Search Results (17)

Surface water degradation has intensified due to anthropogenic pressures, especially in urban areas, where unplanned land use compromises the integrity of aquatic ecosystems. This study investigated the relationship between water quality and land use in a Permanent Preservation Area (PPA) within an urban perimeter in Caçador, Santa Catarina, Brazil. Monthly sampling was conducted throughout 2024 at 11 points distributed along urban and rural sections of the river and its tributaries. Physicochemical and microbiological parameters were evaluated, and the Water Quality Index (WQI) established by the National Sanitation Foundation (NSF) was calculated in order to associate the results with the sampling points, complemented by Principal Component Analysis (PCA) to identify multivariate patterns of spatial variability in water quality across the study area. In parallel, the PPA within the urban perimeter was delimited according to current environmental legislation, and land use was classified using ArcGIS and Google Earth Pro. The results revealed greater water quality degradation in urban stretches of the river, particularly at sampling point SP7, which recorded the lowest dissolved oxygen concentration (3.10 mg L⁻¹), alongside elevated values of biochemical oxygen demand (5.23 mg L⁻¹), total phosphorus (2.94 mg L⁻¹), nitrate (18.75 mg L⁻¹), and thermotolerant coliforms (2759.20 MPN 100 mL⁻¹). The WQI ranged from 40.18 (SP7: bad category) to 73.57 (SP1: good category), reflecting a pronounced spatial gradient of water quality degradation associated with increasing urbanization along the river course. Mapping of the PPAs revealed that only 43.72% of the total area was covered by native vegetation, while the remaining 56.28% was occupied by anthropogenic land uses, including miscellaneous use (30.32%), agriculture (9.09%), buildings (6.09%), roads (4.64%), and railway infrastructure (5.81%). PCA accounted for 89.06% of the total data variance and indicated that greater interaction of sampling points with urbanized areas was consistently associated with reduced water quality, thereby demonstrating the direct influence of anthropogenic activities on the environmental parameters assessed throughout the study area. These findings demonstrate that land use patterns directly affect water quality and reinforce the need for riparian forest restoration, expanded sanitation infrastructure, and more sustainable urban planning. Full article

The objective of this study was to assess and model the condition and resilience of the Cunas River using integrated indices and multivariate statistics in order to determine the impact of anthropogenic pressure and enhance water security in the Peruvian Andes. Stations in the upper, middle, and lower reaches of the river were monitored during the rainy and dry seasons, applying quality indices (NSF-WQI, WA-WQI, CCME-WQI, and I-WQI), principal component analysis (PCA), hierarchical cluster analysis (HCA), and Spearman’s rank correlation (ρ) to assess the intensity and direction of associations between physical–chemical parameters. The results reveal severe degradation in the lower section of the river, with critical hypoxia and extreme coliform levels during the dry season, drastically exceeding the levels in the upper reach. The I-WQI demonstrated superior performance (322.24; Unfit) by being more sensitive than the NSF-WQI (53.15–59.87). PCA confirmed that low flow explains the greatest variance in pollution (PC1 71.55%), while HCA identified maximum synergy (rescaling distance < 1) between biochemical oxygen demand (BOD₅) and total phosphorus, indicating the collapse of self-purification capacity. The HCA identified a maximum synergy between BOD₅ and total phosphorus during the low-flow season, while the PCA confirmed that low discharge intensifies pollutant concentrations. These findings support the need for resilience-based governance that prioritizes the protection of natural infrastructure. Full article

Physicochemical and microbiological parameters are important indicators of drinking water quality. This study assessed the quality of groundwater used for drinking in four regions of Kosovo at 16 locations using an integrated assessment framework that combined physicochemical, microbiological, and Water Quality Index (WQI) approaches. The results reveal substantial spatial variability in water quality. While most physicochemical parameters remained within recommended limits, elevated values of total dissolved solids (up to 2792.5 mg/L), electrical conductivity (up to 2768.5 µS/cm), nitrate (up to 60.75 mg/L), and phosphate (up to 0.875 mg/L) were observed at several locations, indicating localized hydrogeochemical and anthropogenic influences. Dissolved oxygen levels were generally low (0.68–5.49 mg/L), reflecting limited aeration conditions in groundwater systems. Microbiological analysis revealed critical contamination, with Escherichia coli concentrations up to 299.9 CFU/100 mL, and all sampling sites exceeded permissible limits, indicating widespread fecal pollution and rendering the groundwater unsafe for direct consumption. WQI assessment further confirmed this condition, where 93.75% of locations were classified as medium quality using the NSF-WQI method, whereas the WA-WQI method categorized 68.75% of samples as poor and 6.25% as very poor. The novelty of this study lies in the integrated evaluation of hydrogeochemical processes and microbiological contamination using dual WQI methods and multivariate statistical analysis, providing a comprehensive understanding of groundwater degradation pathways. The findings are significant for policymakers, environmental managers, and public health authorities, highlighting the urgent need for groundwater treatment, improved sanitation infrastructure, and sustainable water resource management strategies in vulnerable regions. Full article

