Intelligent Prediction Modeling of Water Quality Using Artificial Neural Networking: Nambiyar River Basin, Tamil Nadu, India

Delta regions of the Cauvery River basin are one of the significant areas of rice production in India. In spite of large-scale utilization of the river basin for irrigation and drinking purposes, the lack of appropriate water management has seemingly deteriorated the water quality due to increasing anthropogenic activities. Vellore is the second most populous district of Tamil Nadu in India where the Palar River flowing towards east for about 295 Km. Vellore is surrounded by many leather tanneries and small scale dying industries and their effluents are discharged into the Palar river causing impact on the quality of the underground water. To assess the extent of deterioration, physicochemical characteristics of surface water were analyzed select regions of Cauvery Delta River basin and Palar region, Tamil Nadu, during March 2016 to May 2016. This study aimed to examine quality of drinking groundwater. The results represented whether the water was suitable or unsuitable for drinking purposes in this area. It was also observed that some areas like Tiruvarur, Needamangalam, Kamalapuram, Arcot, Soraiyur, Ranipet had low quality drinking water. It is suggested to take some necessary measures for supplying desirable water to the people living in these areas.

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APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR PREDICTING THE WATER QUALITY INDEX IN THE PARAKAI LAKE, TAMIL NADU, INDIA

Applied Ecology and Environmental Research ◽

10.15666/aeer/1702_19471958 ◽

2019 ◽

Vol 17 (2) ◽

pp. 1947-1958 ◽

Cited By ~ 1

Author(s):

S SAHAYA VASANTHI ◽

S ADISH KUMAR

Keyword(s):

Neural Network ◽

Water Quality ◽

Artificial Neural Network ◽

Water Quality Index ◽

Quality Index ◽

Tamil Nadu ◽

Artificial Neural

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Spatial Evaluation of Groundwater Quality Using GIS and WQI in Gadilam River Basin, Tamil Nadu, India

Journal of Geology Geography and Geoecology ◽

10.15421/112150 ◽

2021 ◽

Vol 30 (3) ◽

pp. 546-561

Author(s):

K. Mohammed Rizwan ◽

V. Thirukumaran ◽

M. Suresh

Keyword(s):

Water Quality ◽

Groundwater Quality ◽

River Basin ◽

Quality Index ◽

Tamil Nadu ◽

Interpolation Method ◽

Quality Parameters ◽

Groundwater Samples ◽

Spatial Interpolation Method

The aims of the current research are to assess the drinking water quality of the groundwater in the Gadilam River Basin, which is located in the northern part of Tamil Nadu, by identifying the groundwater quality index and examine its suitability for drinking. The current work determines the levels of groundwater quality parameters based on 120 groundwater samples; 50 samples from Archaean formation, 34 samples from Quaternary formation, 35 samples from Tertiary formation and the remaining sample from Cretaceous formation. Additionally, this research compares the determined levels with the various standards for drinking. Furthermore, the variability of parameters of the groundwater quality is explored in this paper by using the spatial interpolation method. The conclusion of this research reveals that the groundwater quality parameters such as Calcium (Ca2+), Magnesium (Mg2+), Nitrate (NO32-), Fluoride (F-), Sulphate (SO42-), Bi-carbonate (HCO3-) and Percentage of Hydrogen (pH) values are observed to be within the limiting value for WHO 2017 in all the formations during the seasons in which they were taken. The water quality index (WQI) values of the Archaean, Quaternary and Tertiary formations are found to be less than 100 meq/L in all stations in both seasons. In order of WQI, these stations come under the category of “Excellent” and “Good”. The Piper trilinear classification of groundwater samples fall in the field of mixed Ca-Mg-Cl, and No dominance, some of the samples represent Na-K, Cl types of water.

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Water Pollution and Its Causes in the Tuojiang River Basin, China: An Artificial Neural Network Analysis

Sustainability ◽

10.3390/su13020792 ◽

2021 ◽

Vol 13 (2) ◽

pp. 792

Author(s):

Zheng Zeng ◽

Wei-Ge Luo ◽

Zhe Wang ◽

Fa-Cheng Yi

Keyword(s):

Neural Network ◽

Water Pollution ◽

Water Quality ◽

Artificial Neural Network ◽

River Basin ◽

Back Propagation ◽

Oxygen Demand ◽

Ammonia Nitrogen ◽

National Standards ◽

Artificial Neural

This work aimed to assess the water quality of the Tuojiang River Basin in recent years to provide a better understanding of its current pollution situation, and the potential pollution risks and causes. Water quality parameters such as dissolved oxygen (DO), ammonia–nitrogen (NH3-N), total phosphorus (TP), the permanganate index (CODMn), five-day biochemical oxygen demand (BOD5), pH, and concentrations of various heavy metals were measured in the Tuojiang River, according to the national standards of the People’s Republic of China. Samples were collected between 2012 to 2018 at 11 national monitoring sites in the Tuojiang River Basin. The overall water pollution situation was evaluated with back propagation artificial neural network (BP-ANN) analysis. The pollution causes were analyzed considering both industrial wastewater discharge in the upper reaches and the current pollution situation. We found potential risks of excessive NH3-N, TP, Cd, Hg, and Pb concentrations in the Tuojiang River Basin. Moreover, corresponding water pollution control suggestions were given.

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