The Phromhot Canal is the only natural water source for consumption and agriculture the Sa Kaeo special economic zone, Thailand. At present, the Phromhot Canal is facing a serious problem with water quality. Our study carried out to analyze and assess the pollution carrying capacity of the natural water resource. The sampling sites were examined 7 stations cut across the downstream areas. All these stations were served as the control station to represent the actual condition of the Phromhot Canal. The results indicated that the water quality of the Phromhot Canal after flowing through the Aranyaprathet Municipality's wastewater treatment plant (AM's-WWTP) was severely contaminated. Effluents from the AM's-WWTP does not meet the effluent quality standard of the Ministry of Natural Resources and Environment, Thailand. In addition, it can flow into the water body up to 6,439.55 m3/day. The maximum amount of a pollutant (in terms of BOD loading) allowed to enter a water body of the Phromhot Canal should be ≤ 0.08 kgBOD/day (dry period) and 16.52 kgBOD/day (wet period). While the Phromhot Canal has to carry BOD loading up to 51.12 kgBOD/day. For this reason, the Phromhot Canal at after flowing through the WWTP was unable to the pollution carrying capacity. From the field survey, the AM's-WWTP is not suitable for wastewater treatment, which has a capacity of 923.93 m3/day. Therefore, it is necessary to strictly control the drainage of the wastewater from the Aranyaprathet Municipality's wastewater treatment system, both quantitative and geographic.

The changes in diatom assemblages along an urban-to-rural gradient were characterized to assess the ecological status of the Sai Gon River, Vietnam. Diatoms and physico-chemical variables were measured at 10 stations during dry and rainy season. One-way ANOVA showed that diatom metrics and physicochemical variables were significantly different (p < 0.05) between the upper course sites and both the middle- and the lower sites. However, no significant differences were observed between the middle course sites and the lower course sites. Achnanthidium minutissimum and A. exigua were potential indicators of low nutrient in the upper course sites; Melosira granulata and Navicula viridula were preferred moderately eutrophic water in the middle course sites; while Navicula cryptocephala and Nitzschia palea were tolerant to very heavy pollution and dominant in the lower course sites. Canonical correlation analysis (CCA) results showed that concentration of TSS, TN, TP, BOD5 and COD were the most important factors in structuring benthic diatom communities in the Sai Gon River. The results of this study indicated that diatom community was sensitive to changes in urban condition and could be used as an indicator of urbanization.

The present study has been conducted to assess the surface water quality of Halda River from September 2015 to March 2016. DO, BOD5, COD, pH, EC, Chloride, Alkalinity, and Hardness concentrations in water samples have been found to range within 0.93-5.15 mg/L, 30-545 mg/L, 43-983 mg/L, 6.3-7.3, 110-524 uS/cm, 12-56 mg/L, 35-67 mg/L, and 38-121 mg/L, respectively. Multivariate statistical analyses, such as Principal Component Analysis (PCA) as well as Correlation Matrix (CM) have revealed significant anthropogenic pollutant intrusions in water. Cluster Analysis (CA) has indicated decent results of rendering three different groups of resemblance between the two sampling sites, reflecting the different water quality indicators of the river system. A very strong positive linear relation has been found between COD and BOD (1.000), hardness and EC (0.993), pH and DO (0.979), hardness and COD (0.929), hardness and BOD (0.924), EC and COD (0.922), and EC and BOD (0.916) at a significance level of 0.01, proving their common origin entirely from industrial effluents, municipal wastes, and agricultural activities. River Pollution Index (RPI) has indicated that the water from rivers at Kalurghat and Modhunaghat varied from low to high pollution, which is due to the former area's being mostly industrial zone with some domestic sewage, while the latter underwent less industrial activities. On the contrary, lots of agricultural activities have been found in Modhunaghat. Use of river water can pose serious problems to human health and aquatic ecosystem via biological food chain. The present research suggests special preference for proper management of the river with eco-friendly automation along with development of the country's sustainable economic.

