Development of Water Quality Index and Regression Model for Assessment of Groundwater Quality

Ambiga, K.; Annadurai, R.

doi:10.23953/cloud.ijarsg.88

Cited by 11 publications

(3 citation statements)

References 13 publications

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“…Multiple regression analysis determines the relationship between independent and dependent variables. It fits a best line and predicts the impact of two or more independent variables on a dependent variable [16]. The regression model is considered significant and suitable when p-value is smaller than 0.05.…”

Section: Methodsmentioning

confidence: 99%

Surface Water Quality Trends and Regression Model through SPSS in Udaipur, Rajasthan

Choudhary

2021

Preprint

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Surface water quality status and trend of Udaipur's main lakes namely, Fatehsagar, Pichola lake and Udaisagar has been identify through 10 years data collected from ENVIS Centre under on Control of Pollution of Water, Air and Noise, hosted by Central Pollution Control Board. Water quality data was collected for the parameters like BOD, DO, pH, Conductivity, NN, Fecal coliform, Total coliform to determine the water pollution level and water treatment requirements. Overall water quality status has been improved during 2016 to 2019 due to waste water treatment plant. Udaisagar is most polluted lake among three lakes. Fecal coliform was suddenly increased in 2018 due to leakage of sewage line near the Pichola Lake. These lakes are interconnected and very useful for drinking, industrial, agricultural and tourism purpose and proper maintenance will be helpful for all dimensional growth of the city. A regression model for BOD was also developed for these lakes. Dependency of Temperature, pH, Dissolved oxygen, NN, Fecal coliform and Total coliform were checked on BOD through SPSS multiple regression analysis. It is found that only Temperature and Total Coliform affects the values of BOD. The variance analysis showed p-values of < 0.05 and no multicollinearity was diagnosed, with VIF values of < 10.

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Section: Methodsmentioning

confidence: 99%

Surface Water Quality Trends and Regression Model through SPSS in Udaipur, Rajasthan

Choudhary

2021

Preprint

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“…The study states that water quality is dependent on the type of pollutant added and the nature of mineral found. Ambiga et al [15] carried out ground water quality assessment from 35 locations in Ranipet, Vellore district, Tamil Nadu. Different parameters were examined using regression model.…”

Section: Calcium and Magnesiummentioning

confidence: 99%

Review on Physicochemical Characteristics of Ground Water and Their Health Effects

Vohra¹

2023

J. Mech. Constr. Eng.

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Ground water is well described through some physical and chemical characteristics viz temperature, pH, turbidity, electric conductivity, total dissolved solid, total hardness, total alkalinity, nitrates, chlorides, fluorides and metal ions like calcium, magnesium, iron etc. Ground water is commonly used as drinking water for human worldwide, because it is quite economic, easy to use and less vulnerable to contamination than surface water. Nowadays, industrialization, urbanization, fast growth of civilization and increase in population have led to deterioration of the groundwater quality rapidly. Domestic and industrial discharge, landfills, improper drainage system, seepage through sewer lines, agricultural practices such as intense use of pesticides and fertilizers, uneven rainfall and mismanagement are some of major causes for its pollution. Therefore, it is necessary that the quality of ground water should be checked regularly for some physical and chemical parameters as their presence in water above the permissible limit has a serious effect on human health. Hence assessment of physicochemical characteristics of ground water is very important for human health studies and therefore an important research topic in recent years. In the present work, physicochemical characteristics associated with ground water are reviewed along with their health effects.

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“…From the descriptive analysis minimum, maximum, mean, range, standard deviation, variance, skewness and kurtosis were obtained [15]. Correlation analysis is a preliminary bivariate technique adopted to establish the degree of relationship between the parameters involved in a physico chemical process [16]. If the correlation coefficient is close to +1 or -1 then the relationship between the parameters is good and if the coefficient is near zero there is no relationship between the parameters at significant level (p) of < 0.01 [17].…”

Section: Correlation Analysismentioning

confidence: 99%

Groundwater Quality Variation and Regression Analysis � a Case Study Around Municipal Dumpsite in India

Susaiappan¹,

Somanathan²,

Sulthan³

et al. 2021

Rev. Chim.

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The quality of water around a municipal dumpsite is greatly affected by the leaching chemicals from the landfill. The aim of this study is to assess the groundwater quality and to develop and compare the performance of Statistical Package of Social Science (SPSS) regression and Artificial Neural Network models around municipal dumpsite in Tamil Nadu, India. The groundwater samples were collected every month from the 16 sampling points during the study period from January 2013 to December 2017. The physico chemical parameters of the samples such as pH, acidity, alkalinity, Hardness, Chloride, Sulphate and Total Dissolved Solids (TDS) were analysed and Water Quality Index (WQI) was arrived. From this data, the highest and the lowest polluted points S14 and S5 respectively, among the 16 sampling points was found. Correlation analysis showed that TDS exhibited a high positive correlation with chloride and hardness. Two models using SPSS regression and one model using ANN modeling were developed to predict the TDS in the sampling points. The prediction capabilities of the ANN were compared with the SPSS regression models. The maximum percentage of error obtained from ANN and SPSS were 7.5% and 15.6% at S5 sampling point. ANN models were more accurate than the SPSS multi nonlinear regression models having the same inputs and output.

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Development of Water Quality Index and Regression Model for Assessment of Groundwater Quality

Cited by 11 publications

References 13 publications

Surface Water Quality Trends and Regression Model through SPSS in Udaipur, Rajasthan

Surface Water Quality Trends and Regression Model through SPSS in Udaipur, Rajasthan

Review on Physicochemical Characteristics of Ground Water and Their Health Effects

Groundwater Quality Variation and Regression Analysis � a Case Study Around Municipal Dumpsite in India

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