Assessment of underground water quality and water quality index across the Noyyal River basin of Tirupur District in South India

Krishnamoorthy, N.; Thirumalai, R.; Sundar, M.; Anusuya, M.; Kumar, P. Manoj; Hemalatha, E.; Prasad, M. Mohan; Munjal, Neha

doi:10.1016/j.uclim.2023.101436

Cited by 38 publications

(6 citation statements)

References 30 publications

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“…Temperature, pH, dissolved oxygen, total suspended solids, ammonia, nitrite, and nitrate concentrations have to be continuously measured to evaluate the permissible levels for aquaponic systems that provide information about the survival, growth, and food intake of fish. , Also, pH is an excellent indicator to observe the nutritional profile in freshwater fishery sectors, including calcium, magnesium, iron, manganese, and zinc, and monitoring the electrical conductivity, pH, and oxidation–reduction potential becomes vital in brackish water fish cultures . The same parameters can also be used to assess the quality of groundwater that could be compromised by anthropogenic activities, industrial effluents, , and algal bloom contamination. , …”

Section: Discussionmentioning

confidence: 99%

“… 39 , 40 Also, pH is an excellent indicator to observe the nutritional profile in freshwater fishery sectors, including calcium, magnesium, iron, manganese, and zinc, 41 and monitoring the electrical conductivity, pH, and oxidation–reduction potential becomes vital in brackish water fish cultures. 42 The same parameters can also be used to assess the quality of groundwater that could be compromised by anthropogenic activities, 43 industrial effluents, 44 , 45 and algal bloom contamination. 46 , 47 …”

Section: Discussionmentioning

confidence: 99%

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Sub-Liquid and Atmospheric Measurement Instrument To Autonomously Monitor the Biochemistry of Natural Aquatic Ecosystems

2023

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Monitoring the biochemistry of aquatic ecosystems is critical to understanding the biogeochemical cycling induced by microorganisms. They play a vital role in climate-gaseous drivers associated with natural ecosystems, such as methane emission in wetlands and peatlands; gas cycling and fixation: methane, sulfur, carbon, and nitrogen; water quality assessment and remediation; monitoring oxygen saturation due to contamination and algal proliferation; and many more. Microorganisms interact with these environments inducing diurnal and seasonal changes that have been, to date, poorly characterized. To aid with the long-term insitu monitoring of natural aquatic ecosystems, we designed a Subliquid and Atmospheric Measurement (SAM) instrument. This floating platform can autonomously measure various sub-liquid and atmospheric parameters over a long time. This paper describes the design of SAM and illustrates how its long-term operation can produce critical information to complement other standard laboratory-based microbiological studies.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Sub-Liquid and Atmospheric Measurement Instrument To Autonomously Monitor the Biochemistry of Natural Aquatic Ecosystems

2023

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“…Combining the WQI with the Geographical Information System (GIS) to illustrate spatial variation in water quality and identify vulnerable sites assists in decision-making for sustainable groundwater management [34]. To demonstrate that groundwater is suitable for drinking, a WQI is utilized [34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Groundwater Quality through Hydrochemistry Using Principal Components Analysis (PCA) and Water Quality Index (WQI) in Kızılırmak Delta, Turkey

