River Surface Water Research Articles

A dataset of 1 km grid drainage density in China (2019)

Drainage density is an outcome of the combined influence of watershed landform, climate, soil, and vegetation. As a comprehensive characterization index, the measurement and monitoring of drainage density is of great significance to environmental protection and water resources allocation in regional watersheds. This paper uses river water surface vector data from the third National Land Survey, extracting the river center line. Then, the kilometer grid network production software is employed to generate the dataset of 1 km grid drainage density in China. Rigorous quality control and quality inspection measures throughout all stages of data processing have been implemented, including river surface vector extraction, river skeleton line extraction, and kilometer grid density calculation, to ensure the correctness, integrity and consistency of the data. This dataset can be used for national and regional hydrogeological analysis, soil erosion estimation, planning and layout of basic monitoring station network, etc.

River Water Level and Water Surface Slope Measurement From Spaceborne Radar and LiDAR Altimetry: Evaluation and Implications for Hydrological Studies in the Ganga River

River Water Level and Water Surface Slope Measurement From Spaceborne Radar and LiDAR Altimetry: Evaluation and Implications for Hydrological Studies in the Ganga River

Carbapenemase-producing bacteria recovered from Nairobi River, Kenya surface water and from nearby anthropogenic and zoonotic sources.

Carbapenem-resistant bacteria (CRB) present a significant global public health concern. Sub-Saharan Africa has borne a heavy burden of CRB with a reported prevalence of up to 60% in some patient populations. es in Africa focus on clinical CRB isolates, with limited data on their spread in the natural environment. Therefore, the purpose of this study was to report the recovery of CRB from Nairobi River surface waters and nearby anthropogenic and zoonotic sources in Nairobi County, Kenya. A total of 336 CRB were recovered from 336 (250 mL) samples, with 230 of the samples (68.5%) producing one or more CRB isolates. CRB were recovered most commonly from untreated sewage influent (100% of 36 samples; 79 total isolates), treated effluent (93% of 118 samples; 116 total isolates), Nairobi River surface waters upstream (100% of 36 samples; 57 total isolates), downstream (100% of 36 samples; 45 total isolates), and way downstream from the wastewater treatment plant (73% of 11 samples; 19 total isolates), slaughterhouse effluent discharges 1.5%, (5/336), animal contact areas 0.9%, (3/336), a manhole sewer from the affluent neighborhood of Karen at 2.7%, (9/336) respectively. The CRB included Escherichia coli (158, 47%), Klebsiella pneumoniae (74, 22%), and Enterobacter spp (43, 13%). Aeromonas spp (29, 9%) Acinetobacter baumannii (12, 3.6%), Citrobacter freundii (7, 2.1%), Pseudomonas aeruginosa (5, 1.5%) and other species (8, 2.4%). CRB genotypes included blaNDM (246, 73.2%), blaKPC (40, 12%), blaVIM (51, 15.2%), blaOXA-48-like (65, 19.3%), blaIMP (15, 4.5%), and blaGES (7, 2.1%). Sixty-nine of the CRB isolates (20.5%) harbored multiple carbapenemase-encoding genes. Our results indicate that clinically important CRB are commonly present in Nairobi River surface water and from nearby wastewater and livestock sources. These pose an important public health threat that requires urgent intervention strategies and additional investigation.

Does mangrove leave falling dominate the bury of polycyclic aromatic hydrocarbons in the mangrove of China?

