Application of Correlation and Regression Models in Predicting the Physico-chemical Quality of Groundwater from Insitu Measured Parameters

2021 ◽  
Vol 6 (6) ◽  
pp. 19-38
Author(s):  
J. E. Agori ◽  
H. U. Nwoke ◽  
B. C. Okoro ◽  
B. U. Dike
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Correlation Coefficient ◽  
Regression Models ◽  
Correlation Coefficients ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Analysis Tool ◽  
Regression Equations ◽  
Physico Chemical

Groundwater is the major source of municipal and private potable water supply for meeting the drinking, domestic, agricultural and industrial requirements on man around the world. The cost of analyzing water quality in the laboratory to ascertain its potability is usually high and sometimes not available. Groundwater samples were collected from fifty (50) spatially referenced bore well locations in Warri and its environs in the dry and wet seasons (November 2019 to January 2020) in the study area. The water samples were analyzed for twenty-six (26) physical, chemical and bacteriological parameters both in the field and laboratory in line with APHA standard procedures for testing water and waste water inorder to evaluate the status of potability of groundwater across Warri, Delta State Nigeria. The data analysis tool in Microsoft Excel was used to explore and study the interrelationship between some conservative parameters measured in the field (pH, EC, TDS, and DO) as independent variables and some cations, anions and heavy metals (Na, Mg, Ca, HCO3, SO4 Cl, Fe, Cd, Cr, Cu and Pb) analysed in the laboratory as dependent variables. The results obtained from the parameters analysed insitu in the field which are cheap to perform and easily affordable were used to check and evaluate and the inter-relationships with some cations, anions and heavy metals. Highly correlated water quality parameters were determined by correlation coefficient (R) values obtained from correlation matrix and related by Regression equations (models). The regression models can be adopted to predict the concentration of these cations, anions and heavy metals before the rigorous laboratory analysis, to serve as a quick check for concentration of most disease-causing pollutants and to save time, money and resources, especially the near absence of AAS for analysing heavy metals in a good number of laboratories. The regression models developed in the study can be used for monitoring the water quality parameters by knowing the concentration of independent parameters obtained in the field alone. There is a relationship between variables which show that one variable actually causes changes in another variable. It was observed that multiple regression models can predict most parameters at 5% level of significance. Significantly positive correlation at 1 and 5% was found between many parameters. This technique studied and calculated the correlation coefficients between various physico-chemical parameters of drinking water and provided an excellent device for the calculation of parameter values within realistic degree of accuracy. The results proved to be easiest, useful, and rapid means for monitoring of water quality with the help of systematic calculations of correlation coefficient. It is recommended to treat groundwater prior to domestic use.

Classification and Prediction of Goldfish Population and Water Quality Using a Potentiometric E-Tongue

2017 ◽  
Vol 60 (4) ◽  
pp. 1037-1044
Author(s):  
Zhenbo Wei ◽  
Yu Zhao ◽  
Jun Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Pattern Recognition ◽  
Comprehensive Evaluation ◽  
Back Propagation ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Pattern Recognition Methods

Abstract. In this study, a potentiometric E-tongue was employed for comprehensive evaluation of water quality and goldfish population with the help of pattern recognition methods. Four water quality parameters, i.e., pH and concentrations of dissolved oxygen (DO), nitrite (NO2-N), and ammonium (NH3-N), were tested by conventional analysis methods. The differences in water quality parameters between samples were revealed by two-way analysis of variance (ANOVA). The cultivation days and goldfish population were classified well by principal component analysis (PCA) and canonical discriminant analysis (CDA), and the distribution of each sample was clearer in CDA score plots than in PCA score plots. The cultivation days, goldfish population, and water parameters were predicted by a T-S fuzzy neural network (TSFNN) and back-propagation artificial neural network (BPANN). BPANN performed better than TSFNN in the prediction, and all fitting correlation coefficients were >0.90. The results indicated that the potentiometric E-tongue coupled with pattern recognition methods could be applied as a rapid method for the determination and evaluation of water quality and goldfish population. Keywords: Classify, E-tongue, Goldfish water, Prediction.

scholarly journals Investigation of surface water quality of the Buriganga river in Bangladesh: Laboratory and spatial analysis approaches

2019 ◽  
Vol 28 (2) ◽  
pp. 147-158
Author(s):  
Mohammad Saiful Islam ◽  
Romana Afroz ◽  
Md Bodruddoza Mia
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Quality Standard ◽  
Quality Parameters ◽  
Average Concentration ◽  
Water Quality Parameters ◽  
Economic Implications ◽  
Permissible Limits ◽  
Buriganga River

