scholarly journals Exploring Artificial Intelligence Techniques for Groundwater Quality Assessment

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1172
Author(s):  
Purushottam Agrawal ◽  
Alok Sinha ◽  
Satish Kumar ◽  
Ankit Agarwal ◽  
Ashes Banerjee ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Traditional Approach ◽  
Human Life ◽  
Large Data ◽  
Quality Parameters ◽  
Support Vector ◽  
Artificial Intelligence Techniques

Freshwater quality and quantity are some of the fundamental requirements for sustaining human life and civilization. The Water Quality Index is the most extensively used parameter for determining water quality worldwide. However, the traditional approach for the calculation of the WQI is often complex and time consuming since it requires handling large data sets and involves the calculation of several subindices. We investigated the performance of artificial intelligence techniques, including particle swarm optimization (PSO), a naive Bayes classifier (NBC), and a support vector machine (SVM), for predicting the water quality index. We used an SVM and NBC for prediction, in conjunction with PSO for optimization. To validate the obtained results, groundwater water quality parameters and their corresponding water quality indices were found for water collected from the Pindrawan tank area in Chhattisgarh, India. Our results show that PSO–NBC provided a 92.8% prediction accuracy of the WQI indices, whereas the PSO–SVM accuracy was 77.60%. The study’s outcomes further suggest that ensemble machine learning (ML) algorithms can be used to estimate and predict the Water Quality Index with significant accuracy. Thus, the proposed framework can be directly used for the prediction of the WQI using the measured field parameters while saving significant time and effort.

GIS-based Spatio-Temporal and Geostatistical Analysis of Groundwater Parameters of Lahore Region Pakistan and their Source Characterization

2021 ◽  
Author(s):  
Sadia Ismail ◽  
M Farooq Ahmed
Keyword(s):  
Water Quality ◽  
Groundwater Quality ◽  
Water Quality Index ◽  
Physicochemical Parameters ◽  
Quality Index ◽  
Large Data ◽  
Quality Parameters ◽  
Source Characterization ◽  
Data Set ◽  
Spatio Temporal

Abstract Assessment of groundwater quality is critical, especially in the areas where it is continuously deteriorating due to unplanned industrial growth. This study utilizes GIS-based spatio-temporal and geostatistics tools to characterize the groundwater quality parameters of Lahore region. For this purpose, a large data set of the groundwater quality parameters (for a period of 2005–2016) was obtained from the deep unconfined aquifers. GIS-based water quality index (WQI) and entropy water quality index (EWQI) models were prepared using 15 water quality parameters pH (power of hydrogen), TDS (Total dissolve solids), EC (Electrical conductivity), TH (Total hardness), Ca2+ (Calcium), Mg2+ (Magnesium), Na+ (Sodium), K+ (Potassium), Cl− (Chloride), As (Arsenic), F (Fluoride), Fe (Iron), HCO3− (Bicarbonate), NO3− (Nitrate), and SO42− (Sulfate). The data analysis exhibits that 12% of the groundwater samples fell within the category of poor quality that helped to identify the permanent epicenters of deteriorating water quality index in the study area. As per the entropy theory, Fe, NO3−, K, F, SO42− and As, are the major physicochemical parameters those influence groundwater quality. The spatio-temporal analysis of the large data set revealed an extreme behavior in pH values along the Hudiara drain, and overall high arsenic concentration levels in most of the study area. The geochemical analysis shows that the groundwater chemistry is strongly influence by subsurface soil water interaction. The research highlights the significance of using GIS-based spatio-temporal and geostatistical tools to analyze the large data sets of physicochemical parameters at regional level for the detailed source characterization studies.

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.

Evaluation of Ground Water Quality For AL Shuwayja area –Wasit Provence Using GIS Technique

2017 ◽  
Vol 1 (2) ◽  
pp. 1-11
Author(s):  
Ali Nasser Hilo
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Ground Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Poor Quality ◽  
Quality Parameters ◽  
Ground Water Quality ◽  
Water Index ◽  
The City

