Hydrogeochemical characterization and groundwater quality assessment in a coal mining area, India

Tiwari, Ashwani Kumar; Maio, Marina De; Singh, Prasoon Kumar; Singh, Abhay Kumar

doi:10.1007/s12517-015-2209-5

Cited by 59 publications

(22 citation statements)

References 26 publications

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“…The zones of C4S2 and C3S1 indicate high-to-very high salinity and low-to-medium alkali water, which are not suitable for soils with restricted drainage and it requires a special management for salinity control (Sappa et al 2014) Residual sodium carbonate (RSC) RSC is measured to indicate the sodium hazard in water. Irrigation water having [5 RSC value is considered as harmful to the growth of plants, whereas water having [2.5 RSC value is not considered suitable for irrigation, and \2.5 RSC value is considered as suitable for irrigation (Tiwari et al 2016b). The study area RSC value ranges from 0 to 9 with the mean value of 1 (Table 2).…”

Section: Water Quality Indexmentioning

confidence: 99%

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Groundwater quality assessment using geospatial and statistical tools in Salem District, Tamil Nadu, India

Arulbalaji

Gurugnanam

2016

Appl Water Sci

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The water quality study of Salem district, Tamil Nadu has been carried out to assess the water quality for domestic and irrigation purposes. For this purpose, 59 groundwater samples were collected and analyzed for pH, electrical conductivity (EC), total dissolved solids (TDS), major anions (HCO 3-, CO 3-, F-, Cl-, NO 2-? NO 3-, and SO 4 2-), major cations (Ca 2? Mg 2? , Na ? , and K ?), alkalinity (ALK), and hardness (HAR). To assess the water quality, the following chemical parameters were calculated based on the analytical results, such as Piper plot, water quality index (WQI), sodium adsorption ratio (SAR), magnesium hazard (MH), Kelly index (KI), and residual sodium carbonate (RSC). Wilcox diagram represents that 23% of the samples are excellent to good, 40% of the samples are good to permissible, 10% of the samples are permissible to doubtful, 24% of the samples are doubtful unsuitable, and only 3% of the samples are unsuitable for irrigation. SAR values shows that 52% of the samples indicate high-to-very high and low-to-medium alkali water. KI values indicate good quality (30%) and not suitable (70%) for irrigation purposes. RSC values indicate that 89% of samples are suitable for irrigation purposes. MH reveals that 17% suitable and 83% samples are not suitable for irrigation purposes and for domestic purposes the excellent (8%), good (48%), and poor (44%). The agricultural waste, fertilizer used, soil leaching, urban runoff, livestock waste, and sewages are the sources of poor water quality. Some samples are not suitable for irrigation purposes due to high salinity, hardness, and magnesium concentration. In general, the groundwater of the Salem district was polluted by agricultural activities, anthropogenic activities, ion exchange, and weathering. Keywords Geochemistry Á Water quality index Á Wilcox diagram Á Kelley index Á Magnesium hazard Á Residual sodium carbonate Á USSL diagram

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Section: Water Quality Indexmentioning

confidence: 99%

“…Magnesium hazard (MH) The excess amount of Mg in the groundwater affects the quality of soil, resulting in poor agricultural returns (Tiwari et al 2016b). Magnesium hazard in groundwater [50 is considered as harmful and unsuitable for irrigation use (Szabolcs and Darab 1964).…”

Section: Water Quality Indexmentioning

confidence: 99%

Groundwater quality assessment using geospatial and statistical tools in Salem District, Tamil Nadu, India

Arulbalaji

Gurugnanam

2016

Appl Water Sci

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“…Application of geographical information systems (GIS) provides spatial mapping, which gained immense popularity among the other data interpretation techniques. Its application in water resources becomes inevitable, and several researchers are using this method extensively in their studies [8][9][10][11][12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Assessment of corrosion and scaling potential of the groundwater in the Thanjavur district using hydrogeochemical analysis and spatial modeling techniques

Kumar

2019

SN Appl. Sci.

