scholarly journals GIS-Based Evaluation of Water Quality Index of Groundwater Resources in West Bokaro coalfield, India

2014 ◽  
Vol 9 (3) ◽  
pp. 843-850 ◽  
Author(s):  
Ashwani Tiwari ◽  
Prasoon Singh ◽  
Mukesh Mahato
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Groundwater Resources ◽  
West Bokaro Coalfield

Assessment of water quality in groundwater resources of Iran using a modified drinking water quality index (DWQI)

2013 ◽  
Vol 30 ◽  
pp. 28-34 ◽  
Author(s):  
Mohammad Reza Mohebbi ◽  
Reza Saeedi ◽  
Ahmad Montazeri ◽  
Kooshiar Azam Vaghefi ◽  
Sharareh Labbafi ◽  
...  
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Groundwater Resources ◽  
Drinking Water Quality

scholarly journals Assessment of Groundwater Quality for Drinking and Domestic Purposes through Local Survey and Water Quality Index in Vietnam

2021 ◽  
Vol 56 (2) ◽  
pp. 83-93
Author(s):  
Huynh The An ◽  
Tran Thi Ngoc Bich ◽  
Chen Yi-Ching ◽  
Tran Thi Thu Hien
Keyword(s):  
Water Quality ◽  
Groundwater Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Groundwater Resources ◽  
Total Hardness ◽  
Nitrate Content ◽  
Physical Parameters ◽  
Groundwater Exploitation ◽  
Groundwater Samples

The quality of groundwater resources is increasingly declining, significantly affecting people’s life and health. The study aims to assess public perception on existing groundwater quality and scheme over conventionally used free groundwater. The contemporaneous analytical procedures applied to determine the concentration of physical parameters: total dissolved solids and total solids and chemical parameters: pH, nitrite (N-NO2-), nitrate (N- NO3-), ammonium (N-NH4+/ NH3), iron (FeII + III) and total hardness were collected for 30 drinking water well samples located in 5 Quarters (An Hoa, An Loi, Ben Don, Phu Hoa, and Phu Nghi) to calculate the water quality index. The results show that up to 96% of people still use groundwater as their main source of drinking, domestic purposes, although groundwater quality is showing a serious decline in quality. The low pH index ranges from 3.0 ÷ 4.5. On average, 3.5 ÷ 4.0 pH of groundwater samples are outside the permissible limit according to VN standards 09: 2015 (5.5 - 8.5), which makes the water acidic, which harmful to human health. Besides, 10% of groundwater samples had high nitrate content, and 6.67% of water samples had ammonium content that did not meet VN standards 09: 2015. The current state of groundwater quality is not good for cooking and drinking. The results will benefit future groundwater exploitation to support more evidence of water quality and deteriorate the water quality soon, ultimately proving to be disastrous for all living beings in the region.

scholarly journals Evaluation of groundwater quality for drinking and irrigation purposes using GIS-based water quality index in urban area of Abaya-Chemo sub-basin of Great Rift Valley, Ethiopia

2021 ◽  
Vol 11 (9) ◽  
Author(s):  
Tamru Tesseme Aragaw ◽  
Gopalakrishnan Gnanachandrasamy
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Spatial Distribution ◽  
Groundwater Quality ◽  
Water Quality Index ◽  
Rift Valley ◽  
Quality Index ◽  
Groundwater Resources ◽  
Drinking And Irrigation ◽  
Great Rift Valley

AbstractGroundwater is the major resource for drinking and irrigation purposes in urban areas of Abaya-Chemo sub-basin of Great Rift Valley, Ethiopia. There is an incredible increase in demand in the sub-basin for good-quality groundwater resources. However, the exhaustive irrigation and rapid urbanization has posed a serious threat to groundwater quality in the urban districts of sub-basin like Arba Minch town. The aim of the study was to evaluate the groundwater quality status and to map their spatial distribution with respect to the suitability for drinking and irrigation purposes in Arba Minch town, Ethiopia. Fourteen bore well samples were examined for geochemical variations and groundwater qualities. The spatial distribution maps of quality parameters were prepared using the kriging method in ArcGIS 10.3. Drinking water quality index, sodium adsorption ratio (SAR), percentage sodium (Na%), residual sodium carbonate (RSC), and permeability index (PI) were considered for drinking and irrigation suitability assessment. Comparison of the hydrochemical results with the World Health Organization (WHO) and Ethiopian drinking water standards (ES) and various classifications revealed that the current status of the groundwaters is suitable for drinking and irrigation purposes except for a few sites at the northwestern part of the study area. The WQI results revealed that 7% and 64% of samples fall from excellent to good classes for drinking categories. Irrigation indices also demonstrated that 80% of samples fall in good classes for irrigation purposes. About 75 percent of samples belong to Ca–Mg-HCO3 facies, and the reaming samples belong to Ca–Mg–Cl facies. The results of the study concluded that the proposed approach is reliable and efficient for the groundwater pollution status evaluation and can also be applied in decision making for effective groundwater resources monitoring in the study area.

