Search Results (12)

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

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

Water quality assessments are essential for providing information regarding integrated water resource management processes. This study presents the results of a spatial and seasonal surface water quality assessment of the Burío river sub-catchment in Costa Rica. Fourteen sample campaigns were conducted at eight sample sites between 2005 and 2010. Seasonal variations were evaluated using linear mixed-effects models where dissolved oxygen, total solids, and nitrate showed significant differences between dry and wet seasons (p < 0.05). Cluster analysis identified three clusters at the top, middle, and bottom of the catchment that were consistent with land use patterns, and principal component analysis identified the main parameters that were affecting 84% of the total variance in water quality (biochemical oxygen demand, dissolved oxygen, total phosphate, and nitrate). The National Sanitation Foundation Water Quality Index (NSF-WQI) results indicated the majority of the river consisted of mainly “medium” water quality, although “bad” and “good” water quality results were identified depending on sample site and season. This methodological approach provides a useful monitoring technique for local governments that can be used for further remediation strategies. Full article