Evaluation of Surface Water Quality by Using GIS and a Heavy Metal Pollution Index (HPI) Model in a Coal Mining Area, India

Tiwari, Ashwani Kumar; Maio, Marina De; Singh, Prasoon Kumar; Mahato, Mukesh Kumar

doi:10.1007/s00128-015-1558-9

Cited by 149 publications

(71 citation statements)

References 25 publications

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“…Additionally, many complementary methods have been used to strengthen the analysis efficiency. Multivariate statistical analyses to determine heavy metal sources (Race et al, 2015) and geographic information system (GIS) techniques have also been used to assess the spatial distribution of pollutants and determine input sources (Tiwari et al, 2015;Tiwari et al, 2016). Previous studies of heavy metal risk assessment rarely consider spatial-temporal variations in heavy metal pollution.…”

Section: Introductionmentioning

confidence: 99%

Risk analysis of heavy metal concentration in surface waters across the rural-urban interface of the Wen-Rui Tang River, China

Huang

Xia

et al. 2018

Environmental Pollution

211

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Section: Introductionmentioning

confidence: 99%

Risk analysis of heavy metal concentration in surface waters across the rural-urban interface of the Wen-Rui Tang River, China

Huang

Xia

et al. 2018

Environmental Pollution

211

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“…HPI can be classified into three categories: high, medium, and low. High stands for greater than 30, medium for between 15 and 30, and low for less than 15 [31]. In this research we used the ISIRI standard for HPI evaluation (which is the same as the WHO standard).…”

Section: Heavy Metal Pollution Index (Hpi)mentioning

confidence: 99%

“…Moreover, it shows the necessary solutions to schedule and decrease negative effects of these pollutants for water resource planning. Geographical information system (GIS) is a useful and effective tool for saving data, showing spatial data, analyzing parameters spatially, and integrating for desirable output that can be used for decision making in various fields such as environmental protection [18][19][20]. In the current study, pollution of Ardabil aquifer groundwater in terms of NO 3 , NO 2 , and heavy metals was investigated and analyzed.…”

Section: Introductionmentioning

confidence: 99%

Seasonal Assessment of Nitrate, Nitrite, and Heavy Metals Pollution in Groundwater of Ardabil Aquifer, Iran

Rezaverdinejad¹,

Rahimi²

2017

Pol. J. Environ. Stud.

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One of the most important resources for drinking water is groundwater. Recently, the quality of groundwater has been endangered due to several reasons, including human activities, vast agricultural activities, and the discharge of industrial wastewater containing nitrogen (N) and heavy metals. For this study we investigated the values of NO 3 , NO 2 , and some heavy metals and analyzed the groundwater of the Ardabil Aquifer area in wet and dry seasons. For this purpose we evaluated 76 wells in the study area. In order to analyze the results we used World Health Organization (WHO), U.S. Environmental Protection Agency (EPA), and Institute of Standard and Industrial Research of Iran (ISIRI) standards. The results indicated that, according to WHO and ISIRI, 10.5% of wells and, according to the EPA, 69.7% of wells have NO 3 above the standard level in the wet season, but in the dry season, according to WHO and ISIRI,29% and, according to the EPA, 80.6% of the wells have NO 3 above the permissible level. However, according to all standards, NO 2 values are less than the permissible level for drinking consumption. In terms of evaluation criteria of the simultaneous presence of NO 3 and NO 2 in drinking water (K), 29% of wells in the dry season and 13.15% of wells in the wet season have NO 3 and NO 2 problems. In order to find an appropriate interpolation method and zoning parameter of NO 3 and NO 2 , different interpolation methods were evaluated and Kriging method with the lowest error was chosen for zoning the parameters. According to zoning maps, in the wet season the Namin and south Ardabil areas, which have the most drinking water wells, contain values of NO 3 above the permissible levels, whereas the values of NO 3 are at the mediocre level in the dry season. In addition to NO 3 and NO 2 analysis, the evaluation of heavy metals pollution indices in the aquifer include: heavy metal pollution index (HPI), heavy metal evaluation index (HEI), and contamination degree (C d ). Generally, according to the EPA, in terms of NO 3 and NO 2 pollution, Ardabil aquifer is in an undesirable condition, and according to WHO and ISIRI standards, this area has a mediocre level of undesirable condition. According to HPI and C d indices, most parts are in a high class of heavy metal pollution, as well.

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“…Recharge water is, therefore, a significant vehicle for percolating and transporting contaminants Fig. 6 Aquifer media rating map within the vadose zone to the saturated zone (aquifer) (Rahman 2008 (Singh et al 2010;Singh et al 2013c;Verma and Singh 2013;Mahato et al 2014;Tiwari et al 2015). The net recharge varies from 1.42 to 7.57 inches/year.…”

Section: Net Rechargementioning

confidence: 99%

A GIS based DRASTIC model for assessing groundwater vulnerability of Katri Watershed, Dhanbad, India

Ghosh

Tiwari

Das

2015

Model. Earth Syst. Environ.

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Groundwater vulnerability assessment could be defined as the degree of assimilation capacity of the area to the contaminant from surrounding surface above the aquifer. It has become an important element for sustainable natural resource management and proper landuse planning. This study aims at estimating shallow aquifer vulnerability by applying the GIS based DRASTIC model in Katri watershed, Dhanbad, Jharkhand. The probable groundwater quality decline due to various anthropogenic activities within the Katri watershed has necessitated this study using a combination of DRASTIC and GIS method as an effective method for groundwater pollution risk assessment. This model is based on the seven hydrogeological data layers that provide the input to the modelling. It corresponds to the initials of seven layers i.e. Depth of water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and hydraulic Conductivity. The mapping of the DRASTIC index allows us to delineate zones with various degrees of pollution vulnerability. The study reveals that about 16.91 % of the watershed area is exposed to high-risk, 30.69 % exposed to medium-risk, and 52.4 % exposed to low risk. The south eastern and south western parts of the watershed are dominated by high vulnerability classes while the south, north western and lower middle portions are characterized by moderate vulnerability classes. The elevated northern, north eastern, and middle part of the study area displayed low aquifer vulnerability.

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Evaluation of Surface Water Quality by Using GIS and a Heavy Metal Pollution Index (HPI) Model in a Coal Mining Area, India

Cited by 149 publications

References 25 publications

Risk analysis of heavy metal concentration in surface waters across the rural-urban interface of the Wen-Rui Tang River, China

Risk analysis of heavy metal concentration in surface waters across the rural-urban interface of the Wen-Rui Tang River, China

Seasonal Assessment of Nitrate, Nitrite, and Heavy Metals Pollution in Groundwater of Ardabil Aquifer, Iran

A GIS based DRASTIC model for assessing groundwater vulnerability of Katri Watershed, Dhanbad, India

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