Solute Geochemistry and Multivariate Analysis of Water Quality in the Guohua Phosphorite Mine, Guizhou Province, China

Das

et al. 2019

Front. Public Health

Continuous decline in potable water sources has raised serious concerns over human health. Developing countries are the most affected in this regard due to a lack of proper hygiene maintenance. Sikkim, an Eastern Himalayan state with mountains as the predominant topological features, harbors several perennial natural springs. Spring water is the primary source of potable water for the population in four districts of the state viz. East, West, North and South. Recent outbreaks of water-borne diseases and the relative lack of scientific studies on its potential correlation with the water quality of the area have educed this study. Physicochemical parameters of springs, community reservoirs, and household water were analyzed by ICP-MS and multi probe meter. Using the membrane filtration method, the microbial quality of the water samples during different seasons was assessed, primarily evaluating the presence of fecal indicators viz. Escherichia coli , total coliform and Enterococcus . The seasonal risk category of the water sources was also determined. Most of the physicochemical parameters of the spring water were within the permissible limits of WHO standards. However, water from four districts was recorded with traces of toxic heavy metals like mercury (0.001–0.007 mg/l), lead (0.001–0.007 mg/l), and selenium (0.526–0.644 mg/l), which are above the permissible limits of WHO. All the spring water samples were categorized as Mg-HC type and can be predicted as shallow fresh ground water based on the piper analysis. Microbial confirmatory testing indicated severe fecal contamination of water sources with high counts of total coliform (TC), Escherichia coli (EC) and Enterococcus (EN). The highest level of TC was recorded from West Sikkim (37.26 cfu/100 ml) and the lowest in North Sikkim (22.13 cfu/100 ml). The highest level of contamination of E. coli and Enterococcus was found in East Sikkim (EC = 8.7 cfu/100 ml; EN = 2.08 cfu/100 ml) followed by South Sikkim (EC = 8.4 cfu/100 ml; EN = 2.05 cfu/100 ml). There was a significant positive correlation between the contamination levels of the spring water and the community reservoir tank. As far as the seasonal variation is concerned, the rainy season showed the most contamination with coliform correlating with a high incidence of different water-borne diseases (East = 86%; West = 100%; South = 100%; North = 80%).

Section: Methodsmentioning

confidence: 99%

Physicochemical Parameters and Alarming Coliform Count of the Potable Water of Eastern Himalayan State Sikkim: An Indication of Severe Fecal Contamination and Immediate Health Risk

Das

et al. 2019

Front. Public Health

“…The irrigation water quality is determined by the chemical compositions in water and has significant impacts on the production of crops. Irrigation water of excellent quality combined with sustainable agricultural practices can maximize the yield of crops [8,20]. In this research, the quality of irrigation water was evaluated by sodium adsorption ratio (SAR), residual sodium carbonate (RSC), sodium percentage (Na%), permeability index (PI) and magnesium hazard (MH).…”

Section: Irrigation Water Quality Evaluationmentioning

confidence: 99%

Phreatic Water Quality Assessment and Associated Hydrogeochemical Processes in an Irrigated Region Along the Upper Yellow River, Northwestern China

Liu

Zhao

Yang

et al. 2020

Water

Groundwater resources are playing an increasingly vital role in water supply for domestic and irrigation purposes in the Yinchuan Plain, along with the reduction in water transfer from the Yellow River. This study aimed to identify the current status of phreatic water quality and associated hydrogeochemical processes in an irrigated region along the upper Yellow River. A total of 78 water samples were collected in September 2018 for chemical analysis. Results showed that the phreatic water was excellent or good in most areas west of the Yellow River, while it was poor or very poor quality in some places east of the Yellow River. The nitrate contamination is particularly severe in the pluvial-alluvial plain, relating to the localized fine-grained zone with low permeability. Most samples had no sodium hazard but had magnesium hazard. Additionally, the overall evolutionary trend of the phreatic water showed the transformation of Ca-Mg-HCO 3 into Na-Cl-SO 4 type. Rock weathering and evaporation jointly predominate the evolution of phreatic water chemistry. The main geochemical processes involve the dissolution/precipitation of gypsum, halite, dolomite. and calcite, along with the cation exchange. Insights from this work have important implications for groundwater sustainable management in such irrigated regions along the upper Yellow River.

“…Although WQIs are significant tools for assessing water quality in hydrochemical studies, multivariate statistical analysis are often commonly used to evaluate water quality such as Cluster Analysis (CA) [39,40]. Therefore, CA is a multivariate technique to classify the physicochemical parameters into classes according to the interrelation between the chemical constituencies of surface water resources [41].…”

Section: Introductionmentioning

confidence: 99%

Application of Irrigation Water Quality Indices and Multivariate Statistical Techniques for Surface Water Quality Assessments in the Northern Nile Delta, Egypt

Elsayed

Hussein

Moghanm

et al. 2020

Water

Under sustainable development conditions, the water quality of irrigation systems is a complex issue which involves the combined effects of several surface water management parameters. Therefore, this work aims to enhance the surface water quality assessment and geochemical controlling mechanisms and to assess the validation of surface water networks for irrigation using six Water Quality Indices (WQIs) supported by multivariate modelling techniques, such as Principal Component Regression (PCR), Support Vector Machine Regression (SVMR) and Stepwise Multiple Linear Regression (SMLR). A total of 110 surface water samples from a network of surface water cannels during the summers of 2018 and 2019 were collected for this research and standard analytical techniques were used to measure 21 physical and chemical parameters. The physicochemical properties revealed that the major ions concentrations were reported in the following order: Ca2+ > Na+ > Mg2+ > K+ and alkalinity > SO42− > Cl− > NO3− > F−. The trace elements concentrations were reported in the following order: Fe > Mn > B > Cr > Pb > Ni > Cu > Zn > Cd. The surface water belongs to the Ca2+-Mg2+-HCO3− and Ca2+-Mg2+-Cl−-SO42− water types, under a stress of silicate weathering and reverse ion exchange process. The computation of WQI values across two years revealed that 82% of samples represent a high class and the remaining 18% constitute a medium class of water quality for irrigation use with respect to the Irrigation Water Quality (IWQ) value, while the Sodium Percentage (Na%) values across two years indicated that 96% of samples fell into in a healthy class and 4% fell into in a permissible class for irrigation. In addition, the Sodium Absorption Ratio (SAR), Permeability Index (PI), Kelley Index (KI) and Residual Sodium Carbonate (RSC) values revealed that all surface water samples were appropriate for irrigation use. The PCR and SVMR indicated accurate and robust models that predict the six WQIs in both datasets of the calibration (Cal.) and validation (Val.), with R2 values varying from 0.48 to 0.99. The SMLR presented estimated the six WQIs well, with an R2 value that ranged from 0.66 to 0.99. In conclusion, WQIs and multivariate statistical analyses are effective and applicable for assessing the surface water quality. The PCR, SVMR and SMLR models provided robust and reliable estimates of the different indices and showed the highest R2 and the highest slopes values close to 1.00, as well as minimum values of RMSE in all models.