Water Quality Analysis Research Articles

Empowering Navajo Nation's Water Quality Monitoring through State-of-the-Art Paper-Electrochemical Sensors

The NSF-PREM research collaborative effort between Navajo Technical University (NTU) and Harvard University aims to address the critical issue of water contamination within the Navajo Nation. Decades of uranium mining and mineral extraction have left a lasting mark on the Navajo land and groundwater resources, necessitating effective solutions. The Nano-electrochemical Analysis and Energy Storage Laboratory (NEST LAB) at NTU has developed flexible paper-based sensors integrated with advanced electrochemical techniques to detect heavy metal concentrations in water samples. These sensors are cost-effective, easy to fabricate, and highly reliable, offering real-time monitoring capabilities. The projects core goal is to expedite water quality analysis and empower the Navajo community to detect potential contamination promptly. By distributing these sensors to local chapter houses, residents can independently assess groundwater quality, fostering a sense of ownership and proactive environmental stewardship. This partnership exemplifies the power of community-driven solutions and trains Navajo students to get involved in scientific innovation to safeguard the environment for future generations in the Navajo Nation.

Spatiotemporal variation of water quality in the context of suspended particulate matter in Laguna Mar Chiquita Lake, Argentina using ACOLITE

This study investigates seasonal variations in water quality at Laguna Mar Chiquita Lake, Argentina, by employing remote sensing techniques to analyze Suspended Particulate Matter (SPM) which offers valuable insights into the lake's environmental health. Landsat 8–9 OLI/TIRS data from 2014–2023 was utilized for spectral analysis of water quality, processed using ACOLITE software for accurate quantitative data. Results show SPM concentrations ranging from 0.823 to 44.172 mg/l, with significant seasonal variations. Higher SPM concentrations post-monsoon indicate increased anthropogenic influence, particularly in the northern area. Pollution from tourism and industrial activities is lower pre-monsoon but spikes post-monsoon and during monsoon, suggesting unfavorable conditions. Effective management and continuous monitoring are crucial for maintaining lake quality and ecosystem health.

A comprehensive analysis of water quality of open wells at Alevuru and Badagabettu-76 village of Udupi Taluk, Karnataka, India

Abstract The availability of pure water is one of the most essential requirements for all living organisms. In rural areas of Udupi, Karnataka, India, well water serves as the primary source of water for residents. Hence the objectives of the study were to find the physical and chemical characteristics of the well water sources in Udupi taluk; and to assess the suitability of the well water sources in Udupi taluk for drinking purposes by determining water quality index (WQI). Water samples (n=24) were collected from open wells from Alevuru and Badagabettu-76 villages of Udupi taluk during October 2023. Water quality parameters analyzed were pH, total dissolved solids, electrical conductivity, turbidity, total alkalinity, total hardness, dissolved oxygen, nitrate, chloride, sulphate, chemical oxygen demand and iron. The WQI revealed that the well water in majority of the sites was fit for drinking. All parameters were within the permissible limits in majority of the wells except for iron and pH.

Evaluation of SENTINEL-2 products-based algorithms in estimating water pollutants of the River Niger in Bamako

Monitoring surface water quality on a spatio-temporal scale is very important to restrict the entry of polluting components into water bodies, particularly rivers. Traditional techniques of assessing water quality are typically costly and time-consuming. With the advent of remote sensing technologies and the availability of high-resolution satellite images in recent years, a significant opportunity for water quality monitoring has arisen. Our study aims to test the use of Sentienl-2 multispectral imaging sensors in estimating three important water quality parameters: chlorophyll-a, Colored Dissolved Organic Matter and Total Suspended Matter in Niger River. Sentinel-2 satellite data were acquired in 2020. Atmospheric correction was performed using Sen2cor from the Sentinel toolbox to obtain a geometrically corrected Sentinel-2 multispectral image. We selected multiple water-body indices from the literature based on their spectral reflection characteristics, analyze correlations between the reflectance values of water body indices and the water quality parameters of synchronous measured sampling points in order to obtain an optimal water body index for estimating water quality parameters (WQP) in Niger River. Five regression functions were used in this study: linear regression, exponential, logarithmic, power and polynomial regression. The performance and accuracy of these regression models were evaluated by correlating spectral reflectance band ratio against the in situ water quality parameters (WQP) concentrations. Polynomial regression gave a higher performance and accuracy based on their R values. The best spectral index was selected to assess the spatio-temporal distribution of water pollutants in the Niger River in Bamako and its surroundings. The results showed that the polynomial regression of 6th degree provided the best fit had the best spectral band ratio and in situ Chl-a, CDOM and TSM concentrations which were respectively achieved with band index of B2/B3 (R2 = 0.78), B3/B6 (R 2 = 0.79) and B3/B4 (R 2 = 0.63). Therefore, the best band ratio was selected to evaluate Chl-a spatio-temporal in Niger River water in Bamako. The results of this study showed seasonal variability of the water pollutants in the Niger River. This highlights the potential of the Sentinel-2 products for water quality analysis. As a conclusion, the Sentinel-2 images could be helpful for precise water quality control of Niger River in Bamako.

