东江中游水质时空分异特征及影响因素研究

运用多元统计方法，对东江中游水质自动站（河源临江站和惠州剑潭站）2009-2012年水质监测数据进行时空分异特征及影响因素研究。结果表明：水站水质在Ⅰ类～Ⅲ类之间；空间特征差异为 T 与 TB 差异不显著，pH 值、EC、DO、IMn、NH3-N 及 TP均存在极显著差异；水期体征差异为河源临江站除 DO各水期差异显著外，其他指标差异不明显，惠州剑潭站 pH值、EC、IMn与 TP各水期均呈显著差异，NH3-N 水期差异不显著。Pearson 相关性分析表明，T 是制约河源临江站水体 DO的主要相关因子，营养盐作用相对较低；惠州剑潭站水体 DO 与 T、TP及 IMn呈极显著负相关关系。通过因子分析，识别出影响惠州剑潭水质的主因子，量化了水体理化性质、地表径流及人为污染对水质变化的贡献。     

Restoration of the Kissimmee River, Florida: Water Quality Impacts from Canal Backfilling

The planned restoration of the Kissimmee River ecocystem will backfill approximately 35 km of flood control canal (C-38) that cuts through the meandering river channel, re-establish natural flow patterns, and restore the river/floodplain ecosystem. Water quality monitoring, including nutrients, total suspended solids (TSS), turbidity, dissolved oxygen (DO), and mercury, was conducted during a pilot `test fill' project to determine if soil disturbance during canal backfilling would negatively impact these water quality constituents. Surface water nutrient concentrations varied little between sites. Generally, highest concentrations occurred prior to construction, with lowest concentrations occurring during and after construction. During construction, TSS concentrations increased at sites immediately upstream, downstream, and adjacent to the construction area. Increased turbidity was generally restricted to areas immediately upstream and downstream of the test plug, with maximum levels occurring during the initial construction phase. Some downstream increases in turbidity were observed; however, impacts were short-term, lasting less than 24 h. Depresssed DO levels (<2 mg/l) were observed upstream of the test plug following completion of the initial plug across C-38. Dissolved oxygen levels remained low for approximately 6 weeks, with no apparent ecological impacts. Total mercury (HgT) within canal sediment ranged from 9.2–180 ng/g and methylmercury concentrations ranged from 0.037–0.708 ng/g. Concentration of total mercury and total methylmercury (MeHgT) in the backfill material were much lower than concentrations in the canal sediment. No significant change in aqueous HgT concentrations occurred over the sampling period, although construction-induced turbidity could have temporarily caused a slightly elevated concentration immediately downstream of the construction site. Methylmercury concentrations in the water column ranged from 0.033–0.518 ng/l. No significant differences in mean MeHgT concentrations occured between sites or between sampling dates, except at one downstream site where MeHgT declined significantly over the sampling period.     

Water Quality Assessment and Modeling of an Effluent-Dominated Stream, the Notwane River, Botswana

In an effort to assess current and future water quality of the only perennial river in southeastern Botswana, this study presents water quality monitoring and modeling results for the effluent-dependent Notwane River. The water quality along the Notwane River, pre- and post-implementation of secondary wastewater treatment, was compared and results demonstrated that water quality improved after the new wastewater treatment plant (WWTP) went online. However, stream standards for chemical oxygen demand, total dissolved phosphorous, and fecal coliform were exceeded in most locations and the critical dissolved oxygen (DO) reached concentrations of less than 4 mg L⁻¹. High dissolved P concentrations and intense macrophyte growth at the impounding ponds and at sites within 30 km of the effluent waste stream confluence suggest that eutrophication was a function of P release from the ponds. Results of DO modeling demonstrated that an unpolluted inflow at approximately 10 km downstream of the confluence was responsible for raising DO concentrations by 2.3 mg L⁻¹, while SOD was responsible for a decline in DO concentrations of 1.4 mg L⁻¹ at 6 km downstream of the confluence. Simulations also showed higher DO concentrations during winter months, when water temperatures were lower. Simulations, in which the distributed biochemical oxygen demand (BOD) loading from cattle excrement was decreased, produced nominal increases in DO concentrations. An increase in WWTP BOD loadings to projected 2020 values resulted in a 1.3 mg L⁻¹ decrease in the critical DO concentration. Furthermore, a decrease in treatment plant efficiency, from 94% to 70% BOD removal, produced critical DO concentrations and anoxia along much of the modeled reach. This has significant implications for Gaborone, especially if decreased WWTP efficiency occurs as a result of the expected future increase in pollutant loadings.     

Developing an environmental water quality monitoring program for Haraz River in Northern Iran

Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH₃, EC, BOD, TSS, DO, PO₄, NO₃, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations × 12 parameters = 36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations × 18 parameters = 234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).     

Application of Water Quality Indices and Dissolved Oxygen as Indicators for River Water Classification and Urban Impact Assessment

The usefulness of water quality indices, as the indicators of water pollution, for assessment of spatial-temporal changes and classification of river water qualities was verified. Four water quality indices were investigated: WQI (considering 18 water quality parameters), WQI(min) and WQI(m) (considering five water quality parameters: temperature, pH, DO, EC and TSS) and WQI(DO) (considering a single parameter, DO). The water quality indices WQI(min), WQI(m) and WQI(DO) could be of particular interest for the developing countries because of the minimum analytical cost involved. As a case study, water quality indices were used to evaluate spatial and temporal changes of the water quality in the Bagmati river basin (Nepal) for the study period 1999-2003. The results allowed us to determine the serious negative effects of the city urban activity on the river water quality. In the studied section of the river, the water quality index (WQI) was 71 units (classified as good) at the entry station and 47.6 units (classified as bad) at the outlet station. For the studied period, a significant decrease in water quality (mean WQI decrease = 11.6%, p = 0.042) was observed in the rural areas. A comparative analysis revealed that the urban water quality was significantly bad as compared with rural. The analysis enabled to classify the water quality stations into three groups: good water quality, medium water quality and bad water quality. WQI(min) resulted in overestimation of the water quality but with similar trend as with WQI and is useful for the periodic routine monitoring program. The correlation of WQI with WQI(min) and DO resulted two new indices WQI(m) and WQI(DO), respectively. The classification of waters based on WQI(m) and WQI(DO) coincided in 90 and 93% of the samples, respectively.     

Design of sampling locations for river water quality monitoring considering seasonal variation of point and diffuse pollution loads

The design of a water quality monitoring network (WQMN) is a complicated decision-making process because each sampling involves high installation, operational, and maintenance costs. Therefore, data with the highest information content should be collected. The effect of seasonal variation in point and diffuse pollution loadings on river water quality may have a significant impact on the optimal selection of sampling locations, but this possible effect has never been addressed in the evaluation and design of monitoring networks. The present study proposes a systematic approach for siting an optimal number and location of river water quality sampling stations based on seasonal or monsoonal variations in both point and diffuse pollution loadings. The proposed approach conceptualizes water quality monitoring as a two-stage process; the first stage of which is to consider all potential water quality sampling sites, selected based on the existing guidelines or frameworks, and the locations of both point and diffuse pollution sources. The monitoring at all sampling sites thus identified should be continued for an adequate period of time to account for the effect of the monsoon season. In the second stage, the monitoring network is then designed separately for monsoon and non-monsoon periods by optimizing the number and locations of sampling sites, using a modified Sanders approach. The impacts of human interventions on the design of the sampling net are quantified geospatially by estimating diffuse pollution loads and verified with land use map. To demonstrate the proposed methodology, the Kali River basin in the western Uttar Pradesh state of India was selected as a study area. The final design suggests consequential pre- and post-monsoonal changes in the location and priority of water quality monitoring stations based on the seasonal variation of point and diffuse pollution loadings.     

Seasonal variations in physico-chemical characteristics of River Yamuna in Haryana and its ecological best-designated use

Various physico-chemical characteristics of the River Yamuna flowing in Haryana through Delhi were studied in the summer (April 1998) and winter (Jan.-Feb. 1999). Ecological parameters like dissolved oxygen (DO), pH, nitrate (NO3-), sulfate (SO4(2-)), and phosphate (PO4(3-)), were analyzed and compared with standard permissible limits to assess the best-designated use of the river water for various purposes. The river in Delhi upstream was of better quality whereas the Delhi downstream stretch was polluted as indicated by very low DO and high total dissolved solids (TDS), electric conductivity (EC), total hardness, Na+, K+, Cl-, F- and SO4(2-). The differences in various parameters were statistically significant (p < 0.01) when compared for the Delhi upstream and downstream stretches of the river, particularly in summer. DO and TDS were found to be two important parameters, which showed strong correlation with several other parameters and hence can serve as good indices of river water quality. The river tended to recover from the pollution stress after flowing through a distance of about 80 km downstream of Delhi.     

Spatiotemporal classification of environmental monitoring data in the Yeongsan River basin, Korea, using self-organizing maps

Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.     

Effects of land use types on surface water quality across an anthropogenic disturbance gradient in the upper reach of the Hun River, Northeast China

Surface water quality is vulnerable to pollution due to human activities. The upper reach of the Hun River is an important water source that supplies 52 % of the storage capacity of the Dahuofang Reservoir, the largest reservoir for drinking water in Northeast China, which is suffering from various human-induced changes in land use, including deforestation, reclamation/farming, urbanization and mine exploitation. To investigate the impacts of land use types on surface water quality across an anthropogenic disturbance gradient at a local scale, 11 physicochemical parameters (pH, dissolved oxygen [DO], turbidity, oxygen redox potential, conductivity, biochemical oxygen demand [BOD₅], chemical oxygen demand [COD], total nitrogen [TN], total phosphorus [TP], NO ₃ ^? -N, and NH ₄ ⁺ -N) of water from 12 sampling sites along the upper reach of the Hun River were monitored monthly during 2009–2010. The sampling sites were classified into four groups (natural, near-natural, more disturbed, and seriously disturbed). The water quality exhibited distinct spatial and temporal characteristics; conductivity, TN, and NO ₃ ^? -N were identified as key parameters indicating the water quality variance. The forest and farmland cover types played significant roles in determining the surface water quality during the low-flow, high-flow, and mean-flow periods based on the results of a stepwise linear regression. These results may provide incentive for the local government to consider sustainable land use practices for water conservation.     

Water Quality Assessment of an Untreated Effluent Impacted Urban Stream: The Bharalu Tributary of the Brahmaputra River, India

Guwahati, the lone city on the bank of the entire midstream of the Brahmaputra River, is facing acute civic problem due to severe depletion of water quality of its natural water bodies. This work is an attempt towards water quality assessment of a relatively small tributary of the Brahmaputra called the Bharalu River flowing through the city that has been transformed today into a city drainage channel. By analyzing the key physical, chemical and biological parameters for samples drawn from different locations, an assessment of the dissolved load and pollution levels at different segments in the river was made. Locations where the contaminants exceeded the permissible limits during different seasons were identified by examining spatial and temporal variations. A GIS developed for the watershed with four layers of data was used for evaluating the influence of catchment land use characteristics. BOD, DO and total phosphorus were found to be the sensitive parameters that adversely affected the water quality of Bharalu. Relationship among different parameters revealed that the causes and sources of water quality degradation in the study area were due to catchments input, anthropogenic activities and poor waste management. Elevated levels of total phosphorus, BOD and depleted DO level in the downstream were used to develop an ANN model by taking total phosphorus and BOD as inputs and dissolved oxygen as output, which indicated that an ANN based predictive tool can be utilized for monitoring water quality in the future.     

