A probabilistic water quality index for river water quality assessment: a case study

Available water quality indices have some limitations such as incorporating a limited number of water quality variables and providing deterministic outputs. This paper presents a hybrid probabilistic water quality index by utilizing fuzzy inference systems (FIS), Bayesian networks (BNs), and probabilistic neural networks (PNNs). The outputs of two traditional water quality indices, namely the indices proposed by the National Sanitation Foundation and the Canadian Council of Ministers of the Environment, are selected as inputs of the FIS. The FIS is trained based on the opinions of several water quality experts. Then the trained FIS is used in a Monte Carlo analysis to provide the required input-output data for training both the BN and PNN. The trained BN and PNN can be used for probabilistic water quality assessment using water quality monitoring data. The efficiency and applicability of the proposed methodology is evaluated using water quality data obtained from water quality monitoring system of the Jajrood River in Iran.     

Assessing the water quality index of water treatment plant and bore wells, in Delhi, India

Water quality monitoring exercise was carried out with water quality index (WQI) method by using water characteristics data for bore wells and a water treatment plant in Delhi city from December 2006 to August 2007. The water treatment plant received surface water as raw water, and product water is supplied after treatment. The WQI is used to classify water quality as excellent, good, medium, bad, and very bad. The National Sanitation Foundation WQI procedure was used to calculate the WQI. The index ranges from 0 to 100, where 100 represents an excellent water quality condition. Water samples were collected monthly from a bore well in Nehru Camp (site 1), a bore well in Sanjay Gandhi pumping station (site 2), and water treatment plant in Haiderpur (site 3). Five parameters were analyzed, namely, nitrate, pH, total dissolved solids, turbidity, and temperature. We found that the WQI was around 73–80 in site 3, which corresponds to “good,” and it decreased to 54.32–60.19 and 59.93–70.63 in site 1 and site 2, respectively, indicating that these bore wells were classified as “medium” quality.     

Stagnant surface water bodies (SSWBs) as an alternative water resource for the Chittagong metropolitan area of Bangladesh: physicochemical characterization in terms of water quality indices

The concern over ensuing freshwater scarcity has forced the developing countries to delve for alternative water resources. In this study, we examined the potential of stagnant surface water bodies (SSWBs) as alternative freshwater resources in the densely populated Chittagong metropolitan area (CMPA) of Bangladesh??where there is an acute shortage of urban freshwater supply. Water samples were collected at 1-month intervals for a period of 1 year from 12 stations distributed over the whole metropolis. Samples were analyzed for pH, water temperature (WTemp), turbidity, electrical conductivity (EC), total dissolved solids, total solids, total hardness, dissolved oxygen (DO), chloride, orthophosphates, ammonia, total coliforms (TC), and trace metal (Cd, Cr, Cu, Pb, As, and Fe) concentrations. Based on these parameters, different types of water quality indices (WQIs) were deduced. WQIs showed most of CMPA-SSWBs as good or medium quality water bodies, while none were categorized as bad. Moreover, it was observed that the minimal water quality index (WQI_m), computed using five parameters: WTemp, pH, DO, EC, and turbidity, gave a reliable estimate of water quality. The WQI_m gave similar results in 72% of the cases compared with other WQIs that were based on larger set of parameters. Based on our finding, we suggest the wider use WQI_m in developing countries for assessing health of SSWBs, as it will minimize the analytical cost to overcome the budget constraints involved in this kind of evaluations. It was observed that except turbidity and TC content, all other quality parameters fluctuated within the limit of the World Health Organization suggested standards for drinking water. From our findings, we concluded that if the turbidity and TC content of water from SSWBs in CMPA are taken care of, they will become good candidates as alternative water resources all round the year.     

Water Quality Changes in Chini Lake, Pahang, West Malaysia

A study of the water quality changes of Chini Lake was conducted for 12 months, which began in May 2004 and ended in April 2005. Fifteen sampling stations were selected representing the open water body in the lake. A total of 14 water quality parameters were measured and Malaysian Department of Environment Water Quality Index (DOE-WQI) was calculated and classified according to the Interim National Water Quality Standard, Malaysia (INWQS). The physical and chemical variables were temperature, dissolved oxygen (DO), conductivity, pH, total dissolved solid (TDS), turbidity, chlorophyll-a, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), ammonia-N, nitrate, phosphate and sulphate. Results show that base on Malaysian WQI, the water in Chini Lake is classified as class II, which is suitable for recreational activities and allows body contact. With respect to the Interim National Water Quality Standard (INWQS), temperature was within the normal range, conductivity, TSS, nitrate, sulphate and TDS are categorized under class I. Parameters for DO, pH, turbidity, BOD, COD and ammonia-N are categorized under class II. Comparison with eutrophic status indicates that chlorophyll-a concentration in the lake was in mesotrophic condition. In general water quality in Chini Lake varied temporally and spatially, and the most affected water quality parameters were TSS, turbidity, chlorophyll-a, sulphate, DO, ammonia-N, pH and conductivity.     

