Multivariate statistical analyses for water and sediment quality index development: A study of susceptibility in an urban river

Balancing aquaculture and estuarine ecosystems: machine learning-based water quality indices for effective management

This study delves into the environmental impact of inland aquaculture on estuarine ecosystems by examining the water quality of four estuarine streams within the key inland aquaculture zone of South India. In this region, extensive and intensive aquaculture practices are common, posing potential challenges to estuarine health. The research explores the predictive capabilities of the Gaussian elimination method (GEM) and machine learning techniques, specifically multi-linear regression (MLR) and support vector regressor (SVR), in forecasting the water quality index of these streams. Through comprehensive evaluation using performance metrics such as coefficient of determination (R2) and average mean absolute percentage error (MAPE), MLR and SVR demonstrate higher prediction efficiency. Notably, employing key water parameters as inputs in machine learning models is also more effective. Biochemical oxygen demand (BOD) emerges as a critical water parameter, identified by both MLR and SVR, exhibiting high specificity in predicting water quality. This suggests that MLR and SVR, incorporating key water parameters, should be prioritized for future water quality monitoring in intensive aquaculture zones, facilitating timely warnings and interventions to safeguard water quality.

Regulating greenhouse gas dynamics in tidal wetlands: Impacts of salinity gradients and water pollution

Tidal wetlands play a critical role in emitting greenhouse gases (GHGs) into the atmosphere; our understanding of the intricate interplay between natural processes and human activities shaping their biogeochemistry and GHG emissions remains lacking. In this study, we delve into the spatiotemporal dynamics and key drivers of the GHG emissions from five tidal wetlands in the Scheldt Estuary by focusing on the interactive impacts of salinity and water pollution, two factors exhibiting contrasting gradients in this estuarine system: pollution escalates as salinity declines. Our findings reveal a marked escalation in GHG emissions when moving upstream, primarily attributed to increased concentrations of organic matter and nutrients, coupled with reduced levels of dissolved oxygen and pH. These low water quality conditions not only promote methanogenesis and denitrification to produce CH4 and N2O, respectively, but also shift the carbonate equilibria towards releasing more CO2. As a result, the most upstream freshwater wetland was the largest GHG emitter with a global warming potential around 35 to 70 times higher than the other wetlands. When moving seaward along a gradient of decreasing urbanization and increasing salinity, wetlands become less polluted and are characterized by lower concentrations of NO3-, TN and TOC, which induces stronger negative impact of elevated salinity on the GHG emissions from the saline wetlands. Consequently, these meso-to polyhaline wetlands released considerably smaller amounts of GHGs. These findings emphasize the importance of integrating management strategies, such as wetland restoration and pollution prevention, that address both natural salinity gradients and human-induced water pollution to effectively mitigate GHG emissions from tidal wetlands.

Evaluation and monitoring of the water quality of an Argentinian urban river applying multivariate statistics

In this work, we present the water quality assessment of an urban river, the San Luis River, located in San Luis Province, Argentina. The San Luis River flows through two developing cities; hence, urban anthropic activities affect its water quality. The river was sampled spatially and temporally, evaluating ten physicochemical variables on each water sample. These data were used to calculate a Simplified Index of Water Quality in order to estimate river water quality and infer possible contamination sources. Data were statistically analyzed with the opensource software R, 4.1.0 version. Principal component analysis, cluster analysis, correlation matrices, and heatmap analysis were performed. Results indicated that water quality decreases in areas where anthropogenic activities take place. Robust inferential statistical analysis was performed, employing an alternative of multivariate analysis of variance (MANOVA), MANOVA.wide function. The most statistically relevant physicochemical variables associated with water quality decrease were used to develop a multiple linear regression model to estimate organic matter, reducing the variables necessary for continuous monitoring of the river and, hence, reducing costs. Given the limited information available in the region about the characteristics and recovery of this specific river category, the model developed is of vital importance since it can quickly detect anthropic alterations and contribute to the environmental management of the rivers. This model was also used to estimate organic matter at sites located in other similar rivers, obtaining satisfactory results.

Typology and classification of water quality in an intermittent river in a semi-arid Mediterranean climate

The typology and classification of rivers are highly relevant concepts in the field of limnology and freshwater ecology. Water body typology systematically categorizes water bodies based on their natural attributes, while water body classification groups them based on specific criteria or purposes for management, regulatory, or administrative reasons. Both concepts play important roles in understanding and managing water resources effectively. This scientific article focuses on the ZAT River in Morocco as a model for studying low-flow and intermittent rivers. The objective is to develop an accurate model for the typology and classification of small, low-flow rivers into homogeneous classes based on natural and anthropogenic factors. The study also investigates the impact of human activities on altering the uniformity and reference nature of the water body. The typology of water bodies is carried out according to the European methodology specified in The European Commission's Water Framework Directive (WFD) in 2000. The classification of water bodies is conducted by assessing their chemical and biological quality using the weighted index (WI), the Iberian Biological Monitoring Working Group (IBMWP) index, and multivariate statistical methods such as principal component analysis (PCA) for confirming water quality assessment. The results indicate the possibility of dividing the basin into four water bodies. Water bodies show homogeneity in terms of chemical quality when human influence is minimal or during periods of high river flow. However, increased human influence and decreased river flows lead to heterogeneity in chemical quality, indicating an unstable state. This study is the first of its kind in arid and semi-arid intermittent rivers, where such an approach could be suggested to determine their typology and classification.

