Hydro-chemical Survey and Quantifying Spatial Variations in Groundwater Quality in Coastal Region of Chennai, Tamilnadu, India – a case study

Rawat, Kishan Singh; Jacintha, T. German Amali; Singh, Sudhir Kumar

doi:10.22146/ijg.27443

Cited by 10 publications

(4 citation statements)

References 27 publications

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“…Depending on an estimate, the value at an unsampled location can be estimated as a weighted average of values at points within a particular cut-off distance, or from a specified number of the closest points (typically 10 to 30), where weights are usually inversely proportional to a power of distance [60,61]. These approaches are useful for processing spatial data at local and global scales, as well as for managing surface water resources [62,63].…”

Section: Spatial Distributions Of Water Quality Indicatorsmentioning

confidence: 99%

Using Optimized Two and Three-Band Spectral Indices and Multivariate Models to Assess Some Water Quality Indicators of Qaroun Lake in Egypt

et al. 2021

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Standard methods are limited for monitoring and managing water quality indicators (WQIs) in real-time and on a large scale. Consequently, there is an urgent need to use reliable, practical, swift, and cost-effective monitoring tools that can be easily deployed and assist decision makers in assessing key indicators relevant to surface water quality in a comprehensive manner. Surface water samples were collected and evaluated for water quality at 16 distinct sites across the Qaroun Lake in 2018 and 2019. Different WQIs, including total dissolved solids (TDS), transparency, total suspended solids (TSS), chlorophyll-a (Chl-a), and total phosphorus (TP), were tested for aquatic utilization. An integrated approach comprising WQIs, geospatial techniques, hyperspectral reflectance indices (SRIs) (commonly used SRIs, two-band and three-band SRIs (Spectral index calculated from water spectral reflectance of two or three wavelengths)), and partial least square regression (PLSR) models were used to assess the water quality of Qaroun Lake. According to the findings, the water quality attributes are polluted to varying degrees. The majority of commonly used SRIs presented moderately relationship with four WQIs (transparency, TSS, Chl-a, and TP) (R2 = 0.45 to 0.64), while the majority of newly two-band SRIs (NSRIs-2b) indicated moderate to strong relationships with WQIs (R2 = 0.51 to 0.74), and the majority of newly three band SRIs (NSRIs-3b) presented strong relationships with WQIs (R2 = 0.67 to 0.81). Broadly, the highest coefficients of determination were noticed with the NSRIs-3b followed by the NSRIs-2b and then the commonly used SRIs. For example, the NSRIs-3b (NDSI648,712,696) had stronger relationships with transparency, TSS, and Chl-a with R2 = 0.77, 0.66, and 0.81, respectively, than other SRIs. In addition, the NSRIs-3b (NDSI620,610,622) showed the highest R2 of 0.73 with TSS. The NSRIs-3b coupling with PLSR predicted the WQIs with satisfactory accuracy in the calibration (reach up R2 = 0.85) and validation (reach up R2 = 0.81) datasets. The overall findings of this research study showed that deriving an optimized NSRIs-3b from spectrum region and combining it with PLSR model could be a practical tool for managing water quality of the Qaroun Lake by accurately, timely, and non-destructively monitoring the WQIs.

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Section: Spatial Distributions Of Water Quality Indicatorsmentioning

confidence: 99%

Using Optimized Two and Three-Band Spectral Indices and Multivariate Models to Assess Some Water Quality Indicators of Qaroun Lake in Egypt

et al. 2021

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“…Groundwater has become the major source of water use in the agricultural sector in many countries where river and drainage systems are not sufficient. Therefore, poor groundwater quality for irrigation purpose is a matter of worry in recent years (Rawat et al 2018). The study area is characterized by a dry climate, where salinization and alkalinization of water are the main risks that may be associated with irrigation water.…”