The low level of water in rivers in Iraq leads to poor water quality, on that basis; we need to assess Iraq's water resources for uses of irrigation and drinking water. This study present a model accounts for ground water quality by using a water quality index (WQI) for the region defined between the city of Kut and the city of Badra in Wasit province. this study relies on a system of wells set up along the path through the Badra –Kut  and around it  up to 78 wells. The study showed poor quality of ground water in the region of study and it is unsuitability for irrigation and drinking water, as well as provided a solution to the water accumulated in the Shuwayja to reduce the bad effect on groundwater by using a system of branch and collection canals  then pumping at the effluent  of Al  Shuwayja in seasons of rainy season ..Water quality index calculated depend on the basis of various physic-chemical parameters as PH, Ec , TDS, TSS, Nacl , SO4 ,Na , and  Mg. The resultant and analytical are present with use of Arch GIS program – geostastical analysis for the water index and water quality parameters

scholarly journals A study on ground water quality of industrial area at Gajraula (U.P.), India

2009 ◽  
Vol 1 (2) ◽  
pp. 275-279 ◽  
Author(s):  
D. S. Malik ◽  
Pawan Kumar ◽  
Umesh Bharti
Keyword(s):  
Water Quality ◽  
Ground Water ◽  
Water Samples ◽  
Water Quality Index ◽  
Quality Index ◽  
Analytical Techniques ◽  
Industrial Area ◽  
Quality Standard ◽  
Quality Parameters ◽  
Marginal Values

The present study aims to identify the ground water contamination problem in villages located in the close vicinity of Gajraula industrial area at Gajraula (U.P.), India. Ground water samples were collected from different villages at the depth of 40 and 120 feet from earth’s surface layer. Analytical techniques as described in the standard methods for examination of water and waste water were adopted for physico-chemical analysis of ground water samples and the results compared with the standards given by WHO and BIS guidelines for drinking water. Water quality index was calculated for quality standard of ground water for drinking purposes. The present investigation revealed that the water quality is moderately degraded due to high range of seven water quality parameters such as Temperature (18.33-32.36 0C), conductivity (925.45-1399.59 μmho/cm), TDS (610.80-923.73 mgL-1), Alkalinity (260.17- 339.83 mgL-1), Ca-Hardness (129.68-181.17 mgL-1), Mg-Hardness (94.07-113.50 mgLÉ1) and COD (13.99-25.62 mgL-1). The water quality index (WQI) also indicated the all the water quality rating comes under the standard marginal values (45-64) i.e. water quality is frequently threatened or impaired and conditions usually depart from natural or desirable levels.

Evaluation of Water Quality of Hemren Lake

2013 ◽  
Vol 6 (2) ◽  
pp. 57-76
Author(s):  
SAAD SH. SAMMEN
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Quality Parameters ◽  
Lake Ecosystem ◽  
Index Method ◽  
Weighted Arithmetic ◽  
Canadian Council ◽  
Calcium Magnesium

In this study Water Quality Index (WQI) was applied in Hemren Lake, Diyala province, Iraq using ten water quality parameters (pH, Electrical Conductivity, Hardness, Total Dissolve Soluble, Sodium, Calcium, Magnesium, Potassium, Chloride, Phosphate) from 2008 to 2010 to evaluate the suitability of Hemren Lake ecosystem for drinking and irrigation uses. The Weighted Arithmetic Index method (WAM) and the Canadian Council of Ministers of the Environment Water Quality Index methodology (The CWQI 1.0 model) were used to calculate the water quality index (W.Q.I). The results indicated that drinking water quality of Hemren Lake is good and marginal for the study period according to (WAM) and (CCME) respectively, while the irrigation water quality is good and according to (WAM) and (CCME). It is suggested that monitoring of the lake is necessary for proper management. Application of the WQI is also suggested as a very helpful tool that enables the public and decision makers to evaluate water quality of lakes in Iraq.

scholarly journals A Multidisciplinary Approach for Evaluating Spatial and Temporal Variations in Water Quality

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 853 ◽  
Author(s):  
Viet Thang Le ◽  
Nguyen Hong Quan ◽  
Ho Huu Loc ◽  
Nguyen Thi Thanh Duyen ◽  
Tran Duc Dung ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Water Quality ◽  
Confusion Matrix ◽  
Temporal Variations ◽  
Machine Learning Techniques ◽  
Spatial And Temporal Variations ◽  
Support Vector ◽  
Domestic Water ◽  
Supply Source ◽  
Artificial Intelligence Techniques