Mangrove wetlands are vital coastal ecosystems that can absorb and accumulate pollutants. Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants that pose potential risks to ecosystems and human health. However, their source and transport fate in mangrove areas are poorly understood. This study investigates 29 PAHs pollution of water and sediment in Zhangjiangkou Mangrove Wetland, the northernmost large-scale mangrove wetland reserve in China. We examine the distribution, source, transport mechanisms and risk assessment of PAHs. The results show that the concentrations of PAHs in mangrove sediment range from 55.62 to 347.36 ng/g (DW), with 5-ring PAHs being the dominant species. While the concentrations of PAHs in surface water range from 10.61 to 46.39 ng/L, with 2-ring PAHs and alkylated PAHs being the dominant species. The PAHs concentrations in surface water and sediment of river are higher than those in mangrove area, indicating that mangrove water could receive PAHs through tidal exchange. Based on diagnostic ratios (DRs), principal component analysis (PCA), and positive matrix factorization (PMF), we infer that the leaf deposition (48.55%) could be an important pathway of PAHs in mangrove sediment except for river water transport (51.45%), while the PAHs in estuary water originate mainly from point sources such as biomass burning (50.96%) and traffic emission (49.04%). The range of toxic equivalents in surface water and sediment was 2.73–16.09 ng TEQ g−1 and 0.03–3.63 ng/L, respectively. Although the ecological risk assessment suggests that the PAHs pollution in surface water and sediment poses a low risk, we recommend more attention to the protection of the mangrove ecosystem. This study reveals that mangrove leaf falling might be a significant mechanism of PAH sequestration in the mangrove system, which deserves more attention in future research.

Inter-event and intra-event dynamics of microplastic emissions in an urban river during rainfall episodes

Urban rivers represent the major conduits for land-sourced microplastics in the global oceans, yet the real-time dynamics of their emissions in rivers during rainfall (and runoff) events are poorly understood. Herein, we report the results of high-frequency sampling of microplastic particles (MPs) and fibers (MPFs) in the surface water of an urban river in Japan over the course of three rainfall events (i.e., light, moderate, and heavy rainfalls). The event mean concentrations (EMCs) of MPs amounted to 35,000 items/m3, 929,000 items/m3, and 331,000 items/m3; and the corresponding total loads were 0.5 kg, 19.8 kg, and 35.0 kg for light, moderate and heavy rainfalls, respectively. The inter-event total loads of MPs correlate well with the total rainfall, while the concentrations were linked with the number of antecedent dry days. The dynamic trends show that <2000 μm MPs displayed first flush effects during light to moderate rainfall events (>50% mass discharged with the initial 20–40% of flow). Small-sized MPs (10–40 μm) mobilized rapidly at lower rainfall intensities, whereas MPs over 2000 μm discharged immediately after the peak rainfall intensity. Moreover, <70 μm MPs depicted a surge following heavy rainfall events due to turbulent flow conditions reverting the deposited MPs into suspension. Overall, the three events increased the loads by 4–110 folds, and EMCs by 10–350 folds compared to the concentrations during dry weather while portraying a significant impact on 300–1000 μm MPs. The dynamics of MPs were correlated with those of suspended solids in river water, and the characteristics were comparable to the same of road dust sampled in Japan. Although the dynamic trends between MPs and MPFs in river water were comparable, MPFs were relatively less impacted by rain, likely due to the intervention of separate sewer systems in the study area.

Hydrochemical background of 222Rn in surface waters of Lower Silesia (SW Poland)

The purpose of the conducted research was to create the first Polish database on 222Rn activity concentration in surface (river) waters in one of Poland’s 16 voivodeships (the highest-level administrative division unit in Poland), and thereby complement the worldwide database on 222Rn activity concentration in such waters. To this end, the research area was limited to Lower Silesian voivodeship (6.4% of the area of Poland; 7.8% of its population), which, in geological terms, can be divided into three parts differing in geological structure, characterised by a decreasing proportion of crystalline rocks on the surface. The ranges of 222Rn activity concentrations measured in these areas were: 0.21–24.44 Bq/dm3 for the Sudetes, 0.08–4.27 Bq/dm3 for the Fore-Sudetic Block, and 0.09–3.37 Bq/dm3 for the Fore-Sudetic Monocline. Based on the obtained 222Rn activity concentrations in river waters, the authors determined the hydrochemical background. It was: 0.26–1.33 Bq/dm3 for the Sudetes, 0.18–0.92 Bq/dm3 the Fore-Sudetic Block, and 0.12–0.48 Bq/dm3 for the Fore-Sudetic Monocline. The range of 222Rn activity concentrations measured in river waters in the whole Lower-Silesian voivodeship was 0.08–24.44 Bq/dm3. It means that river waters in this voivodeship satisfy the radiologic requirements for water intended for human consumption in terms of 222Rn activity concentration.

