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Reza Saeedi - One of the best experts on this subject based on the ideXlab platform.
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a modified Drinking Water Quality index dwqi for assessing Drinking source Water Quality in rural communities of khuzestan province iran
Ecological Indicators, 2015Co-Authors: Mehrnoosh Abtahi, Najmeh Golchinpour, Kamyar Yaghmaeian, Mohammad Rafiee, Mahsa Jahangirirad, Alidad Keyani, Reza SaeediAbstract:Abstract We reconsidered the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) to achieve an efficient Drinking Water Quality index (DWQI) for assessment of Drinking source Water Quality in rural communities of Khuzestan Province, Iran in 2009–2013. In contribution with a panel of Water Quality experts, the CCME WQI was mainly modified by four changes: (1 and 2) assigning weight factors for input parameters and index factors, (3) modifying excursion concept for carcinogens and bioaccumulative pollutants and (4) removing effect of unequal measurements of input parameters. The DWQI characterizes the Drinking source Water Quality through comparing the measured values of input parameters with relevant benchmarks. The DWQI score (from 0 to 100) classifies the Water Quality in five categories as poor (0–54.9), marginal (55.0–69.9), fair (70.0–84.9), good (85.0–94.9) and excellent (95.0–100). Based on the DWQI, the temporal changes of the rural Drinking source Water Quality were not significant; while the spatial variations of the Water Quality were considerable across the province, so the DWQI scores in the northern counties were higher than that in the southern ones. At the county level, the highest and lowest average scores of the DWQI (±standard deviation: SD) were observed in Izeh and Shadegan to be 90 ± 5 and 69 ± 10, respectively. Based on the DWQI, proportions of the Drinking Water sources with the excellent, good, fair, marginal and poor qualities were determined to be 6.7, 59.1, 26.2, 7.8 and 0.1%, respectively. Turbidity and Ryznar Index (RI) were introduced respectively as the health-based and esthetic parameters with the most violations (22.7 and 63.2%, respectively). The results of the case study and sensitivity analysis indicated that the DWQI is a simple, flexible, stable and reliable index and could be used as an effective tool to characterize Drinking source Water Quality.
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assessment of Water Quality in groundWater resources of iran using a modified Drinking Water Quality index dwqi
Ecological Indicators, 2013Co-Authors: Mohammad Reza Mohebbi, Kooshiar Azam Vaghefi, Ahmad Montazeri, Reza Saeedi, Sharareh Labbafi, Sogol Oktaie, Mehrnoosh Abtahi, Azita MohagheghianAbstract:An innovative Drinking Water Quality index (DWQI) based on the Canadian DWQI was developed as “modified DWQI” and applied for assessing the Water Quality in all of the groundWater resources that are used as the source of Drinking Water in urban areas of Iran in 2011. Assignment of weight factors for input parameters was the modification carried out in the DWQI. In development of the modified DWQI, twenty-three Water Quality parameters and relevant Iranian standards for Drinking Water Quality were selected as input parameters and benchmarks, respectively. The modified DWQI is calculated for each sampling station over one year using three factors: the number of parameters that excurse benchmarks, the number of measurements in a dataset that excurse benchmarks and the magnitude of excursion from benchmarks in the violator measurements. The modified DWQI contains two sub-indices: health-based index as “modified HWQI” and acceptability index as “modified AWQI”. The modified DWQI and its sub-indices scores range from 0 to 100 and classify Water Quality in five categories as poor, marginal, fair, good and excellent, respectively. The results of the case study revealed that the nationwide average scores of the modified DWQI, HWQI and AWQI in the groundWater resources were 85, 79 and 91, respectively and overall situation of Water Quality in the groundWater resources was described as good. According to the modified DWQI value, about 95% of the groundWater flowrates were in the good condition, also in 3 and 2% of the groundWater flowrates, Water Quality was determined to be fair and marginal, respectively. This study indicated that the modified DWQI and its sub-indices could describe the overall Water Quality of Water bodies easily, reliably and correctly and have the potential suitability for extensive application all over the world.
Mehrnoosh Abtahi - One of the best experts on this subject based on the ideXlab platform.
