饮用水源水质评价指数法探讨

对水利部水环境监测评价研究中心定期向社会发布的部分重点城市主要供水水源地水资源质量旬报所采用的评价方法——水质指数法进行了分析,针对该方法存在的缺陷提出了改进的水质指数法。     

Relationship between landscape characteristics and surface water quality

The effects of landscape characteristics on surface water quality were evaluated in terms of land-use condition, soil type and slope. The case area, the Chichiawan stream in the Wulin catchment in Taiwan, is Formosan landlocked salmon's natural habitat. Due to the agriculture behavior and mankind's activities, the water and environmental quality has gradually worsened. This study applied WinVAST model to predict hydrological responses and non-point source pollution (NPSP) exports in the Wulin catchment. The land-use condition and the slope of land surface in a catchment are major effect factors for watershed responses, including flows and pollutant exports. This work discussed the possible variation of watershed responses induced by the change of land-use condition, soil type and slope, etc. The results show that hydrological responses are highly relative to the value of Curve Number (CN); Pollutant exports have large relation to the average slope of the land surface in the Wulin catchment.     

Evaluation of surface water quality characteristics by using multivariate statistical techniques: A case study of the Euphrates river basin, Turkey

The surface water quality of the Euphrates river basin in Turkey are evaluated by using the multivariate statistical techniques known as factor analysis (FA) and multidimensional scaling (MDS) analysis. When FA was applied to the water quality data obtained from the 15 different surface water quality monitoring stations, two factors were identified, which were responsible from the 86.02% of the total variance of the water quality in the Euphrates river basin. The first factor called the urban land use factor explained 44.20% of the total variance and the second factor called the agricultural use factor explained 41.81% of the total variance. MDS technique showed that electrical conductivity (EC), percent sodium (Na%) and total salt are the most important variables causing difference in the water quality analysis.     

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.     

Storm water contamination and its effect on the quality of urban surface waters

We studied the effect of storm water drained by the sewerage system and discharged into a river and a small reservoir, on the example of five catchments located within the boundaries of the city of Poznań (Poland). These catchments differed both in terms of their surface area and land use (single- and multi-family housing, industrial areas). The aim of the analyses was to explain to what extent pollutants found in storm water runoff from the studied catchments affected the quality of surface waters and whether it threatened the aquatic organisms. Only some of the 14 studied variables and 22 chemical elements were important for the water quality of the river, i.e., pH, TSS, rain intensity, temperature, conductivity, dissolved oxygen, organic matter content, Al, Cu, Pb, Zn, Fe, Cd, Ni, Se, and Tl. The most serious threat to biota in the receiver came from the copper contamination of storm water runoff. Of all samples below the sewerage outflow, 74 % exceeded the mean acute value for Daphnia species. Some of them exceeded safe concentrations for other aquatic organisms. Only the outlet from the industrial area with the highest impervious surface had a substantial influence on the water quality of the river. A reservoir situated in the river course had an important influence on the elimination of storm water pollution, despite the very short residence time of its water.     

Environmental monitoring of Micro Prespa Lake basin (Western Macedonia,Greece): hydrogeochemical characteristics of water resources and quality trends

The Micro Prespa basin is a trilateral catchment area of significant importance with a unique ecosystem closely related to the homonymous lake. In this frame, a fully operational monitoring project was carried out including continuous real-time measurements in Micro Prespa Lake with the use of a multi-sensor probe, as well as periodical sampling and analyses of all available water systems for an extended set of 85 parameters. Four main interacting water systems were identified, including alluvial and karstic aquifers, Micro Prespa Lake and adjacent drainage network. The results outlined that general environmental conditions are satisfying in respect to the relative legislation and the hydrogeochemical signatures. However, trends of environmental pressures were ascertained as a result of natural (geogenic) factors, embracing seasonal peaks for Ni, Pb, and NH₄ mainly in groundwater systems. Based on chlorophyll a records, Micro Prespa is classified as oligotrophic to slightly mesotrophic, subjected to seasonal variations. Heavy metal concentrations are low, except Ni which appears to have elevated values during the dry hydrological period. Finally, the hydrogeochemistry of drainage network is primarily influenced by surface runoff of the surrounding mountainous areas, hence elevated phosphorus values of the Aghios Germanos stream are possibly linked with the leaching of the granitic formations on the east.     