Section: Irrigation Water Qualitymentioning

confidence: 99%

“…Increasing water demand has forced people to depend on groundwater resulting in high water extraction from groundwater reserves (Singh et al 2006;Thakur et al 2013). The good quality of groundwater is important for future planning and management (Rawat et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Physicochemical evolution and evaluation of groundwater quality in Mougheul area (Southwest of Algeria)

2021

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In arid areas, the pressure on water resources and in particular on groundwater resources is on the rise, mainly due to increasing demand and the deterioration of water quality. In this context, the present work aims to follow the annual evolution, between 2009 and 2019 of the physicochemical parameters, and to evaluate the quality of groundwater of the region of Mougheul, by determining the data of pH, TDS, conductivity and the concentrations of major ions ( Ca+2, Mg+2, Na+, K+, Cl−, HCO3−, SO4−2, NO3−) of 07 water points. The results revealed that all the levels of the physicochemical parameters do not exceed the WHO potability standards, except high values were observed at the level of well W6 which exceeds the limits recommended by the WHO (50 mg /l). The diagram of Schöeller and Berkaloff shows that the groundwater has the bicarbonate magnesium facies. The representation of the data on the Piper triangular diagram shows that W6 has the facies chlorinated and calcium sulfate and magnesium and the other water points have the facies bicarbonate calcium and magnesium. SAR values show that the groundwater of Mougheul is excellent for irrigation. The classification according to the Wilcox diagram shows that the groundwater of Mougheul in general is good quality, but the well of W6 water is suitable for irrigation and requires monitoring the evolution of salinity.

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“…Geographical Information System (GIS) is commonly used in the field of water quality investigation (Singh et al 2013a, b;Thakur et al 2016;Rawat and Singh 2018a;Rawat et al 2018c) and climate-related studies (Gajbhiye et al 2016) to prepare the thematic maps. The interpolated maps of WQI gives detailed information to decision makers (Singh et al 2013b;Rawat et al 2018;Rawat et al 2018b;Rawat et al 2018c;Rawat et al 2018d).…”

Section: Introductionmentioning

confidence: 99%

Integrated Framework for Identification of Polluted Zones in Coastal Areas of Thiruvallur District of Tamil Nadu (India)

Rawat

2019

IJG

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In this research work, hydro-geochemical characteristics were determined from twenty groundwater samples and classified into water quality zones on the basis of the World Health Organization (WHO 2006) using inverse distance weighted interpolation technique. Groundwater samples were analyzed with respect to calcium (Ca2+), magnesium (Mg2+), sodium (Na+), HCO3, total nitrate (NO2+NO3ˉ), chloride (Cl−), sulphate (SO42−), total dissolved solids (TDS), hydrogen ion concentration (pH) and electrical conductivity (EC) were measured form groundwater samples. The water quality indices (WQI1 and NPI = WQI2) were used to categorize the water. Water Quality Index (WQI) value suggest that the 65% groundwater samples (excellent + good) are safe for drinking uses and 35% groundwater samples (very poor + poor) needs treatment before consumptive uses from WQI1. Further, NPI (WQI2), shows 40% and 60% of groundwater falls under good and poor condition respectively. The findings highlight that the groundwater of few areas requires some degree of treatment before consumptive uses.

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Hydro-chemical Survey and Quantifying Spatial Variations in Groundwater Quality in Coastal Region of Chennai, Tamilnadu, India – a case study

Cited by 10 publications

References 27 publications

Using Optimized Two and Three-Band Spectral Indices and Multivariate Models to Assess Some Water Quality Indicators of Qaroun Lake in Egypt

Using Optimized Two and Three-Band Spectral Indices and Multivariate Models to Assess Some Water Quality Indicators of Qaroun Lake in Egypt

Physicochemical evolution and evaluation of groundwater quality in Mougheul area (Southwest of Algeria)

Integrated Framework for Identification of Polluted Zones in Coastal Areas of Thiruvallur District of Tamil Nadu (India)

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