Water quality constrained adjustment planning for regional breeding management with nonlinear programming model under uncertainty in Wenchang City, China

Basin water pollution caused by livestock, poultry and fish breeding is still a serious problem for remote villages, however, reliable regional breeding management programming have the potentials to improve pollution status. This paper focuses on the optimal model design and water quality analysis of the livestock, poultry and fish breeding system for Wenchang City, China. Methods of multi-objective programming (MOP), interval parameter programming (IPP), fuzzy-stochastic parameter programming (FSPP), and chance constrained programming (CCP) were incorporated into the developed model to tackle multi uncertainties described by interval values, probability distributions, fuzzy membership function. Based on the estimation of local breeding potential and current situation of surface water section, a multi-objective mixed fuzzy-stochastic nonlinear programming optimization model is presented with one-dimensional water quality model. In order to evaluate the environmental carrying capacity of livestock, poultry and fishery manure, predict its development trend and investigate the implementation effect of different emission reduction policies, this paper designs quantization system of the urban water environmental carrying capacity for the model. The results indicated that the water environment pollutant absorption capacity and carrying capacity of Wenchang city have approached the limit especially the towns in the northeast of City which limited the overall development space of the City. The modeling results are valuable for supporting the adjustment of the existing livestock, poultry and fish breeding schemes within a complicated system benefit and surface water quality situation under uncertainty.

Water Quality Identification and Analysis of Saguling Reservoir, West Bandung Regency

The Saguling Reservoir in West Bandung Regency is crucial for local water supply and biodiversity. However, water quality has significantly declined due to human activities, environmental changes, and poor waste management. This degradation jeopardizes the reservoir's clean water supply and the ecological health of surrounding communities. This research used the STORET (Storage and Retrieval) method to assess water quality through purposive sampling in the most affected zones, analyzing physical, chemical, and biological parameters at multiple depths. Key indicators, such as dissolved oxygen, nutrient concentrations, and heavy metal presence, were measured. Results show severe water quality deterioration, especially in deeper sections with less sunlight and aeration. Elevated nitrate and phosphate levels, mainly from agricultural runoff and residential waste, exceeded environmental safety standards. Toxic heavy metals like lead and mercury were also detected, posing serious risks to aquatic life and human health. The study highlights that deeper water zones are critically impacted by pollutants, stressing the need for better regulatory frameworks and waste management. Immediate strategic interventions are crucial to restore and protect the Saguling Reservoir's water quality for future generations.

Integration of Geophysical and Hydrochemical Methods to Determine the Groundwater Contamination in Al-Hosayniat Landfill South East Mafraq City, Jordan