Microplastic particles in river sediments and water of southwestern Nigeria: insights on the occurrence, seasonal distribution, composition, and source apportionment.

Microplastics (MPs) are globally recognized as an emerging environmental threat, particularly in the aquatic environment. This study presents baseline data on the occurrence and distribution of MPs in sediments and surface water of major rivers in southwestern Nigeria. Microplastics were extracted by density separation and polymer identification using Fourier transformed infrared spectroscopy in attenuated total reflectance mode (FTIR-ATR). The abundance of MPs in surface sediment and water samples across all locations ranged from 12.82 to 22.90 particle/kg dw and 6.71 to 17.12 particle/L during the dry season and 5.69 to 14.38 particle/kg dw and 12.41 to 22.73 particle/L during the wet season, respectively. On average, fiber constituted the highest percentage of MP in sediments (71%) and water (67%) while foam accounted for the lowest values of 0.6% and 1.7%, respectively. Polypropylene(PP) and polyethylene (PE) were the main MPs across all locations based on Fourier transform infrared spectroscopy (FTIR). MPs of size < 1mm were the most abundant (≥ 55%) on average in both water and sediments. The study identified run-off from human activities and industrial wastewater as potential sources of MP exposure based on positive matrix factorization. The study suggests assessing the impact of different land-use activities on MPs occurrence and distribution in addition to quantifying MPs in seafood as a way forward in food safety management systems for further studies. This study confirmed the occurrence and widespread distribution of MPs in surface water and sediments and provides a database on MP pollution in Nigeria.

Petroleum Hydrocarbon Pollution in Surface Water and Sediments of the Lower Northern Dvina River

Petroleum Hydrocarbon Pollution in Surface Water and Sediments of the Lower Northern Dvina River

Microplastic Quantification in Aquatic Birds: Biomonitoring the Environmental Health of the Panjkora River Freshwater Ecosystem in Pakistan.

Microplastic pollution has become a global concern, with potential negative impacts on various ecosystems and wildlife species. Among these species, ducks (Anas platyrhynchos) are particularly vulnerable due to their feeding habits and proximity to aquatic environments contaminated with microplastics. The current study was designed to monitor microplastic (MP) pollutants in the freshwater ecosystem of the Panjkora River, Lower Dir, Pakistan. A total of twenty (20) duck samples were brought up for four months and 13 days on the banks of the river, with no food intake outside the river. When they reached an average weight of 2.41 ± 0.53 kg, all samples were sacrificed, dissected, and transported in an ice box to the laboratory for further analysis. After sample preparation, such as digestion with 10% potassium hydroxide (KOH), density separation, filtration, and identification, the MP content was counted. A total of 2033 MP particles were recovered from 20 ducks with a mean value of 44.6 ± 15.8 MPs/crop and 57.05 ± 18.7 MPs/gizzard. MPs detected in surface water were 31.2 ± 15.5 MPs/L. The major shape types of MPs recovered were fragments in crop (67%) and gizzard (58%) samples and fibers in surface water (56%). Other types of particles recovered were fibers, sheets, and foams. The majority of these detected MP particles were in the size range of 300-500 µm (63%) in crops, and 50-150 µm (55%) in gizzards, while in water samples the most detected particles were in the range of 150-300 µm (61%). Chemical characterization by FTIR found six types of polymers. Low-density polyethylene (LDPE) had the greatest polymer detection rate (39.2%), followed by polyvinyl chloride (PVC) (28.3%), high-density polyethylene (HDPE) (22.7%), polystyrene (6.6%), co-polymerized polypropylene (2.5%), and polypropylene homopolymer (0.7%). This study investigated the presence of microplastics in the crops and gizzards of ducks, as well as in river surface water. The results revealed the significant and pervasive occurrence of microplastics in both the avian digestive systems and the surrounding water environment. These findings highlight the potential threat of microplastic pollution to wildlife and ecosystems, emphasizing the need for further research and effective mitigation strategies to address this pressing environmental concern.