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.     

Identification of mangrove water quality by multivariate statistical analysis methods in Pondicherry coast,India

Different multivariate statistical analysis such as, cluster analysis, principal component analysis, and multidimensional scale plot were employed to evaluate the trophic status of water quality for four monitoring stations. The present study was carried out to determine the physicochemical parameters of water and sediment characteristics of Pondicherry mangroves—southeast coast of India, during September 2008–December 2010. Seasonal variations of different parameters investigated were as follows: salinity (10.26–35.20 psu), dissolved oxygen (3.71–5.33 mg/L), pH (7.05–8.36), electrical conductivity (26.41–41.33 ms⁻¹), sulfide (1.98–40.43 mg/L), sediment texture sand (39.54–87.31%), silt (9.89–32.97%), clay (3.06–31.20%), and organic matter (0.94–4.64%). pH, temperature, salinity, sand, silt, clay, and organic matter indicated a correlation at P < 0.01. CA grouped the four seasons in to four groups (pre-monsoon, monsoon, post-monsoon, summer) and the sampling sites in to three groups. PCA identified the spatial and temporal characteristics of trophic stations and showed that the water quality was worse in stations 3 and 4 in the Pondicherry mangroves.     

Chironomidae and Oligochaeta for water quality evaluation in an urban river in southeastern Brazil

Considering the importance of benthic macroinvertebrates for diagnosis of variations in the ecological conditions of aquatic habitats, the aim of this study was to investigate the structure of the Chironomidae and Oligochaeta assemblages along an organic pollution gradient. The fauna specimens were obtained with the use of artificial substrates, and the environmental variables were recorded at five sites of the São Lourenço River, during 12 months. Metrics of the assemblage and detrended correspondence analysis were used to verify the response of the fauna to the pollution gradient. Procrustes analysis was used to verify whether the data on the Chironomidae and Oligochaeta assemblages, as well as the taxonomic and numerical resolution of these groups, provide similar results in relation to the pollution gradient. The richness, evenness, and taxonomic composition of the Chironomidae and Oligochaeta assemblages varied significantly among the collection sites, with distinct conservation conditions. Genera of the subfamilies Orthocladiinae and Tanypodinae were associated with the sites upstream of the urban area, where the dissolved oxygen levels are higher. Species of Oligochaeta and the genus Chironomus were associated with more organically polluted sites. No concordance was observed in the response of the Chironomidae and Oligochaeta assemblages in relation to the environmental variables, indicating the need to use both groups in biomonitoring studies. On the other hand, both the data on composition (presence or absence) and those on the lowest taxonomic resolution (abundance of subfamilies) were effective to diagnose the pollution gradient in the river studied. Therefore, when the environmental conditions along a river’s gradient are contrasting, we suggest the use of the lowest taxonomic resolution of Chironomidae and Oligochaeta in biomonitoring. That procedure considerably reduces the assessment time, besides being a method that can be used by people not specializing in the taxonomy of groups.     

profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.     

Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems

This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO₃, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH₃, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH₃, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures.     

Assessment of water quality using multivariate statistical techniques in the coastal region of Visakhapatnam,India

The present study was intended to develop a Water Quality Index (WQI) for the coastal water of Visakhapatnam, India from multiple measured water quality parameters using different multivariate statistical techniques. Cluster analysis was used to classify the data set into three major groups based on similar water quality characteristics. Discriminant analysis was used to generate a discriminant function for developing a WQI. Discriminant analysis gave the best result for analyzing the seasonal variation of water quality. It helped in data reduction and found the most discriminant parameters responsible for seasonal variation of water quality. Coastal water was classified into good, average, and poor quality considering WQI and the nutrient load. The predictive capacity of WQI was proved with random samples taken from coastal areas. High concentration of ammonia in surface water during winter was attributed to nitrogen fixation by the phytoplankton bloom which resulted due to East India Coastal Current. This study brings out the fact that water quality in the coastal region not only depends on the discharge from different pollution sources but also on the presence of different current patterns. It also illustrates the usefulness of WQI for analyzing the complex nutrient data for assessing the coastal water and identifying different pollution sources, considering reasons for seasonal variation of water quality.     

