Evaluation of water quality using water quality index (WQI) method and GIS in Aksu River (SW-Turkey)

Assessment of Water Quality Profile Using Numerical Modeling Approach in Major Climate Classes of Asia

A river water quality spatial profile has a diverse pattern of variation over different climatic regions. To comprehend this phenomenon, our study evaluated the spatial scale variation of the Water Quality Index (WQI). The study was carried out over four main climatic classes in Asia based on the Koppen-Geiger climate classification system: tropical, temperate, cold, and arid. The one-dimensional surface water quality model, QUAL2Kw was selected and compared for water quality simulations. Calibration and validation were separately performed for the model predictions over different climate classes. The accuracy of the water quality model was assessed using different statistical analyses. The spatial profile of WQI was calculated using model predictions based on dissolved oxygen (DO), biological oxygen demand (BOD), nitrate (NO₃), and pH. The results showed that there is a smaller longitudinal variation of WQI in the cold climatic regions than other regions, which does not change the status of WQI. Streams from arid, temperate, and tropical climatic regions show a decreasing trend of DO with respect to the longitudinal profiles of main river flows. Since this study found that each climate zone has the different impact on DO dynamics such as reaeration rate, reoxygenation, and oxygen solubility. The outcomes obtained in this study are expected to provide the impetus for developing a strategy for the viable improvement of the water environment.

Applying multi-criteria analysis for preliminary assessment of the properties of alginate immobilized Myriophyllum spicatum in lake water samples

The preliminary assessment of the properties of alginate immobilized aquatic weed Myriophyllum spicatum beads-MsAlg in a multi-element system of nine Serbian lakes water samples was done. Herein, the results obtained in the biosorption experiment with MsAlg contents of twenty-two elements analysed by inductively coupled plasma-optical emission spectrometry, biosorption capacity, element removal efficiency, total hardness (TH) and quality index of water (WQI) are presented. Scanning electron microscopy with energy dispersive X-ray spectroscopy was used for the characterization of M. spicatum and its beads. The study showed that aluminium, magnesium and strontium were adsorbed by MsAlg in the water samples from all examined lakes; barium and iron in the water samples from six lakes. The overall average efficiency of MsAlg in biosorption of elements was in the following order: Al > Ba > Sr > Fe > Mg (58.6, 51.7, 48.2, 23.9 and 17.7%, respectively). The increase of TH and WQI values after the biosorption was noticed in all studied lake water samples. The most significant correlations for pH were regarding the contents of B, Mg and Ca, whereas WQI was highly correlated to the contents of B and Mg, and pH. The complexity of the obtained data was explained by Cluster Analysis and Principal Component Analysis, which showed good discrimination capabilities between the water samples taken from different locations. Considering that the invasive M. spicatum is natural, widespread and that its immobilization is cheap and eco-friendly, presented findings could be helpful in further assessment of MsAlg beads for its potential use as biofilter.

Water quality of the Uppanar estuary, Southern India: Implications on the level of dissolved nutrients and trace elements

The current status of the water quality in terms of nutrients and trace elements were assessed in the Uppanar river estuary, Southern India. Twenty-five sampling stations were monitored in the study area, which is dominated by anthropogenic activities such as agriculture, settlements and fishing harbour in the downstream. Whereas, the upstream and midstream is dominated by barren lands and industrial hub respectively. Nutrients and trace elements such as nitrate, phosphate, iron and lead exceed the permissible limit of WHO drinking water guidelines. The water quality index derived from WHO permissible limits reveal that most of the samples fall under fair to good category. The marginal to fair water quality is noticed in the midstream to downstream region, where anthropogenic activities are high. The multivariate statistical analysis divulges that the overall water quality is controlled by two major sources such as natural weathering of soil/bedrock and agricultural and industrial activities.