INFLUENCE ON GROUNDWATER EXCHANGE BETWEEN CONFLUENTS ON THE ECOLOGICAL QUALITY OF SURFACEWATER BODIES

The article raises the question of the influence on surface water bodies downstream of the Dnipro River, taking into account the geological influence on one river on another. Such studies are necessary to establish the factors influencing the composition of surface waters of rivers and to determine the stability of the ecological quality of surface water bodies such as the left tributaries of the Dnipro – Desna, Sula, Psel, Vorskla and Samara. Detection of the influence on upstream tributaries on downstream, taking into account the presence of groundwater, was carried out using the example of chloride dynamics. Correlational dependences were constructed between chloride concentrations in observation posts located the closest to Dnipro. The obtained results confirm the influence of tributaries on each other. In order to confirm the conclusions obtained regarding the influence on rivers due to groundwater, studies with other impurities present in tributaries are needed. The obtained results can be used for the development and implementation of a mathematical model for forecasting the ecological state of surface water bodies within the sub-basin.

Temporal and spatial variation of microplastics in the urban rivers of Harbin

This study was to investigate temporal and spatial variation of microplastics in surface water and sediment in the urban rivers of Harbin during dry and wet season. Water samples (n = 25) in Xinyi River (n = 13) and Ashe River (n = 12) were collected from the selected sampling points. Microplastics in urban rivers in Harbin included polyethylene (PE), polypropylene (PP), polystyrene (PS), polyamide (PA), polyvinyl chloride (PVC) and polyethylene terephthalate (PET). The results show that urban rivers in Harbin had relatively mild microplastic abundance with most fragments in shape and colorless in color. PP and PE were the major polymers in surface water samples, while PVC and PET were the major polymers in sediment, which were dominated by large-size and granulate shape microplastics. Source apportionment demonstrate that the main sources of microplastics in Xinyi River and Ashe River during dry season were domestic wastewater and effluent from rainfall, while the main sources of microplastics in Xinyi River and Ashe River during wet season were wastewater, atmospheric sedimentation, and agricultural source. The morphology of microplastics in surface water and sediment in urban rivers of Harbin was negatively correlated with water velocity and positively correlated with the concentration of suspended matter, dissolved oxygen, and conductivity. Riparian vegetation on the sides of Xinyi and Ashe River decreased migration process of microplastics by vegetal purification and then resulted in low abundance of microplastics. In conclusion, this study highlighted the occurrence characteristics, source apportionment and environmental influencing factors of microplastics in urban rivers of Harbin, which may develop new insights into the reduction of abundance of microplastics in the urban rivers.

Seasonal variations of microplastics in surface water and sediment in an inland river drinking water source in southern China

The aim of this study was to examine microplastic (size distribution of 0.05–5 mm) occurrence and distribution in drinking water source of XJ River during both flooding and dry periods. Surface water and sediment samples were collected from the CS City section of the river in August and December 2020. During the flooding period, microplastic abundances were observed at 0.72–18.6 (7.32 ± 2.36) items L−1 in surface water and 26.3–302 (150 ± 75.6) items kg−1 dry weight (dw) in sediment. In the dry period, abundances were slightly higher at 2.88–17.7 (11.0 ± 3.08) items L−1 and 27.0–651 (249 ± 182) items kg−1 dw, respectively. Microplastics were found in higher concentrations in urban areas and downstream of wastewater treatment plants, suggesting anthropogenic sources. The diversity in shapes, colors, and types of microplastics in surface waters and sediments indicates specialized enrichment processes and persistent sources of microplastic pollution. Approximately 60 % of the microplastic particles identified fall within the 50–100 μm range. Furthermore, a significant correlation was observed between these smaller-sized particles and the overall prevalence of microplastics. Fourier-transform infrared spectroscopy and scanning electron microscopy indicated that the microplastics had been subjected to weathering in the environment, contributing to the production of oxygen-containing functional groups and surface cleavage features. The utilization of energy dispersive spectroscopy revealed the presence of microplastics associated with various heavy metals, highlighting the intricate nature of microplastic pollution. Moreover, the high abundance of microplastics may pose a potential ecological risk to the aquatic environment of the XJ River. The results of this study demonstrate concerning levels of microplastics in the XJ River, despite its status as a high-quality water source.