The development of a surface water evaluation index is a critical factor in the assessment, restoration and protection of stream water quality. Quantifying water pollution in specific grade using dominant parameters is important, as this can explain the current state of water pollution with accuracy. As a result, an integrated multi-parameter water quality index has been developed. It is based on the 10 most prevailing parameters (pH, conductivity, nitrate ions, phosphate ions, Escherichia coli number, cadmium, chromium, lead, copper and manganese) with a scale of 1 to 4, wherein the grades are classified into 1: good; 1.1-1.5: slightly polluted; 1.6-2.0: moderately polluted; 2.1-2.9: heavily polluted and 3.0-4.0: gravely polluted. The measuring stick used was according to the 2011 background values of the World Health Organization (WHO) in which a value of 0.1 was attributed for each, so that the final grade can be calculated. Water quality data were successfully fitted in an integrated multi-parameter water quality index to measure the river water level of pollution, and effectively represented every water bodies. This innovative index is able to quantify pollution with respect to seasons, geography and geomorphology of the respective rivers. Although operative, this index still lacks scientific integrity and as such, more synoptic experiments in the rivers of developing countries are recommended to attain a pragmatic feature.

This study was undertaken to evaluate concentration of Uranium (U) in the drinking water of the Tonk district of Rajasthan (India). The main objective of the study is to determine the distribution of Uranium concentration and the geochemical behavior of Uranium in pre-monsoon (PRM) and post-monsoon (POM) drinking water samples. Uranium was measured by LED fluorimeter. Total 318 drinking water samples were collected for both seasons. It is observed that the water quality of all the samples is within the limits prescribed by WHO (30 µg/L) except a few, and can be used for domestic purposes. The Uranium concentration was found to be in the range 0.21 to 173.72 µg/L with a mean value of 8.58 µg/L in pre-monsoon and 0.21 to 162.34 µg/L with a mean value of 11.22 µg/L in post-monsoon samples. The geochemistry of the study area shows rock-water interaction. The order of average anionic concentration is found to be HCO3 – > Cl – > SO4 2– > NO3 –. Although no definite trend of seasonal variation in the concentration of U was observed, large samples have higher Uranium concentrations in post-monsoon than pre-monsoon.

In the eastern region of the Algerian Northern Sahara, the groundwater is the only resource for drinking water supply and irrigation. This study aimed to assess the physical-chemical quality of groundwater with exposition of the fluoride distribution in the eastern region of Algeria taking as case study Ouargla area. The sampling campaign was carried out in such a way to cover the exploited aquifers (Miopliocene and Senonian).  Water temperature, pH, conductivity, hardness, alkalinity, principal ions (Sodium, Potassium Calcium, Magnesium, Bicarbonates, Nitrates, Sulfates, and Chlorides) and the fluoride content in the groundwater were measured and determined. Examination and validation of obtained results were by the use ionic balance method and the hydrochemical analysis by Piper, Stabler and Richards diagrams. The obtained results of our study show that the groundwater of the Ouargla area presents a chlorinated sodium and potassium facies. Moreover, the groundwater quality in the study area is of poor quality; it is hard and characterized by very high mineralization, The Richards' diagram indicates that the groundwater of the study area are unsuitable for irrigation. The spatial distribution of fluoride ions in groundwater of the terminal complex shows that fluoride levels in Ouargla exceed the World Health Organization standard.

Aquatic macroinvertebrates play significant roles in the benthic zone of the aquatic ecosystem and they have different tolerance level to pollution. Globally, macroinvertebrates are usedas bioindicators in determining the ecological health and water quality status of aquatic ecosystem. Therefore, this study focused on the community structure of benthic macroinvertebrates in River Ugbalo, south-south Nigeria. Macroinvertebrates and physicochemical parameters were sampled in three marked out stations between March 2018 and February 2020. Physicochemical parameters were analyzed following standard procedures, while macroinvertebrates were collected with Kick net and Van Veen grab. Physicochemical parameters showed that the water quality of the three stations sampled were fair considering the values of pH, turbidity, sulphate, nitrate, phosphate, DO, BOD, and EC which were within the World Health Organization and Federal Environmental Protection Agency of Nigeria. Cluster analysis based on Bray- Curtis similarity showed that macroinvertebrates were clustered by stations rather than seasons. A total of 5,580 macroinvertebrates individuals were recorded showing high biodiversity in the river. Diptera was the most abundant Order with 2,488 individuals followed by Odonata with 697 individuals. The least represented Order was Lepidoptera with 13 individuals. The diversity indices showed that Margalef index (5.93), Simpson diversity (0.95), Evenness (0.63), and Shannon-Weiner index (3.30) were highest in Station 1. This research work showed that the water quality of the studied stations was fair and station 3 was the most perturbed station.  We recommend the enactment and enforcement of policies that will lead to aquatic ecosystem restoration.

