scholarly journals Application of Multivariate Approaches to the Hydro-chemical Assessment of the Ghodaghodi Lake, Sudurpaschim Province, Nepal

2021 ◽  
Vol 19 (2) ◽  
pp. 46-54
Author(s):  
Ramesh Raj Pant ◽  
Khadka Bahadur Pal ◽  
Kiran Bishwakarma ◽  
Lal B Thapa ◽  
Alina Dangol ◽  
...  
Keyword(s):  
Water Quality ◽  
Major Ions ◽  
Monsoon Season ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Total Hardness ◽  
Multivariate Statistical ◽  
Kelly’S Ratio ◽  
Magnesium Adsorption Ratio ◽  
Low Ionic Strength

Wetlands are considered the most diverse and productive ecosystems in the world, providing life-sustaining ecological services. Hydrochemical variables of the Ghodaghodi Lake situated in Far west Nepal were studied using multivariate statistical approaches to investigate the characteristics of water quality of the lake. A total of 10water samples were collected and analyzed for water temperature, pH, electrical conductivity, total dissolved solids, total hardness, salinity, dissolved oxygen, major ions, and dissolved Si in the pre-monsoon season during 2017.The water quality assessment was carried out by applying sodium percentage, sodium adsorption ratio, permeability index, Kelly’s ratio, magnesium adsorption ratio, action ratio of soil structural stability, and water quality index. Multivariate statistical techniques were used to evaluate the geochemical and anthropogenic processes and to identify factors influencing the ionic concentrations. The results revealed that the water was slightly alkaline with low ionic strength and remarkable spatial variations. The hydrochemistry of the lake was mainly controlled by rock weathering as the dominant Ca2+-HCO3- facies. The principal component analysis provided three major components exhibiting the diverse sources of natural and anthropogenic chemicals, including agricultural fertilizers, leakage of sewages near the human settlements, etc. The measured hydrochemical parameters indicate that lake water lies within the safe drinking water and irrigational standards. However, special consideration should be taken to control the concentrations of NO3- due to increasing anthropic activities.

scholarly journals Water quality assessment and geochemical processes in the unconfined coastal Boa Viagem Aquifer, Recife, NE Brazil

2021 ◽  
pp. 56-77
Author(s):  
Thyego Silva ◽  
Mariucha Lima ◽  
Teresa Leitão ◽  
Tiago Martins ◽  
Mateus Albuquerque
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Water Quality Assessment ◽  
Multivariate Statistical Analyses ◽  
Multivariate Statistical ◽  
Rock Interaction ◽  
Groundwater Samples ◽  
Water Rock Interaction

A hydrochemical study was conducted on the Quaternary Aquifer, in Recife, Brazil. Groundwater samples were collected in March–April 2015, at the beginning of the rainy season. Conventional graphics, ionic ratios, saturation indices, GIS mapping, and geostatistical and multivariate statistical analyses were used to water quality assessment and to characterize the main hydrochemical processes controlling groundwater’s chemistry. Q-mode hierarchical cluster analysis separated the samples into three clusters and five sub-clusters according to their hydrochemical similarities and facies. Principal Component Analysis (PCA) was employed to the studied groundwater samples where a three-factor model explains 80% of the total variation within the dataset. The PCA results revealed the influence of seawater intrusion, water-rock interaction, and nitrate contamination. The physico-chemical parameters of ~30% groundwaters exceed the World Health Organization (WHO) guidelines for drinking water quality. Nitrate was found at a concentration >10 mg NO3−/L in ~21% of the wells and exceeded WHO reference values in one. The integrated approach indicates the occurrence of the main major hydrogeochemical processes occurring in the shallow marine to alluvial aquifer as follow: 1) progressive freshening of remaining paleo-seawater accompanying cation exchange on fine sediments, 2) water-rock interaction (i.e., dissolution of silicates), and 3) point and diffuse wastewater contamination, and sulfate dissolution. This study successfully highlights the use of classical geochemical methods, GIS techniques, and multivariate statistical analyses (hierarchical cluster and principal component analyses) as complementary tools to understand hydrogeochemical processes and their influence on groundwater quality status to management actions, which could be used in similar alluvial coastal aquifers.