This study evaluated the influence of soil health in riparian and ecotone zones on water quality in four high-Andean rivers (Atillo, Ozogoche, Yasepan, and Cebadas) within the Cebadas River sub-basin, Ecuador. Soil and water samples were collected from 20 sites during three field campaigns (2022–2024). Soil properties included organic carbon concentration, soil organic carbon stock (SOC), bulk density, moisture, and potential microbial activity estimated through laboratory CO₂–C efflux. Water quality parameters were integrated into the National Sanitation Foundation Water Quality Index (NSF-WQI), and riparian condition was assessed using the QBR-And index. Multivariate statistical approaches, including Random Forest and Classification and Regression Trees (CART), were used to identify the most influential predictors of ecosystem quality. Results revealed marked spatial contrasts. Riparian SOC stocks ranged from 22.8 to 32.8 Mg C/ha in the more disturbed Cebadas and Yasepan rivers to 91.4–133.6 Mg C/ha in the better-conserved Atillo and Ozogoche systems. Sites with higher SOC and lower bulk density consistently exhibited better water quality, with NSF-WQI values classified as “good”, whereas more degraded sites showed lower riparian quality and “fair” water quality. Riparian forest quality was strongly correlated with water quality (r = 0.81). Random Forest models identified ammoniacal nitrogen, fecal coliforms, and altitude as the most influential predictors of riparian ecosystem condition. These findings demonstrate that soil health and riparian integrity are tightly linked to water quality patterns in high-Andean fluvial systems and support their integration into ecosystem-based watershed management. Full article

Lake Kotokel, the largest lake on the eastern shore of Lake Baikal, has historically served as an important fishery and recreational resource. However, it underwent an ecological crisis and a Haff disease outbreak in 2008–2009. Hydraulic engineering interventions were subsequently implemented, and the lake was closed to tourism and fishing for an extended period. This study provides the first comprehensive analysis of Lake Kotokel’s water level fluctuations from 1985 to 2022 and evaluates hydrochemical data collected between 2015 and 2024. A comparative assessment of the seasonal variability in Lake Kotokel’s condition during 2023–2024 and 2008–2009 was conducted using various water quality indices, including the Russian Specific Combinatorial Water Pollution Index (SCWPI) and Basic Anthropogenic Load Index (ALI), as well as the international National Sanitation Foundation Water Quality Index (NSF-WQI) and Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI). Trophic state indices, such as Carlson’s Trophic State Index (CTSI) and the Trophic Index (TRIX), were also applied. The analysis revealed a seasonal decline in water quality, transitioning from pure (“excellent”) and “light eutrophic” index classifications in spring to polluted (“marginal”) and “hypertrophic” index classifications in summer and autumn. This study demonstrated that a combination of unfavorable factors, including significant lake-level fluctuations, prolonged high temperatures during the vegetative period, and the discharge of fracture-vein waters, led to a sharp decline in water quality and an increase in the lake’s trophic status. Elevated levels of iron, manganese, COD, pH, and ammonium detected in water samples in 2024, alongside incidents of fry mortality in spring and summer and intense algal blooms, raise concerns as they may signal a potential recurrence of Haff disease in the lake. Full article