Monitoring of potentially toxic cyanobacteria using an online multi-probe in drinking water sources

Toxic cyanobacteria threaten the water quality of drinking water sources across the globe. Two such water bodies in Canada (a reservoir on the Yamaska River and a bay of Lake Champlain in Québec) were monitored using a YSI 6600 V2-4 (YSI, Yellow Springs, Ohio, USA) submersible multi-probe measuring in vivo phycocyanin (PC) and chlorophyll-a (Chl-a) fluorescence, pH, dissolved oxygen, conductivity, temperature, and turbidity in parallel. The linearity of the in vivo fluorescence PC and Chl-a probe measurements were validated in the laboratory with Microcystis aeruginosa (r(2) = 0.96 and r(2) = 0.82 respectively). Under environmental conditions, in vivo PC fluorescence was strongly correlated with extracted PC (r = 0.79) while in vivo Chl-a fluorescence had a weaker relationship with extracted Chl-a (r = 0.23). Multiple regression analysis revealed significant correlations between extracted Chl-a, extracted PC and cyanobacterial biovolume and in vivo fluorescence parameters measured by the sensors (i.e. turbidity and pH). This information will help water authorities select the in vivo parameters that are the most useful indicators for monitoring cyanobacteria. Despite highly toxic cyanobacterial bloom development 10 m from the drinking water treatment plant's (DWTP) intake on several sampling dates, low in vivo PC fluorescence, cyanobacterial biovolume, and microcystin concentrations were detected in the plant's untreated water. The reservoir's hydrodynamics appear to have prevented the transport of toxins and cells into the DWTP which would have deteriorated the water quality. The multi-probe readings and toxin analyses provided critical evidence that the DWTP's untreated water was unaffected by the toxic cyanobacterial blooms present in its source water.     

Assessing the risk posed by high-turbidity water to water supplies

The objective of this study is to assess the risk of insufficient water supply posed by high-turbidity water. Several phenomena can pose risks to the sufficiency of a water supply; this study concerns risks to water treatment plants from particular properties of rainfall and raw water turbidity. High-turbidity water can impede water treatment plant operations; rainfall properties can influence the degree of soil erosion. Thus, water turbidity relates to rainfall characteristics. Exceedance probabilities are presented for different rainfall intensities and turbidities of water. When the turbidity of raw water is higher than 5,000 NTU, it can cause operational problems for a water treatment plant. Calculations show that the turbidity of raw water at the Ban-Sin water treatment plant will be higher than 5,000 NTU if the rainfall intensity is larger than 165 mm/day. The exceedance probability of high turbidity (turbidity >5,000 NTU) in the Ban-Sin water treatment plant is larger than 10%. When any water treatment plant cannot work regularly, its ability to supply water to its customers is at risk.     

Evaluation of drinking water treatment and quality in Takua Pa, Thailand

After 2004 Indian Ocean Tsunami, which hit and devastated several Countries in Southeast Asia, University of Brescia and Mahidol University started a project on water monitoring and treatment for drinking purposes in Takua Pa district (Thailand), the most damaged by the tsunami. In particular, this paper presents the results of a study conducted to evaluate the effectiveness of Takua Pa drinking water treatment plant and to identify actions that could be adopted to improve its performances. The results show that, even if the effluent usually meets Thai guide values, except for pH which is already too acid in the influent, the plant needs several structural and managerial improvements, such as filtration and sedimentation upgrade, coagulation/flocculation and final disinfection re-organization, use of proper registers to better plan and control employees activities. Moreover, it was determined that water quality in the distribution network is characterized by turbidity and organic matter values higher than those evaluated in the plant effluent.     