scholarly journals Water quality assessment of a tropical river using water quality index (WQI), multivariate statistical techniques and GIS

2019 ◽  
Vol 9 (7) ◽  
Author(s):  
Sanjoy Shil ◽  
Umesh Kumar Singh ◽  
Pankaj Mehta
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Monsoon Season ◽  
Saturation Index ◽  
Stability Index ◽  
Water Quality Assessment ◽  
Multivariate Statistical ◽  
Two Samples ◽  
Langelier Saturation Index

Abstract Mahananda River is an important river in India and Bangladesh, as the people of both the countries use the water extensively, without sufficient and reliable information about water qualities and pollution status. The purpose of this study is to evaluate the water quality of the river and to analyse the suitability for drinking, agricultural and industrial uses. This is why this study on the Mahananda River is extremely important for the region. For this study, samples from fourteen sampling stations were collected in pre-monsoon and post-monsoon seasons in 2016 and water quality index (WQI), agriculture and industry-related indices were computed. WQI values designated two sampling stations out of fourteen sampling stations as ‘very bad’ category and another two sampling stations as ‘bad’ category. The pH values of some sampling stations slightly exceeded the upper permissible limit. USSL diagram analysis classified two samples of pre-monsoon season in C2S1 category which indicates a medium salinity and low sodium water. Magnesium hazard values of four sampling stations are above 50% suggesting not suitable for irrigation. However, some indices like sodium per cent, residual sodium carbonate and residual sodium bicarbonate, Kelly’s index, permeability index and potential salinity allow the water for use in irrigation purposes. Langelier Saturation Index and aggressive index values designate the water as moderately aggressive or non-aggressive. Ryznar Stability Index values designate the water as ‘aggressive’ or ‘very aggressive’ indicating unsuitability for industrial uses. Sampling stations S-1, S-2, S-8 and S-14 need special attention.

Hydrochemical Assessment Of Jhilmila Lake, Kanchanpur, Nepal

2021 ◽  
Vol 14 (14) ◽  
pp. 124-131
Author(s):  
Khadka Bahadur Pal ◽  
Kiran Bishwakarma ◽  
Tarka Bahadur Chalaune ◽  
Durga Upadhaya ◽  
Tark Raj Joshi ◽  
...  
Keyword(s):  
Water Quality ◽  
Sustainable Management ◽  
Principal Component ◽  
Organic Pollution ◽  
Quality Parameters ◽  
Standard Test ◽  
Total Hardness ◽  
Test Procedures ◽  
Multivariate Statistical ◽  
Wetland Ecosystems

Freshwater contamination remains a challenging issue for the sustainable management of wetland ecosystems. This study aims to evaluate the water quality of Jhilmila Lake, Kanchanpur, Nepal by adopting standard test procedures, geochemical indices, and multivariate statistical analysis. The surface water samples were collected during the postmonsoon season in 2018 to assess the hydrochemical parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS) and dissolved oxygen (DO), ammonium (NH4+ ), sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), chloride (Cl-), sulphate (SO42-), nitrate (NO3-), phosphate (PO43-), bicarbonate (HCO3-) and total hardness (TH). The EC ranged from 162-190 µS/cm while TDS was 87-101 mg/L. The concentration of DO in the lake was in the range of 4.77-6.21 mg/L, indicated mild organic pollution. Moreover, the results revealed the moderate alkaline nature of water with the pattern of average ionic dominance of Ca2+>Na+>Mg2+ >K+>NH4+ for cations, and HCO3˗> Cl-> SO42- > NO3- > PO43- for anions. The principal component analysis demonstrated four major components indicating the association of EC, TDS, Ca2+, Mg2+, and HCO3- ; Na+ , PO43- and SO42-; NO3- and K+ ; and Cl- for PC1, PC2, PC3, and PC4, respectively exhibiting both the geogenic and anthropic origin. Overall, the Jhilmila Lake was less polluted, and all the measured water quality parameters were found within permissible limits in terms of drinking purposes. The findings of this study could help for the sustainable management of the lake by providing better insights into the water quality and hydrochemistry of the lake.