The impact of drought is intensifying due to climate change, leading to significant environmental consequences, particularly concerning river water quality. While drought is typically classified as meteorological or hydrological, studies assessing its environmental impacts remain limited. Drought-induced hydrological alterations in rivers often degrade water quality, necessitating the development of an environmental drought index. This study introduces a novel methodology for calculating an index to evaluate the effects of drought on river water quality, specifically applied to tributaries of the Nakdong River in South Korea. The index was constructed by reviewing existing water quality and drought indices, selecting relevant parameters, and weighting each factor following the National Sanitation Foundation Water Quality Index (NSFWQI) methodology. Factors integrated into the index encompass both meteorological and hydrological indicators, with priority given to variables measurable in real time. Real-time parameters—such as flow rate, cumulative precipitation, days without rainfall, and sensor-based metrics (pH, electrical conductivity [EC], dissolved oxygen [DO], and total organic carbon [TOC])—were incorporated. Additionally, for rivers with upstream dams, dam discharge data were included to reflect its influence on flow conditions. The applicability of the calculated index was assessed by comparing index values to observed water quality data. A class interval structure was implemented to enhance the index’s usability across diverse riverine conditions. Furthermore, the utility of the index was validated by comparing it to the basin’s target water quality, thereby assessing its sensitivity to drought-induced water quality deterioration. The environmental drought index proposed in this study enables the proactive and real-time monitoring of water quality under drought conditions. When applied to 10 tributaries of the Nakdong River, the index demonstrated a clear correlation between drought conditions and water quality deterioration. This index provides a practical tool for river management, facilitating early response strategies to mitigate water quality impacts associated with environmental drought. Full article

The Water Quality Index (WQI) is a tool designed to provide a singular figure representing the overall water quality status of a water body. This study applies Malaysia WQI, National Sanitation Foundation WQI (NSFWQI) and statistical analysis to investigate the impact of diverse pollution sources on the Brunei River’s water quality, a critical aquatic ecosystem affected by the rapid escalation of urbanization, industrial activities, and agricultural runoff. Principal component analysis (PCA), expert judgement, and correlation analysis were used to propose parameters for developing Brunei River’s WQI. Eight monitoring stations were selected to analyze 16 water quality parameters (pH, water temperature (T), dissolved oxygen (DO), oxidation-reduction potential (ORP), chemical oxygen demand (COD), the five-day biochemical oxygen demand (BOD₅), salinity, electrical conductivity (EC), total dissolved solids (TDS), turbidity, total suspended solids (TSS), ammoniacal-nitrogen (NH₃-N), fecal coliform (FC), total coliform (TC), phosphate and nitrate (NO₃⁻) in this study. The results showed that NSFWQI classified the Brunei River as moderately polluted, while Malaysia (WQI) status was classified as slightly polluted except for Station Q around the quarry area. Statistical analysis revealed that the primary pollution sources are anthropogenic activities such as quarrying, domestic waste, and agricultural and urban runoff. Other specific areas of concern with low WQI and significant pollution levels are situated at Kampong Ayer Stations (N and J) due to proximal anthropogenic activities. The proposed water quality parameters for developing Brunei River’s WQI are pH, DO, EC, FC, NO₃⁻, BOD₅, T, TSS, turbidity and phosphate. This study addresses the current pollution status of the Brunei River and sets a precedent for future research emphasizing collaborative data-driven strategies for water quality management. Full article

Surface water resources have played a fundamental role in the development of human societies. Considering that different agricultural and industrial activities are carried out in the Acacias River basin, the main objective of this research was to analyze the influence of land use on the water quality in this area by identifying the main sources that influence river water quality. The methodology consisted of establishing 12 sampling stations with different land uses at three times. The National Sanitation Foundation-Water Quality Index (NSF-WQI) was applied to the obtained water quality evaluation data. The main results showed that the stations associated with urban centers presented a higher concentration in the following variables: fecal coliforms, biochemical oxygen demand (BOD) and phosphates. The principal components analysis revealed a close relation between the parameters of fecal coliforms, phosphates and BOD, and the pollution processes by organic matter, which are probably related to domestic and industrial wastewater discharges, and to detergents in urbanized areas. The parameters with the greatest range of values were total dissolved solids and turbidity. These results coincide with what was observed in the correlation analysis. Finally, nitrates showed higher concentrations at stations 6 and 7, associated with agricultural and industrial influence areas (i.e., oil palm crops in the basin). This study about the Acacias River is, thus, extremely important for the region, and concludes that the river’s self-purifying capacity allows improved water quality in the areas where the predominant land use is not associated with human settlements. Full article

