakeside river network is relatively small in wet season, which is lower than that in normal season and dry season.

2.2 Sample collection and determination

Samples for this survey were collected in situ in November 2019 at 28 points 0.5m from the water surface in the Lake Shore network area using YH-S7 to monitor the flow velocity of the water body, and three representative points in different flow areas were selected for analysis. The sample was stored for experimental treatment. 500-1000ml of the sample was pumped and filtered by Brucellofer funnel (Shan et al., 2022). The filter membrane was acetate fiber membrane, and 0.45µm was filtered. After filtration, the membrane was dried to a constant weight (DeLaune et al., 2016), and the larger particles and impurities were screened out with 150µm. The contents under the sieve were encapsulated with tin foil paper and put into sealing bags, and stored for testing. The samples to be tested were sent to modern Analysis Center of Nanjing University for SEM-EDS detection. SEM images of suspended particles were obtained by taking 250mg samples and using S-3400N scanning electron microscope. The types of suspended sand elements were detected and quantitatively analyzed by ex-250 energy spectrometer attached to scanning electron microscope. The Myratek portable suspended matter /TSS meter was used to average the results of multiple vertical planes successively collected along the cross section of the monitoring station to obtain the suspended sediment concentration of each monitoring point (Allison et al., 2012). 1 g of dried suspended sand was dissolved with HCl, HNO3, HClO4, and HF under high temperature and pressure, and then the Ni content in the suspended sand was determined by inductively coupled plasma mass spectrometry (ICP-MS).

In this study, two-dimensional suspended sand graininess analysis was carried out using image processing software Image Pro Plus (IPP) for SEM images of different flow velocity zones within the Lake Shore network. Image-pro plus (IPP) is a top-notch 2D and 3D image analysis software developed by Media Cybernetics, which combines image acquisition, processing and analysis functions for a wide range of applications in fluorescence imaging, quality control, materials imaging and many other scientific, medical and industrial applications (Yu et al., 2013). The software is not only powerful in image processing and analysis, but also has a wealth of measurement capabilities (Zhang et al., 2015). To ensure measurement accuracy and avoid errors, ten electron microscope photographs of each point at different angles and magnifications were selected for analysis (Chen et al., 2022; Yang and Liu, 2020). Manual analysis of particle morphology, avoiding the influence of non-suspended particles such as algae and microplastics, averaging the same particle three times to avoid errors caused by manual outlining, and achieving accurate measurements of the projected area (A), profile perimeter (P), geometric mean particle size (GD), roundness (RO) and roughness (FD).

2.3 Statistical analysis

The descriptive statistical analysis method arithmetic mean (AVG) was used to quantitatively assess the morphological characteristics of the suspended sand particles (Zhou et al., 2022), the standard deviation (S.D) was used to measure the inhomogeneity of the particle morphology at each point, and the uneven level (UEL) was used to express the inhomogeneity of the particle morphology in each area.

$$uneven level=\frac{1}{n}\sum _{i=1}^{n}\left|\frac{p-P}{P}\right|$$

In the formula: p is the mean value of a morphological parameter at a point in the plain river network; P is the mean value of a morphological parameter within the waters of the plain river network; n is the number of points in the study area.

3.1 Differences in physical characteristics

In this paper, the morphological characteristics of suspended sand particles are compared in terms of both particle size and shape, and the geometric mean grain size (GD) is used to measure the suspended sand grain size. Fewer materials are deposited in the faster flowing waters of the plain river network, and the water column is dominated by materials with large particles, and the larger particles are more gravitational and less likely to be carried along with the flow of water. Conversely, in the slower flowing waters of the plain river network, it is difficult for the river to carry small particles to flow because of the slower flow and the relatively high amount of sedimentary material. Therefore, on the whole, the AVGGD in the slow flow area (5.15µm) is smaller than the AVGGD in the flat flow area (5.56µm) and smaller than the AVGGD in the strong flow area (5.77µm); the S.DGD of the particle population ranges from 5.1 to 6.1, and the corresponding S.D values are smaller at the points with smaller GD in the lake network, i.e. the particle size is relatively concentrated and uniform. For example, the smallest GD value at the slow-flowing area of the river network is 3.95 µm at the Lu Dian Qiao Bin, and the corresponding S.D value is 4.91.

Roundness (RO) and roughness (FD) were used to measure the shape characteristics of the suspended sand particles. UELRO between 0.15 and 0.21. The FD values of the suspended sand particle population ranged from 1.077 to 1.080, with small differences in FD values within each flow velocity zone, and the AVGFD in the slow flow velocity zone (1.078) was smaller than the AVGFD in the advection velocity zone (1.079) and smaller than the AVGFD in the strong flow velocity zone (1.080), the S.DFD of the particle population ranged from 0.017 to 0.020, and the UELFD between points within each zone ranged from 0.001 ~ 0.003.

