scholarly journals Assessment of Quality Index of Water by Using Different Physico-Chemical Parameters in Rabale Waterbody, Navi-Mumbai, Maharashtra, India

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Singh Pooja ◽  
Jadhav Anita S
Keyword(s):  
Water Quality ◽  
Chemical Oxygen Demand ◽  
Water Body ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Quality Data ◽  
Chemical Parameters ◽  
Rapid Urbanization ◽  
Physico Chemical

Water is a must for all living things. Reservoir and lake water is used for a variety of purposes, including drinking water, agricultural, commercial, recreational, and aquaculture. However, due to rising population pressures, which has resulted in rapid urbanization, industrialization, and modern agricultural practices, water pollution has become a major issue in recent years. The water quality index is a single number that reflects overall water quality at a specific place and time. To compute, water quality index (WQI) we used Temperature, pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (B.O.D), Chemical Oxygen Demand (C.O.D), Alkalinity, Electrical Conductivity, Turbidity, and Chemical Oxygen Demand (C.O.D), Nitrite-Nitrogen, Nitrate-Nitrogen and Hardness were the physico-chemical parameters investigated in this study. The water quality index is to transform complicated water quality data into information that the general public can use. The Water Quality Index was calculated using the Weighted Arithmetic Water Quality Index (WQI). The measured WQI was then used to assess the water quality in Rabale water body. The water quality index (WQI) of the lake was 49.813, 53.483, and 53.045 during the pre-monsoon, monsoon, and post-monsoon periods, respectively. When comparing seasonal variations, WQI values show that water status is fairly good during the pre-monsoon but is low during the monsoon and postmonsoon seasons, thus water from Rabale water body may be used for a variety of industrial purposes.

scholarly journals Assessment of water quality index: a case study in Old Brahmaputra river of Mymensingh District in Bangladesh

2016 ◽  
Vol 27 (3) ◽  
pp. 355-361 ◽  
Author(s):  
Z Muyen ◽  
M Rashedujjaman ◽  
MS Rahman
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Chemical Parameters ◽  
Brahmaputra River ◽  
Physico Chemical

This study was conducted to measure the water quality parameters of old Brahmaputra River in Mymensingh district near Bangladesh Agricultural University to determine the water quality index (WQI) of the River Brahmaputra. Water quality focuses on various aspects of the physico-chemical parameters by which the quality of the water body can easily be elucidated. Three different locations were selected within the study area. Water samples were collected in April 2015 from these three locations along the river and analyzed for these physico-chemical parameters: pH, Dissolve Oxygen (DO), Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Ammoniacal Nitrate (AN), Suspended Solids (SS). The values of these parameters were used to calculate the WQI based on the equation derived by the Department of Environment (DoE) Malaysia. The WQI was found to be 57.58, which falls in the class IV category and means that the water is “very polluted” and as of April 2015, this water is not suitable for public water supply, not suitable for recreational purpose, has limited potential for aquaculture but is suitable for irrigation.Progressive Agriculture 27 (3): 355-361, 2016

scholarly journals Development of water quality index of ex-mining ponds in Malaysia

2019 ◽  
Vol 15 (1) ◽  
pp. 54-60 ◽  
Author(s):  
Isa Baba Koki ◽  
Sharifuddin Md Zain ◽  
Low Kah Hin ◽  
Azman Azid ◽  
Hafizan Juahir ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Human Consumption ◽  
Chemical Parameters ◽  
Metal Pollutants ◽  
Physico Chemical ◽  
Klang Valley ◽  
Mining Water ◽  
Quality Status