scholarly journals Performance of machine learning methods in predicting water quality index based on irregular data set: application on Illizi region (Algerian southeast)

2021 ◽  
Vol 11 (12) ◽  
Author(s):  
Saber Kouadri ◽  
Ahmed Elbeltagi ◽  
Abu Reza Md. Towfiqul Islam ◽  
Samir Kateb
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Groundwater Resources ◽  
Absolute Error ◽  
Quality Parameters ◽  
Support Vector ◽  
Multilinear Regression ◽  
Data Set ◽  
Artificial Neural Network Ann

AbstractGroundwater quality appraisal is one of the most crucial tasks to ensure safe drinking water sources. Concurrently, a water quality index (WQI) requires some water quality parameters. Conventionally, WQI computation consumes time and is often found with various errors during subindex calculation. To this end, 8 artificial intelligence algorithms, e.g., multilinear regression (MLR), random forest (RF), M5P tree (M5P), random subspace (RSS), additive regression (AR), artificial neural network (ANN), support vector regression (SVR), and locally weighted linear regression (LWLR), were employed to generate WQI prediction in Illizi region, southeast Algeria. Using the best subset regression, 12 different input combinations were developed and the strategy of work was based on two scenarios. The first scenario aims to reduce the time consumption in WQI computation, where all parameters were used as inputs. The second scenario intends to show the water quality variation in the critical cases when the necessary analyses are unavailable, whereas all inputs were reduced based on sensitivity analysis. The models were appraised using several statistical metrics including correlation coefficient (R), mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE), and root relative square error (RRSE). The results reveal that TDS and TH are the key drivers influencing WQI in the study area. The comparison of performance evaluation metric shows that the MLR model has the higher accuracy compared to other models in the first scenario in terms of 1, 1.4572*10–08, 2.1418*10–08, 1.2573*10–10%, and 3.1708*10–08% for R, MAE, RMSE, RAE, and RRSE, respectively. The second scenario was executed with less error rate by using the RF model with 0.9984, 1.9942, 3.2488, 4.693, and 5.9642 for R, MAE, RMSE, RAE, and RRSE, respectively. The outcomes of this paper would be of interest to water planners in terms of WQI for improving sustainable management plans of groundwater resources.

scholarly journals Assessment of Groundwater Quality Using Water Quality Index and Geographic Information System in Kumbotso Local Government Area, Kano State, Nigeria

2021 ◽  
Vol 5 (2) ◽  
pp. 569-581
Author(s):  
A.A. Saidu ◽  
S. Danazumi ◽  
S.M. Hamza
Keyword(s):  
Water Quality ◽  
Information System ◽  
Geographic Information System ◽  
Groundwater Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Groundwater Resources ◽  
Geographic Information ◽  
Total Hardness ◽  
Arid Environments

Water managers are faced with issues of groundwater resources management in dry land environments characterized by increasing population growth and prolonged dry period. Pollution of such resources has become a problem of notable importance in many arid and semi-arid environments of the developing countries. Unplanned urbanization; industrialization coupled with an increase in agricultural expansion has adversely affected groundwater quality. This study provides an overview of the status of groundwater quality in Kumbotso L.G.A using Water Quality Index. Physico-chemical parameters of pH, total dissolved solids, total hardness, magnesium, chloride, nitrate, calcium, and sulphate were measured from 12 groundwater samples. The results of the analysis were compared to the WHO standards to ascertain conformity with the guidelines. The Geographic Information System (GIS) was employed for mapping the distribution of various quality parameters as well as the overall groundwater quality condition. The overall map produced shows that 53.42km2 of the study area representing 33.81% were of excellent quality while 104.58km2 representing 66.19% of the area was found to be of good quality. Thus, a GIS based map developed can be a useful practical tool by water managers, policymakers and concerned communities in taking strategic decisions towards effective management of groundwater in the study area.

GIS-based Evaluation of Water Quality Index of groundwater resources around Tuticorin coastal city, south India

2013 ◽  
Vol 71 (6) ◽  
pp. 2847-2867 ◽  
Author(s):  
S. Selvam ◽  
G. Manimaran ◽  
P. Sivasubramanian ◽  
N. Balasubramanian ◽  
T. Seshunarayana
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
South India ◽  
Groundwater Resources ◽  
Coastal City

Hydrochemistry and Water Quality Index of groundwater resources in Enugu north district, Enugu, Nigeria

2019 ◽  
Vol 191 (3) ◽  
Author(s):  
Nwachukwu R. Ekere ◽  
Vitus E. Agbazue ◽  
Benedict U. Ngang ◽  
Janefrances N. Ihedioha
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Groundwater Resources
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