A review on antibiotics in the environment, resistance in microbes, impact on human health and treatment and future strategies for tackling the global problem

The introduction of antibiotics was a blessing to human civilization as the antibiotics saved several million human and animal lives. Due to overuse and misuse of antibiotics by humans in the healthcare, and agriculture sectors, the residues of the antibiotics were reported in all the segments of the environment (surface water, groundwater, river water, soil, sediments, wastewater effluent, hospital effluent, livestock, fish, fruits, vegetables and milk) from ng to mg/L or kg that results in the rapid increase in the number of antibiotic resistant bacteria. Antibiotic resistance has been listed by the World Health Organization before Covid 19 as one of the top 10 threats to human health globally. Though antibiotic resistance is inevitable it is mainly anthropogenic and is an important factor of increased healthcare costs, longer hospital stay stress on hospital beds and ICU and higher rates of morbidity and mortality. The invention of new antibiotics to cope the resistant bacterial infection is the need of the hour but as bacterial infections is not an ongoing process (have a lower return) unlike chronic diseases hypertension, and diabetes the pharmaceutical companies are not very interested in the inventions. This article discusses the antibiotics in the different compartments of the environment, the antibacterial mechanisms of the antibiotics, causes of development and mechanisms of antibiotic resistance in bacteria and mechanisms/methods to combat antibiotic resistance.

Combining Satellite Optical and Radar Image Data for Streamflow Estimation Using a Machine Learning Method

River water surface extent can be extracted from optical and radar satellite images; this is useful for estimating streamflow from space. The radiation characteristics of open water from the visible and microwave bands are different and provide independent information. In this study, for the purpose of improving streamflow estimation from space for data-sparse regions, a method that combines satellite optical and radar images data for streamflow estimation using a machine learning technique was proposed. The method was demonstratedthrough a case study in the river segment upstream of the Ganzi gauging station on the Yalong River, China. Utilizing the support vector regression (SVR) model, the feasibility of different combinations of water surface area derived from Sentinel-1 synthetic aperture radar images (AREA_SAR), modified normalized difference water index derived from Landsat 8 images (MNDWI), and reflectance ratios between NIR and SWIR channels derived from MODIS images (RNIR/RSWIR) for streamflow estimation were evaluated through three experiments. In Experiment I, three models using AREA_SAR (Model 1), MNDWI (Model 2), and a combination of AREA_SAR and MNDWI (Model 3) were built; the mean relative error (MRE) and mean absolute error (MAE) of streamflow estimates corresponding to the SVR model using both AREA_SAR and MNDWI (Model 3) were 0.19 and 31.6 m3/s for the testing dataset, respectively, and were lower than two models using AREA_SAR (Model 1) or MNDWI (Model 2) solely as inputs. In Experiment II, three models with AREA_SAR (Model 4), RNIR/RSWIR (Model 5), and a combination of AREA_SAR and RNIR/RSWIR (Model 6) as inputs were developed; the MRE and MAE for the model using AREA_SAR and RNIR/RSWIR (Model 6) were 0.25 and 56.5 m3/s, respectively, which outperformed the two models treating AREA_SAR (Model 4) or MNDWI (Model 5) as single types of inputs. In Experiment III, three models using AREA_SAR (Model 7), MNDWI, and RNIR/RSWIR (Model 8) and the combination of AREA_SAR, MNDWI and RNIR/RSWIR (Model 9) were built; combining all three types of satellite observations (Model 9) exhibited the highest accuracy, for which the MRE and MAE were 0.18 and 18.4 m3/s, respectively. The results of all three experiments demonstrated that integrating optical and microwave observations could improve the accuracy of streamflow estimates using a data-driven model; the proposed method has great potential for near-real-time estimations of flood magnitude or to reconstruct past variations in streamflow using historical satellite images in data-sparse regions.