Chlorination and water quality monitoring within a public drinking water supply in Rawalpindi Cantt (Westridge and Tench) area, Pakistan

Concern over the presence of fecal coliform in public drinking water supplies has been expressed in recent years in Pakistan since it has been regarded as pathogenic organism of prime importance in gastroenteritis. Two major drinking water distribution systems in the Cantt area of Rawalpindi district covering the Westridge and Tench areas was monitored over a 2-month period to determine the prevalence of fecal coliform and chlorine residual. The collected samples were examined for total chlorine, free chlorine residual, chloramines, total coliforms, fecal coliforms, and turbidity. The drinking water quality monitoring in the distribution network was performed by collecting samples from water source, overhead reservoir, and residential taps. In the Westridge area, total chlorine varied from the lowest value of 0.27 mg/L at Station # W-5 to the highest value of 0.42 mg/L at Station # W-2, total coliforms varied from 1.1 to 3.6 most probable number (MPN)/100 mL with presence of Escherichia coli in all samples, total dissolved solids (TDS) ranged from 199.5 to 205 mg/L, conductivity fluctuated between 399 and 411 microS/cm, and turbidity varied from 0.43 to 0.73 NTU. In the Tench area, the value of total chlorine ranged from 0.14 mg/L at Station # T-7 to 0.55 mg/L at Station # T-1. Total coliform varied from 3.6 to 5.1 MPN/100 mL and fecal coliform were detected at all the stations except at Station # T-1. TDS ranged from 201.4 to 257 mg/L, conductivity varied from 343 to 513 microS/cm, and turbidity ranged between 0.66 and 1.55 NTU. It is recommended to the respective agencies to ensure that the chlorine residual is available at consumer end.     

对饮用水中游离性余氯测定条件的研究

系统研究了反应时间、水温、显色剂的用量及pH对游离性余氯测定的影响,优化选择最佳测定条件为控制水样pH<8,水温25℃,显色剂用量2.5 ml,加入显色剂后立即比色测定游离性余氯。在此条件下,测定3种生活饮用水游离性余氯,回收率为96.7%~99.8%,测定结果与《生活饮用水标准检验法》(GB 5750-85)中37.3滴定法颇为一致。     

Drinking water quality assessment in Southern Sindh (Pakistan)

The southern Sindh province of Pakistan adjoins the Arabian Sea coast where drinking water quality is deteriorating due to dumping of industrial and urban waste and use of agrochemicals and yet has limited fresh water resources. The study assessed the drinking water quality of canal, shallow pumps, dug wells, and water supply schemes from the administrative districts of Thatta, Badin, and Thar by measuring physical, chemical, and biological (total coliform) quality parameters. All four water bodies (dug wells, shallow pumps canal water, and water supply schemes) exceeded WHO MPL for turbidity (24%, 28%, 96%, 69%), coliform (96%, 77%, 92%, 81%), and electrical conductivity (100%, 99%, 44%, 63%), respectively. However, the turbidity was lower in underground water, i.e., 24% and 28% in dug wells and shallow pumps as compared to open water, i.e., 96% and 69% in canal and water supply schemes, respectively. In dug wells and shallow pumps, limits for TDS, alkalinity, hardness, and sodium exceeded, respectively, by 63% and 33%; 59% and 70%, 40% and 27%, and 78% and 26%. Sodium was major problem in dug wells and shallow pumps of district Thar and considerable percent in shallow pumps of Badin. Iron was major problem in all water bodies of district Badin ranging from 50% to 69% and to some extent in open waters of Thatta. Other parameters as pH, copper, manganese, zinc, and phosphorus were within standard permissible limits of World Health Organization. Some common diseases found in the study area were gastroenteritis, diarrhea and vomiting, kidney, and skin problems.     

Artificial neural network modeling of dissolved oxygen in reservoir

The water quality of reservoirs is one of the key factors in the operation and water quality management of reservoirs. Dissolved oxygen (DO) in water column is essential for microorganisms and a significant indicator of the state of aquatic ecosystems. In this study, two artificial neural network (ANN) models including back propagation neural network (BPNN) and adaptive neural-based fuzzy inference system (ANFIS) approaches and multilinear regression (MLR) model were developed to estimate the DO concentration in the Feitsui Reservoir of northern Taiwan. The input variables of the neural network are determined as water temperature, pH, conductivity, turbidity, suspended solids, total hardness, total alkalinity, and ammonium nitrogen. The performance of the ANN models and MLR model was assessed through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated DO values. The results reveal that ANN estimation performances were superior to those of MLR. Comparing to the BPNN and ANFIS models through the performance criteria, the ANFIS model is better than the BPNN model for predicting the DO values. Study results show that the neural network particularly using ANFIS model is able to predict the DO concentrations with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.     