Spatiotemporal variations of hydrogeochemistry and its controlling factors in the Gandaki River Basin, Central Himalaya Nepal

The characterization and assessment of water quality in the head water region of Himalaya is necessary, given the immense importance of this region in sustaining livelihoods of people and maintaining ecological balance. A total of 165 water samples were collected from 55 sites during pre-monsoon, monsoon and post-monsoon seasons in 2016 from the Gandaki River Basin of the Central Himalaya, Nepal. The pH, EC values and TDS concentrations were measured in-situ and the concentrations of major ions (Ca²⁺, Mg²⁺, K⁺, Na⁺, Cl^-, SO₄^2-, NO₃^-) and Si were analyzed in laboratory. Correlation matrices, paired t-test, cluster analysis, principal component analysis (PCA), the Piper, Gibbs, and Mixing plots, and saturation index were applied to the measurements for evaluating spatiotemporal variation of the major ions. The results reveal mildly alkaline pH values and the following pattern of average ionic dominance: Ca²⁺>Mg²⁺>Na⁺>K⁺ for cations and HCO₃^->SO₄^2->Cl^->NO₃^- for anions. The results of PCA, Gibbs plot and the ionic relationships displayed the predominance of geogenic weathering processes in areas with carbonate dominant lithology. This conclusion is supported by geochemically different water facies identified in the Piper plot as Ca-HCO₃ (83.03%), mixed Ca-Mg-Cl (12.73.0%) and Ca-Cl (4.24%). Pronounced spatiotemporal heterogeneity demonstrates the influence of climatic, geogenic and anthropogenic conditions. For instance, the Ca²⁺-SO₄^2-, Mg²⁺-SO₄^2- and Na⁺-Cl^- pairs exhibit strong positive correlation with each other in the upstream region, whereas relatively weak correlation in the downstream region, likely indicating the influence of evapo-crystallization processes in the upstream region. Analyses of the suitability of the water supply for drinking and irrigation reveal that the river has mostly retained its natural water quality but poses safety concern at a few locations. Knowledge obtained through this study can contribute to the sustainable management of water quality in the climatically and lithologically distinct segments of the Himalayan river basins.

Optofluidic Technology for Water Quality Monitoring

Water quality-related incidents are attracting attention globally as they cause serious diseases and even threaten human lives. The current detection and monitoring methods are inadequate because of their long operation time, high cost, and complex process. In this context, there is an increasing demand for low-cost, multiparameter, real-time, and continuous-monitoring methods at a higher temporal and spatial resolution. Optofluidic water quality sensors have great potential to satisfy this requirement due to their distinctive features including high throughput, small footprint, and low power consumption. This paper reviews the current development of these sensors for heavy metal, organic, and microbial pollution monitoring, which will breed new research ideas and broaden their applications.

Multi-scale analysis of the relationship between landscape patterns and a water quality index (WQI) based on a stepwise linear regression (SLR) and geographically weighted regression (GWR) in the Ebinur Lake oasis

Water quality is highly dependent on landscape characteristics. This study explored the relationships between landscape patterns and water quality in the Ebinur Lake oasis in China. The water quality index (WQI) has been used to identify threats to water quality and contribute to better water resource management. This study established the WQI and analyzed the influence of landscapes on the WQI based on a stepwise linear regression (SLR) model and geographically weighted regression (GWR) models. The results showed that the WQI was between 56.61 and 2886.51. The map of the WQI showed poor water quality. Both positive and negative relationships between certain land use and land cover (LULC) types and the WQI were observed for different buffers. This relationship is most significant for the 400-m buffer. There is a significant relationship between the water quality index and landscape index (i.e., PLAND, DIVISION, aggregation index (AI), COHESION, landscape shape index (LSI), and largest patch index (LPI)), demonstrated by using stepwise multiple linear regressions under the 400-m scale, which resulted in an adjusted R ² between 0.63 and 0.88. The local R ² between the LPI and LSI for forest grasslands and the WQI are high in the Akeqisu River and the Kuitun rivers and low in the Bortala River, with an R ² ranging from 0.57 to 1.86. The local R ² between the LSI for croplands and the WQI is 0.44. The local R ² values between the LPI for saline lands and the WQI are high in the Jing River and low in the Bo River, Akeqisu River, and Kuitun rivers, ranging from 0.57 to 1.86.