In this paper, a study on the development  of water quality index of ex-mining ponds was carried out for proper assessment  and utilization of the abundant ex-mining ponds in Malaysia. Heavy metals were analyzed using inductively coupled plasma mass spectrophotometer (ICPMS), and physico chemical parameters were analyzed in-situ. Chemometric analysis was successfully applied for the parameter selection process. The water quality index of existing Malaysian river did not accommodate the toxic metal pollutants that dominanted in ex-mining water. The acceptable index should therefore incorporate the metal pollutants in order to evaluate the quality status of ex-mining water for human consumption which is the major point of consideration. Two water quality indices were developed to assess the water quality status of ex-mining ponds with reference to Malaysia’s water quality standard (INWQS). The heavy metal index was comprised of contribution from Pb, As, and Cd as the selected metals, while the physico-chemical parameter index has BOD, pH, DO, and AN. Chemometric analysis revealed the dominance of the selected heavy metals in ex-mining water, and physico-chemical parameters were important in water quality monitoring. Heavy metal water quality index revealed that most ex-mining ponds in Klang Valley were classified to be very poor hence could not be used for human consumption. Due to domestic input in some of the lakes in Klang Valley, the physico-chemical water quality index was in very poor status as well.  In Melaka and Negeri Sembilan, ex-mining ponds and lakes were classified as excellent in both indices.    

scholarly journals Assessment of Water Quality of Okomu Wetland Using Water Quality Index

2020 ◽  
Vol 4 (2) ◽  
pp. 450-457
Author(s):  
S. I. Ehiorobo ◽  
A. E. Ogbeibu
Keyword(s):  
Water Quality ◽  
Water Body ◽  
Water Quality Index ◽  
Quality Index ◽  
Anthropogenic Activities ◽  
Physicochemical Characteristics ◽  
Poor Quality ◽  
Quality Data ◽  
Water Quality Data

The water quality of the Okomu Wetland was evaluated using the Water Quality Index (WQI) technique which provides a number that expresses overall water quality of a water body or water sample at a particular time. Sampling of physicochemical parameters spanned two years covering the wet and dry seasons and the water quality data were obtained from 10 sampling locations; Ponds 36, 52, 54, 61, 64, 90, 94, Arhakhuan Stream, Okomu River (Agekpukpu) and Okomu River (Iron bridge) all within the Okomu National Park. Parameters such as Total Dissolved Solids (TDS), Turbidity, pH, Electrical conductivity (EC), Chlorine (Cl), Nitrate (NO3), Sulphate (SO4), Sodium (Na), Magnesium (Mg), (Iron) Fe, Chromium (Cr), Zinc (Zn), Copper (Cu), Manganese (Mn), Lead (Pb), and Nikel (Ni) were used to compute WQI and the values obtained for the wetland ranged between 34.36 and 167.28. The Index shows that pond 36, 52 and 54 are unfit for drinking with values between 103.86 and 167.28; ponds 61 and 64 are of the very poor quality category with WQI values of 95.19 and 92.44 respectively, Pond 90, pond 94, Arhakhuan Stream and Okomu River (Agekpukpu) are of poor quality and WQI values between and 53.58 and 73.15. Whereas, the Okomu River (Iron bridge) is within the good water quality (34.36) category. The Okomu River by Iron bridge is of good quality rating while other sampled points were of poor, very poor or unfit for drinking though these water bodies are mostly free from anthropogenic activities because of the conservative status of the study area. A major source of pollution within the wetland is surface runoff. The water quality of the wetland may not be suitable for man’s consumption especially pond water which are majorly impacted by runoff, yet very important for the survival and sustenance of the forest animals and plants. The water quality index (WQI) interprets physicochemical characteristics of water by providing a value which expresses the overall water quality and thus, reveals possible pollution problems of a water body. It turns complex water quality data into information that is easily understandable and usable by scientists, researchers and the general public.

scholarly journals Investigation of Water Quality Index of River Noyyal and Its Connected Ponds Coimbatore Tamilnadu India

2019 ◽  
Vol 35 (3) ◽  
pp. 1125-1131
Author(s):  
M. Jeyaraj ◽  
A. Indhuleka ◽  
C. Arunpaul
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Biological Parameters ◽  
Sampling Locations ◽  
Physico Chemical ◽  
Coimbatore District

