2019
DOI: 10.3390/ijerph16030357
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Combining Spatial Analysis and a Drinking Water Quality Index to Evaluate Monitoring Data

Abstract: Drinking water monitoring is essential for identifying health-related risks, as well as for building foundations for management of safe drinking water supplies. However, statistical analyses of drinking water quality monitoring data are challenging because of non-normal (skewed distributions) and missing values. Therefore, a new method combining a water quality index (WQI) with spatial analysis is introduced in this paper to fill the gap between data collection and data analysis. Water constituent concentratio… Show more

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Cited by 18 publications
(17 citation statements)
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“…Nowadays, geographical information system (GIS) has been widely used as an effective tool to integrate various databases and develop solutions for assessing water quality, reducing water resources problems, preventing flooding and understanding the natural environment (Venkatramanan et al 2019). Precautionary indicators of potential environment-related health problems include groundwater quality distribution maps and risk assessment maps (Arnous et al 2011;Gnanachandrasamy et al 2015;Ameen 2019;Li et al 2019).…”
Section: Introductionmentioning
confidence: 99%
“…Nowadays, geographical information system (GIS) has been widely used as an effective tool to integrate various databases and develop solutions for assessing water quality, reducing water resources problems, preventing flooding and understanding the natural environment (Venkatramanan et al 2019). Precautionary indicators of potential environment-related health problems include groundwater quality distribution maps and risk assessment maps (Arnous et al 2011;Gnanachandrasamy et al 2015;Ameen 2019;Li et al 2019).…”
Section: Introductionmentioning
confidence: 99%
“…As stated by Aleem et al (2018), the combination of GWQI and spatial analysis has proved to be a robust tool for assessing groundwater quality [44,45]. The geographic information system (GIS) enables the use of various interpolation methods for GWQI spatial analysis, such as proximity interpolation, inverse distance weighted interpolation, and the kriging interpolation method (KIM) [46,47]. Compared to other interpolation methods, the KIM method employs statistical approaches to eliminate spatial trends in data.…”
Section: Introductionmentioning
confidence: 99%
“…From 1990 to 2012, an estimated 488 million Chinese gained access to improved water sources (WHO/ UNICEF 2014), and, in roughly the same period (1990 to 2013), the age-standardized death rate associated with diarrheal disease decreased by 95.2% (Zhou et al 2016). Although industrial, agricultural, and other chemical contaminants in drinking water are a growing problem in China and elsewhere, with respect to reducing acute drinking water-associated health risks in rural China, the control of pathogens in drinking water remains a government priority (Li et al 2019b(Li et al , 2020.…”
Section: Introductionmentioning
confidence: 99%
“…2016 ). Although industrial, agricultural, and other chemical contaminants in drinking water are a growing problem in China and elsewhere, with respect to reducing acute drinking water-associated health risks in rural China, the control of pathogens in drinking water remains a government priority ( Li et al. 2019b , 2020 ).…”
Section: Introductionmentioning
confidence: 99%