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a modified Drinking Water Quality index dwqi for assessing Drinking source Water Quality in rural communities of khuzestan province iran
Ecological Indicators, 2015Co-Authors: Mehrnoosh Abtahi, Najmeh Golchinpour, Kamyar Yaghmaeian, Mohammad Rafiee, Mahsa Jahangirirad, Alidad Keyani, Reza SaeediAbstract:Abstract We reconsidered the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) to achieve an efficient Drinking Water Quality index (DWQI) for assessment of Drinking source Water Quality in rural communities of Khuzestan Province, Iran in 2009–2013. In contribution with a panel of Water Quality experts, the CCME WQI was mainly modified by four changes: (1 and 2) assigning weight factors for input parameters and index factors, (3) modifying excursion concept for carcinogens and bioaccumulative pollutants and (4) removing effect of unequal measurements of input parameters. The DWQI characterizes the Drinking source Water Quality through comparing the measured values of input parameters with relevant benchmarks. The DWQI score (from 0 to 100) classifies the Water Quality in five categories as poor (0–54.9), marginal (55.0–69.9), fair (70.0–84.9), good (85.0–94.9) and excellent (95.0–100). Based on the DWQI, the temporal changes of the rural Drinking source Water Quality were not significant; while the spatial variations of the Water Quality were considerable across the province, so the DWQI scores in the northern counties were higher than that in the southern ones. At the county level, the highest and lowest average scores of the DWQI (±standard deviation: SD) were observed in Izeh and Shadegan to be 90 ± 5 and 69 ± 10, respectively. Based on the DWQI, proportions of the Drinking Water sources with the excellent, good, fair, marginal and poor qualities were determined to be 6.7, 59.1, 26.2, 7.8 and 0.1%, respectively. Turbidity and Ryznar Index (RI) were introduced respectively as the health-based and esthetic parameters with the most violations (22.7 and 63.2%, respectively). The results of the case study and sensitivity analysis indicated that the DWQI is a simple, flexible, stable and reliable index and could be used as an effective tool to characterize Drinking source Water Quality.
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assessment of Water Quality in groundWater resources of iran using a modified Drinking Water Quality index dwqi
Ecological Indicators, 2013Co-Authors: Mohammad Reza Mohebbi, Kooshiar Azam Vaghefi, Ahmad Montazeri, Reza Saeedi, Sharareh Labbafi, Sogol Oktaie, Mehrnoosh Abtahi, Azita MohagheghianAbstract:An innovative Drinking Water Quality index (DWQI) based on the Canadian DWQI was developed as “modified DWQI” and applied for assessing the Water Quality in all of the groundWater resources that are used as the source of Drinking Water in urban areas of Iran in 2011. Assignment of weight factors for input parameters was the modification carried out in the DWQI. In development of the modified DWQI, twenty-three Water Quality parameters and relevant Iranian standards for Drinking Water Quality were selected as input parameters and benchmarks, respectively. The modified DWQI is calculated for each sampling station over one year using three factors: the number of parameters that excurse benchmarks, the number of measurements in a dataset that excurse benchmarks and the magnitude of excursion from benchmarks in the violator measurements. The modified DWQI contains two sub-indices: health-based index as “modified HWQI” and acceptability index as “modified AWQI”. The modified DWQI and its sub-indices scores range from 0 to 100 and classify Water Quality in five categories as poor, marginal, fair, good and excellent, respectively. The results of the case study revealed that the nationwide average scores of the modified DWQI, HWQI and AWQI in the groundWater resources were 85, 79 and 91, respectively and overall situation of Water Quality in the groundWater resources was described as good. According to the modified DWQI value, about 95% of the groundWater flowrates were in the good condition, also in 3 and 2% of the groundWater flowrates, Water Quality was determined to be fair and marginal, respectively. This study indicated that the modified DWQI and its sub-indices could describe the overall Water Quality of Water bodies easily, reliably and correctly and have the potential suitability for extensive application all over the world.
Azita Mohagheghian - One of the best experts on this subject based on the ideXlab platform.