Arıman,

Soydan-Oksal,

Beden

et al. 2024

Water

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This study aimed to characterize the chemical composition and spatial distribution of groundwater in the Kızılırmak Delta of Turkey and to evaluate the suitability of groundwater in the Kızılırmak Delta for drinking water use through a Water Quality Index (WQI) assessment. Eleven water parameters, including nitrate (NO3−), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), chloride (Cl−), potassium (K+), bicarbonate (HCO3−), sulfate (SO42−), hardness (measured as CaCO3), electrical conductivity (EC), and pH were analyzed to determine the water quality of each groundwater sample. The WQI was determined using the weighted arithmetic index method and the method specified by the Canadian Council of Ministers of the Environment (CCME). The spatial distribution of the result for all observation wells was plotted. Principal Component Analysis (PCA) was generated utilizing the analytical data from eleven selected samples. As a result of the study, according to the calculated WQI values, the water in most of the wells was not suitable for drinking purposes. The minimum Ca2+ concentration in the study area was 108,817 mg/L, and the maximum was 692,382 mg/L, which showed that the samples in all wells exceeded the WHO limit. The same situation is valid for Mg2+, and the values vary between 100.383 and 5183.026 mg/L. From the spatial distribution of the water quality parameters it has been understood that the eastern part of the region is more suitable than the western part for drinking purposes. The results from correlation analysis showed the strongest positive correlation between Mg2+ and Na+ and Na+ and EC as 0.989. The present study shows that the groundwater of the delta, which has deteriorating water quality, should be treated before it is used for drinking water and protected from contamination hazards.

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“…In contrast, comprehensive evaluations take into account the status of various participating indicators, leading to reliable and comprehensive assessment results that are intuitive and easy to understand. As part of the comprehensive evaluation approach, the WQI has been widely applied and researched [13][14][15][16][17][18]. The WQI model generally includes four components: the selection of water quality indicators, assigning scores to the indicators, determining the weights of the indicators, and aggregating the results.…”

Section: Introductionmentioning

confidence: 99%

Groundwater Quality Assessment Based on the Random Forest Water Quality Index—Taking Karamay City as an Example

Xiong,

Zhang,

Sun

et al. 2023

Sustainability

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In the past few decades, global industrial development and population growth have led to a scarcity of water resources, making sustainable management of groundwater a global challenge. The Water Quality Index (WQI) serves as a comprehensive method for assessing water quality and can provide valuable recommendations at the water quality level, optimizing policies for groundwater management. However, the subjectivity and uncertainty of the traditional WQI have negative impacts on evaluation outcomes, particularly in determining indicator weights and selecting aggregation functions. The proposed water quality index for groundwater based on the random forest (RFWQI) model in this study addresses these issues. It selects water quality indicators based on the actual pollution situation in the study area, employs an advanced random forest model to rank water quality indicators, determines indicator weights using the rank centroid method, scores the indicators using a sub-index function designed for groundwater development, and compares the results of two commonly used aggregation functions to identify the optimal one. Based on the aggregated scores, the water quality at 137 monitoring sites is classified into five levels: “Excellent”, “Good”, “Medium”, “Poor”, or “Unacceptable”. Among the 11 water quality indicators (sodium, sulfate, chloride, bicarbonate, total dissolved solids, fluoride, boron, nitrate, pH, CODMn, and hardness), chloride was given the highest weight (0.236), followed by total dissolved solids (0.156), and sodium was given the lowest weight (0.008). The random forest model exhibits a good prediction capability before hyperparameter tuning (86% accuracy, RMSE of 0.378), and after grid search and five-fold cross-validation, the optimal hyperparameter combination is determined, further improving the performance of the random forest model (94% accuracy, F1-Score of 0.967, AUC of 0.91, RMSE of 0.232). For the newly developed groundwater sub-index function, interpolation is used to score each indicator, and after comparing two aggregation functions, the NSF aggregation function is selected as the most suitable for groundwater assessment. Overall, most of the groundwater in the study area was of poor quality (52.5% of low quality) and not suitable for drinking.

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Assessment of underground water quality and water quality index across the Noyyal River basin of Tirupur District in South India

Cited by 38 publications

References 30 publications

Sub-Liquid and Atmospheric Measurement Instrument To Autonomously Monitor the Biochemistry of Natural Aquatic Ecosystems

Sub-Liquid and Atmospheric Measurement Instrument To Autonomously Monitor the Biochemistry of Natural Aquatic Ecosystems

Assessment of Groundwater Quality through Hydrochemistry Using Principal Components Analysis (PCA) and Water Quality Index (WQI) in Kızılırmak Delta, Turkey

Groundwater Quality Assessment Based on the Random Forest Water Quality Index—Taking Karamay City as an Example

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