This investigation deals with the determination of various physico-chemical and biological parameters of surface water quality of river Noyyal and its connected ponds at Coimbatore, India. Based on their significance, the sampling locations were selected. There are five sampling locations were selected like river Noyyal at sorce (S1), Perur Lake, (S2), Ukkadam Pond (S3), Singanallur Lake (S4) and Sulur Pond (S5), and samples were collected from each locations at river Noyyal basin in and around Coimbatore district. The surface water quality index determination is prerequisite and essential. In this present work, from different methods of water quality determination, the most commonly used index of National Sanitation Foundation water quality index (NSF-WQI) has been followed. The physico-chemical and biological parameters such as dissolved oxygen, faecal coliforms counts, pH, biochemical oxygen demand, phosphate, nitrates, turbidity, and total dissolved solids were investigated. Except in Noyyal river at source (S1) all the measured parameters are showed to be very high compared to limits suggested by WHO particularly during summer season and thereby it is not suitable for public use.

A construction of water quality index considering physicochemical properties for drinking purposes in a rural settlement: a case study of Gajraula region, Ganga River Basin (North India)

2012 ◽  
Vol 12 (6) ◽  
pp. 818-828 ◽  
Author(s):  
Bineet Singh ◽  
Jaspal Singh Chauhan ◽  
Anuraag Mohan
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Rating Scale ◽  
Rural Settlement ◽  
North India ◽  
Quality Data ◽  
Rapid Urbanization ◽  
Water Quality Data

A simple methodology based on several key variables of groundwater chemistry is used to create a water quality index (WQI), with the aim of monitoring the influence of industrial and rapid urbanization on a typical rural settlement. The applicability of the constructed indices as an assessment and communication tool is evaluated in a case study of Gajraula and its suburb of JP Nagar district in northern India. The water quality data from 2007 to 2009 were analysed for 12 different locations surrounding Gajraula for two seasons, i.e. wet and dry. Five point rating scale was used to classify water quality for each of the study locations. Rating curves were drawn based on the tolerance limits of drinking waters. In the present study, the WQI demonstrated a modest increase in wet seasons (August to November) than dry seasons (February to June) for all locations with a few exceptions. Hardness, total dissolved solids, NO3−, biochemical oxygen demand, and Fe in most cases were found to be responsible for the decline in seasonal WQI for various locations. However, the WQI around Gajraula varied from 50.6 to 87.7 and was found to be satisfactory except for some locations.

scholarly journals Some Physico-Chemical Parameter's Assessment for The Groundwater Samples of Kathlal Tehsil, Gujarat, India in Summer Season

2019 ◽  
pp. 811-814
Author(s):  
Pravin Mevada ◽  
G. R. Jani ◽  
Preksha Patel
Keyword(s):  
Water Quality ◽  
Ground Water ◽  
Water Samples ◽  
Water Quality Index ◽  
Quality Index ◽  
Summer Season ◽  
Chemical Parameters ◽  
Physico Chemical ◽  
Groundwater Samples ◽  
Tube Wells

The present study deals with Assessment of Physico-Chemical parameters of ground water samples of Kathlal tehsil. Physio-Chemical parameters like EC, Temperature, TDS, Ca2+ , Mg2+ , Na+, K+ ,Cl-, CO32-, HCO3-, SO42- , NO3-, F- were analyzed in this present study. The samples were collected in April-2013 (Summer Season). Total 10 samples of groundwater was carried out from Tube wells/Bore wells of Kathlal Tehsil in order to assess water quality index.

scholarly journals NARX-based water quality index model of Air Busuk River using chemical parameter measurements

