Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis

Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis Publisher

Radfard M¹ ; Seif M² ; Ghazizadeh Hashemi AH³ ; Zarei A^{4, 5} ; Saghi MH⁶ ; Shalyari N⁷ ; Morovati R¹ ; Heidarinejad Z⁸ ; Samaei MR¹

Show Affiliations

1. Department of Environmental Health Engineering, School of Public Health, Shiraz University of Medical Sciences, Shiraz, Iran
2. Department of Epidemiology, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
3. Shahid Beheshti University of Medical Sciences, Tehran, Iran
4. Department of Environmental Health Engineering, Faculty of Health, Gonabad University of Medical Sciences, Gonabad, Iran
5. Social Determinants of Health Research Center, Department of Health, School of Public Health, Gonabad University of Medical Sciences, Gonabad, Iran
6. Department of Environmental Health Engineering, School of Public Health, Sabzevar University of Medical Sciences, Sabzevar, Iran
7. Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
8. Food Health Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

Source: MethodsX Published:2019

Abstract

Drinking water sources may be polluted by various pollutants depending on geological conditions and agricultural, industrial, and other human activities. Ensuring the safety of drinking water is, therefore, of a great importance. The purpose of this study was to assess the quality of drinking groundwater in Bardaskan villages and to determine the water quality index. Water samples were taken from 30 villages and eighteen parameters including calcium hardness (CaH), total hardness (TH), turbidity, pH, temperature, total dissolved solids (TDS), electrical conductivity (EC), alkalinity (ALK), magnesium (Mg2+), calcium (Ca2+), potassium (K+), sodium (Na+), sulphate (SO4 2−), bicarbonate (HCO3 −), fluoride (F−), nitrate (NO3 −), nitrite (NO2 −)and chloride (Cl−)were analyzed for the purpose for this study. The water quality index of groundwater has been estimated by using the ANFIS. The spatial locations are shown using GPS. The results of this study showed that water hardness, electrical conductivity, sodium and sulfate in 66, 13, 45 and 12.5% of the studied villages were higher than the Iranian drinking water standards, respectively. Based on the Drinking Water Quality Index (DWQI), water quality in 3.3, 60, 23.3 and 13.3% of villages was excellent, good, poor and very poor, respectively. • Groundwater is one of the sources of drinking water in arid and semi-arid regions such as Bardaskan villages, which monitor the quality of these resources in planning for improving the quality of water resources. • The DWQI can clearly provide information associated with the status of water quality resources in Bardaskan villages. • The results of this study clearly indicated that with appropriate selection of input variables, ANFIS as a soft computing approach can estimate water quality indices properly and reliably. • Some parameters were in the undesirable level is some villages. Therefore, the government should try to improve the chemical and physical quality of drinking water in these areas with the necessary strategies. © 2019 The Authors

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Style	Citing Format
MLA	Radfard M, et al.. "Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis." MethodsX, vol. 6, no. , 2019, pp. 1021-1029.
APA	Radfard M, Seif M, Ghazizadeh Hashemi AH, Zarei A, Saghi MH, Shalyari N, Morovati R, Heidarinejad Z, Samaei MR (2019). Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis. MethodsX, 6(), 1021-1029.
Chicago	Radfard M, Seif M, Ghazizadeh Hashemi AH, Zarei A, Saghi MH, Shalyari N, Morovati R, Heidarinejad Z, Samaei MR. "Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis." MethodsX 6, no. (2019): 1021-1029.
Harvard	Radfard M et al. (2019) 'Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis', MethodsX, 6(), pp. 1021-1029.
Vancouver	Radfard M, Seif M, Ghazizadeh Hashemi AH, Zarei A, Saghi MH, Shalyari N, et al.. Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis. MethodsX. 2019;6():1021-1029.
BibTex	@article{ author = {Radfard M and Seif M and Ghazizadeh Hashemi AH and Zarei A and Saghi MH and Shalyari N and Morovati R and Heidarinejad Z and Samaei MR}, title = {Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis}, journal = {MethodsX}, volume = {6}, number = {}, pages = {1021-1029}, year = {2019} }
RIS	TY - JOUR AU - Radfard M AU - Seif M AU - Ghazizadeh Hashemi AH AU - Zarei A AU - Saghi MH AU - Shalyari N AU - Morovati R AU - Heidarinejad Z AU - Samaei MR TI - Protocol for the Estimation of Drinking Water Quality Index (Dwqi)In Water Resources: Artificial Neural Network (Anfis)And Arc-Gis JO - MethodsX VL - 6 IS - SP - 1021 EP - 1029 PY - 2019 ER -

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