This work has been conducted to evaluate the water quality of the Buriganga river. In situ water quality parameters and water samples were collected from 10 locations in January 2016 and analyzed later in laboratory for water quality parameters such as pH, Eh, EC, TDS, cations (Na+, K+, Ca2+, Mg2, As3+), anions (Cl-, HCO3-, NO2-, NO3-, SO42-, F-, Br-, PO43-), heavy metals (Cr2+, Pb2+, Zn2+, Cd+2, Fe2+, Mn2+) to see whether or not the level of these parameters are within the permissible limits. The average values of pH, Eh, EC and temperature were 7.31, –214.9 mV, 928.9 μs/cm and 21.4°C, respectively; the average concentration of Na+, K+, Ca2+, Mg2+, and As3+ were 109.62, 13.38, 46.78, 13.98 and 0.018 mg/l, respectively, while the concentrations of Cl-,HCO3-, PO43-, SO42-, NO3-, NO2-, F and Br -were 79, 331.06, 2.22, 84.32, 0.0254, 0.058, 0.224 and 0.073 mg/l, respectively; and the concentration of heavy metals Pb2+, Zn2+, Fe2+ and Mn2+were 0.28, 0.053, 0.17 and 0.23 mg/l, respectively. The study indicates that most of the parameters are within the permissible limits set by Bangladesh water quality standard. The concentrations of K+, Mn2+, and Pb2+ were beyond the permissible limits meaning that that the water of Buriganga is not safe for drinking. The people living beside Buriganga river should be more cautious about using the polluted/contaminated river water. The concerned authorities should take urgent necessary steps to improve the degraded water quality of the river considering the ecological, environmental and economic implications associated with it. Dhaka Univ. J. Biol. Sci. 28(2): 147-158, 2019 (July)

Water Quality Parameters and Macroinvertebrates Index of Biotic Integrity of the Jimma Wetlands, Southwestern Ethiopia

2010 ◽  
Vol 3 ◽  
pp. 79-99 ◽  
Author(s):  
Hayal Desta Yimer ◽  
Seyoum Mengistou
Keyword(s):  
Water Quality ◽  
Human Disturbance ◽  
Ecological Status ◽  
Quality Parameters ◽  
Index Of Biotic Integrity ◽  
Water Quality Parameters ◽  
Biotic Integrity ◽  
Chemical Parameters ◽  
Southwestern Ethiopia ◽  
Physico Chemical

The wetlands located at the periphery of Jimma town, southwestern Ethiopia, have critical roles in providing a range of ecological and socio-economic benefits, yet they are subject to increasing anthropogenic disturbances, notably through agriculture, settlement, intensive grazing and brick-making. This study assessed the ecological status of these wetlands, and examined the scale of the human disturbances that local communities might impose on them. Macroinvertebrate communities, water quality parameters, and human disturbance scores were assessed. Except for electrical conductivity and water temperature, no significant difference (P < 0.05) was found in physico-chemical parameters between the sampled sites. Nitrate was the only parameter that correlated with significant influence on species richness of the sampled macroinvertebrates. A total of 10 metrics were used to generate the index of biotic integrity (IBI). This IBI was then tested based on macroinvertebrate data collected. Ways of assessing and evaluating the existing ecological status of the wetlands are discussed in the context of physico-chemical parameters, IBI based on macroinvertebrates and human disturbance scales. Key Words: Catchments land use; Water quality; Macroinvertebrate; Index of Biotic Integrity; Wetland DOI: 10.3126/jowe.v3i0.2265 Journal of Wetlands Ecology, (2009) Vol. 3, pp 77-93

scholarly journals Assessment of Physicochemical Water Quality Parameters and Heavy Metals Concentration in Water Samples from Buriganga River Adjacent to Dhaka City

2017 ◽  
Vol 9 (2) ◽  
pp. 97-104
Author(s):  
MMM Hoque ◽  
PP Deb
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
River Water ◽  
Water Samples ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Water Quality Parameter ◽  
Dhaka City ◽  
Standard Level ◽  
Buriganga River