With increasing urbanization and industrialization, soil and forest resources are facing considerable pressure, as well as the demand for water for domestic, agricultural, and industrial activities. Therefore, it is essential to conduct regular assessments of water quality and ensure that water is consistently maintained in the context of ecosystem services (ESs). Our objective was to apply the driving forces–pressures–state–impacts–responses (DPSIR) model to understand the cause–effect relationships and interactions with anthropogenic pressures on deforestation and water quality in the Talgua River watershed and associated valley and plain areas in central-eastern Honduras. Physicochemical and microbiological analyses were conducted to determine the water quality index (NSF–WQI) and other contamination indexes. The results identified high contamination by coliforms, up to 920.00 NPM/100 mL, and high levels of contamination by organic matter (ICOMO, 0.65), solids (ICOSUS, 0.79), mineralization (ICOMI, 0.99), and the presence of bacteria (BPI, 8.50), as well as the development of eutrophication processes (ICOTRO), resulting in generally low water quality. These problems were caused by the socio-demographic and economic growth of the area, as well as the high demand for water, vulnerability to climate change, and intense agro-livestock and industrial activity, which led to deforestation processes, changes in land use, and contamination of natural water bodies that impacted the overexploitation of aquifers. After applying the DPSIR model, strategies are proposed for the management and administration of the watershed aimed at preserving the water, soils, and forest resources, while promoting stakeholder, business, education sector, and public administration participation. Full article

In the past few decades, global industrial development and population growth have led to a scarcity of water resources, making sustainable management of groundwater a global challenge. The Water Quality Index (WQI) serves as a comprehensive method for assessing water quality and can provide valuable recommendations at the water quality level, optimizing policies for groundwater management. However, the subjectivity and uncertainty of the traditional WQI have negative impacts on evaluation outcomes, particularly in determining indicator weights and selecting aggregation functions. The proposed water quality index for groundwater based on the random forest (RFWQI) model in this study addresses these issues. It selects water quality indicators based on the actual pollution situation in the study area, employs an advanced random forest model to rank water quality indicators, determines indicator weights using the rank centroid method, scores the indicators using a sub-index function designed for groundwater development, and compares the results of two commonly used aggregation functions to identify the optimal one. Based on the aggregated scores, the water quality at 137 monitoring sites is classified into five levels: “Excellent”, “Good”, “Medium”, “Poor”, or “Unacceptable”. Among the 11 water quality indicators (sodium, sulfate, chloride, bicarbonate, total dissolved solids, fluoride, boron, nitrate, pH, COD_Mn, and hardness), chloride was given the highest weight (0.236), followed by total dissolved solids (0.156), and sodium was given the lowest weight (0.008). The random forest model exhibits a good prediction capability before hyperparameter tuning (86% accuracy, RMSE of 0.378), and after grid search and five-fold cross-validation, the optimal hyperparameter combination is determined, further improving the performance of the random forest model (94% accuracy, F1-Score of 0.967, AUC of 0.91, RMSE of 0.232). For the newly developed groundwater sub-index function, interpolation is used to score each indicator, and after comparing two aggregation functions, the NSF aggregation function is selected as the most suitable for groundwater assessment. Overall, most of the groundwater in the study area was of poor quality (52.5% of low quality) and not suitable for drinking. Full article

In this work, the possibility of using four water quality indices (WQIs) to evaluate the quality status of small rivers in the Mediterranean region (Northern Greece) was investigated. The WQIs selected were the NSF WQI, Oregon WQI, CCME WQI and Prati’s Index of Pollution and were applied to three rivers, namely Laspias, Kosynthos and Lissos, located in the prefectures of Xanthi and Rhodope, Northern Greece. The individual indices were calculated based on the values of 11 physicochemical parameters derived from field measurements and chemical laboratory analyses of water samples at two monitoring stations in each river. The in situ measurements and samplings were executed at a frequency of approximately 10 days and lasted 20, 12 and 10 months for rivers Laspias, Kosynthos and Lissos, respectively. The comparative results from the four indices in the three rivers showed that for rivers Kosynthos and Lissos, which had comparable values of physicochemical parameters, Prati’s and CCME indices classified these water bodies into the highest quality classes, the NSF WQI into a slightly lower class and the Oregon WQI into the lowest classes of quality ranking. Regarding Laspias River, whose physicochemical parameter values indicated inferior water quality than the other two rivers, the Oregon index ranked this water body in the lowest quality class, while the other indices in slightly higher classes. In conclusion, regarding the water quality of ephemeral streams in the Mediterranean, it seems that the Oregon index is stricter followed by the NSF, and then, Prati’s and CCME WQIs. Full article