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In this study, corrosiveness and scaling potential of groundwater in the Thanjavur district are evaluated based on the chemical analyses of 34 groundwater samples and GIS-based geostatistical mapping techniques. Total dissolved solid values show that six out of 34 samples exceeded the WHO drinking water standard 1000 mg/L. Piper plot shows that majority of the samples are mixed Ca-Mg-Cl type, Ca-HCO 3 type and Na-Cl. The results of the physicochemical parameters were used to calculate the most popular corrosion and scaling indices such as Langelier index (LI), aggressive index (AI), Ryznar index (RI), Puckorius index (PI) and Larson-Skold index (LS). Results of LI show that 41% samples have corroding tendency (LI < 0) and 59% of the samples have scaling tendency (LI > 0). AI has the same result as 41% of the water is moderately corrosive and the remaining has scaling tendency. RI suggests that 88% of the samples have corrosive tendency and 12% have rigorous corrosive tendency. Values of the PI suggest that all the samples were corrosive. Finally, the LS values show that 62% of the samples have scaling tendency and the remaining have corrosion tendency. In general, groundwater in the Thanjavur district shows both corrosive and scaling tendencies, which can cause severe damage to the machineries in the industries. Spatial variation of the corrosive and scaling indices suggests that the central region of the district has more corrosive tendencies and the western and eastern regions have more scaling tendencies.

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“…The natural processes like weathering of rocks/soils, atmospheric precipitation etc., play an important role in the chemical constitution of groundwater [1] [2]. Further exploitation of groundwater due to agrarian, industrial and urban activities plays a critical part in the degradation of groundwater quality [3].…”

Section: Introductionmentioning

confidence: 99%

Application of ANN and MLR Models on Groundwater Quality Using CWQI at Lawspet, Puducherry in India

Nathan¹,

Saravanane²,

Sundararajan³

2017

GEP

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With respect to groundwater deterioration from human activities a unique situation of co-disposal of non-engineered Municipal Solid Waste (MSW) dumping and Secondary Wastewater (SWW) disposal on land prevails simultaneously within the same campus at Puducherry in India. Broadly the objective of the study is to apply and compare Artificial Neural Network (ANN) and Multi Linear Regression (MLR) models on groundwater quality applying Canadian Water Quality Index (CWQI). Totally, 1065 water samples from 68 bore wells were collected for two years on monthly basis and tested for 17 physio-chemical and bacteriological parameters. However the study was restricted to the pollution aspects of 10 physio-chemical parameters such as EC, TDS, TH,, Mg 2+ and K + . As there is wide spatial variation (2 to 3 km radius) with ground elevation (more than 45 m) among the bore wells it is appropriate to study the groundwater quality using Multivariate Statistical Analysis and ANN. The selected ten parameters were subjected to Hierarchical Cluster Analysis (HCA) and the clustering procedure generated three well defined clusters. Cluster wise important physiochemical attributes which were altered by MSW and SWW operations, are statistically assessed. The CWQI was evolved with the objective to deliver a mechanism for interpreting the water quality data for all three clusters. The ANOVA test results viz., F-statistic (F = 134.55) and p-value (p = 0.000 < 0.05) showed that there are significant changes in the average values of CWQI among the three clusters, thereby confirming the formation of clusters due to anthropogenic activities. The CWQI simulation was performed using MLR and ANN models for all three clusters. Totally, 1 MLR and 9 ANN models were considered for simulation. Further the performances of ten models were compared using R 2 , RMSE and MAE (quantitative indicators). The analyses of the results revealed that both MLR and ANN models were fairly good in pre- 100dicting the CWQI in Clusters 1 and 2 with high R 2 , low RMSE and MAE values but in Cluster 3 only ANN model fared well. Thus this study will be very useful to decision makers in solving water quality problems.

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Hydrogeochemical characterization and groundwater quality assessment in a coal mining area, India

Cited by 59 publications

References 26 publications

Groundwater quality assessment using geospatial and statistical tools in Salem District, Tamil Nadu, India

Groundwater quality assessment using geospatial and statistical tools in Salem District, Tamil Nadu, India

Assessment of corrosion and scaling potential of the groundwater in the Thanjavur district using hydrogeochemical analysis and spatial modeling techniques

Application of ANN and MLR Models on Groundwater Quality Using CWQI at Lawspet, Puducherry in India

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