The K-S significance tests for GD, RO, FD in each flow zone of the riverine network were all below 0.001, so the geospatial variability of GD, RO, FD was highly significant. According to the statistical analysis of particle shape, in the waterfront river network, the heterogeneity of physical properties within a point is S.DFD < S.DRO < S.DGD; the heterogeneity of physical properties between points is also UELFD < UELRO < UELGD; combined with the results of the inter-regional variability analysis, it is clear that with the refinement of the evaluation of the physical properties of particles from GD, RO to FD, the variation of particle morphological properties The variation between regions, although still different, tends to be the same overall.

3.2 Differences in chemical properties

From SEM-EDS analysis, it can be seen that the suspended sand particles in each sample within the river network of the shoreline contain the four basic elements of C, O, Al and Si, and the proportion of the four basic elements of C, O, Al and Si in each point is higher than 95%. The geographical and spatial differences make the characteristic elements different in different areas of the lakeside river network. The abundance of the slow-flowing and strong-flowing areas of the river network is relatively similar, with some points containing the characteristic elements Mg, Fe and Na, while the abundance of the flat-flowing areas is relatively high, with some points containing the characteristic elements Mg, Fe, Na and K. In general, there is one more element species in flat velocity zone than in slow velocity zone and strong velocity zone. The K-S test for differences in the elemental content of suspended sand particles between the flow velocity zones showed that the elemental differences between the strong, flat and slow flow velocity zones were all less than 0.05, so the elements in the three flow velocity zones were different and highly significant.

There are significant differences in the elemental species within the zones, with the basic elements C, O, Al and Si being present within the different flow rates. In the strong flow zone, both Hongqiao and Liqiao of the Liangxi River contain the special elements Mg, and Qingqi Bridge of the Liangxi River contains the special elements Mg, Fe and Na; in the flat flow zone, Caowangjing Dongjiang Bridge contains only the basic elements at the point, and Liangdong Bridge and Caowangjing Dongjiang Bridge of the Panbu Bridge contain the special elements Mg, Fe, Na and K in addition to the basic elements. In the slow flow zone, the Rao Xiu Bridge site at Lu Dian Qiao Bang contains only basic elements, while the Wenge and Han Cui Bridge sites at Lu Dian Qiao Bang contain Mg, Fe and Na special elements in addition to basic elements. The points containing fewer elements are all located at the connection of lakes and rivers, while the points containing more specific elements are mostly located in the middle of the river network, and these differences in location lead to large differences in element types between points.

The K-S test of elemental content within the regions shows a large variation in elemental content within the three flow velocity regions. The highest abundance and the highest content of characteristic elements were found in the flat velocity zone, and the average percentage content of characteristic elements were Mg (0.25%), Na (0.15%), Fe (0.14%) and K (0.13%). The average percentages of the characteristic elements in the slow-flowing zone are Mg (0.17%), Na (0.07%) and Fe (0.05%) in descending order, while the average percentages of the characteristic elements in the strong-flowing zone are Mg (0.32%), Na (0.08%) and Fe (0.05%) in descending order. The average percentages of the characteristic elements in the different flow velocity zones are in the same order from highest to lowest, with M being the characteristic element with the highest average percentage content in each zone.

Figure 4 Distribution of elemental content of suspended sediment (a) to (c) average content of elemental mass fraction (W%) and elemental percentage (A%) in the three flow regions (d) basic elemental percentage at the point (e) characteristic elemental percentage at the point.

3.3 Reason for variance

In this paper, the reasons for the spatial differences of suspended sand particles and elements were analyzed from hydrology and water quality conditions and characteristics of eroded soil. Hydrological water quality conditions are the main reason for the difference in suspended sand particle morphology. The parameters related to hydrological water quality conditions include total nitrogen (TN), total phosphorus (TP), flow velocity (V) and suspended particle concentration (SSC). The Pearson correlation test was conducted between the parameters related to hydrological and water quality conditions and the morphological parameters of suspended sand particles (GD, FD, RO), and the test results showed that the GD, FD, RO of suspended sand particles were positively correlated with the flow velocity, in which the FD of suspended sand particles was significantly positively correlated with the flow velocity. The GD, FD and RO of suspended sand particles were not correlated with TN, TP, V and SSC. This means that the particle population is larger and more spherical in shape at high flow rates in the waters of the lakeside network.

Particle size is one of the most important factors affecting the content of metallic elements in the particulate state (Vandecasteele et al., 2002), and Al is the most abundant metallic element in the earth's crust. It has been shown that the content of Al in particulate matter increases linearly with decreasing particle size, therefore the content of Al in particulate matter can reflect the size of the particle size (Hill and Aplin, 2001). The influence of particle size effects on the elemental content of metals in the particulate state was investigated in the water system of the Lake Shore network by studying the correlation between the elemental content of Al contained in the particulate matter and the content of the remaining metal elements. The results show that the elemental content of Al shows a strong correlation with the elemental content of Mg and Si.