An integration of Geophysical – Electromagnetic and hydro-chemical methods was used to investigate the potential of groundwater contamination due to Al-Hosayniat Municipal Landfill (HL) southeast of Mafraq city. Twenty-five Time Domain Electromagnetic (TDEM) soundings were carried out inside and outside the HL in addition to one WNW-ESE Very Low Frequency (VLF) profile. The TDEM's results help to define the subsurface geology and structures down to 240m depth. The results also depict the presence of a major fault striking NW-SE that crosses the whole landfill, this fault is documented in the surface geological map, and it was delineated and imaged by TDEM measurements and detected at larger depths. VLF results also detected the presence of a major fault beneath the landfill. The presence of the fault just beneath the HL may enhance the leachate movement which can imply groundwater contamination hazards for a longer period as it is a preferential pathway for contaminants. The results of water quality analyses of adjacent wells show higher concentrations of Na+, SO-24, TDS in some wells and this can be ascribed to agricultural activities and over-pumping in the area rather than landfill leachate. The heavy metal concentrations were found to be within the permissible limits and did't indicate direct contamination due to the HL. However, Fluorite (F-) shows a high concentration of (1.3mg/l) in WS4 and WS5 wells and approaches the permissible limit (1.5mg/l) according to the Jordan Water Standards (JWS). Bromide (Br) shows high concentration of (0.6mg/l) in well Al-2462.

NITRINET: A predictive model for nitrification in reclaimed water distribution in pressurised irrigation networks

In this work, a new model (NITRINET) to simulate nitrification processes in pressurised irrigation distribution networks fed with reclaimed water is developed and applied to the Tintín Irrigation District distribution network as case study (Montilla, southern Spain). The importance of this model relies on the fact that the nutrient chemical composition of reclaimed water varies spatially along the network. The water quality analyses carried out in the Irrigation District have shown that nitrate concentrations increase along the distribution network in contrast to the reduction observed in the ammoniacal forms. This confirms that nitrification processes occur inside the pipes. Thus, the model combines the hydraulic simulation of the distribution network and the modelling of nitrification processes to predict the concentration of ammoniacal nitrogen (NH4+-N) and nitric nitrogen (NO3--N) in water arriving at farms. This model is of great applicability to the irrigation sector, given that to carry out precision fertigation strategies and optimise the amount of fertiliser applied, it is necessary to determine the concentration of nutrients present in water arriving at farms. The nutrients that reclaimed water already carries must be considered when planning fertilisation. This allows for a reduction in the amount of fertiliser applied to the soil, which has a positive impact both on the environment and on farmers’ incomes. Simulations performed with NITRINET have shown promising results, predicting the concentration of NH4+-N and NO3--N in irrigation water with mean absolute errors of 1.49 mg·L−1 and 1.25 mg·L−1, respectively.

Comparative analysis of water quality in two Wetlands of Berhampore, Murshidabad, West Bengal

Comparative analysis of water quality in two Wetlands of Berhampore, Murshidabad, West Bengal

Water quality analysis and source apportionment in estuaries along the coast of the Bohai Sea, North China

Water quality analysis and source apportionment in estuaries along the coast of the Bohai Sea, North China

Assessment of water quality from different water supply sources in the Kyiv district of the city of Kharkiv

Purpose To evaluate the quality of drinking water from various sources of water supply on the example of the Kyiv district of the city of Kharkiv. Methods. Field (selection of water samples from various sources), laboratory-analytical analysis of water quality, statistical (processing of received data and comparative analysis). Results. Water samples were taken from various sources of water supply: natural spring water, water from wells, from a well, from the city water supply and from drinking water dispensers. In the samples of artesian water of the "Roganska" trade mark (automatic water dispenser), no exceeding of the normative values ​​was determined for any indicator. Water samples from wells and centralized water supply have elevated levels of total hardness, chlorine, nitrate and iron content, which requires the restriction of their use as drinking water without additional treatment. Water samples from private wells have an increased level of general mineralization, salinity and electrical conductivity of water. Methods of purifying tap water from common salts at home were studied: water freezing, filtration, settling, boiling. Conclusions. On the basis of organoleptic, physico-chemical and toxicological parameters of water quality, according to DSTU 4808, water from the machine of TM "Roganska" corresponds to the 1st quality class, spring water - 2nd class, water from wells - 3rd class, and water from a well and centralized water supply - 4th class. In order to improve the quality of tap water from common salts at home, freezing and filtration are recommended.