A new method for water quality assessment: by harmony degree equation

Water quality assessment is an important basic work in the development, utilization, management, and protection of water resources, and also a prerequisite for water safety. In this paper, the harmony degree equation (HDE) was introduced into the research of water quality assessment, and a new method for water quality assessment was proposed according to the HDE: by harmony degree equation (WQA-HDE). First of all, the calculation steps and ideas of this method were described in detail, and then, this method with some other important methods of water quality assessment (single factor assessment method, mean-type comprehensive index assessment method, and multi-level gray correlation assessment method) were used to assess the water quality of the Shaying River (the largest tributary of the Huaihe in China). For this purpose, 2 years (2013-2014) dataset of nine water quality variables covering seven monitoring sites, and approximately 189 observations were used to compare and analyze the characteristics and advantages of the new method. The results showed that the calculation steps of WQA-HDE are similar to the comprehensive assessment method, and WQA-HDE is more operational comparing with the results of other water quality assessment methods. In addition, this new method shows good flexibility by setting the judgment criteria value HD₀ of water quality; when HD₀ = 0.8, the results are closer to reality, and more realistic and reliable. Particularly, when HD₀ = 1, the results of WQA-HDE are consistent with the single factor assessment method, both methods are subject to the most stringent "one vote veto" judgment condition. So, WQA-HDE is a composite method that combines the single factor assessment and comprehensive assessment. This research not only broadens the research field of theoretical method system of harmony theory but also promotes the unity of water quality assessment method and can be used for reference in other comprehensive assessment.

Assessing river water quality using water quality index in Lake Taihu Basin, China

Lake Taihu Basin, one of the most developed regions in China, has received considerable attention due to its severe pollution. Our study provides a clear understanding of the water quality in the rivers of Lake Taihu Basin based on basin-scale monitoring and a water quality index (WQI) method. From September 2014 to January 2016, four samplings across four seasons were conducted at 96 sites along main rivers. Fifteen parameters, including water temperature, pH, dissolved oxygen (DO), conductivity, turbidity (tur), permanganate index (COD_Mn), total nitrogen, total phosphorus, ammonium (NH₄-N), nitrite, nitrate (NO₃-N), calcium, magnesium, chloride, and sulfate, were measured to calculate the WQI. The average WQI value during our study period was 59.33; consequently, the water quality was considered as generally "moderate". Significant differences in WQI values were detected among the 6 river systems, with better water quality in the Tiaoxi and Nanhe systems. The water quality presented distinct seasonal variation, with the highest WQI values in autumn, followed by spring and summer, and the lowest values in winter. The minimum WQI (WQI_min), which was developed based on a stepwise linear regression analysis, consisted of five parameters: NH₄-N, COD_Mn, NO₃-N, DO, and tur. The model exhibited excellent performance in representing the water quality in Lake Taihu Basin, especially when weights were fully considered. Our results are beneficial for water quality management and could be used for rapid and low-cost water quality evaluation in Lake Taihu Basin. Additionally, we suggest that weights of environmental parameters should be fully considered in water quality assessments when using the WQI_min method.

Water quality assessment of the ecologically stressed Hooghly River Estuary, India: A multivariate approach

Spatio-temporal and seasonal variation of the water quality characteristics of the Hooghly River Estuary, India were studied considering eight stations of diverse eco-hydrological characteristics. Wide variations in turbidity, total dissolved solids and fecal coliform exceeded the permissible BIS drinking water level limit. The estuary is observed to be relatively low-oxygenated, mesotropic and phosphate limiting. Spatial heterogeneity and impact of the southwest monsoon were remarkably pronounced in the distribution of the inorganic nutrients revealing the following values (expressed in μgatml^-1): nitrate+nitrite (2.42-37.19), phosphate (0.41-1.52) and silicate (38.5-187.75). Water Quality Index (WQI) values confirmed the prevailing 'bad' condition, detrimental for sustenance of aquatic biota. Results of Principal Component Analysis identified the major factors liable for water quality deterioration while cluster analysis categorized the stations on the basis of similar water quality status. The authors recommend adopting preventive measures for water quality improvement linked to biodiversity conservation.

