CCME WQI在入海河流(鳌江)感潮河段水质评价中的应用

水质指数(WQI)在环境保护的日常工作中发挥了重要作用。以鳌江为例,运用加拿大环境部长理事会水质指数(CCME WQI)方法,选取pH、溶解氧、高锰酸盐指数、氨氮、总氮、总磷、石油类、氟化物、阴离子表面活性剂、粪大肠菌群10项水质监测项目,评估了入海河流干流感潮河段4个监测断面的地表水环境质量,并对CCME WQI与最差因子法以及CCME WQI优缺点进行比较和分析。研究结果显示,2014年埭头、江屿、方岩渡、江口渡监测断面水质分别为良好、较差、中等、中等。与传统水质评价最差因子法比较,运用CCME WQI评价结果容忍度较高,更贴近实际水质状况。CCME WQI量化形式为属地流域环境管理带来便利。监测断面水质目标和参评项目对CCME WQI评价结果起决定性作用。针对CCME WQI在实际应用中存在的问题给出了建议。     

基于超标风险改进的加拿大水质指数及其应用

将三角模糊数和超标风险度引入加拿大水质指数(CCME-WQI),建立了能够反映超标风险的改进型CCMEWQI。改进后的CCME-WQI通过计算水质指标的超标隶属度与超标风险,可实现对水质不确定性与超标风险的综合考量。在此基础上,评价了重庆市某水库2016—2019年水质状况。结果显示:改进后的CCME-WQI的评价结果较仅反映最差指标类别的单因子评价法的评价结果更为全面、客观。基于超标风险改进的CCME-WQI考虑了即将超标但尚未超标的水质因子存在的风险,在结果显示上比改进前的CCME-WQI更为全面、严格,更适用于评价一段时间内的水体污染程度和超标状态。     

Application of CCME Water Quality Index to Monitor Water Quality: A Case Study of the Mackenzie River Basin, Canada

All six ecosystem initiatives evolved from many years of federal, provincial, First Nation, local government and community attention to the stresses on sensitive habitats and species, air and water quality, and the consequent threats to community livability. This paper assesses water quality aspect for the ecosystem initiatives and employs newly developed Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) which provides a convenient mean of summarizing complex water quality data that can be easily understood by the public, water distributors, planners, managers and policy makers. The CCME WQI incorporates three elements: Scope – the number of water quality parameters (variables) not meeting water quality objectives (F ₁); Frequency – the number of times the objectives are not met (F ₂); and Amplitude. the extent to which the objectives are not met (F ₃). The index produces a number between 0 (worst) to 100 (best) to reflect the water quality. This study evaluates water quality of the Mackenzie – Great Bear sub-basin by employing two modes of objective functions (threshold values): one based on the CCME water quality guidelines and the other based on site-specific values that were determined by the statistical analysis of the historical data base. Results suggest that the water quality of the Mackenzie-Great Bear sub-basin is impacted by high turbidity and total (mostly particulate) trace metals due to high suspended sediment loads during the open water season. Comments are also provided on water quality and human health issues in the Mackenzie basin based on the findings and the usefulness of CCME water quality guidelines and site specific values.     

Performance of biotic indices in comparison to chemical-based Water Quality Index (WQI) in evaluating the water quality of urban river

In order to evaluate the water quality of one of the most polluted urban river in Malaysia, the Penchala River, performance of eight biotic indices, Biomonitoring Working Party (BMWP), BMWP^Thai, BMWP^Viet, Average Score Per Taxon (ASPT), ASPT^Thai, BMWP^Viet, Family Biotic Index (FBI), and Singapore Biotic Index (SingScore), was compared. The water quality categorization based on these biotic indices was then compared with the categorization of Malaysian Water Quality Index (WQI) derived from measurements of six water physicochemical parameters (pH, BOD, COD, NH₃-N, DO, and TSS). The river was divided into four sections: upstream section (recreational area), middle stream 1 (residential area), middle stream 2 (commercial area), and downstream. Abundance and diversity of the macroinvertebrates were the highest in the upstream section (407 individual and H′?=?1.56, respectively), followed by the middle stream 1 (356 individual and H′?=?0.82). The least abundance was recorded in the downstream section (214 individual). Among all biotic indices, BMWP was the most reliable in evaluating the water quality of this urban river as their classifications were comparable to the WQI. BMWPs in this study have strong relationships with dissolved oxygen (DO) content. Our results demonstrated that the biotic indices were more sensitive towards organic pollution than the WQI. BMWP indices especially BMWP^Viet were the most reliable and could be adopted along with the WQI for assessment of water quality in urban rivers.     