Assessment of surface water quality using multivariate statistical techniques: a case study of Behrimaz Stream, Turkey

Multivariate statistical techniques, such as cluster analysis (CA), principal component analysis, and factor analysis, were applied for the evaluation of temporal/spatial variations and for the interpretation of a water quality data set of the Behrimaz Stream, obtained during 1 year of monitoring of 20 parameters at four different sites. Hierarchical CA grouped 12 months into two periods (the first and second periods) and classified four monitoring sites into two groups (group A and group B), i.e., relatively less polluted (LP) and medium polluted (MP) sites, based on similarities of water quality characteristics. Factor analysis/principal component analysis, applied to the data sets of the two different groups obtained from cluster analysis, resulted in five latent factors amounting to 88.32% and 88.93% of the total variance in water quality data sets of LP and MP areas, respectively. Varifactors obtained from factor analysis indicate that the parameters responsible for water quality variations are mainly related to discharge, temperature, and soluble minerals (natural) and nutrients (nonpoint sources: agricultural activities) in relatively less polluted areas; and organic pollution (point source: domestic wastewater) and nutrients (nonpoint sources: agricultural activities and surface runoff from villages) in medium polluted areas in the basin. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and interpretation of data sets and, in water quality assessment, identification of pollution sources/factors and understanding temporal/spatial variations in water quality for effective stream water quality management.     

Application of multivariate statistical techniques in the assessment of surface water quality in Uluabat Lake, Turkey

The application of different multivariate statistical approaches for the interpretation of a complex data matrix obtained during the period 2004-2005 from Uluabat Lake surface water is presented in this study. The dataset consists of the analytical results of a 1 year-survey conducted in 12 sampling stations in the Lake. Twelve parameters (T, pH, DO, [Formula: see text], NH(4)-N, NO(2)-N, NO(3)-N, [Formula: see text], BOD, COD, TC, FC) were monitored in the sampling sites on a monthly basis (except December 2004, January and February 2005, a total of 1,296 observations). The dataset was treated using cluster analysis, principle component analysis and factor analysis on principle components. Cluster analysis revealed two different groups of similarities between the sampling sites, reflecting different physicochemical properties and pollution levels in the studied water system. Three latent factors were identified as responsible for the data structure, explaining 77.35% of total variance in the dataset. The first factor called the microbiological factor explained 32.34% of the total variance. The second factor named the organic-nutrient factors explained 25.46% and the third factor called physicochemical factors explained 19.54% of the variances, respectively.     

物元分析在水质富营养化评价中的应用（续）

本文运用物元分析对扬州瘦西湖水质富营养化进行综合评价。通过计算综合关联度得到综合评价结果,文中用实例与模糊综合评判法进行了对比,结果令人满意。该法具有计算简便,评价合理的优点。     

Trend evaluation of water quality parameters in the Niagara and St. Lawrence Rivers

Physical and chemical (nutrients and major ions) indicators of water quality monitored by Environment Canada between 1977 and 1987 in the Niagara River at Niagara-on-the-Lake and in the St. Lawrence River at Wolfe Island are analyzed for seasonal and annual variations. Parametric methods such as moving averages and linear regression and nonparametric methods (Spearman's rank coefficient) are used to test for the existence of trends in these data. The results indicate that specific conductivity, sodium and chloride have decreased significantly over the period of study. During the same period there is no significant trend for either discharge and nutrients.     