As soil is an important source of suspended sand in water bodies, the influence of eroded soil properties on the elemental composition of suspended sand particles is considered here (Du et al., 2022). In terms of soil particle size, the lowest gravel content was found in the estuary of the flat-flow velocity zone and the highest in the estuary of the slow-flow velocity zone; the difference in gravel content between the two was four to eight times, which was a significant difference. The gravel content in the study area ranged from 571.1 to 650.5 g/kg, all of which were greater than 500 g/kg, and the gravel content in the estuary of each flow velocity zone was slightly higher than that in the near-shore sites, and the particle size of the soil was larger. The sand and clay content in the estuaries of the low-flow zones are comparable, both being about 110 g/kg, while the sand content in the estuaries of the flat-flow zones is slightly lower than the clay content, and the difference in clay content between the low-flow and flat-flow zones is significant, making the flat-flow zones more abundant than the slow-flow and strong-flow zones, and having special elements K.

3.4 Heavy metal adsorption capacity

Particulate matter is the main carrier of pollutant diffusion in the water column, the reasons for this phenomenon include the strong sorption of heavy metals and nutrients. The sorption capacity of suspended sand particles for pollutants is not only influenced by the physical characteristics of the particles (particle size, etc.) and the chemical environment of the water column (ph, salinity, organic matter, etc.), but the ability of suspended sand particles to sorb Zn and Ni heavy metals also has a significant positive correlation with the particle Al content (R₂ > 0.69), i.e. the elemental characteristics of suspended sand particles are related to the sorption capacity of Zn and Ni.

Heavy metals present in the water column as ions are readily adsorbed, complexed or co-precipitated by sediments or particulate matter suspended in the water column. In this paper, the influence of the two-dimensional morphology and elemental properties of suspended sand particles on the enrichment capacity of heavy metals is explored using Ni as an example.

Metal enrichment factors (EFs) are often used to help assess whether metals are enriched in natural concentrations. The calculation of EFs usually involves normalizing metal concentrations to Fe or Al. Al was chosen for geochemical normalization in this study because it has low yield variability, is considered a clastic component of sediments, and is the most frequently used element in coastal and estuarine environments (Kersten and Smedes, 2002; Maanan et al., 2015). Normalization of conserved elements explains the diagenetic and sedimentary inputs of elements of interest, enhancing the prediction of anthropogenic contamination by enrichment factors (Duodu et al., 2016).

Studies have shown that the sorption capacity of heavy metals is related to the particle size, specific surface area and surface roughness of the particles. In previous studies, only the particle size of the particulate matter was considered, and the smaller the particle size, the stronger the heavy metal adsorption capacity. This research approach approximates the particulate matter as a smooth sphere for analysis, ignoring the influence of factors such as the surface roughness of the particulate matter on the adsorption capacity. In this study, the particle size, roundness and roughness are taken into account to fit the shape function of the particles, thus proposing a comprehensive shape function model that affects the Ni enrichment capacity.

SP = F₁(GD,RO,FD)=k₁RO + k₂FD + k₃/GD + k₄ (3)

In the formula: SP is the shape factor; k₁, k₂, k₃, k₄ are the parameters.

In this study, four particle physicochemical characterisation factors, GD, RO, FD and Al content (Al%), were used as analytical variables, and the enrichment factor AE was used to characterise the sorption capacity of suspended sand for Ni in order to remove the interference of soil background values.

Based on the data of particle roundness, roughness and mean particle size, multiple regressions were carried out in combination with the functional model (3) to obtain the integrated shape function for each region. Combining the regional integrated shape functions with the functional model (4), the function AE was obtained for the influence of the physical and chemical properties of suspended sand particles on the sorption of heavy metals as follows:

AE = aF₁(GD,RO,FD)+bF₂༈Al༉+c ༈4༉

Where: AE is the ability of suspended sand particles to enrich for heavy metals; F₁ is the effect of morphological properties; F₂ is the effect of elemental properties; a, b and c are parameters. To consider the practical significance, the constraints a > 0 and b > 0.

A comparison of the linear fit of the Ni enrichment factor EF with particle AE, SP, GD and 1/GD in each region shows that the interpretation of particle shape in the riparian network is improved by considering the particle shape factor compared to the effect of particle size only (EF-GD or EF-1/GD). A combination of particle shape factors (RO, FD) and Al content (EF- AE) gives the most accurate interpretation of Ni sorption by particles.