2021 ◽  
Vol 23 (3) ◽  
pp. 1663
Author(s):  
Muhammad Ierfan Hasnan ◽  
Azhar Jaffar ◽  
Norashikin M. Thamrin ◽  
Mohamad Farid Misnan ◽  
Ahmad Ihsan Mohd Yassin ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Chemical Parameters ◽  
Chemical Parameter ◽  
Marine Life ◽  
Index Model ◽  
Satisfactory Performance ◽  
Input Structure

<p>Water quality plays a major role in issues related to public health and marine life. Hence, monitoring river for contaminations is vital for ensuring safe and sustainable water resources. Conventional method for assessing water quality index is costly as it requires considerable amount of time and laboratory resources. Therefore, this study proposes a water quality index model based on artificial neural network. A six-year data for Air Busuk River is obtained from the Department of Environment. Dissolved oxygen, biological oxygen demand, and ammoniacal nitrogen has shown high correlation with water quality index. The water quality index model is then developed based on these parameters, employing the non-linear autoregressive with exogeneous input structure. Generally, the model which is based on three chemical parameters has shown satisfactory performance with overall regression of 0.8767 and passed the correlation function tests. The model offers a potentially efficient method for assessing water quality with cost-saving benefits for government agencies and monitoring authorities.</p>

Application of Artificial Neural Network to Predict the Water Quality Index of Brahmani River Basin Odisha, India

2018 ◽  
Vol 6 (8) ◽  
pp. 205
Author(s):  
Binayini Bhagat ◽  
D. P. Satapathy
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Artificial Neural Network ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Physico Chemical ◽  
Artificial Neural

Water is one of the prime elements responsible for subsistence on the earth. The scarcity of potable water is gradually increasing with the increase in population. The surface water quality is a very crucial and sensitive issue and is also a great environmental concern worldwide. Surface water pollution by physical, chemical, radiological and biological contaminants can be considered as an epidemic at times, all over the world. The present research work aims at assessing the water quality index (WQI) in the surface water of Brahmani river basin in Odisha by monitoring five sampling locations. The surface water samples data were subjected to comprehensive physico-chemical analysis besides general parameters. The monthly water quality parameters were collected and analyzed from five selected gauging stations of Odisha during the months of January to December from 2011 to 2016. Eleven physical, chemical and biological water quality parameters viz. pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Electrical Conductivity(EC), Nitrogen as nitrate (Nitrate-N), Total Coli-form Bacteria(TC), Fecal Coli-form Bacteria(FC), Chemical Oxygen Demand (COD), Nitrogen as ammonia (NH4-N), Total Alkalinity (TA) as CaCO3, Total Hardness (TH) as CaCO3 were selected for the analysis. Analysis of water quality for Brahmani River is done by Water Quality Index (WQI). Prediction of water quality index is done by using Artificial Neural Network (ANN).  It is apparent from WQI values that Talcher and Panposh recorded the water quality as moderate to poor and nearly unsuitable during the years 2011-2016 indicating water as not safe for domestic purposes and needs treatment, the WQI values of Kamalanga ranged from good to poor and the WQI values of Aul and Pottamundai ranged from good to moderate. Eleven physico-chemical parameters were involved in this analysis as input variables and water quality index as output variable. Two models were proposed to identify the most effective model in an attempt to predict the WQI.  Correlation between the parameters was carried out to find out the significant parameters affecting WQI. The ANN developed was trained and tested successfully using the available data sets and the performance of ANN models were determined by coefficient of determination (R2) and Root Mean Square Error (RMSE). Results show that ANN-1 gives the higher value of R2 in summer, monsoon and winter season (0.989, 0.976 and 0.959) and low RMSE (2.1865, 2.0768 and1.9657) as compared to that of the second model (ANN-2) which gives R2 value as 0.933, 0.945 and 0.943 and RMSE value as 2.8765, 2.5456 and 1.2745 for summer, monsoon and winter seasons respectively. Hence this study triggered the use of Artificial Neural Network to predict the Water Quality Index (WQI) rather than using the traditional WQI equation.

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