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.     

河流水质综合评价方法的统一和改进

在分析我国河流水质综合评价方法存在的问题以及河流水质综合评价方法研究现状的基础上 ,以国家对全国水环境质量系统管理需要为目的 ,提出了对河流水质综合评价方法的要求 ,并针对综合污染指数法的缺陷 ,提出了改进的综合水质指数方法     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

Chemometric characterization of river water quality

Various industrial facilities in the city of Varanasi discharge their effluent mixed with municipal sewage into the River Ganges at different discharge points. In this study, chemometric tools such as cluster analysis and box–whisker plots were applied to interpret data obtained during examination of River Ganges water quality. Specifically, we investigated the temperature (T), pH, total alkalinity, total acidity, electrical conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), nitrate nitrogen (N), phosphate (PO ₄ ^2? ), copper (Cu), cadmium (Cd), chromium (Cr), nickel (Ni), iron (Fe), lead (Pb), and zinc (Zn) in water samples collected from six sampling stations. Hierarchical agglomerative cluster analysis was conducted using Ward’s method. Proximity distance between EC and Cr was the smallest revealing a relationship between these parameters, which was confirmed by Pearson’s correlation. Based on proximity distances, EC, Cr, Ni, Fe, N, COD, temperature, BOD, and total acidity comprised one group; Zn, Pb, Cd, total alkalinity, Cu, and phosphate (PO ₄ ^2? ) were in another group; and DO and pH formed a separate group. These groups were confirmed by Pearson’s correlation (r) values that indicated significant and positive correlation between variables in the same group. Box–whisker plots revealed that as we go downstream, the pollutant concentration increases and maximum at the downstream station Raj Ghat and minimum at the upstream station Samane Ghat. Seasonal variations in water quality parameters signified that total alkalinity, total acidity, DO, BOD, COD, N, phosphate (PO ₄ ^2? ), Cu, Cd, Cr, Ni, Fe, Pb, and Zn were the highest in summer (March–June) and the lowest during monsoon season (July–October). Temperature was the highest in summer and the lowest in winter (November–February). DO was the highest in winter and the lowest in summer season. pH was observed to be the highest in monsoon and the lowest in summer season.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Deterioration of water quality of Surma river

Surma River is polluted day by day by human activities, poor structured sewerage and drainage system, discharging industrial and household wastes. The charas (natural channels) are responsible for surface runoff conveyance from its urban catchments to the receiving Surma River. Water samples have been collected from a part of Surma River along different points and analyzed for various water quality parameters during dry and monsoon periods. Effects of industrial wastes, municipal sewage, and agricultural runoff on river water quality have been investigated. The study was conducted within the Chattak to Sunamganj portion of Surma River, which is significant due to the presence of two major industries – a paper mill and a cement factory. The other significant feature is the conveyors that travel from India to Chattak. The river was found to be highly turbid in the monsoon season. But BOD and fecal coliform concentration was found higher in the dry season. The water was found slightly acidic. The mean values of parameters were Conductivity 84–805 μs; DO: dry-5.52 mg/l, monsoon-5.72 mg/l; BOD: dry-1mg/l, monsoon-0.878 mg/l; Total Solid: dry-149.4 mg/l, monsoon-145.7 mg/l. In this study, an effort has been taken to investigate the status of concentration of phosphate (PO⁻⁴) and ammonia–nitrogen (NH₄–N) at four entrance points of Malnichara to the city, Guali chara, Gaviar khal and Bolramer khal. Data has been collected from March–April and September–October of 2004. Concentrations have been measured using UV Spectrophotometer. Although the phosphate concentration has been found within the limit set by DOE for fishing, irrigation and recreational purposes, however ammonia–nitrogen has been found to exceed the limit.     

Assessment of elemental contaminants in water and fish samples from Aba river

The elemental contaminants in water and fish samples from Aba river were studied. The elements studied were Zn, Ni, As, Hg, Co and Mn. Three water samples and three samples of different fish species were collected from different locations in the river. The water and fish samples were analysed for elemental contaminants using Atomic Absorption Spectrophotometer (AAS). The elemental toxicants Zn and Mn were identified in appreciable amounts in fresh fish species namely, Lates niloticus and Oriochronis niloticus, of mean values 8.012 ppm and 0.861 ppm, respectively. The analysis also shows arsenic concentration of mean value 0.01 ppm in Lates niloticus. The analysis of frozen fish samples purchased from the Waterside market located near the river shows Ni and Hg levels of mean values 0.83 ppm and 0.02 ppm, respectively. The levels of elemental contaminants As, Zn, Hg and Mn from the water samples have mean values 0.082 ppm, 11.284 ppm, 0.201 ppm and 1.024 ppm, respectively. There are five industries that discharge waste products into Aba river. In view of this, there is a need to determine the level of pollution of the river, since the inhabitants depend on the river for their drinking water, fishing and other domestic uses. This study is aimed at determining the level of heavy metal toxicants in fish and water samples from the river. The effect of these elemental contaminants and the associated health hazards were examined.     