Evaluating the Efficiency of Coagulation in the Removal of Dissolved Organic Carbon from Reservoir Water using Fluorescence and Ultraviolet Photometry

The present study used ultraviolet absorption (UVa) and the florescence intensity (FI) to evaluate the coagulation efficiency for removing dissolved organic carbon (DOC) in the raw water from Min-Ter, Li-Yu-Ten and Yun-Ho-Shen reservoirs in Taiwan. The results indicated that the ratio of DOC removal rate and FI removal rate was maintained at about 1 at various coagulant dosages. However, the ratio of DOC removal rate and UVa removal rate decreased as the coagulant dosage increased. In addition, after coagulation, the use of florescence intensity instead of total organic carbon (TOC) is better than UVa for measuring the DOC removal rate of the raw waters gathered in different months from the three reservoirs. Furthermore, a good linear relationship between florescence intensity and DOC removal rate was observed, and the DOC/FI ratio of raw water from each reservoir can be used to predict the DOC residual concentration after enhanced coagulation. This result shows that fluorescence analysis can be used for on-line and continuous monitoring the effectiveness of organic matter removal in water treatment.     

Occurrence of Giardia and Cryptosporidium in Italian water supplies

A total of 21 samples: raw water (RW) samples; water samples after coagulation with aluminium sulfate (clarified water: CW); and water after chlorination (treated water: TW) from a water purification plant that treats river surface water from the neighbourhood of Foggia (Italy), were analysed for the presence of Giardia cysts and Cryptosporidium oocysts. Bacteriological indicator of faecal contamination (total and faecal coliforms, faecal streptococci,), total bacterial count at 22 and 36 degrees C and physicochemical parameters (turbidity, temperature, pH) were evaluated. Cryptosporidium oocysts were not found in any samples examined, while Giardia cysts were found only in RW samples, with the maximal concentration of 8 cysts/100 l. A positive correlation was found between the Giardia densities and quality parameters such as TC, FC and TBC at 22 degrees C. Giardia levels in raw water samples correlated (p < 0.05) with TC, FC and with temperature. No other water quality parameters was consistently correlated with cysts level.     

Ground water quality in the Kathmandu valley of Nepal

A study was undertaken to assess the quality of groundwaters in the Kathmandu Valley, Nepal. The groundwater samples were randomly collected from shallow well, tube well, and deep-tube wells located at different places of Kathmandu, Lalitpur, and Bhaktapur districts in the Kathmandu valley. Physical, chemical, and microbiological parameters of the samples were evaluated to estimate the groundwater quality for drinking water. It was found that the groundwater in the valley is vulnerable to drink due to presence of iron and coliform bacteria. Iron was estimated to be much higher then the acceptable limit of World Health Organization (WHO) drinking-water quality guidelines (1.9 mg/L). Total coliform bacteria enumerated in groundwaters significantly exceeded the drinking-water quality standard and observed maximum coliform (267 CFU/100 mL) in shallow wells. The electrical conductivity and turbidity were found to be 875 ??S/cm and 55 NTU, respectively, which are above the WHO recommendations for drinking water guidelines. However, pH value was measured within the acceptable limit. Arsenic, chloride, fluoride, and hardness concentrations were found to be in agreement with the recommendations of WHO drinking-water quality guidelines.     

Determination of trace heavy metals in harvested rainwater used for drinking in Hebron (south West Bank,Palestine) by ICP-MS

Rainwater samples harvested for drinking from the west part of Hebron (south of West Bank in Palestine), the largest city in the West Bank, were analyzed for the content of different trace heavy metals (Cr, Mn, Co, Ni, Cu, Zn, Mo, Ag, Cd, Bi, and Pb) by inductively coupled plasma mass spectrometry (ICP-MS). This study was conducted to determine the water quality of harvested rainwater used for drinking of south West Bank (case study, Hebron area). A total of 44 water samples were collected in November 2012 from 44 house cisterns used to collect rainwater from the roofs of houses. The samples were analyzed for their pH, temperature, electrical conductivity, total dissolved solids, and different heavy metal contents. The pH of all water samples was within the US Environmental Protection Agency limits (6.5–8.5), while some water samples were found to exceed the allowed WHO limit for total dissolved solids (TDSs) in drinking water. Results showed that concentrations of the heavy metals vary significantly between the 44 samples. Results also showed that the concentration of five heavy metals (Cr, Mn, Ni, Ag, and Pb) is higher than the WHO limits for these heavy metals in drinking water. Overall, our findings revealed that harvested rainwater used for drinking of this part of south West Bank is contaminated with heavy metals that might affect human health.     