Detection of seasonal variations in surface water quality using discriminant analysis

In the study, discriminant analysis (DA) was applied to water quality data set monitored in winter and summer months along 3 years to investigate seasonal variations of Tahtali Reservoir water quality. The variables were divided into two categories as “parameters naturally found in surface waters—Al, Fe, Mn, F, Ba, Cl, and SO₄” and “pollutants—biochemical oxygen demand, chemical oxygen demand, and NO₃”. Linear discriminant functions were calculated to distinguish between winter and summer samples. Results revealed that water quality variables (naturally found in surface water and also pollutants) were distinctly different between two seasons. Seasonal changes of water quality caused by anthropogenic activities should be taken into consideration by the water managers especially in summer seasons in which higher concentrations were observed. The study showed that DA can be applied successfully to establish the seasonal variation in surface water quality and make it possible to design a future temporal sampling strategy in an optimal manner.     

Comparative analysis of regional water quality in Canada using the Water Quality Index

The Canadian Council of Ministers for the Environment (CCME) has developed a Water Quality Index (WQI) to simplify the reporting of complex water quality data. This science-based communication tool tests multi-variable water data against numeric water quality guidelines and/or objectives to produce a single unit-less number that represents overall water quality. The CCME WQI has been used to rate overall water quality in spatial and temporal comparisons of site(s). However, it has not been used in a comparative-analysis of exposure sites to reference sites downstream of point source discharges. This study evaluated the ability of the CCME WQI to differentiate water quality from metal mines across Canada at exposure sites from reference sites using two different types of numeric water quality objectives: (1) the water quality guidelines (WQG) for the protection of freshwater aquatic life and (2) water quality objectives determined using regional reference data termed Region-Specific Objectives (RSO). The application of WQG to the CCME WQI was found to be a good tool to assess absolute water quality as it relates to national water quality guidelines for the protection of aquatic life, but had more limited use when evaluating spatial changes in water quality downstream of point source discharges. The application of the RSO to the CCME WQI resulted in assessment of spatial changes in water quality downstream of point source discharges relative to upstream reference conditions.     

Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques

This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA), were used to study the spatial variations of the most significant water quality variables and to determine the origin of pollution sources. Twenty-three water quality parameters were initially selected and analyzed. Three spatial clusters were formed based on HACA. These clusters are designated as downstream of Langat river, middle stream of Langat river, and upstream of Langat River regions. Forward and backward stepwise DA managed to discriminate six and seven water quality variables, respectively, from the original 23 variables. PCA and FA (varimax functionality) were used to investigate the origin of each water quality variable due to land use activities based on the three clustered regions. Seven principal components (PCs) were obtained with 81% total variation for the high-pollution source (HPS) region, while six PCs with 71% and 79% total variances were obtained for the moderate-pollution source (MPS) and low-pollution source (LPS) regions, respectively. The pollution sources for the HPS and MPS are of anthropogenic sources (industrial, municipal waste, and agricultural runoff). For the LPS region, the domestic and agricultural runoffs are the main sources of pollution. From this study, we can conclude that the application of environmetric methods can reveal meaningful information on the spatial variability of a large and complex river water quality data.     

Assessment of surface water quality using a growing hierarchical self-organizing map: a case study of the Songhua River Basin,northeastern China,from 2011 to 2015

The analysis of a large number of multidimensional surface water monitoring data for extracting potential information plays an important role in water quality management. In this study, growing hierarchical self-organizing map (GHSOM) was applied to a water quality assessment of the Songhua River Basin in China using 22 water quality parameters monitored monthly from 13 monitoring sites from 2011 to 2015 (14,782 observations). The spatial and temporal features and correlation between the water quality parameters were explored, and the major contaminants were identified. The results showed that the downstream of the Second Songhua River had the worst water quality of the Songhua River Basin. The upstream and midstream of Nenjiang River and the Second Songhua River had the best. The major contaminants of the Songhua River were chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), total phosphorus (TP), and fecal coliform (FC). In the Songhua River, the water pollution at downstream has been gradually eased in years. However, FC and biochemical oxygen demand (BOD₅) showed growth over time. The component planes showed that three sets of parameters had positive correlations with each other. GHSOM was found to have advantages over self-organizing maps and hierarchical clustering analysis as follows: (1) automatically generating the necessary neurons, (2) intuitively exhibiting the hierarchical inheritance relationship between the original data, and (3) depicting the boundaries of the classification much more clearly. Therefore, the application of GHSOM in water quality assessments, especially with large amounts of monitoring data, enables the extraction of more information and provides strong support for water quality management.     