Groundwater arsenic contamination in Brahmaputra river basin: a water quality assessment in Golaghat (Assam), India

Distribution of arsenic (As) and its compound and related toxicology are serious concerns nowadays. Millions of individuals worldwide are suffering from arsenic toxic effect due to drinking of As-contaminated groundwater. The Bengal delta plain, which is formed by the Ganga?CPadma?CMeghna?CBrahmaputra river basin, covering several districts of West Bengal, India, and Bangladesh is considered as the worst As-affected alluvial basin. The present study was carried out to examine As contamination in the state of Assam, an adjoining region of the West Bengal and Bangladesh borders. Two hundred twenty-two groundwater samples were collected from shallow and deep tubewells of six blocks of Golaghat district (Assam). Along with total As, examination of concentration levels of other key parameters, viz., Fe, Mn, Ca, Na, K, and Mg with pH, total hardness, and SO $_{4}^{2-}$ , was also carried out. In respect to the permissible limit formulated by the World Health Organization (WHO; As 0.01 ppm, Fe 1.0 ppm, and Mn 0.3 ppm for potable water), the present study showed that out of the 222 groundwater samples, 67%, 76.4%, and 28.5% were found contaminated with higher metal contents (for total As, Fe, and Mn, respectively). The most badly affected area was the Gamariguri block, where 100% of the samples had As and Fe concentrations above the WHO drinking water guideline values. In this block, the highest As and Fe concentrations were recorded 0.128 and 5.9 ppm, respectively. Tubewell water of depth 180 ± 10 ft found to be more contaminated by As and Fe with 78% and 83% of the samples were tainted with higher concentration of such toxic metals, respectively. A strong significant correlation was observed between As and Fe (0.697 at p < 0.01), suggesting a possible reductive dissolution of As?CFe-bearing minerals for the mobilization of As in the groundwater of the region.     

模糊数学在湟水流域水质综合评价中的应用

应用模糊数学进行环境质量的综合评价,获得了良好的结果.     

Detection of water quality changes along a river system

Water quality monitoring networks are generally multi-purpose, and thus the data generated are expected to provide information on a set of objectives. Two questions that are fundamental to these objectives are the detection of long term trends and of differences between locations. The extent to which these questions can be answered and the types of statistical methods which can be used are considered in a case study of conventional parameters sampled monthly for nine years. Regression and nonparametric methods, which explicitly account for seasonality, are compared for both the determination of change over time and of differences between locations. Changes over time in the form of step changes and differences between locations which depend upon season were found.     

Water quality assessment of Ogun river, South West Nigeria

The quality of Ogun river in South-West, Nigeria was studied by a field survey for a period of 1 year (covering dry season and rainy season). Water samples were collected from thirteen sites and analysed for physico-chemical and bacteriological parameters as well as heavy metals using standard methods. Generally, the values obtained for turbidity, phosphate, oil and grease, iron and faecal coliform from all the sites in both seasons were above the maximum acceptable limit set by the World Health Organization (WHO) for drinking water. Also, the manganese content from all the sites in the dry season, lead concentrations from three sites in the dry season and cadmium concentrations from some sites in both seasons were above the WHO limit. The values obtained for total dissolved solids, dissolved oxygen and chloride at site M in the dry season and nitrate at site J in the rainy season were also above the WHO limit. Pollution of Ogun river water along its course is evidenced by the high concentrations of pollution indicators, nutrients and trace metals above the acceptable limit. This poses a health risk to several rural communities who rely on the river primarily as their source of domestic water. The study showed a need for continuous pollution monitoring programme of surface waters in Nigeria.     

Spatiotemporal trend analysis of recent river water quality conditions in Japan

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.     

Impact assessment of pesticide residues in fish of Ganga river around Kolkata in West Bengal

An investigation was conducted from 2001 to 2005 for determining the residual concentration of five pesticides, viz., total-HCH, total-DDT, total-Endosulfan, Dimethoate and Malathion in fish samples collected from various points of the river Ganga. Fish samples were analyzed for pesticide residues using standard laboratory procedures by GC method. It was found that total-HCH concentration remains above the MRL values for maximum number of times in comparison to four other pesticides. The pesticide contamination to fish may be due to indiscriminate discharge of polluted and untreated sewage-sludge to the river. The pesticide contents in some places are alarming. Thus proper care, maintenance, treatment and disposal of sewage water and sludge are most vital and should be the prime thrust for the nation.     