Multivariate analysis of drinking water quality parameters in Bhopal, India

Pollution of water bodies is one of the areas of major concern to environmentalists. Water quality is an index of health and well being of a society. Industrialization, urbanization and modern agriculture practices have direct impact on the water resources. These factors influence the water resources quantitatively and qualitatively. The study area selected were the Upper lake and Kolar reservoir of Bhopal, the state capital of Madhya Pradesh, India. The Upper lake and Kolar reservoir both are the important sources of potable water supply for the Bhopal city. The physico–chemical parameters like temperature, pH, turbidity, total hardness, alkalinity, BOD, COD, Chloride, nitrate and phosphate were studied to ascertain the drinking water quality.     

Poly(sodium acrylamidoalkanoates) in water treatment

Poly(sodium 6-acrylamidocaproate), poly(sodium 11-acrylamidoundecanoate), poly(sodium 11-N-methylacrylamidoundecanoate) and poly(sodium 11-N-ethylacrylamidoundecanoate) have been synthesized. The performance of these anionic polyelectrolytes as coagulant aids in water treatment was assessed by the jar test. The effects of polymer dosage and pH on their performances were investigated in order to establish the optimum flocculation conditions. The effectiveness of these polyelectrolytes as well as a commercially available cationic polyamine organic coagulant aid was compared in terms of floc size, settling rate and the quality of treated water. Poly(sodium 6-acrylamidocaproate) and poly(sodium 11-acrylamidoundecanoate) were superior to poly(sodium 11-N-methylacrylamidoundecanoate) and poly(sodium 11-N-ethylacrylamidoundecanoate), and they are as effective as the commercial cationic coagulant aid.     

Assessment of tap water quality and corrosion scales from the selected distribution systems in northern Pakistan

Corrosion deposits formed within drinking water distribution systems deteriorate drinking water quality and resultantly cause public health consequences. In the present study, an attempt was made to investigate the concurrent conditions of corrosion scales and the drinking water quality in selected water supply schemes (WSS) in districts Chitral, Peshawar, and Abbottabad, northern Pakistan. Characterization analyses of the corrosion by-products revealed the presence of α-FeOOH, γ-FeOOH, Fe₃O₄, and SiO₂ as major constituents with different proportions. The constituents of all the representative XRD peaks of Peshawar WSS were found insignificant as compared to other WSS, and the reason could be the variation of source water quality. Well-crystallized particles in SEM images indicated the formation of dense oxide layer on corrosion by-products. A wider asymmetric vibration peak of SiO₂ appeared only in Chitral and Abbottabad WSS, which demonstrated higher siltation in the water source. One-way ANOVA analysis showed significant variations in pH, turbidity, TDS, K, Mg, PO₄, Cl, and SO₄ values, which revealed that these parameters differently contributed to the source water quality. Findings from this study suggested the implementation of proper corrosion prevention measures and the establishment of international collaboration for best corrosion practices, expertise, and developing standards.     

供水厂水质状况分析

通过对西江某供水厂的水源水与出厂水水质进行分析研究 ,可知供水厂的水处理效果主要表现在对降低出水的浊度、色度和总细菌数等指标上 ,对大部分水溶性物质的减少无效或效果较低。为保证和提高饮用水的安全性和水质 ,除需提高供水厂的水处理效果和能力外 ,根本出路在于从环境管理与立法等角度 ,加大对水源水的保护力度 ,减少对饮用水源的排污     

Assessment of water quality parameters of the Harike wetland in India, a Ramsar site, using IRS LISS IV satellite data

This study aims at the classification and water quality assessment of Harike wetland (Ramsar site) in India using satellite images from the Indian Remote Sensing satellite, Resourcesat (IRS P6). The Harike wetland is a converging zone of two rivers, Beas and Sutlej. The satellite images of IRS Linear Imaging Self Scanner (LISS) IV multispectral sensor with three bands (green, red, and near infrared (NIR)) and a spatial resolution of 5.8 m were classified using supervised image classification techniques. Field points for image classification and water sampling were recorded using a Garmin eTrex Global Positioning System. The water quality parameters assessed were dissolved oxygen, conductivity, pH, turbidity, total and suspended solids (SS), chemical oxygen demand, and Secchi disk transparency (SDT). Correlations were established between turbidity and SS, SS and SDT, and total solids and turbidity. Using reflectance values from the green, red, and NIR bands, we then plotted the water quality parameters with the mean digital number values from the satellite imagery. The NIR band correlated significantly with the water quality parameters, whereas, using SDT values, it was observed that the green and the red reflectance bands were able to distinguish the waters from the two rivers, which have different water qualities.