Water quality assessment based on the water quality index method in Lake Poyang: The largest freshwater lake in China

Twenty-four samplings were conducted every 3 months at 15 sites from January 2009 to October 2014 in Lake Poyang, and 20 parameters were analyzed and classified into three groups (toxic metals, easily treated parameters, and others). The assessment results based on water quality index (WQI) showed that the water quality in Lake Poyang was generally "moderate", according to the classification of the surface water quality standard (GB3838-2002) in China, but a deteriorating trend was observed at the interannual scale. Seasonally, the water quality was best in summer and worst in winter. Easily treated parameters generally determined the WQI value in the assessment, especially total nitrogen (TN) and total phosphorus (TP), while toxic metals and other parameters in Lake Poyang were generally at low and safe levels for drinking water. Water level (WL) has a net positive effect on water quality in Lake Poyang through dilution of environmental parameters, which in practice means TN. Consequently, local management agencies should pay more attention to nutrient concentrations during the monitoring schedule, as well as during the low-water periods which manifest a relatively bad water quality state, especially with the prevailing low WL observed recently in Lake Poyang.

Water quantity and hydrochemical quality monitoring of Laspias River, North Greece

The water quantity and quality of Laspias River, located in Xanthi Prefecture, Thrace, North Greece, are studied. A data collection program was designed at five stations along the main river course and its main tributary. Sampling frequency was about once every 10 days. Temperature (T), electrical conductivity (EC), pH, and dissolved oxygen were measured in situ simultaneously with discharge measurements. Moreover, water samples were collected and analyzed for the determination of nitrites, nitrates, ammonium, total phosphorus, biochemical oxygen demand, chemical oxygen demand, total suspended solids and alkalinity, according to standard methods. Anions (i.e., SO₄^-2 and Cl^-) and cations (i.e., Li⁺, Na⁺, Mg⁺², and Ca⁺²) were determined using ion chromatography (Dionex ICS-3000 ion chromatograph). The results showed that there is an impact of point (e.g., wastewater treatment plant effluent and farms) and non-point (e.g., agricultural activities) sources of pollution on the EC values, and chloride, nitrogen and phosphorus concentrations in the river water. The trophic state of Laspias River, based on nutrient concentrations, was found eutrophic. Based on the Canadian Council of Ministers of Environment Water Quality Index, the river water quality ranged from "poor" to "marginal" category, indicating the need for management measures in order to improve it.

Evaluation of water quality based on a machine learning algorithm and water quality index for the Ebinur Lake Watershed, China

The water quality index (WQI) has been used to identify threats to water quality and to support better water resource management. This study combines a machine learning algorithm, WQI, and remote sensing spectral indices (difference index, DI; ratio index, RI; and normalized difference index, NDI) through fractional derivatives methods and in turn establishes a model for estimating and assessing the WQI. The results show that the calculated WQI values range between 56.61 and 2,886.51. We also explore the relationship between reflectance data and the WQI. The number of bands with correlation coefficients passing a significance test at 0.01 first increases and then decreases with a peak appearing after 1.6 orders. WQI and DI as well as RI and NDI correlation coefficients between optimal band combinations of the peak also appear after 1.6 orders with R² values of 0.92, 0.58 and 0.92. Finally, 22 WQI estimation models were established by POS-SVR to compare the predictive effects of these models. The models based on a spectral index of 1.6 were found to perform much better than the others, with an R² of 0.92, an RMSE of 58.4, and an RPD of 2.81 and a slope of curve fitting of 0.97.