Times series record of water quality analysis during flood time in Cauvery River basin, Tamil Nadu, India

We determine the spatial and temporal changes in the physicochemical and nutritional parameters of water quality in the Cauvery River basin. We also analyze the effects of anthropogenic and natural factors on the physicochemical and nutritional parameters. The river water samples were collected over a time series record of 6-h intervals for 6 days during and after flooding time. The combination of physicochemical and nutritional parameters generated a large dataset, which was processed using statistical analysis. In addition, statistical analysis was used to calculate the correlation coefficients and plot the regression equations relating various parameters to electrical conductivity (EC). The resulting average values of pH, EC, and total dissolved solids (TDS) showed significant differences in the time series record of the study period (i.e., pH = 8.24, EC = 220 S/m, and TDS = 157.1 mg/L). The values of the following nutritional parameters in floodwater were also determined: orthophosphate = 0.13 mg/L, phosphate = 0.1 mg/L, nitrite = 2.11 mg/L, nitrate = 0.79 mg/L, and ammonia = 4.47 mg/L. Our findings indicates that flooding can deteriorate the groundwater quality, resulting in a decrease in water quality and an increase in contamination levels, which can have detrimental effects on both the environment and human health. This information is crucial to decision making in flood risk management, water resource planning, and conservation efforts to protect both human and ecological systems.

Screening the Performance of a Reverse Osmosis Pilot-Scale Process That Treats Blended Feedwater Containing a Nanofiltration Concentrate and Brackish Groundwater.

A two-stage pilot plant study has been completed that evaluated the performance of a reverse osmosis (RO) membrane process for the treatment of feedwater that consisted of a blend of a nanofiltration (NF) concentrate and brackish groundwater. Membrane performance was assessed by monitoring the process operation, collecting water quality data, and documenting the blended feedwater's impact on fouling due to microbiological or organic means, plugging, and scaling, or their combination. Fluorescence and biological activity reaction tests were used to identify the types of organics and microorganisms present in the blended feedwater. Additionally, scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) were used to analyze suspended matter that collected on the surfaces of cartridge filters used in the pilot's pretreatment system. SEM and EDS were also used to evaluate solids collected on the surfaces of 0.45 µm silver filter pads after filtering known volumes of NF concentrate and RO feedwater blends. Water quality analyses confirmed that the blended feedwater contained little to no dissolved oxygen, and a significant amount of particulate matter was absent from the blended feedwater as defined by silt density index and turbidity measurements. However, water quality results suggested that the presence of sulfate, sulfide, iron, anaerobic bacteria, and humic acid organics likely contributed to the formation of pyrite observed on some of the membrane surfaces autopsied at the conclusion of pilot operations. It was determined that first-stage membrane productivity was impacted by the location of cartridge filter pretreatment; however, second-stage productivity was maintained with no observed flux decline during the entire pilot operation's timeline. Study results indicated that the operation of an RO process treating a blend of an NF concentrate and brackish groundwater could maintain a sustainable and productive operation that provided a practical minimum liquid discharge process operation for the NF concentrate, while the dilution of RO feedwater salinity would lower overall production costs.

Water quality analysis, treatment, and economic feasibility of water services of the Neora River in the fringe area of Neora-Valley National Park, India

ABSTRACT Surface water assessment is essential for an accurate water management plan. The present investigation was focused on quality analysis, treatment, and economic feasibility of the River Neora, a raw water source in the fringe area of the Neora-Valley National Park, India. Pearson's correlations showed a positive correlation (0.629) between temperature and total solids (TS), whereas a negative correlation (−0.23) for dissolved oxygen with other parameters. In ANOVA, F-value (>1) was obtained for all parameters except BOD5. The water quality index (WQI) was determined to find out whether the river water meets the drinking water requirements for local inhabitants in the lower fringe. A high coliform count (approximately 4.5/100 mL) downstream further warranted the design of an advanced treatment, the electrochemical oxidation batch reactor. To maintain the water quality grade, the estimation of water benefits was mandatory. The water consumption for domestic and non-domestic purposes was calculated at 5,314,400 and 1,470,000,000 L/yr, respectively. Obtainability and no tax coverage might have led to the overexploitation of water, which paved the way for monetary evaluation (US$695.29). This study provided an overview of the potential of River Neora, which can be restored in the long run by adopting the water development policies by the government.