Source apportionment of polychlorinated biphenyls in surface water and sediments from River Otamiri, Imo State

Polychlorinated biphenyls (PCBs) are a group of toxic, long-lasting substances that have a high propensity to accumulate in the environment as organic pollutants which can cause potential risk to the environment. In this regard, the concentration and sources of PCBs in the surface water and sediment of River Otamiri in Imo State was investigated. This study collected surface water and sediment samples from River Otamiri at four sampling points. It was analyzed for PCBs concentration using an Agilent 7890A gas chromatograph coupled to an Agilent 5975C mass selective detector. Twenty-eight PCB congeners were detected in the water and sediment samples. Also, the PCB congeners' descriptive statistics (mean and standard deviation) in the studied matrices were reported. The concentration of PCB congeners for the surface water and sediment ranged from 622.87–935.84 ng L−1 and 1621.03–2748.17 μg kg−1 respectively. The concentration of PCB congeners in the studied matrices revealed that PCB-118 had the highest concentration, while the lowest concentration was recorded in PCB-157. Statistical methods were used to identify the source of the pollutant in the studied matrices. Pearson's correlation coefficient for PCBs in sediment and surface water samples was calculated, and the results revealed that all the sampling points showed a strong and positive correlation with each other, indicating a similar origin/source. Based on this study's findings from principal component analysis (PCA), the origin/source of the pollutant was similar and was attributed to geogenic factors such as the leaching of soils from waste dumpsites and auto-mechanic workshops around the River Otamiri. In addition, ANOVA of PCBs in the surface water and sediments revealed a p-value less than 0.05 in all the studied matrices. The study's findings suggest that using statistical methods can give a scientific basis for monitoring and determining the source of polychlorinated biphenyls in surface water and sediments. In conclusion, government agencies are to develop environmental policies and framework that will guide and protect the environment from organic pollutants (PCBs) that will pose risk to the surface water and sediments of rivers.

Computing River Discharge Using Water Surface Elevation Based on Deep Learning Networks

Accurately computing river discharge is crucial, but traditional computing methods are complex and need the assistance of many other hydraulic parameters. Therefore, it is of practical value to develop a convenient and effective auto-computation technique for river discharge. Water surface elevation is relatively easy to obtain and there is a strong relationship between river discharge and water surface elevation, which can be used to compute river discharge. Unlike previous usage of deep learning to predict short-term river discharge that need multiple parameters besides water level, this paper proved that deep learning has the potential to accurately compute long-term river discharge purely based on water level. It showed that the majority of relative errors on the test dataset were within ±5%, particularly it could operate continuously for almost one year with high precision without retraining. Then, we used BiGRU to compute river flow with different hyperparameters, and its best RMSE, NSE, MAE, and MAPE values were 256 m3/s, 0.9973, 207 m3/s, and 0.0336, respectively. With this data-driven based technology, it will be more convenient to obtain river discharge time series directly from local water surface elevation time series accurately in natural rivers, which is of practical value to water resources management and flood protection.

Microplastic accumulation in oysters: Insights from aquaculture and laboratory conditions

Microplastics, emerging pollutants, are present in seafood and pose a potential health risk to consumers. The objective of this study was to assess microplastic concentrations in the surface water, sediments, and oysters of the Cha Va River, an aquaculture production area in southern Vietnam. Laboratory experiments were also conducted to examine rates of ingestion by and bioconcentration of microplastics in oysters. Microparticles including microplastics were measured in all samples collected from the field, and presented 9–27 items m−3 in surface water, 3300–8000 items kg−1 dry weight in sediments, and 0.67–8.33 items ind−1 or 0.02–0.33 items g−1 wet weight in oysters. Fibre shapes and blue colour were the most common while polypropylene, polyester, polyethylene, and polyethylene terephthalate acrylate, alkyd were identified. The presence of microparticles in surface water and sediment was influenced by the complex vertical motion characteristic of tidal environments whereas the microparticles in natural oysters seemed to be closer related to those in sediment than in the surface water. Laboratory experiments showed that oysters incubated in 10 and 1000 microplastics L−1 tanks accumulated 4.1 ± 2.0 and 19.0 ± 11.0 microplastics per individual, respectively. However, bioconcentration of microplastics in oysters was higher (12.37 ± 6.95) in tanks with lower microplastic concentrations than in tanks with higher microplastic concentrations (0.62 ± 0.35). It is a high potential human health risk to the local oyster-consumers because of the annually microparticle ingestion from 657 to 3942 items per person. We suggested further studies on the severity of this potential health risk and policies for minimising microplastic emissions into the environment in Vietnam.