The primary goal of this study is to investigate the classification capability of several artificial intelligence techniques, including the decision tree (DT), multilayer perceptron (MLP) network, Naïve Bayes, radial basis function (RBF) network, and support vector machine (SVM) for evaluating spatial and temporal variations in water quality. The application case is the Song Quao-Ca Giang (SQ-CG) water system, a main domestic water supply source of the city of Phan Thiet in Binh Thuan province, Vietnam. To evaluate the water quality condition of the source, the government agency has initiated an extensive sampling project, collecting samples from 43 locations covering the SQ reservoir, the main canals, and the surrounding areas during 2015–2016. Different classifying models based on artificial intelligence techniques were developed to analyze the sampling data after the performances of the models were evaluated and compared using the confusion matrix, accuracy rate, and several error indexes. The results show that machine-learning techniques can be used to explicitly evaluate spatial and temporal variations in water quality.

scholarly journals Evaluation of Water Quality of the Titas River Using NSF Water Quality Index

2010 ◽  
Vol 3 (1) ◽  
pp. 151 ◽  
Author(s):  
S. Islam ◽  
T. Rasul ◽  
J. Bin Alam ◽  
M. A. Haque
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Laboratory Tests ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Huge Amount ◽  
Water Quality Status ◽  
Quality Status

The Titas River, a trans-boundary river of Bangladesh flows almost the entire Brahmanbaria district, consumes a huge amount of sewage, agricultural discharges and runoff, waste produced from human excreta, discharges of two oil mills and contaminants from other minor sources. A study is conducted to find the water quality status of the river during the period from July 2008 to June 2009 and by using National Sanitation Foundation (NSF) water quality index, the probable use of this water is predicted. This work consists of laboratory tests for the evaluation of some water quality parameters of the Titas and to identify its probable use in various purposes. The results of the laboratory tests and NSF water quality index suggest that the water can be used for recreation, pisciculture and irrigation purposes but requires treatment before using for drinking.Keywords: Water pollution; Faecal coliform; Dissolved oxygen (DO); Biochemical oxygen demand (BOD).© 2011 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.doi:10.3329/jsr.v3i1.6170                 J. Sci. Res. 3 (1), 151-159 (2011)

scholarly journals Assessment of coastal surface water quality for irrigation purpose

2020 ◽  
Vol 15 (4) ◽  
pp. 960-972
Author(s):  
M. F. Serder ◽  
M. S. Islam ◽  
M. R. Hasan ◽  
M. S. Yeasmin ◽  
M. G. Mostafa
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Water Type ◽  
Post Monsoon ◽  
Irrigation Purpose

Abstract The study aimed to assess the coastal surface water quality for irrigation purposes through the analysis of the water samples of some selected estuaries, rivers, and ponds. The analysis results showed that the mean value of typical water quality parameters like electrical conductivity (EC), total dissolved solids (TDS), sodium (Na+), and chloride (Cl−) ions exceeded the permissible limit of the Department of Environment (DoE), Bangladesh 2010, and FAO, 1985 for the pre- and post-monsoon seasons. The Piper diagram indicated a Na-Cl water type, especially during the pre- and post-monsoon seasons. The water quality parameters in the areas showed a higher amount than the standard permissible limits, indicating that the quality is deteriorating. The water quality index values for domestic uses showed very poorly to unsuitable in most of the surface waters except pond water, especially during the pre- and post-monsoon periods. The surface water quality index for irrigation purpose usages was found to be high and/ or severely restricted (score: 0–55) during the pre- and post-monsoon seasons. The study observed that due to saline water intrusion, the water quality deterioration started from post-monsoon and reached its highest level during the pre-monsoon season, which gradually depreciates the water quality in coastal watersheds of Bangladesh.

scholarly journals Assessment of Variation in Water Quality Index (WQI) of Groundwater in North Goa, India

2016 ◽  
Vol 11 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Gopal Krishan ◽  
C. P. Kumar ◽  
B.K. Purandara ◽  
Surjeet Singh ◽  
N. C Ghosh ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Temporal Variations ◽  
Quality Parameters ◽  
Spatial And Temporal Variation ◽  
Total Hardness ◽  
Future Planning ◽  
Groundwater Samples ◽  
Domestic Use

A water quality index (WQI) is a tool which numerically summarizes the information from multiple water quality parameters into a single value and this information can be used to assess spatial and temporal variations in overall water quality. However, these indices are time and region specific and may be influenced by local factors. In the present study, water quality index has been worked out to assess the spatial and temporal variation of groundwater quality status for future planning and management of North Goa. Data of 19 groundwater samples were collected in the year 2005 during January, March and April, are used for the analysis. The Water Quality Index has been computed using four parameters viz. pH, Total Dissolved Solids, Total Hardness and Chloride. The WQI results show that the overall water quality class is ‘good’ and water is acceptable for domestic use.

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