In the face of ongoing anthropogenic climate change, river water quality assessment has become increasingly important for maintaining ecological balance and supporting local and downstream livelihoods. This research aims to create a new water quality index (WQI) to assess water quality in the Andean highlands (>2000 m.a.s.l.) for climate change adaptation and mitigation. We examined water physicochemical and bacteriological parameters and the benthic macroinvertebrate (BM) community in three micro-watersheds in Achupallas, Ecuador, to achieve our goal. We analyzed water quality at 41 sampling points, and samples (replicates) were taken for nine consecutive months. In addition, we evaluated the accuracy of the WQI developed by the U.S. National Sanitation Foundation (NSF) in 1970 (WQI_NSF). The BM community in the Andes highlands was used to develop and calibrate a new WQI, the Andean Biotic Index* (ABI*). We calibrated the ABI* taxon score in the area where the WQI_NSF made the most accurate water quality measurements. Our results show that the sigma value framework quantifies WQI_NSF accuracy. Therefore, a higher sigma value means we measured water quality more accurately. There was no correlation between the WQI_NSF and the Andean Biotic Index (ABI). The ABI* considers the presence of BMs and their sensitivity to pollution to measure water quality. The results also show a strong statistical link between the ABI* and the WQI_NSF. The ABI* can aid mountain communities in adjusting to climate change. Mountain dwellers can monitor a stream’s water quality by observing the BM communities. However, the ABI* is not a substitute for the WQI_NSF or biological studies. Full article

Water quality indices (WQIs) are practical and versatile instruments for assessing, organizing, and disseminating information about the overall quality status of surface water bodies. The use of these indices may be beneficial in evaluating aquatic system water quality. The CCME (Canadian Council of Ministers of the Environment) and NSF (National Science Foundation) WQIs were used for the assessment of surface water (depth = 1 m) in Lake Union, Washington State. These WQIs were used in surface water at Lake Union, Seattle. The modified versions of the applied WQIs incorporate a varied number of the investigated parameters. The two WQIs were implemented utilizing specialized, publicly accessible software tools. A comparison of their performance is offered, along with a qualitative assessment of their appropriateness for describing the quality of a surface water body. Practical conclusions were generated and addressed based on the applicability and disadvantages of the evaluated indexes. When compared to the CCME-WQI, it is found that the NSF-WQI is a more robust index that yields a categorization stricter than CCME-WQI. Full article

The economic development, livelihood and drinking water of millions of people in the central plateau of Iran depend on the Qarah-Chay River, but due to a lack of inappropriate monitoring, it has been exposed to destruction and pollution. Consequently, an assessment of the river’s water quality is of utmost importance for both the management of human health and the maintenance of a safe environment, which can be achieved by determining the best locations for pollution monitoring stations along rivers. In this study, artificial neural networks (ANNs) has been used to optimize the locations for Qarah-Chay River monitoring stations in Markazi province, Iran. The data are collected based on the Iranian Water Quality Index (IRWQI), the US National Sanitation Foundation Water Quality Index (NSFWQI) and the Oregon Water Quality Index (OWQI). The database is given to a multilayer perceptron (MLP) neural network along with a geographic information system (GIS). The output of this study identified six pollution monitoring stations on the river, which are mainly downstream due to the accumulation of land uses and the concentration of pollution. The gradient of the MLP network training courses model from the proposed monitoring stations is 0.062299. In addition, the performance evaluation criteria of the proposed MLP model for F1-score, recall, precision and accuracy were 0.85, 0.84, 0.88 and 0.88, respectively. The results obtained help managers to properly monitor the river’s water resources with accuracy, efficiency and lower cost; furthermore, the findings were able to provide scientific references for river water quality monitoring and river ecosystem protection. Full article

Until now, there was no simple procedure to test the performance of water quality indices (WQIs) or, in other words, to perform their meta-evaluation. The purpose of this study is to provide a meta-evaluation approach of two widely used WQIs and suggestions for selecting one or both of them for application in groundwater quality assessment as proposed by the European Union. The meta-evaluation concept is based on testing the performance of two widely known WQIs by applying classification of Water Framework Directive (WFD; 2000/60/EC) and Groundwater Directive (GWD; 2006/118/EC) which was used as a reference. The Canadian Council of Ministers of Environment (CCME) and National Sanitation Foundation (NSF-WQI) have been selected for evaluation. These WQIs were applied in an agricultural area of the Mediterranean region where six sub-datasets for an entire hydrological year were available. This study uses all the available water quality data (52 monitoring stations × 2 sampling periods × 15 parameters) which is systematically collected at the area studied. The CCME-WQI is a rather strict index since it estimates statistically significantly lower values than the NSF-WQI. Based on the performance of the examined indices, it is shown that, mostly, the CCME-WQI classification findings are close to those of the GWD. Full article