The Duero Diatom Index (DDI) for river water quality assessment in NW Spain: design and validation

Diatom indices developed in certain geographic regions are frequently used elsewhere, despite the strong evidence that such metrics are less useful when applied in regions other than that where species–environment relationships were originally assessed, showing that species have particular autoecological requirements in different geographic areas. The goal of this study was to develop a new metric, the Duero Diatom Index (DDI), aimed at monitoring water quality in Duero basin watercourses (NW Spain). In summer 2008 and 2009, a total of 355 epilithic diatom samples were collected following standard protocols. The 2008 samples were used to develop the DDI, whereas the samples collected during 2009 were used in the index testing. Weighted averages method was used to derive the autoecological profiles of diatoms with respect to pH, conductivity, biological oxygen demand, ammonia, nitrates, and phosphates. The optimum and tolerance values for the measured environmental variables were determined for 137 taxa with abundances and frequencies of occurrence above 1 %, and subsequent trophic indicator and sensitivity values were defined for the DDI. The correlation between the observed and the diatom-inferred nutrient concentrations was highest for phosphates (ρ _S?=?0.72). Significant statistical relationship were observed between DDI values and the chemistry-based General Quality Index values (p?=?0.006) and the specific pollution index (SPI) diatom metric (p?=?0.04). DDI has demonstrated a better correlation with water chemistry than SPI diatom metric.     

Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.     

地表水环境质量定性评价

针对目前缺乏统一的地表水环境质量定性评价准则的现状,根据我国主要水体的污染程度,提出了断面、河流、水系水质定性评价方法。     

苏州城区河道水质现状分析

跟踪了苏州城区内27个重点河流断面半年的监测数据,重点监测了溶解氧、氨氮、总磷、高锰酸盐指数4个富营养化指标。计算了各种污染物单因子污染指数、主要污染物分担率和平均污染指数,并对水质污染程度进行综合评价。结果表明,在苏州城区河道的27个重点监测断面中,大部分属于中度污染,水体的主要污染物为溶解氧、氨氮和总磷。分析了可能导致城区河道水体污染的主要原因,并提出治理建议。     

Chemometrics in assessment of seasonal variation of water quality in fresh water systems

The spatial and temporal distribution of polycyclic aromatic hydrocarbons (PAHs) was investigated in Gomti River, a major tributary of the Ganga river (India). A total of 96 samples (water and sediments) were collected from eight different sites over a period of 2 years and analysed for 16 PAHs. The total concentrations of 16 PAHs in water and bed sediments ranged between 0.06 and 84.21 ??g/L (average (n?=?48), 10.33 ± 19.94 ??g/L) and 5.24?C3,722.87 ng/g dw [average (n?=?48): 697.25 ± 1,005.23 ng/g dw], respectively. In water, two- and three-ring PAHs and, in sediments, the three- and four-ring PAHs were the dominant species. The ratios of anthracene (An)/An + phenenthrene and fluoranthene (Fla)/Fla + pyrene were calculated to evaluate the possible sources of PAHs. These ratios reflected a pattern of pyrolytic input as a major source of PAHs in the river. Principal component analysis, further, separated the PAHs sources in the river sediments, suggesting that both the pyrolytic and petrogenic sources are contributing to the PAHs burden. The threat to biota of the river due to PAHs contamination was assessed using effect range low and effect range median values, and the results suggested that sediment at some occasions may pose biological impairment.     

Persistent organochlorine residues in fish and water birds from the Biobio river,Chile

Concentrations of polychlorinated biphenyls (PCBs), DDT and its metabolites, HCH isomers and hexachlorobenzene (HCB) were determined in fish and birds from different locations in the Biobio river basin (central Chile). Samples collected near the mouth of the river contained high concentrations of PCBs, reflecting the massive use of these xenobiotics in the urban and industrial areas of Concepcion and Talcauano. Samples collected in the central part of the basin contained very high concentrations of lindane that coincide with the widespread use of lindane-based pesticides (purified -HCH) in this area. DDT was distributed homogeneously throughout the basin, except at Laguna Icalma, the source of the river in the Andes. Most PCB residues in fish and birds consisted of congeners between penta- and hepta-chlorobiphenyls. In fish, the predominant congeners were the pentachlorobiphenyl 23445 (IUPAC number 118) and the hexachlorobiphenyl 2234455 (PCB-153); in birds 224455 (PCB-180) prevailed.     

A saprobic index for biological assessment of river water quality in Brazil (Minas Gerais and Rio de Janeiro states)

Based upon several years of experience in investigations with macrozoobenthos in rivers in the states of Minas Gerais and Rio de Janeiro, a biological assessment system has been developed to indicate pollution levels caused by easily degradable organic substances from sewers. The biotic index presented here is aimed at determining water’s saprobic levels and was, therefore, named the “Saprobic Index for Brazilian Rivers in Minas Gerais and Rio de Janeiro states” (ISMR). For this purpose, saprobic valences and weights have been established for 122 taxa of tropical macrozoobenthos. Investigations were carried out in little, medium sized and big rivers in mountains and plains. Through ISMR, a classification of water quality and the respective cartographic representation can be obtained. Data collection and treatment methods, as well as the limitations of the biotic index, are thoroughly described. ISMR can also be used as an element to establish complex multimetric indexes intended for an ecological integrity assessment, where it is essential to indicate organic pollution.