Considering lakeside river network area, the parameters of high, moderate velocity (a, b, c, d, k₁, k₂) average processing to $\stackrel{-}{AE}$, this value can better evaluate the suspended sediment particles of Ni concentration skills.

The comparative analysis of EF, AE and GD at each site showed that the AE values at each site in the Lake Shore network fit better with the EF values relative to the GD values, while the suspended sand values were proportional to the EF values in all areas except for the Wenge Bridge in the Lake Shore network. Therefore, the AE values are better able to assess the sorption of Ni by suspended sand at each point in the area than the GD values (Fig. 6-d). The highest Ni sorption by suspended sand particles was found in the slow-flowing plain river network (EF = 4.28; AE = 4.42).

Suspended sand particles play an important role in pollutant migration and transformation, but little attention has been paid to the spatial differences of suspended sand particles morphology and element composition and their impact on the environment. In this paper, based on the actual SEM-EDS measurements, a large number of particle measurements were processed in an attempt to find the differences in the two-dimensional morphological characteristics (GD, RO, FD) and elemental properties of suspended sand particles in typical waters in the slow, flat and strong flow areas of the coastal lake network, to analyse the reasons for the differences, and to establish a coupled function model of suspended sand particle morphology and elements, which can scientifically reflect the differences in the Ni enrichment capacity of suspended sand particles in the waters. Analysis of the mean and standard deviation of GD, RO and FD of the suspended sand population in typical waters, as well as the heterogeneity within the area, shows that the smallest particle size, roundness and roughness are found in the slow flowing river network and the largest particle size, roundness and roughness are found in the strong flowing river network. With the refinement of the physical properties of particles from GD, RO to FD, the change of particle shape characteristics tends to be stable. Although there are still differences between regions, the overall trend is the same. In different flow rate regions, the average percentage content of characteristic elements is basically the same from high to low, and Mg is the highest average percentage content of characteristic elements in each region. The sand content of the estuary is slightly lower than the viscous content in the flat velocity zone, and the difference in viscous content between the low velocity zone and the flat velocity zone is significant, which makes the abundance in the flat velocity zone greater than that in the slow and strong velocity zones, and has a special element K. The integrated shape function model SP was fitted to influence the Ni enrichment capacity, and the enrichment factor AE was used to characterize the Ni sorption capacity of suspended sand. Compared with particle size, the integrated shape function model SP can better reflect the enrichment capacity (AE) of suspended sand for Ni in the watershed. The AE values therefore provide a better assessment of the amount of Ni sorbed by suspended sand between sites in the region than does GD (Fig. 6-d). The highest Ni sorption by suspended sand particles (AE = 3.65; EF = 4.74) was found in the slow-flowing plain river network. This model provides an idea for quantitative analysis of heavy metal enrichment capacity difference of suspended sediment between point sites by SEM-EDS. However, the current work at the macro-basin scale may lead to chance and does not adequately consider the effects of wind direction and flocculation of the suspended sand itself.

Ethical Approval

I certify that: the research will be undertaken in line with all appropriate, University, legal and local standards and regulations. I have attempted to identify the risks that may arise in conducting this research and acknowledge my obligation to (and rights of) any participants. no work will begin until all appropriate permissions are in place.

Consent to Participate

All the participants would like to take part.

Consent to Publish

All the participants would like to publish.

Authors Contributions

Hua Wang: Methodology, Conceptualization, Supervision.

Xueqi Tian: Writing-Reviewing & Editing, Visualization, Software, Validation, Formal analysis.

Zilin Shen: Supervision, Writing-Reviewing & Editing, Software.

Weihao Yuan: Data acquisition, Investigation.

Yichuan Zeng: Writing-Original draft preparation, Conceptualization.

Yuanyuan Li: Data curation.

Funding

This work was supported by the National Natural Science Foundation of China (No. 52179064), water conservancy science and technology project of Jiangxi Province (202023ZDKT12), and the Fundamental Research Funds for the Central Universities (No. 2016B06814), and the CRSRI Open Research Program (2-D spatial-temporal investigation on water quality decoupling in the Yangtze River Estuary, CKWV2017504/KY);

Competing Interests

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work，there is no professional or other personal interest of any nature or kind in any product，service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.

Availability of data and materials

The datasets used or analysed during the current study are available from the corresponding author on reasonable request.

Acknowledgements

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Physical and chemical characteristics of suspended sediment in plain river network

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Abstract

Figures

1. Introduction

2 Materials And Methods

2.1 Survey Region

2.2 Sample collection and determination

2.3 Statistical analysis

3. Results And Discussion

3.1 Differences in physical characteristics

3.2 Differences in chemical properties

3.3 Reason for variance

3.4 Heavy metal adsorption capacity

4 Conclusion

Declarations

References

Supplementary Files

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