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assessment of Water Quality in groundWater resources of iran using a modified Drinking Water Quality index dwqi
Ecological Indicators, 2013Co-Authors: Mohammad Reza Mohebbi, Kooshiar Azam Vaghefi, Ahmad Montazeri, Reza Saeedi, Sharareh Labbafi, Sogol Oktaie, Mehrnoosh Abtahi, Azita MohagheghianAbstract:An innovative Drinking Water Quality index (DWQI) based on the Canadian DWQI was developed as “modified DWQI” and applied for assessing the Water Quality in all of the groundWater resources that are used as the source of Drinking Water in urban areas of Iran in 2011. Assignment of weight factors for input parameters was the modification carried out in the DWQI. In development of the modified DWQI, twenty-three Water Quality parameters and relevant Iranian standards for Drinking Water Quality were selected as input parameters and benchmarks, respectively. The modified DWQI is calculated for each sampling station over one year using three factors: the number of parameters that excurse benchmarks, the number of measurements in a dataset that excurse benchmarks and the magnitude of excursion from benchmarks in the violator measurements. The modified DWQI contains two sub-indices: health-based index as “modified HWQI” and acceptability index as “modified AWQI”. The modified DWQI and its sub-indices scores range from 0 to 100 and classify Water Quality in five categories as poor, marginal, fair, good and excellent, respectively. The results of the case study revealed that the nationwide average scores of the modified DWQI, HWQI and AWQI in the groundWater resources were 85, 79 and 91, respectively and overall situation of Water Quality in the groundWater resources was described as good. According to the modified DWQI value, about 95% of the groundWater flowrates were in the good condition, also in 3 and 2% of the groundWater flowrates, Water Quality was determined to be fair and marginal, respectively. This study indicated that the modified DWQI and its sub-indices could describe the overall Water Quality of Water bodies easily, reliably and correctly and have the potential suitability for extensive application all over the world.
L C Rietveld - One of the best experts on this subject based on the ideXlab platform.
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a bayesian belief network model to link sanitary inspection data to Drinking Water Quality in a medium resource setting in rural indonesia
Scientific Reports, 2020Co-Authors: D Daniel, Widya Prihesti Iswarani, Saket Pande, L C RietveldAbstract:Assessing Water Quality and identifying the potential source of contamination, by Sanitary inspections (SI), are essential to improve household Drinking Water Quality. However, no study link the Water Quality at a point of use (POU), household level or point of collection (POC), and associated SI data in a medium resource setting using a Bayesian Belief Network (BBN) model. We collected Water samples and applied an adapted SI at 328 POU and 265 related POC from a rural area in East Sumba, Indonesia. Fecal contamination was detected in 24.4 and 17.7% of 1 ml POC and POU samples, respectively. The BBN model showed that the effect of holistic-combined interventions to improve the Water Quality were larger compared to individual intervention. The Water Quality at the POU was strongly related to the Water Quality at the POC and the effect of household Water treatment to improve the Water Quality was more prominent in the context of better sanitation and hygiene conditions. In addition, it was concluded that the inclusion of extra "external" variable (fullness level of Water at storage), besides the standard SI variables, could improve the model's performance in predicting the Water Quality at POU. Finally, the BBN approach proved to be able to illustrate the interdependencies between variables and to simulate the effect of the individual and combination of variables on the Water Quality.
Sina Zahedi - One of the best experts on this subject based on the ideXlab platform.
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modification of expected conflicts between Drinking Water Quality index and irrigation Water Quality index in Water Quality ranking of shared extraction wells using multi criteria decision making techniques
Ecological Indicators, 2017Co-Authors: Sina ZahediAbstract:Abstract GroundWater resources play a crucial role in most arid/semi-arid regions such as Karaj plain, Iran. Excavation of wells and exploiting Water resources of aquifers have long been known as ordinary solutions to supply Water demands for Drinking, agricultural and industrial purposes. In many agricultural areas such as the above-mentioned region, extraction wells have been utilized for both Drinking and agricultural consumptions, while measures taken for Water Quality monitoring and protecting public health are seriously limited. On the other hand, most of the shared extraction wells in the region used for Drinking purpose have been located near the agricultural lands and they are highly under the risk of getting polluted by Agricultural pesticides. The current paper firstly intends to demonstrate the results obtained from Drinking Water Quality Index (DWQI) as well as Irrigation Water Quality Index (IWQI) and secondly determines probable conflicts that may be aroused in ranking of Water wells using these two methods Subsequently, Multi Criteria Decision Making (MCDM) techniques such as Ordered Weighted Averaging (OWA), Compromise Programing (CP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were employed to decrease effects of the conflicts. It was clarified that MCDMs, to some extent, alleviated contradictions in wells’ ranks −determined by DWQI/IWQI- and authenticated this procedure as an appropriate method for Water Quality ranking in agricultural societies.