A water quality prediction approach for the Downstream and Delta of Dongjiang River Basin under the joint effects of water intakes, pollution sources, and climate change

Water quality prediction is an important means for scientific water environment management and early warning measures. However, its reliability is often restricted by the uncertainties of parameters and pollution sources. Previous methods for resolving these uncertainties still have shortcomings due to low computational efficiency and incomplete coverage of mechanisms. With insufficient data, they also overlooked revealing the comprehensive impact of water intakes, pollution sources, and climate change on water quality in river networks. Insight understanding migration law and the main driving mechanisms under these factors is crucial for water resources and sustainable socioeconomic development. Here, we developed an efficient multi-scenario ensemble water quality prediction (MEWQP) approach to address the deficiency. The Downstream and Delta of Dongjiang River Basin was the demonstrative case. Firstly, we developed multiple parameters and pollution sources inverse estimation method by incorporating the Water Quality Analysis Simulation Program (WASP), general likelihood uncertainty estimation, and inverse methods to improve accuracy. Secondly, the Markov-Chain was used to predict flows affected by climate change. Thirdly, 60 scenarios were analyzed to quantify the impacts of multiple factors on water quality including 5-day biochemical oxygen demand (BOD5), ammonia nitrogen (NH3-N), and dissolved oxygen (DO), and identify an optimized scheme of water intakes. Results show that: (1) WASP has good performance for BOD5, NH3-N, and DO with Mean Absolute Relative Error of 5.87%, 9.19%, and 15.25%, respectively; (2) pollution sources have the greatest impact, followed by extreme climate and intakes. Their combined impacts are greater than individuals; (3) under non-water intakes DO can be improved by 31%, also offset the impact of climate change by 16%; (4) the optimized scheme of intakes could improve DO by 6%. Therefore, decision-makers should simultaneously adjust water intake and reduce pollution sources to obtain high-quality water resources.

Analysis of Water Quality and Plankton Biodiversity in Conservation Area of PT PHE Raja Tempira

Analysis of Water Quality and Plankton Biodiversity in Conservation Area of PT PHE Raja Tempira

Artificial Intelligence-Based Microfluidic Platform for Detecting Contaminants in Water: A Review.

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing pollution control is to detect contaminants in the water. Various methods have been proposed for water quality testing, such as spectroscopy, chromatography, and electrochemical techniques. However, traditional testing methods require the utilization of laboratory equipment, which is large and not suitable for real-time testing in the field. Microfluidic devices can overcome the limitations of traditional testing instruments and have become an efficient and convenient tool for water quality analysis. At the same time, artificial intelligence is an ideal means of recognizing, classifying, and predicting data obtained from microfluidic systems. Microfluidic devices based on artificial intelligence and machine learning are being developed with great significance for the next generation of water quality monitoring systems. This review begins with a brief introduction to the algorithms involved in artificial intelligence and the materials used in the fabrication and detection techniques of microfluidic platforms. Then, the latest research development of combining the two for pollutant detection in water bodies, including heavy metals, pesticides, micro- and nanoplastics, and microalgae, is mainly introduced. Finally, the challenges encountered and the future directions of detection methods based on industrial intelligence and microfluidic chips are discussed.

Changing soil properties influenced vegetation diversity along effluent‐dominated river courses in dry areas of north‐western India

AbstractImproving the environmental quality of effluent‐dominated seasonal rivers is a fundamental challenge for sustaining life in drylands, where people utilize contaminated water to produce food, which ultimately accumulates in the food chain. Preventing further contaminations and phytoremediation are needed to avoid environmental degradation and health risks. This study aimed at analysing water quality and its impacts on soil and vegetation at effluent‐impacted, river‐edge and non‐polluted (control) micro‐habitats at five sites along Luni, Bandi and Jojari Rivers each in western Rajasthan. Soil and water samples were collected and analysed, and vegetation was recorded. River water exhibited high pH (7.60–8.60), electrical conductivity (EC; 2.45–38.20 dS m−1), total dissolved solid (TDS; 1.26–30.86 g L−1), alkalinity (24.0–250.0 mg L−1) and Na (1.50–30.00 g L−1), K (29.0–1100.0 mg L−1), Ca (136.0–3800.0 mg L−1) and Mn (0.05–83.92 mg L−1) concentrations and low NH4‐N, NO3‐N, PO4‐P and heavy metals. Species numbers ranged between 32 along Luni and 20 along Jojari. Soil pH, EC, PO4‐P and shrub richness (R), diversity (H′) and evenness (e') were highest for Bandi, whereas NH4‐N, NO3‐N, K and tree R and H′ were highest for Jojari River. Soil variables decreased and plant diversity increased downstream. Concentrations of Cd, Zn, Cr, Cu and Pb were above the acceptable limit in leaf of Salvadora persica and Prosopis juliflora. Principal component analysis (PCA) revealed significant relationships between different variables of river water, soil, and vegetation and 11 PCA axes. Conclusively, industry effluents negatively affected water, soil and river ecology. Effluent‐impacted soils had high salinity and less diversity adapted by salt‐tolerant species, complementary effects of which contribute to restoring the modified ecosystem and urban greening. Although people utilize effluent‐contaminated water in irrigation, precautions should be taken to avoid environmental and animal/human health risks.