Microplastics in the Syr Darya River Tributaries, Uzbekistan

The objective of the study was a pre-screening of the microplastic (MP) content in surface water and benthic sediments of Kara Darya and Chirchiq rivers, the first-order tributaries of the Syr Darya River (Uzbekistan). For the first time, surface water and benthic sediment samples were taken from this region, and quantitative screening of MPs 0.15–5.00 mm in size was performed. A combined visual and μRaman-based methodology was used to quantify and characterize artificial polymer microparticles from the surface water and bottom sediments of two rivers. The average abundance of MPs in the Kara Darya River and Chirchiq River waters was found to be 4.28 ± 0.09 and 0.95 ± 0.36 items per m3, and that in benthic sediments attained 244 ± 28.9 and 333 ± 11.5 items per kg of dry soil, respectively. MP concentration in surface water and benthic sediments of the Kara Darya River significantly exceeded (p-value &lt; 0.01) that in the Chirchiq River. Microfibers were most abundant; the proportion of MP fibers in the water of the Kara Darya and Chirchiq rivers amounted to 89 and 95%, respectively, and that in benthic sediments of the rivers was 86 and 84%, respectively. The dominance of microfibers may indicate the route of entry to the rivers through domestic wastewater treatment plant discharges. The polymer microparticles in the surface water and benthic sediments of the Kara Darya and Chirchiq rivers were mainly represented by polyethylenterephtalate (PET), which accounted for half of all MPs detected in the Kara Darya River. Microparticles of textile origin were particularly abundant in the Kara Darya River, where viscose and nylon fibers were also found, which suggests the leading role of synthetic textiles in the pollution. The reported data are the first experimental evidence of MP pollution of the Syr Darya tributaries, but the distribution and circulation of MPs in surface water in Central Asia requires further comprehensive studies.

Assessment of the Surface Water Quality of the Gomti River, India, Using Multivariate Statistical Methods

In the present study, the quality of the surface water of the Gomti river (Lucknow, India) was investigated. Lucknow is situated in the centre of Uttar Pradesh, which is most the populated state in India. The locality has experienced rapid, unregulated development activities and population growth in recent decades, both of which have had a negative impact on its ecosystem and environment. Continuous monitoring is required to maintain the ecosystem at the desired level. Nine samples of river water were collected from the Gomti River in Lucknow, and they were analysed for a total of nine different characteristics, including pH, turbidity (Tur), dissolved oxygen (DO), total dissolved solids (TDSs), chemical oxygen demand (COD), chloride ion (Cl-) concentration, temperature (T), biochemical oxygen demand (BOD5) and total hardness (TH). The observed data were analysed using multivariate statistical methods. A cluster analysis (CA) was used to sort the sampling locations into different groups, and a principal component analysis (PCA) was used to find the different sources of pollution. Using a cluster analysis, all the water quality parameters were divided into three groups. Cluster 1 represented the less polluted sites, cluster 2 represented the moderately polluted sites and cluster 3 represented the highly polluted sites. Sampling sites SS8, SS4, S99 and SS7 were highly polluted because of nearby pollution sources such as domestic wastewater and runoff storm water. The principal component analysis yielded two meaningful components that explained 82.4% of the total variation in the data. The first factor and second factor explained 59.022 and 23.363 percentages of the total variance, respectively. It was noticed that major sources of pollution for the Gomti river are storm water runoff and the release of domestic and industrial wastewater from residents and industries, respectively. This study will help policy makers to ensure sustainable practices and reduce negative impacts on the availability and quality of water, allowing for the most efficient use of the Gomti River.

ICE2WSS; An R package for estimating river water surface slopes from ICESat-2

ICE2WSS; An R package for estimating river water surface slopes from ICESat-2