The Status of Surface Water in West Tripura District, India: An Approach by Using Water Quality Index and Multivariate Statistical Technique

2021 ◽  
Vol 18 (2) ◽  
pp. 27-36
Author(s):  
Biplab Roy ◽  
Ajay Kumar Manna
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Principal Component ◽  
Statistical Technique ◽  
Total Hardness ◽  
Multivariate Statistical ◽  
And Cluster Analysis ◽  
Entropy Weighted

The present investigation provides a better interpretation of surface water (rivers, ponds, bills, lakes, etc.) quality utilising entropy weighted water quality index (EWWQI) and different multivariate statistical techniques. Eleven physicochemical parameters including alkalinity, dissolved oxygen (DO), pH, total dissolved solids (TDS), electrical conductivity (EC), calcium (Ca), turbidity, magnesium (Mg), total hardness (TH), chloride (Cl-), and iron (Fe) were analysed and monitored at 23 sampling sites (in December 2018) of West Tripura district. Experimental outcomes of turbidity followed by Fe contamination exceeded recommended WHO standard limit. The maximum values of Fe and turbidity were estimated as 8.745 mg/L and 797.7 NTU, respectively. WQI values confirmed that most of the monitoring locations had poor water quality except three reported areas (S7, S14, and S15) but without Fe and turbidity, estimated WQI confirmed drinkable water condition for entire samples. Multivariate statistical approaches like correlation analysis, principal component analysis (PCA) and cluster analysis (CA) were applied to explore water quality. PCA outcomes recognised three principal factors explaining almost 85% of the total variance. CA investigated three major clusters of 23 sampling sites namely less polluted, highly polluted and moderately polluted zone. Confirming all above, the surface water at the monitoring locations is a major concern which may lead to serious health issues in local people.

Surface Water Quality in the Forest Catchment – A Case Study of Tunga and Bhadra River Stretches, Karnataka

2020 ◽  
pp. 228-235
Author(s):  
Santhosh Kumar T. M1 ◽  
K. L Prakash
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Monsoon Season ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Water Quality Assessment ◽  
Quality Parameters ◽  
Total Hardness ◽  
Post Monsoon ◽  
Post Monsoon Season

A need of water quality assessment of the rivers before enters into the human induced habitations play a vital role in maintenance of ecological balance. The surface water samples were randomly collected from the Tunga and Bhadra reservoirs situated in the downstream catchments of Western Ghats with semi-evergreen and mixed deciduous forests during January 2018 to December 2019. The samples were analyzed as per the Standard Methods prescribed for drinking water analysis. Increased trend of pH in Pre-monsoon and decreased trend in post monsoon season was observed and the mean concentrations of pH was ranged between 7.30 and 8.02. Electrical Conductivity values were found to be <143µS/cm and indicated that the water is suitable for irrigation and drinking purposes. The Total Dissolved Solids and Total Hardness values were indicated as soft water as values are <75 mg/L. A significant relation was noticed between Dissolved Oxygen (DO) and Biochemical Oxygen Demand during Post monsoon season. Whereas, no relationship was existing with water quality parameters in Tunga River and Bhadra reservoirs during monsoon (2019) wherein highest floods were received in this season. An insignificant pollution load was observed as the water flows through forest areas and no relationship exists between past mining activities in the Bhadra river catchment, sedimentation of reservoir and water quality. However, it is suggested to control of alterations in land use / land cover, use of fertilizer and pesticides, mono culture plantations and developmental activities to maintain the water quality in the study area to meet the domestic demands in the downstream.

scholarly journals Water Quality Assessment of Begnas and Rupa Lakes, Lesser Himalaya Pokhara, Nepal