Spatio-seasonal patterns of the impact of wastewater treatment plant effluents on antibiotic resistance in river sediments

There is a growing concern about the risk of antibiotic resistance emergence and dissemination in the environment. Here, we evaluated the spatio-seasonal patterns of the impact of wastewater treatment plant (WWTP) effluents on antibiotic resistance in river sediments. To this purpose, sediment samples were collected in three river basins affected by WWTP effluents in wet (high-water period) and dry (low-water period) hydrological conditions at three locations: (i) upstream the WWTPs; (ii) WWTP effluent discharge points (effluent outfall); and (iii) downstream the WWTPs (500 m downriver from the effluent outfall). The absolute and relative abundances of 9 antibiotic resistance genes (ARGs), 3 mobile genetic element (MGE) genes, and 4 metal resistance genes (MRGs) were quantified in sediment samples, as well as a variety of physicochemical parameters, metal contents, and antibiotic concentrations in both sediment and water samples. In sediments, significantly higher relative abundances of most genes were observed in downstream vs. upstream sampling points. Seasonal changes (higher values in low-water vs. high-water period) were observed for both ARG absolute and relative abundances in sediment samples. Chemical data revealed the contribution of effluents from WWTPs as a source of antibiotic and metal contamination in river ecosystems. The observed positive correlations between ARG and MGE genes relative abundances point out to the role of horizontal gene transfer in antibiotic resistance dissemination. Monitoring plans that take into consideration spatio-temporal patterns must be implemented to properly assess the environmental fate of WWTP-related emerging contaminants in river ecosystems.

Benthic diatoms and macroinvertebrates status with relevant to sediment quality of islands shores in the Nile River, Egypt

Sediments are utilized as a marker for events that endure long enough to manifest their environmental impacts and determine the contamination levels. The purpose of the present study was to highlight the current sediment quality of four Nile islands shores by utilizing a variety of physical, chemical, and biological aspects and indices. In addition, the status of benthic diatoms and macroinvertebrates, as well as their responses to sediment variables were investigated. The metals followed a decreasing concentration order: Al > Fe > Mn > Zn > Ni ≈ Cr > Cu > Co > Pb > Cd. The outcomes of metal pollution indices revealed some localized contaminated sites, by mostly Ni and Cd. In addition, a moderate toxic risk from metals was observed for El-Keratten shores, while the sediments of El-Warraq, El-Zamalek, and El-Manial islands shores were at low toxic risk. A total of 112 diatom species belonging to 24 genera were identified in the total sample set, where most of the diatoms encountered were cosmopolitan. Metals had a remarkable impact on the composition, distribution, and dominance of diatom assemblages, but had little effect on diatom diversity, while there was a noticeable effect of grain size on diatom distribution and diversity. Thirty-four species of benthic invertebrates were identified in the collected samples from the islands shores. The dominant taxa and groups of benthic invertebrates at different islands were affected by various sediment parameters, where the levels and types of such variables differed from one species to another.

Graphical abstract

Impact of anthropogenic activities on an urban river through a comprehensive analysis of water and sediments

The aim of this study was to assess the impact of urban and industrial areas on an urban river through a comprehensive analysis of water and sediments. Six different sites along the San Luis River, Argentina, were characterized by measuring 12 physical-chemical parameters and nine heavy metals according to standard protocols. Metal pollution in sediment samples was evaluated with several indices. Cluster analysis was applied to standardized experimental data in order to study spatial variability. As, Cu, Cr, Mn, Pb, and Zn were the main contributors to sediment pollution, and the industrial zone studied showed moderate enrichment of Co, Cu, and Zn, probably due to anthropogenic activities. Cluster analysis allowed the grouping of the sites: sediment samples were classified into two clusters according to the metal content; water samples were arranged into three groups according to organic matter content. The results were compared with sediment and water quality guidelines. They indicated progressive deterioration of water and sediment quality compared with the background area, mainly in the sites following the industrial park and domestic discharge areas. Moreover, the results showed that the analysis of both water and sediment should be considered to achieve a watershed contamination profile.

Water Quality Index of Suceava River in Suceava City Metropolitan Area

The water quality of rivers worldwide is of persistent interest due to its impact on human life. Five streamwater quality parameters of Suceava River were monitored in 2019 upstream and downstream of Suceava city, Romania: dissolved oxygen, specific conductivity, pH, oxidation-reduction potential, and temperature. Data was recorded at a high temporal frequency, every hour, and produced Water Quality Index (WQI) time series of similar resolution. Our additive WQI has variants with particular advantages. Water quality of Suceava city exhibits a diurnal cycle. Upstream, WQI values indicate a quasi-permanent good water quality; downstream, the water quality oscillates around the average WQI value because of the various sources of water contaminants, especially the wastewaters from the wastewater treatment plant. Parameters from this point source of pollution are taken into account to explain the decaying streamwater quality towards the end of 2019. WQI is useful for detecting time intervals when water self-purification events have a high chance of occurrence.