Water chemical formation mechanism and water quality analysis of Shichuan River under the influence of human activities

ABSTRACT It is necessary to analyze the characteristics of the water environment and factors influencing the basin in order to determine its current ecological status. This study aims to investigate the chemical properties in the Shichuan River Basin using Gibbs diagram, Piper triangle diagram, correlation analysis, factor analysis, and main ion ratio method. The enhanced Nemerow comprehensive index method and fuzzy comprehensive evaluation method are employed for river water quality assessment. The findings reveal that runoff water has a weak alkaline nature with low salinity. The hydrochemical type of river water includes Ca2++Mg2++Na+-SO4 2-, Ca2++Mg2+-SO4 2-+Cl-+HCO3 -, Ca2++Na+-SO4 2-+Cl-+HCO3 -. Silicite and dolomite weathering are identified as primary influencing factors, while evaporite weathering also contributes to variations in chemical composition within the basin's waters. Ca2+, Mg2+, SO4 2- and HCO3 - originate from carbonate rock and silicate rock weathering processes, whereas Na+, K+ and Cl-, are primarily derived from evaporite weathering influenced by domestic sewage and agricultural activities. Agricultural production practices along with discharge of domestic sewage have an impact on Na+, K+, Cl- and NO3 -concentrations in aquatic systems. Water quality at all three monitoring sections falls under level IV classification. Phosphorus emerges as a key limiting factor for eutrophication within this basin's watersheds.

Under the Strong Influence of Human Activities: The Patterns and Controlling Factors of River Water Chemistry Changes—A Case Study of the Lower Yellow River

This study provides an in-depth analysis of the hydrochemical characteristics and their controlling factors in the lower reaches of the Yellow River. Through water quality sampling and analysis over two hydrological periods within a year, combined with hydrochemical methods and machine learning techniques, the study reveals the joint impact of natural factors and human activities on the spatiotemporal variations in hydrochemical constituents. The findings indicate that the water in the lower reaches of the Yellow River exhibits weak alkalinity (the pH is between 7 and 8), with the primary hydrochemical type being HCO3·SO4—Ca·Na·Mg. The temporal variation in the hydrochemical constituents is mainly influenced by rainfall, where nitrate levels are higher during the flood season due to the flushing effect of rainfall, whereas other hydrochemical constituents show an opposite temporal pattern due to the dilution effect of rainfall. The spatial variation in the Yellow River’s hydrochemistry is primarily controlled by a combination of human activities and rainfall. Using Gibbs diagram analysis, it is identified that rock weathering is the main source of ionic constituents, while agricultural fertilization, industrial emissions, and domestic wastewater discharge have significant impacts on the hydrochemical constituents. Compared to other rivers worldwide, the concentration of hydrochemical constituents in the lower reaches of the Yellow River is relatively high, especially nitrate and sulfate, which is closely related to the geological characteristics of the Yellow River basin and intense human activities in the middle and lower reaches. Principal component analysis reveals that the main controlling factors for hydrochemical constituents during the dry season in the lower reaches of the Yellow River are rock weathering dissolution and industrial activities, followed by domestic wastewater; during the flood season, the main controlling factors are rock weathering dissolution and industrial activities, followed by agricultural activities and domestic wastewater. The research findings provide theoretical support for water resource management and water quality protection in the lower reaches of the Yellow River.