2019 ◽  
Vol 15 (2) ◽  
pp. 113-122
Author(s):  
Ramesh R. Pant ◽  
Khadka Bdr. Pal ◽  
Nanda L. Adhikari ◽  
Subash Adhikari ◽  
Akkal D. Mishra
Keyword(s):  
Water Quality ◽  
Nitrate Nitrogen ◽  
Monsoon Season ◽  
Oxygen Demand ◽  
Water Quality Assessment ◽  
Total Hardness ◽  
Who Guidelines ◽  
Lesser Himalaya ◽  
Lesser Himalayas ◽  
Potential Pollution

This study was conducted to assess water quality variations and identify potential pollution sources in two lakes namely Begnas and Rupa, Lesser Himalayas Pokhara, Nepal during monsoon season in June 2016. A total of 18 water samples (n= 9, from each lake) were collected and major physicochemical parameters were analyzed: pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), biological oxygen demand (BOD), nitrate-nitrogen (NO3-N), phosphate- phosphorus (PO4-P), ammonia, chloride, free CO2 and total hardness (TH).The results revealed that the water of both lakes were relatively pure with very less TDS as compared to other lakes considered for the comparison with this study. However, the concentrations of CO2 and phosphates were found to be higher than WHO guidelines for drinking water and also indicated the problem of rapid eutrophication in both of the lakes. Thus, the higher concentrations of organic pollutants and the rapid eutrophication process could be the serious threats that should be considered by the concerned authorities for the sustainability of the lakes in future.

Geochemical and multivariate assessment of water quality in the Rajarani Lake, Dhankuta, Nepal

2020 ◽  
Vol 60 ◽  
pp. 37-49
Author(s):  
Ramesh Raj Pant ◽  
Barsha Adhikari ◽  
Upendra Baral ◽  
Suraj Shrestha ◽  
Shristi Neupane ◽  
...  
Keyword(s):  
Water Quality ◽  
Principal Component ◽  
Statistical Technique ◽  
Total Hardness ◽  
Multivariate Statistical ◽  
Major Cations ◽  
Sampling Locations ◽  
Major Anions ◽  
And Cluster Analysis

The Himalayan freshwater lakes embody treasure of the country, crystal-clear nature of which offers water for drinking, irrigation and other domestic purposes, and provides shelter to numerous species, preserve aquatic biodiversity and habitat of the area. Freshwater lake is one of the major sources of livelihood amenities in Nepal and replenishes groundwater, positively influence the quality of downstream watercourses. In the present study, 20 water samples were collected from different points of Rajarani Lake, and analyzed for water temperature, pH, electrical conductivity (EC), total dissolved solids (TDS), oxygen-reduction potential (ORP), turbidity, dissolved oxygen (DO),total hardness (TH), major cations (Ca2+, Mg2+, K+, Na+ and NH4+) and major anions (HCO3-, Cl-, NO3-, and PO43-). The acquired data were interpreted using multivariate statistical technique with principal component analysis (PCA) and cluster analysis (CA) to evaluate controlling factors and characteristics of sampling locations in the lake.PCA results demonstrated major three factors contributing to water quality in lake with a 73.89% of cumulative variance. Similarly, CA results characterized sampling locations into four clusters indicating differentiation in the chemical concentrations. Results of the assessment through PCA, CA and comparison with other Himalayan lakes indicated that Rajarani Lake is not severely affected by pollution because it is still unexplored and thus pristine in nature. This study suggests that water quality of lake environments needs to be further investigated, focusing on depth-wise and temporal levels for its sustainability.

scholarly journals Water quality assessment and source identification of the Shuangji River (China) using multivariate statistical methods

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245525
Author(s):  
Junzhao Liu ◽  
Dong Zhang ◽  
Qiuju Tang ◽  
Hongbin Xu ◽  
Shanheng Huang ◽  
...  
Keyword(s):  
Water Quality ◽  
Discriminant Analysis ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Temporal Analysis ◽  
Statistical Techniques ◽  
Complex Data ◽  
Monitoring Networks ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical

Multivariate statistical techniques, including cluster analysis (CA), discriminant analysis (DA), principal component analysis (PCA) and factor analysis (FA), were used to evaluate temporal and spatial variations in and to interpret large and complex water quality datasets collected from the Shuangji River Basin. The datasets, which contained 19 parameters, were generated during the 2 year (2018–2020) monitoring programme at 14 different sites (3192 observations) along the river. Hierarchical CA was used to divide the twelve months into three periods and the fourteen sampling sites into three groups. Discriminant analysis identified four parameters (CODMn, Cu, As, Se) loading more than 68% correct assignations in temporal analysis, while seven parameters (COD, TP, CODMn, F, LAS, Cu and Cd) to load 93% correct assignations in spatial analysis. The FA/PCA identified six factors that were responsible for explaining the data structure of 68% of the total variance of the dataset, allowing grouping of selected parameters based on common characteristics and assessing the incidence of overall change in each group. This study proposes the necessity and practicality of multivariate statistical techniques for evaluating and interpreting large and complex data sets, with a view to obtaining better information about water quality and the design of monitoring networks to effectively manage water resources.

scholarly journals Multivariate statistical evaluation of dissolved heavy metals and a water quality assessment in the Lake Aha watershed, Southwest China

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9660
Author(s):  
Shilin Gao ◽  
Zhuhong Wang ◽  
Qixin Wu ◽  
Jie Zeng
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Risk Assessment ◽  
Mine Drainage ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Multivariate Statistical ◽  
Small Watersheds ◽  
Dissolved Heavy Metals ◽  
The Impact

Heavy metals are of public concern in aquatic ecosystems due to their growing release from industries and mining activities. This study investigated the sources, temporal-spatial distributions and water quality of dissolved heavy metals (Mn, Co, Al, Ni, Ba, V, Sb, Fe, Sr) in the Lake Aha watershed, an area under the influence of sewage and acid mining drainage. These heavy metals displayed significant spatial and temporal variabilities. The water quality index results (WQI values ranged from 3.21 to 15.64) and health risk assessment (all hazard indexes are below 1) indicated that dissolved heavy metals in this study pose a low risk for human health. Correlation analysis and principal component analysis indicated that Fe and Sr mainly presented a natural geological feature in the study area, and Mn, Co, Al and Ni were influenced by the acid coal mine drainage, whereas Ba, V and Sb were under the impact of local industrial or medical activities. This study provides new insights into the risk assessment of heavy metals in small watersheds.

scholarly journals Combining Water Quality Indices and Multivariate Modeling to Assess Surface Water Quality in the Northern Nile Delta, Egypt

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2142 ◽  
Author(s):  
Mohamed Gad ◽  
Salah Elsayed ◽  
Farahat S. Moghanm ◽  
Mohammed H. Almarshadi ◽  
Abdullah S. Alshammari ◽  
...  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Nile Delta ◽  
Major Ions ◽  
Surface Water Quality ◽  
Principal Component ◽  
Fundamental Aspect ◽  
Pollution Indices ◽  
Least Squares Regression ◽  
Multivariate Statistical

Assessing surface water quality for drinking use in developing countries is important since water quality is a fundamental aspect of surface water management. This study aims to improve surface water quality assessments and their controlling mechanisms using the drinking water quality index (DWQI) and four pollution indices (PIs), which are supported by multivariate statistical analyses, such as principal component analysis, partial least squares regression (PLSR), and stepwise multiple linear regression (SMLR). Twenty-two physicochemical parameters were analyzed using standard analytical methods for 55 surface water sites in the northern Nile Delta, Egypt. The DWQI results indicated that 33% of the tested samples represented good water, and 67% of samples indicated poor to unsuitable water for drinking use. The PI results revealed that surface water samples were strongly affected by Pb and Mn and were slightly affected by Fe and Cr. The SMLR models of the DWQI and PIs, which were based on all major ions and heavy metals, provided the best estimations with R2 = 1 for the DWQI and PIs. In conclusion, integration between the DWQI and PIs is a valuable and applicable approach for the assessment of surface water quality, and the PLSR and SMLR models can be used through applications of chemometric techniques to evaluate the DWQI and PIs.

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