Combining punctual and high frequency data for the spatiotemporal assessment of main geochemical processes and dissolved exports in an urban river catchment

The assessment of dissolved loadings and the sources of these elements in urban catchments' rivers is usually measured by punctual sampling or through high frequency sensors. Nevertheless, the combination of both methodologies has been less common even though the information they give is complementary. Major ion (Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl^-, SO₄^2-, and alkalinity), organic matter (expressed as Dissolved Organic Carbon, DOC), and nutrients (NO₃^-, and PO₄^3-) are punctually measured in the Deba river urban catchment (538 km²), in the northern part of the Iberian Peninsula (draining to the Bay of Biscay). Discharge, precipitation, and Electrical Conductivity (EC) are registered with a high frequency (10 min) in three gauging stations. The combination of both methodologies has allowed the assessment of major geochemical processes and the extent of impact of anthropogenic input on major composition of riverine water, as well as its spatial and temporal evolution. Three methodologies for loading estimation have been assessed and the error committed in the temporal aggregation is quantified. Results have shown that, even though carbonates dominate the draining area, the water major ion chemistry is governed by an evaporitic spring in the upper part of the catchment, while anthropogenic input is specially noted downstream of three wastewater treatment plants, in all nutrients and organic matter. The results of the present work illustrate how the combination of two monitoring methodologies allows for a better assessment of the spatial and temporal evolution on the major water quality in an urban catchment.

Comprehensive Assessment of Water Quality and Pollution Source Apportionment in Wuliangsuhai Lake, Inner Mongolia, China

Water quality is a key indicator of human health. Wuliangsuhai Lake plays an important role in maintaining the ecological balance of the region, protecting the local species diversity and maintaining agricultural development. However, it is also facing a greater risk of water quality deterioration. The 24 water quality factors that this study focused on were analyzed in water samples collected during the irrigation period and non-irrigation period from 19 different sites in Wuliangsuhai Lake, Inner Mongolia, China. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were conducted to evaluate complex water quality data and to explore the sources of pollution. The results showed that, during the irrigation period, sites in the middle part of the lake (clusters 1 and 3) had higher pollution levels due to receiving most of the agricultural and some industrial wastewater from the Hetao irrigation area. During the non-irrigation period, the distribution of the comprehensive pollution index was the opposite of that seen during the irrigation period, and the degree of pollutant index was reduced significantly. Thus, run-off from the Hetao irrigation area is likely to be the main source of pollution.

Development of a Universal Water Quality Index (UWQI) for South African River Catchments

The assessment of water quality has turned to be an ultimate goal for most water resource and environmental stakeholders, with ever-increasing global consideration. Against this backdrop, various tools and water quality guidelines have been adopted worldwide to govern water quality deterioration and institute the sustainable use of water resources. Water quality impairment is mainly associated with a sudden increase in population and related proceedings, which include urbanization, industrialization and agricultural production, among others. Such socio-economic activities accelerate water contamination and cause pollution stress to the aquatic environment. Scientifically based water quality index (WQI) models are then essentially important to measure the degree of contamination and advise whether specific water resources require restoration and to what extent. Such comprehensive evaluations reflect the integrated impact of adverse parameter concentrations and assist in the prioritization of remedial actions. WQI is a simple, yet intelligible and systematically structured, indexing scale beneficial for communicating water quality data to non-technical individuals, policymakers and, more importantly, water scientists. The index number is normally presented as a relative scale ranging from zero (worst quality) to one hundred (best quality). WQIs simplify and streamline what would otherwise be impractical assignments, thus justifying the efforts of developing water quality indices (WQIs). Generally, WQIs are not designed for broad applications; they are customarily developed for specific watersheds and/or regions, unless different basins share similar attributes and test a comparable range of water quality parameters. Their design and formation are governed by their intended use together with the degree of accuracy required, and such technicalities ultimately define the application boundaries of WQIs. This is perhaps the most demanding scientific need—that is, to establish a universal water quality index (UWQI) that can function in most, if not all, the catchments in South Africa. In cognizance of such a need, this study attempts to provide an index that is not limited to certain application boundaries, with a contribution that is significant not only to the authors, but also to the nation at large. The proposed WQI is based on the weighted arithmetic sum method, with parameters, weight coefficients and sub-index rating curves established through expert opinion in the form of the participation-based Rand Corporation’s Delphi Technique and extracts from the literature. UWQI functions with thirteen explanatory variables, which are NH3, Ca, Cl, Chl-a, EC, F, CaCO3, Mg, Mn, NO3, pH, SO4 and turbidity (NTU). Based on the model validation analysis, UWQI is considered robust and technically stable, with negligible variation from the ideal values. Moreover, the prediction pattern corresponds to the ideal graph with comparable index scores and identical classification grades, which signifies the readiness of the model to appraise water quality status across South African watersheds. The research article intends to substantiate the methods used and document the results achieved.