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.     

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 Composite Water Quality Identification Index on the water quality evaluation in spatial and temporal variations: a case study in Honghu Lake,China

Composite Water Quality Identification Index (CWQII) and multivariate statistical techniques were used to investigate the temporal and spatial variations of water quality in Honghu Lake. The aims are to explore the characteristics of water quality trends in annual, monthly, and site spatial distribution and to identify the main pollution factors. The results showed that the values of CWQII increased from 2.0 to 4.0 from the years 2001 to 2005, then decreased from 2006 and kept a balance between 2.0 and 3.0 from 2006 to 2011, indicating that the water quality of Honghu Lake deteriorated from 2001 to 2005 and has gradually improved since 2006, which were likely achieved after water protection measurements taken since 2004. The monthly change rules of water quality were influenced by a superposition of natural processes and human activities. In samples numbered 1–9 from upstream to downstream, the maximum values of CWQII often occurred in sample site 9 while the minimum ones often occurred in sample site 2, indicating that the water quality near the upstream tributary was the poorest and that in the core zone was the best. Incoming water from the trunk canal of the Sihu area upstream was the largest pollution source. The sensitive pollution nutrients were mainly caused by the total nitrogen, followed by the total phosphorus.     

Water quality monitoring using remote sensing in support of the EU water framework directive (WFD): A case study in the Gulf of Finland

Water quality monitoring using remote sensing has been studied in Finland for many years. But there are still few discussions on water quality monitoring using remote sensing technology in support of water policy and legislation in Finland under the WFD. In this study, we present water quality monitoring using remote sensing in the Gulf of Finland, and focus on the spatial distribution of water quality information from satellite-based observations in support of water policy by a case study of nitrate concentrations in surface waters. In addition, we briefly describe instruments using a system of river basin districts (RBD), highlighting the importance of integrated water resources and river-basin management in the WFD, and discuss the role of water quality monitoring using remote sensing in the implementation of water policy in Finland under the WFD.     

Optimizing water quality monitoring networks using continuous longitudinal monitoring data: a case study of Wen-Rui Tang River, Wenzhou, China

Identification of representative sampling sites is a critical issue in establishing an effective water quality monitoring program. This is especially important at the urban-agriculture interface where water quality conditions can change rapidly over short distances. The objective of this research was to optimize the spatial allocation of discrete monitoring sites for synoptic water quality monitoring through analysis of continuous longitudinal monitoring data collected by attaching a water quality sonde and GPS to a boat. Sampling was conducted six times from March to October 2009 along a 6.5 km segment of the Wen-Rui Tang River in eastern China that represented an urban-agricultural interface. When travelling at a velocity of ～2.4 km h(-1), this resulted in water quality measurements at ～20 m interval. Ammonia nitrogen (NH(4)(+)-N), electrical conductivity (EC), dissolved oxygen (DO), and turbidity data were collected and analyzed using Cluster Analysis (CA) to identify optimal locations for establishment of long-term monitoring sites. The analysis identified two distinct water quality segments for NH(4)(+)-N and EC and three distinct segments for DO and turbidity. According to our research results, the current fixed-location sampling sites should be adjusted to more effectively capture the distinct differences in the spatial distribution of water quality conditions. In addition, this methodology identified river reaches that require more comprehensive study of the factors leading to the changes in water quality within the identified river segment. The study demonstrates that continuous longitudinal monitoring can be a highly effective method for optimizing monitoring site locations for water quality studies.     

