Dataset Information

Data for the evaluation of groundwater quality using water quality index and regression analysis in parts of Nalgonda district, Telangana, Southern India.

ABSTRACT: The main focus of this study is to evaluate the groundwater quality through drinking water quality index and regression analysis in semi-arid region and the results are examined with reference to the drinking water quality standards laid down by WHO. Water quality index (WQI) was determined from fourteen physicochemical parameters like pH, EC, TDS, total hardness, total alkalinity, sodium, potassium, calcium, magnesium, chloride, bromide, nitrate, sulphate and fluoride. The drinking water quality index values range from 32.8 - 442.4, indicating three categories i.e. poor, very poor and unfit, which are inappropriate for drinking. Regarding correlation analysis results, EC, TDS, TH, Na+, Mg2+, Ca2+ and Cl- shows high correlation. Most of the parameters are more or less correlated with each other, regression relations have the same correlation coefficients and pH, Na+, EC, TDS, Mg2+, Ca2+, Cl-, SO4 2-, CO3 2-, TH were significantly positively correlated (R>0.9), indicate the increase in the pollution load.

SUBMITTER: Saikrishna K

PROVIDER: S-EPMC7479319 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Data for the evaluation of groundwater quality using water quality index and regression analysis in parts of Nalgonda district, Telangana, Southern India.

Saikrishna K K Purushotham D D Sunitha V V Reddy Y Sudharshan YS Linga D D Kumar B Kiran BK

Data in brief 20200827

The main focus of this study is to evaluate the groundwater quality through drinking water quality index and regression analysis in semi-arid region and the results are examined with reference to the drinking water quality standards laid down by WHO. Water quality index (WQI) was determined from fourteen physicochemical parameters like pH, EC, TDS, total hardness, total alkalinity, sodium, potassium, calcium, magnesium, chloride, bromide, nitrate, sulphate and fluoride. The drinking water qualit ...[more]

PMID: 32939385

Similar Datasets

Project description:Groundwater resources around the world required periodic monitoring in order to ensure the safe and sustainable utilization for humans by keeping the good status of water quality. However, this could be a daunting task for developing countries due to the insufficient data in spatiotemporal resolution. Therefore, this research work aimed to assess groundwater quality in terms of drinking and irrigation purposes at the adjacent part of the Rooppur Nuclear Power Plant (RNPP) in Bangladesh. For the purposes of achieving the aim of this study, nine groundwater samples were collected seasonally (dry and wet season) and seventeen hydro-geochemical indicators were analyzed, including Temperature (Temp.), pH, electrical conductivity (EC), total dissolved solids (TDS), total alkalinity (TA), total hardness (TH), total organic carbon (TOC), bicarbonate (HCO3-), chloride (Cl-), phosphate (PO43-), sulfate (SO42-), nitrite (NO2-), nitrate (NO3-), sodium (Na+), potassium (K+), calcium (Ca2+) and magnesium (Mg2+). The present study utilized the Canadian Council of Ministers of the Environment water quality index (CCME-WQI) model to assess water quality for drinking purposes. In addition, nine indices including EC, TDS, TH, sodium adsorption ratio (SAR), percent sodium (Na%), permeability index (PI), Kelley's ratio (KR), magnesium hazard ratio (MHR), soluble sodium percentage (SSP), and Residual sodium carbonate (RSC) were used in this research for assessing the water quality for irrigation purposes. The computed mean CCME-WQI score found higher during the dry season (ranges 48 to 74) than the wet season (ranges 40 to 65). Moreover, CCME-WQI model ranked groundwater quality between the "poor" and "marginal" categories during the wet season implying unsuitable water for human consumption. Like CCME-WQI model, majority of the irrigation index also demonstrated suitable water for crop cultivation during dry season. The findings of this research indicate that it requires additional care to improve the monitoring programme for protecting groundwater quality in the RNPP area. Insightful information from this study might be useful as baseline for national strategic planners in order to protect groundwater resources during the any emergencies associated with RNPP.

Dataset Information

Data for the evaluation of groundwater quality using water quality index and regression analysis in parts of Nalgonda district, Telangana, Southern India.

Publications

Data for the evaluation of groundwater quality using water quality index and regression analysis in parts of Nalgonda district, Telangana, Southern India.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets