Comprehensive Water Quality Identification Index Research Articles

Different methods for the evaluation of surface water quality: The Case of the Liao River, Liaoning Province, China

The water-quality index is a grading system for presenting water-quality data and comparing water of varying quality. It can be used in water quality trend analyses and presents valuable information to policy makers, managers, and other nontechnical people. For exploring water quality and identifying the main pollution parameter in the lower reaches of Liao River, Single Factor Evaluation (SFE) method in the form of a Comprehensive Water Pollution Index (CWPI), the Nemerow-Sumitomo Water Quality Index (NWQI), and the Comprehensive Water Quality Identification Index (CWQII) method were used to evaluate water quality in lower reaches of Liao River, Liaoning province, China. The results proved that at Zhaoquan river and Wailiao river the water quality status was good, and Pangxiegou river and Qingshui river showed unsatisfactory water quality status. The major pollution indicator in lower reaches of Liao River was petroleum, and compared with the other assessment methods, CWQII was found to give more useful and objective information, and it is worth further promoting water quality inspections in lower reaches of Liao River. Finally, according to the distribution of industry in the Liao river basin, this study makes some relevant suggestions for sustainable development in the future.

Spatial and seasonal variations of water quality in the upstream plain river networks of the Taihu Basin

在太湖流域上游的宜溧洮滆水系主要河道设置67个监测点，分别于2014年1月（冬季）、4月（春季）、8月（夏季）、11月（秋季）进行水质监测，采用多元统计方法分析了水质的空间差异性和季节性变化，并利用水质标识指数法对水环境质量进行评价.结果表明，宜溧洮滆水系污染程度较严重，总氮（TN）、总磷（TP）和高锰酸盐指数（COD_Mn）浓度年均值分别为4.93、0.26和7.63 mg/L；单因素多元方差分析和聚类分析显示污染物浓度具有显著时空差异性，时间上冬、春季污染程度较高而夏、秋季较低，空间上无锡和常州氮、磷污染较为严重，宜兴和溧阳市有机污染程度较高；水质标识评价结果显示流域内水质基本为IV类或V类，其中TN、TP及COD_Mn是关键污染指标.;Sixty-seven water sampling sites in the Yili-Taoge plain river networks of the upstream area of the Taihu Basin were set to characterize its water quality with spatiotemporal distribution. Water sampling trips were conducted in January (winter), April (spring), August (summer), November (autumn) of 2014, and main water quality parameters were concentrated on nutrients and organic matters. Spatial and seasonal variations of water quality were analyzed by using the multivariate statistical methods and water quality were assessed by employing the comprehensive water quality identification index. The results indicated that pollution degree in the research area was severe. The averaged concentrations of total nitrogen (TN), total phosphorus (TP) and permanganate index (COD_Mn) were 4.93 mg/L, 0.26 mg/L and 7.63 mg/L, respectively. One-way multivariate analysis and cluster analysis showed significantly spatiotemporal patterns of pollutants. Pollution levels in winter and spring were higher than that in summer and autumn. Pollution of nitrogen and phosphorus were heavier in the Wuxi and Changzhou areas, whereas organic matter pollution was more serious in the Yixing and Liyang areas. Water quality in the upstream plain river networks can meet the criteria of Grade IV or V of National Standards for Surface Water Quality, characterized by pollution of TN, TP and COD_Mn.

Water quality assessment and analysis for rehabilitate and management of wetlands: a case study in Nanhai wetland of Baotou, China

Wetland plays an irreplaceable role in many aspects and waters are important part of wetland, the water quality can easily reflect the situation of Wetland. In this study, water quality was assessed on the basis of 5 parameters (DO, NH 4 + -N, TN, TP and CODcr) that were monitored monthly at 5 sites (N 1 ,N 2 ,N 3 ,N 4 and N 5 )from April, 2014 to March, 2015 of the Nanhai Lake in Baotou, China by water pollution index method and comprehensive water quality identification index method. The twelve monitoring months were divided into wet season (Mar., Aug. and Sep.), normal season (Jan., Feb., Apr., Nov. and Dec.) and dry season (May., Jun. and Jul.). The assessment results determined using the water pollution index method showed that the water quality of all the five monitoring sites were inferior Ⅴ, the main contamination was COD. The comprehensive water quality identification index showed that the water quality of the Nanhai Lake were classesⅤ, except for the N 2 in wet season and dry season, the N 1 in dry season and the N 5 in normal season, which were classes inferiorⅤ. All the five monitoring sites don’t achieving the desired water quality standard. According to the analysis, domestic discharge, industrial activities and developed recreation were major threats to water quality of Nanhai Lake.

Comparison of seven water quality assessment methods for the characterization and management of highly impaired river systems.

In the context of water resource management and pollution control, the characterization of water quality impairments and identification of dominant pollutants are of critical importance. In this study, water quality impairment was assessed on the basis of 7 hydrochemical variables that were monitored bimonthly at 17 sites in 2010 along the rural-suburban-urban portion of the Wen-Rui Tang River in eastern China. Seven methods were used to assess water quality in the river system. These methods included single-factor assessment, water quality grading, comprehensive pollution index, the Nemerow pollution index, principle component analysis, fuzzy comprehensive evaluation, and comprehensive water quality identification index. Our analysis showed that the comprehensive water quality identification index was the best method for assessing water quality in the Wen-Rui Tang River due to its ability to effectively characterize highly polluted waters with multiple impairments. Furthermore, a guideline for the applications of these methods was presented based on their characteristics and efficacy. Results indicated that the dominant pollutant impairing water quality was total nitrogen comprised mainly of ammonium. The temporal variation of water quality was closely related to precipitation as a result of dilution. The spatial variation of water quality was associated with anthropogenic influences (urban, industrial, and agriculture activities) and water flow direction (downstream segments experiencing cumulative effects of upstream inputs). These findings provide valuable information and guidance for water pollution control and water resource management in highly polluted surface waters with multiple water quality impairments in areas with rapid industrial growth and urbanization.

Water Quality Assessment and Nitrogen Pollution Sources Analysis of the West Lake, Hangzhou, China

Single factor water quality identification index (SFWQII) and Comprehensive water quality identification index (CWQII) were applied to the data of 6 parameters for water quality of West Lake at 10 different sites and 4 main inflows in the West Lake basin, generated during March 2012 to February 2013. This study evaluated and elucidated the temporal and spatial variation of each parameter on water quality and the main pollution factor of West Lake by SFQII. CWQII based on the SFQII was applied to evaluate the eutrophication level of West Lake and substantiated mesotrophic waters. Stable isotopes of nitrate were used to identify the nitrate sources of West Lake. The δ15NNO3 values in samples from the West Lake and inflows had a range of 2.6‰ to 12.0‰, while the δ15NNO3 values in Qiantang River was 5.3‰, in rainfall was 5.2‰ and in runoff was 3.6‰, respectively. Animal wastes, commercial fertilizer and domestic sewage were the main nitrate sources. The groundwater and denitrification might increase the levels of NO3- in West Lake.

Innovative approach for the development of a water quality identification index—a case study from the Wen-Rui Tang River watershed, China

Many different approaches have been suggested for the assessment of organic pollution and related water quality variables. However, many methods used to assess organic pollution cannot qualitatively estimate the degree of importance of each pollutant. Water quality identification indices can provide comprehensive water quality information, which is both qualitative and quantitative, especially for areas worse than Grade V of the National Surface Water Quality Standard of China. However, this method considers every indicator equally, without considering the degree of importance of each parameter. Consequently, in this study, the entropy weight method was combined with the water quality identification index method. The improved comprehensive water quality identification index was applied to a water quality data-set for the Wen-Rui Tang River in China, which was generated in 2009 during six months of monitoring at 16 different sites and included seven parameters. The results indicated that the improved comprehensive water quality identification index provided an objective evaluation of each water quality indicator. Understanding the significance of each water quality parameter will help to implement more effective water quality improvement plans.

宜兴市莲花荡水系水环境质量现状及其水质评价

莲花荡水系下接乌溪港，是西太湖主要入湖河流之一，水环境功能区划要求其水质达到地表水Ⅲ类。2014年4月(平水期)和7月(丰水期)，对莲花荡水系进行了两次现场调研和采样监测，结果表明：水体中超过Ⅲ类地表水的污染指标主要有高锰酸盐指数、总磷、总氮、氨氮和叶绿素a等，其中氮、磷污染超标严重；受丰水期河水量增加影响，7月份河水水质略优于4月；调研发现，水体主要的污染源为集中畜禽养殖废水、沿岸农村散排生活污水和部分农业面源污染。采用单因子污染指数法、综合水质标识指数法和水体自净能力评价等方法，对莲花荡水系的水环境质量进行了现状评价，结果为：莲花荡水系在平水期和丰水期分别为严重污染和重度污染；综合水质标识类别介于Ⅴ类~劣Ⅴ类黑臭水质之间；水体具有一定的自净能力，且不同时期各河段的自净能力有所不同。 Lianhuadang River System, flowing down with the Wuxi Harbor River, is one of the most important inflow rivers of the West Taihu. Based on the standards of the water environment functional zoning, its water quality should meet the requirement of the Class-III surface water. In April 2014 (average season) and July (abundant season), the field investigation and sampling monitoring have been performed twice respectively in the Lianhuadang River System. The results show that: the contamination indexes in the water exceeding the standard of the Class-III surface water mainly are the permanganate index, the total phosphorus, the total nitrogen, the ammonia nitrogen and the chlorophyll A, of which the contamination of the nitrogen and phosphorus exceed the standard seriously. Due to the influence of the increasing stream flow in abundant season, the water quality in July is slightly better than that in April. According to the survey, the main pollution sources in the water are the waste water of the concentrating livestock and poultry breeding, the coastwise rural domestic sewage, and part of the Agricultural Area Source Pollution . Adopting the single factor contamination index method, the WQI method (the comprehensive water quality identification index method) and the water self-purification ability evaluation method, the results of the current situation evaluation for the water environmental quality of the Lianhuadang Water System show that: most rivers of the Lianhuadang Water System are polluted seriously; the comprehensive water quality identification category is ranged from Class V to inferior class V-stinking sewage; the water body has a certain self-purification ability, and the capacity of self-purification varies in different periods.

Water Pollution Characteristics and Assessment of Lower Reaches in Haihe River Basin

21 water samples were collected from the lower reaches in Haihe River Basin and the pollutant content was detected in May, 2009. The water quality of 11 rivers in this area was assessed with the methods of Single Factor Assessment Method, Comprehensive Pollution Index Method, Fuzzy Comprehensive Evaluation Method and Water Quality Identification Index Method. The results showed that Water Quality Identification Index Method is suitable for water quality assessment of the lower reaches in Haihe River Basin; Single-factor Water Quality Identification Index Method showed that the main pollutants were total nitrogen, ammonia nitrogen, COD, BOD5, permanganate index, fluoride; the pollution belonged to organic and abundant nutrition pollution. Water pollution of all assessed rivers was serious, and inferior class V rivers accounted for 81.8%.The water quality of Qingjinghuang Drain (8.972), Yongding New River (9.654), Ziya New River (10.877), North Drainage River (11.094), Beitang Drainage River (11.376), and the Dagu Drainage River (14.388) was inferior class V and malodorous black, and the pollution level increased orderly. The pollution of rivers in the south of Haihe River was more serious than that in the north.