The aim of this study is to determine the amount of quantitative and qualitative changes in groundwater in the Sarvestan plain in south of Fars province, which is one of the critical plains in Iran in terms of water resources. In this research, zoning maps of electrical conductivity of water in GIS were prepared and various hydrochemical diagrams were illustrated. Different quality parameters of water resources were compared according to the statistical data collected and the experiments performed at the beginning of the 8-year period of the research. Chemical analysis of water samples shows that the groundwater type of most of the studied wells at the beginning of the period (2013) has changed from Ca-Cl and Mg-Cl types to Na-Cl type at end of the time period (2020). Determining the trend of chemical changes shows that the diversity of water samples in terms of anions and cations in water with increasing salinity at the end of the period is less than the variety of samples at the beginning of the period. According to the results of chemical experiments, evaporation, crystallization, and weathering of rocks are the factors that control the composition of groundwater in the study area. This study shows increasing the salinity of groundwater in addition to decreasing precipitation and high water use for agricultural application, due to the type of geological formations, especially the presence of salt domes at groundwater inlets to the plain on the east side of the study area.

The study was conducted to assess surface water quality in Ca Mau peninsula using multivariate statistical analysis. Fifty-one water samples with the parameters of pH, dissolved oxygen (DO), total suspended solids (TSS), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), ammonium (N-NH4+), orthophosphate (P-PO43-) and total coliform were used in the evaluation. Water quality is assessed using national standard and water quality index (WQI). The methods of cluster (CA), discriminant (DA), principal component analysis (PCA) were used to analyze the variation patterns of water quality. The surface water was contaminated with organic matters, suspended solids, nutrients, and microorganisms. DA revealed that DO, TSS, BOD5 and pH contributed 76.91% to the seasonal variation of water quality. Water quality is classified from bad to heavily polluted. CA grouped water quality into 7 clusters and DO, TSS, BOD5, COD and coliform of the clusters 1-3 were significantly higher than those of the clusters 4-7. PCA presented that PC1-PC3 was the main sources affecting water quality, explaining 85.45% of the variation in water quality. The sources of pollution can be human (domestic wastewater, waste from agriculture, fisheries, industry, landfills), natural (hydrological regime, rainwater overflow, river bank erosion). pH, DO, BOD5, COD, TSS, N-NH4+, P-PO43- and coliform have an impact on water quality and need to be continuously monitored. However, for the multivariate statistical method to be more effective, an initial data set with several water quality parameters sampling locations is needed. The current results provide scientific information and support local water quality monitoring activities.

One of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. In this regard, there have many models developed, proposing better management in order to maintain water quality. Most of these models require input parameters that are either hardly available or time-consuming and expensive to measure. Among them, the Artificial Neural Network (ANN) Models, inspired from human brain, are a better choice. The present study has simulated the groundwater quality parameters of Ramhormoz Plain, including Sodium Adsorption Ratio (SAR), Electrical Conductivity (EC), and Total Dissolved Solids (TDS), via ANN and ANN+ Particle Swarm Optimization (PSO) Models and at the end has compared their results with the measured data. The input data for TDS quality parameter is consisted of EC, SAR, pH, SO4, Ca, Mg, and Na, while for SAR, it includes TDS, pH, Na, and Hco3, and as for EC, it involves So4, Ca, Mg, SAR, and pH; all of them, gathered from 2009 to 2015. Results indicate that the highest prediction accuracy for SAR, EC, and TDS is related to the ANN + PSO model with the tangent sigmoid activation function so that both MAE and RMSE statistics have the minimum and R2 the maximum value for the model. Also the highest prediction accuracy is respectively related to EC, TDS, and SAR parameters. Considering the high efficiency of artificial neural network model, by training the PSO algorithm, it can be used in order to make managerial decisions and ensure monitoring and cost reduction results.