Evaluation of surface water quality in aquatic bodies under the influence of uranium mining (MG, Brazil)

The quality of the water in a uranium-ore-mining area located in Caldas (Minas Gerais State, Brazil) and in a reservoir (Antas reservoir) that receives the neutralized acid solution leaching from the waste heaps generated by uranium mining was investigated. The samples were collected during four periods (October 2008, January, April and July 2009) from six sampling stations. Physical and chemical analyses were performed on the water samples, and the data obtained were compared with those of the Brazilian Environmental Standards and WHO standard. The water samples obtained from waste rock piles showed high uranium concentrations (5.62 mg L^?1), high manganese values (75 mg L^?1) and low average pH values (3.4). The evaluation of the water quality at the point considered the limit between the Ore Treatment Unit of the Brazilian Nuclear Industries and the environment (Consulta Creek) indicated contamination by fluoride, manganese, uranium and zinc. The Antas reservoir showed seasonal variations in water quality, with mean concentrations for fluoride (0.50 mg L^?1), sulfate (16 mg L^?1) and hardness (20 mg L^?1) which were low in January, evidencing the effect of rainwater flowing into the system. The concentrations for fluoride, sulfate and manganese were close or above to the limits established by current legislation at the point where the treated mining effluent was discharged and downstream from this point. This study demonstrated that the effluent discharged by the UTM affected the quality of the water in the Antas reservoir, and thus the treatments currently used for effluent need to be reviewed.     

Assessment of surface water quality using multivariate statistical techniques in red soil hilly region: a case study of Xiangjiang watershed, China

In the study, multivariate statistical methods including factor, principal component and cluster analysis were applied to analyze surface water quality data sets obtained from Xiangjiang watershed, and generated during 7 years (1994-2000) monitoring of 12 parameters at 34 different profiles. Hierarchical cluster analysis grouped 34 sampling sites into three clusters, including relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) sites, and based on the similarity of water quality characteristics, the watershed was divided into three zones. Factor analysis/principal component analysis, applied to analyze the data sets of the three different groups obtained from cluster analysis, resulted in four latent factors accounting for 71.62%, 71.77% and 72.01% of the total variance in water quality data sets of LP, MP and HP areas, respectively. The PCs obtained from factor analysis indicate that the parameters for water quality variations are mainly related to dissolve heavy metals. Thus, these methods are believed to be valuable to help water resources managers understand complex nature of water quality issues and determine the priorities to improve water quality.     

Determination of landscape beauties through visual quality assessment method: a case study for Kemaliye (Erzincan/Turkey)

Kemaliye (Erzincan/Turkey) is the member of European Association of Historic Towns and Regions. The aim of this study was to reveal the visual richness of the town; to identify the relationship between landscape spatial pattern and visual quality of the landscape and to offer some suggestions for the future planning in regarding to these visual beauties. The visual quality assessment method was used in this study. The results of the study revealed three landscape types that have the highest visual quality. Among those, the highest one is urban scenery 3 (US3; VQP = 5.9400), the second is geological structure scenery 5 (GSS 5; VQP = 5.9200) and the third natural scenery 3 (NS3; VQP = 5.9133). Visual quality assessment showed that urban pattern, geological structure and natural resources of the region also have visual value. The relationships between landscape spatial pattern and visual quality of landscape indicated that certain characteristics of landscape affected the quality. For instance, as the texture level decreased in natural landscapes and as the green areas increased in geological structure, visual preferences ratio increased. Some suggestions were also made regarding the visual resources use in the region.     

Evaluation of chromium contamination in water, sediment and vegetation caused by the tannery of Jijel (Algeria): a case study

In order to evaluate the chromium (Cr) contamination due to the discharge of waste waters from the tannery of Jijel in the Mouttas river (Algeria), samples of water, sediment and vegetation (Agropyrum repens) were collected during a 6 month period in four stations located upstream (control) and downstream of the tannery. The total chromium was measured by atomic absorption spectrophotometry. Metal inputs were clearly related to effluent discharges from the tannery into the river. Although only traces of chromium were found in water samples upstream of the tannery, very high concentrations (up to 860 times higher) were detected downstream. The contamination was not limited to water of Mouttas River because a same difference in chromium concentrations was also found in sediments and plants Agropyrum repens that were sampled upstream and downstream of the tannery. This work showed that the treatment process used in the wastewater treatment plant of the tannery of Jijel is not able to remove the chromium detected in their influents. The occurrence and chromium levels detected in the aquatic environment represent a major problem concerning drinking water resources and environmental protection of water bodies.