北京市河流氨氮浓度时空演变特征分析

选取2010—2017年北京市地表水监测数据,对河流氨氮(NH 3-N)浓度的时空演变特征进行分析。结果显示,空间上,全市河流NH 3-N浓度整体上保持上游优于下游的分布特征;年均浓度显著下降,由2010年的8.53 mg/L逐年下降至2017年的3.09 mg/L;河流NH 3-N浓度与化学需氧量、总磷呈显著正相关,与溶解氧显著负相关,总氮与NH 3-N的比值随着水质由差到好呈上升状态。污水收集处理和再生水利用是改善北京市河流水质的关键措施。为持续降低河流NH 3-N浓度,改善首都水环境质量,须提高污水处理能力和出水水质,有机结合再生水回用与生态治水理念。     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

Spatial and temporal variations of nitrogen pollution in Wen-Rui Tang River watershed, Zhejiang, China

Water quality has degraded dramatically in Wen-Rui Tang River watershed, Zhejiang, China, especially due to rapid economic development since 1995. This paper aims to assess spatial and temporal variations of the main pollutants (NH??-N, TN, BOD(5), COD(Mn), DO) of water quality in Wen-Rui Tang River watershed, using the geographic information system, cluster analysis (CA) and principal component analysis (PCA). Results showed that concentrations of BOD(5), COD(Mn), NH??-N, and TN were significantly higher in tertiary rivers than in primary and secondary rivers. From April 2006 to March 2007, the concentrations of NH? ?-N (2.25-57.9 mg/L) and TN (3.78-70.4 mg/L) in all samples exceeded Type V national water quality standards (≥2 mg/L), while 5.3% of all COD(Mn) (1.83-27.5 mg/L) and 33.6% of all BOD(5) (0.34-50.4 mg/L) samples exceeded Type V national water quality standards (COD(Mn)?≥ 15 mg/L, BOD(5)?≥ 10 mg/L). Monthly changes of pollutant concentrations did not show a clear pattern, but correlation analysis indicated that NH??-N and TN in tertiary rivers had a significant negative correlation with 5-day cumulative rainfall and monthly rainfall, while there were no significant correlations in primary and secondary rivers. The results of CA and spatial analysis showed that the northern part of Wen-Rui Tang River watershed was the most seriously polluted. This region is characterized by the high population density and industrial and commercial activities. The PCA and spatial analysis indicated that the degraded water quality is caused by anthropogenic activities and poor wastewater management.     

Characteristics of and Human Influences on Nitrogen Contamination in Yellow River System, China

Nitrogen (N) contamination in the Yellow River mainstream and its tributaries was studied using data from 1960 to 2000 from 312 monitoring sites in the Yellow River system. Data showed that N concentrations in the Yellow River have increased since 1960, especially after 1990. N concentrations in the Yellow River mainstream increased from the upper reaches (less than 1.0 mg L(-1) for TN and less than 0.10 mg L(-1) for NH4(+)-N) to lower reaches (higher than 4-5 mg L(-1) for TN and higher than 1.0 mg L(-1) for NH4(+)-N). However, the highest N contaminations (50-250 mg L(-1) for TN and 10-20 mg L(-1) for NH4(+)-N) was found in some tributaries, which was attributed as an effect of industrial wastewater and municipal sewage. Nitrogen concentrations from several monitoring sites were positively correlated with several regional socio-economic indices, such as population density, fertilization rates, livestock, industrial input and GDP. Depending on location, seasonal N concentrations contrasted among watersheds. Monitoring stations located in rural and agricultural areas showed higher N concentrations during the flood season while those located in areas with urban and industrial centers showed higher N concentration during the dry season. Mainstream flow and N concentrations showed a strong inverse relationship; with higher N concentrations as the river flow declined. Intensive water extraction for agricultural irrigation and increasing N input to the river from fertilized agricultural fields could explain the increasing N concentrations during extensive droughts.     