This study was conducted to know the status of physicochemical water quality parameter and heavy metal concentration in the water of Buriganga river, adjoining to Dhaka city. Water samples were collected from five different points of Buriganga river and were analyzed to determine pH, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), biological oxygen demand (BOD), chromium (Cr), lead (Pb), cadmium (Cd), copper (Cu) and manganese (Mn) content. Most of the measured water quality parameters and concentration of heavy metals were exceeded the standard level set by ECR and ADB. Among heavy metals concentration, level of chromium and cadmium were 4-5 times higher than the standard drinking level, these results indicate that surrounding industrial wastewater discharging from textile and tannery industries, which pollute the Buriganga river water. During the observation, at Hazaribagh station BOD level was found 32 times higher than drinking water standard level and 6 times higher than standard irrigation level, indicating Buriganga river water is extremely polluted by microorganism and is not suitable for household and irrigational use. Similarly, DO level at Buriganga river water was 5 times lower than the standard level, which indicates that Buriganga river water is extremely polluted and is unsuitable for aquatic life which are dependent on DO for their sustain. In the present study, the measured level of EC, chromium, cadmium and copper were found higher level as compare to the previous studies.J. Environ. Sci. & Natural Resources, 9(2): 97-104 2016

Determination of Heavy Metals and Other Water Quality Parameters from the South China Sea

2014 ◽  
Vol 48 (1) ◽  
pp. 204-212 ◽  
Author(s):  
Jingxi Li ◽  
Li Zheng ◽  
Xiaofei Yin ◽  
Junhui Chen ◽  
Bin Han ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
South China Sea ◽  
South China ◽  
Quality Parameters ◽  
The South China Sea ◽  
Water Quality Parameters ◽  
The South ◽  
China Sea

Regression models for the prediction of water quality in the stormwater of urban arid catchmentsA paper submitted to the Journal of Environmental Engineering and Science.

2009 ◽  
Vol 36 (2) ◽  
pp. 331-344 ◽  
Author(s):  
M. Nouh ◽  
N. Al-Noman
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Suspended Sediment ◽  
Regression Models ◽  
Stormwater Runoff ◽  
Environmental Engineering ◽  
Regression Equations ◽  
Relative Importance ◽  
Flow Properties ◽  
Water Quality Control

Data from five residential urban arid catchments were used to develop regression equations for predicting mean concentrations of selected heavy metals in the stormwater runoff from duststorm and stormwater flow properties. The selected metals are copper (Cu), lead (Pb), nickel (Ni), zinc (Zn), and iron (Fe). The concentrations of the selected metals were predicted through two groups of equations. The first group of equations relates concentrations of suspended sediment with duststorm and stormwater parameters, whereas the second group relates the concentrations of the suspended sediment with those of heavy metals in the stormwater runoff. The results of the predictions encouraged recommendations on the use of the equations in the investigated catchments and identified the relative importance of the stormwater runoff and duststorms on the accumulation and transportation of heavy metals in the stormwater runoff. Based on the obtained results, recommendations concerning water quality control in arid areas are made.

scholarly journals ESTIMATION OF WATER QUALITY IN A RESERVOIR FROM SENTINEL-2 MSI AND LANDSAT-8 OLI SENSORS

2020 ◽  
Vol V-3-2020 ◽  
pp. 401-408
Author(s):  
F. M. C. Pizani ◽  
P. Maillard ◽  
A. F. F. Ferreira ◽  
C. C. de Amorim
Keyword(s):  
Water Quality ◽  
Multiple Regression ◽  
Regression Models ◽  
Quality Parameters ◽  
Optically Active ◽  
Water Quality Parameters ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Multiple Regression Models ◽  
Sentinel 2

Abstract. The low operational cost of using freely available remote sensing data is a strong incentive for water agencies to complement their field campaigns and produce spatially distributed maps of some water quality parameters. The objective of this study is to compare the performance of Sentinel-2 MSI and Landsat-8 OLI sensors to produce multiple regression models of water quality parameters in a hydroelectric reservoir in Brazil. Physical-chemistry water quality parameters were measured in loco using sensors and also analysed in laboratory from water samples collected simultaneously. The date of sampling corresponded to the almost simultaneous overflight of Sentinel-2B and Landsat-8 satellites which provided a means to perform a fair comparison of the two sensors. Four optically active parameters were considered: chlorophyll-a, Secchi disk depth, turbidity and temperature (the latter using Landsat-8 TIR sensor). Other six optically non-active parameters were also considered. The multiple regression models used the spectral reflectance bands from both sensors (separately) as predictors. The reflectance values were based on averaging kernels of 30 m and 90 m. Stepwise variable selection combined with a priori knowledge based on other studies were used to optimize the choice of predictors. With the exception of temperature, the other optically active parameters yielded strong regression models from both the Sentinel and Landsat sensors, all with r2 > 0.75. The models for the optically non-active parameters produced less striking results with r2 as low as 0.03 (temperature) and as high or better than > 0.8 (pH and Dissolved oxygen).