Surface water quality evaluation and modeling of Ghataprabha River,Karnataka, India

Belgaum city is a developmental hub of Karnataka State in India. In the recent time, the Government of Karnataka has planned to set up many processing industries in the vicinity of Belgaum to meet the growing needs of the region and to ease out the pressure on the already existing industrial hubs in Karnataka State. Ghataprabha, a tributary of river Krishna, is one of the major sources of water supply to Belgaum city and adjoining areas. During the last decade, a lot of anthropogenic activities such as unplanned agricultural activities are ongoing in many parts of the catchment. Therefore, people of Belgaum are more concerned about the quality of water in Ghataprabha river. Considering the significance of water quality of the river, surface water samples were collected during Pre- and Post-monsoon season from selected locations and analyzed for both physical and chemical constituents in the laboratory. The results indicate that the chemical parameters such as bicarbonates, sulphates, chlorides, sodium, potassium, calcium and magnesium are within the permissible limits. QUAL2E model was applied to assess the impact of point and non-point sources of pollution on the river water quality. Results show that the water quality conditions are highly acceptable all along the river stretch. Further, the variation of DO–BOD₅ with river discharge was also estimated. Also, a significant variations in DO (decrease in DO) with the increase in river flow was observed. However, at the downstream end, considerable improvement in DO was noticed which is attributed to the damming effect of the reservoir.     

Monitoring water quality in reservoirs for human supply through multi-biomarker evaluation in tropical fish

Paraíba do Sul River is located at a very densely inhabited region of Brazil crossing the three most industrialized states of the country (S?o Paulo, Minas Gerais and Rio de Janeiro states). As a result, industrial and farming residues as well as urban sewage are frequently disposed without appropriate treatment. The current study aimed at investigating the water quality in three reservoirs along the Paraíba do Sul River (Ilha dos Pombos, Santa Cecília and Santa Branca), through physiological, morphological, biochemical, and genetic biomarkers. The bioindicator chosen was the catfish Pimelodus maculatus, sampled during the dry (June 2008) and rainy (February 2009) seasons. Also, some water physicochemical parameters were analyzed from the sampling sites, but displayed no alterations according to the Brazilian Agency for Water Quality Legislation. Branchial carbonic anhydrase activity was inhibited in the dry season, while renal carbonic anhydrase activity was inhibited in the rainy season in the Santa Branca reservoir, indicating disturbance of osmoregulatory and acid-base regulation processes. Histopathological alterations were observed in the gills (neoplasic and tissue hyperplasia processes) and liver (necrosis), indicating serious damage to the functional integrity of these organs. A high incidence of melanomacrophage centers was observed in the liver, suggesting an intense immune response in all reservoirs. Acetylcholinesterase and catalase activity showed also differences corroborating some morphological results. Likewise, the induction of the micronucleus and DNA damage indicate genotoxicity, but mainly in the Santa Branca reservoir. Thus, the health status of P. maculatus warrants caution in the use of the water from the 3 reservoirs for direct human consumption, particularly after the accidental spill of endosulfan in November 2008, three months before the rainy season sampling.     

A systems approach to modeling Community-Based Environmental Monitoring: a case of participatory water quality monitoring in rural Mexico

Community-Based Environmental Monitoring (CBM) is a social practice that makes a valuable contribution to environmental management and construction of active societies for sustainable future. However, its documentation and analysis show deficiencies that hinder contrast and comparison of processes and effects. Based on systems approach, this article presents a model of CBM to orient assessment of programs, with heuristic or practical goals. In a focal level, the model comprises three components, the social subject, the object of monitoring, and the means of action, and five processes, data management, social learning, assimilation/decision making, direct action, and linking. Emergent properties were also identified in the focal and suprafocal levels considering community self-organization, response capacity, and autonomy for environmental management. The model was applied to the assessment of a CBM program of water quality implemented in rural areas in Mexico. Attributes and variables (indicators) for components, processes, and emergent properties were selected to measure changes that emerged since the program implementation. The assessment of the first 3 years (2010–2012) detected changes that indicated movement towards the expected results, but it revealed also the need to adjust the intervention strategy and procedures. Components and processes of the model reflected relevant aspects of the CBM in real world. The component called means of action as a key element to transit “from the data to the action.” The CBM model offered a conceptual framework with advantages to understand CBM as a socioecological event and to strengthen its implementation under different conditions and contexts.