scholarly journals Access of Ground Water Quality with Associated Physico-Chemical Parameters of Cuttack District, Odisha, India

2019 ◽  
Vol 8 (12S) ◽  
pp. 260-267
Keyword(s):  
Water Quality ◽  
Ground Water ◽  
Correlation Coefficient ◽  
Fluoride Concentration ◽  
Chemical Properties ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
Potentially Toxic Trace Elements

The aim of present investigation was to analyze the variations in the physio-chemical properties of the ground water of Cuttack district Odisha. In the present study 98 samples were collected and analyzed to assess the quality of ground water. The pH, electrical conductivity (EC), total hardness and total alkalinity of the collected 98 samples were in the range of 4.6-7.3, 36-4550 μS/cm, 40-200 mgl-1, 20-680 mgl-1 respectively. Similarly, the other important water quality parameters such as; chloride, nitrate sulphate and phosphate concentration were varies between BDL-327, 1.8-86.25, BDL-194 and BDL to 3.2 mgl-1 respectively. The pH of the alluvial groundwater is controlled by the HCO3. The fluoride concentration was varies from BDL to 2.38 mgl-1. Apart from few samples, 90.81% fluoride contaminated samples comes under the category of quality group A (< 1 mgl-1flouride). Similarly, out of total samples collected only in three samples the uranium concentration estimated to be more than 5ppb. Among the water quality parameters there exist a positive correlation between pH and fluoride with a correlation coefficient of 0.641. From the correlation analysis it is found that, higher concentration of fluorid correlated with higher pH. Similarly the correlation coefficient between calcium and chloride is very high i.e. 0.500, which strongly supported the existence of calcium in the study area is predominantly in the form of CaCl2. Most of the ground water samples meet the requirements of the WHO drinking water standards with respect to salinity, main constituents and potentially toxic trace elements such as uranium

scholarly journals Variation in palladium and water quality parameters and their relationship in the urban water environment

2020 ◽  
Author(s):  
Yuyan Liu ◽  
Fangfang Ding ◽  
Caiye Ji ◽  
Dan Wu ◽  
Lin Wang ◽  
...  
Keyword(s):  
Water Quality ◽  
Correlation Coefficient ◽  
Water Body ◽  
Wet Deposition ◽  
Water Environment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Urban Water ◽  
Rainfall Runoff ◽  
Receiving Water

Abstract Palladium (Pd) is widely used in vehicle exhaust catalysts (VECs) to reduce toxic emissions from motor vehicles. The study aimed to quantitatively determine Pd content and water quality parameters, to analyze the variation differences and to explore the effect of water quality parameters on Pd content in the urban water environment system (wet deposition–rainfall runoff–receiving water body–estuary) of the city of Haikou, Hainan Island, China. The method used in this study included microwave digestion under high pressure and temperature, analysis by inductively coupled plasma mass spectrometry, quality control of the experimental procedure and guaranteed recovery (85% −125%). The results showed that the dissolved Pd average content in the urban water environment system was the highest in rainfall runoff (4.93 ng/L), followed by that in the receiving water body (4.56 ng/L), and it was the lowest in wet deposition (0.1 ng/L). The suspended Pd average content was the highest in the estuary (2.83 ng/L), followed by that in rainfall runoff (1.26 ng/L), and it was the lowest in wet deposition (6 × 10−4 ng/L). The particle–water partition ratio of the estuary Pd was the highest (1.26), followed by that of Pd in rainfall runoff (0.26). The particle–water partition ratio of the wet deposition Pd was the lowest (6 × 10−3). The dissolved Pd was correlated with the pH, Cl−, and total suspended solids (TSS) (correlation coefficient = 0.52, −0.68, 0.39, p &lt; 0.05; regression coefficient = 1.27, −1.39, 0.01). The suspended Pd was only correlated with Cl− and TSS (correlation coefficient = −0.36, 0.76, p &lt; 0.05; regression coefficient = −1.45, 0.01). Cl− and TSS were the most closely related to Pd in the water environment system. Although individual factors such as pH, Cl−, and TSS had certain migration and transformation effects on Pd in the wet deposition–rainfall runoff–receiving water body–estuary system, the probability of strong correlations was not high. In particular, Eh was not related to the dissolved nor suspended Pd content (correlation coefficient = 0.14, 0.13), which may be due to the synergistic effect of the multiple physical factors on Pd. This study was helpful to better understand the environmental behavior of Pd and provided important theoretical support for the prevention and protection against urban water environmental pollution.

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