Water quality assessment and source identification of Daliao river basin using multivariate statistical methods

Multivariate statistical methods, such as cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA), were used to analyze the water quality dataset including 13 parameters at 18 sites of the Daliao River Basin from 2003-2005 (8424 observations) to obtain temporal and spatial variations and to identify potential pollution sources. Using Hierarchical CA it is classified 12 months into three periods (first, second and third period) and the 18 sampling sites into three groups (groups A, B and C). Six significant parameters (temperature, pH, DO, BOD(5), volatile phenol and E. coli) were identified by DA for distinguishing temporal or spatial groups, with close to 84.5% correct assignment for temporal variation analysis, while five parameters (DO, NH(4)(+)-N, Hg, volatile phenol and E. coli) were discovered to correctly assign about 73.61% for the spatial variation analysis. PCA is useful in identifying five latent pollution sources for group B and C (oxygen consuming organic pollution, toxic organic pollution, heavy metal pollution, fecal pollution and oil pollution). During the first period, sites received more oxygen consuming organic pollution, toxic organic pollution and heavy metal pollution than those in the other two periods. For group B, sites were mainly affected by oxygen consuming organic pollution and toxic organic pollution during the first period. The level of pollution in the second period was between the other two periods. For group C, sites were mainly affected by oil pollution during the first period and oxygen consuming organic pollution during the third period. Furthermore, source identification of each period for group B and group C provided useful information about seasonal pollution. Sites were mainly affected by fecal pollution in the third period for group B, indicating the character of non-point source pollution. In addition, all the sites were also affected by physical-chemistry pollution. In the second and third period for group B and second period for group C sites were also affected by natural pollution.     

Using multivariate techniques as a strategy to guide optimization projects for the surface water quality network monitoring in the Velhas river basin,Brazil

Surface water quality monitoring networks are usually deployed and rarely re-evaluated with regard to their effectiveness. In this sense, this work sought to evaluate and to guide optimization projects for the water quality monitoring network of the Velhas river basin, using multivariate statistical methods. The cluster, principal components, and factorial analyses, associated with non-parametric tests and the analysis of violation to the standards set recommended by legislation, identified the most relevant water quality parameters and monitoring sites, and evaluated the sampling frequency. Thermotolerant coliforms, total arsenic, and total phosphorus were considered the most relevant parameters for characterization of water quality in the river basin. The monitoring sites BV156, BV141, BV142, BV150, BV137, and BV153 were considered priorities for maintenance of the network. The multivariate statistical analysis showed the importance of a monthly sampling frequency, specifically the parameters considered most important.     

北方缓流水体水质在线自动监测系统采样口的设计思考

以DO作为水体的污染指标来判定水质类别存在一定的缺陷,北方缓流水体在不同季节常存在不同的DO分层现象,现设在河床底以上0.5米处的自动监测采样口设计缺少科学性。在叙述缓流水体DO特点的同时,介绍一种新的水质在线自动监测采样口的方案,便于类似水体水质自动监测设计中借鉴。     

基于多元统计分析的石头口门水库汇水流域水质综合评价

根据石头口门水库汇水流域的4个监测断面2001～2007年的水质监测数据,应用多元统计分析方法(聚类分析与因子分析)确定主要污染因子并计算权重,从而对流域的水质进行综合评价。结果表明,通过因子分析,提取了3个公因子,第一主因子主要包括溶解氧、氨氮、总氮、高锰酸盐指数、化学需氧量、生化需氧量;第二主因子的主要代表指标是总磷;氟化物、总大肠菌群数对第三主因子贡献明显。由综合评价结果得出,石头口门水库总体属Ⅲ类水质,主要污染因子为总磷;饮马河(烟筒山断面)和岔路河(星星哨水库断面)水质属Ⅲ类,主要受第一主因子影响;双阳河(新安断面)水质属Ⅴ类。流域水质主要受到了农业非点源污染和生活污染的影响。     

云龙湖水质调查与评价

对云龙湖水质进行了调查与评价.在云龙湖东湖、西湖区各设置3个采样点,监测水体中TN、TP、Imn、NH3-N、DO和SD指标;分别使用模糊识别法和湖泊综合营养指数对水体进行水质评价与富营养化评价,结果表明,云龙湖水质级别为III类,其中TN、TP超标明显,水体呈现中度富营养化;不同功能区水质差异明显,东湖区水质优于西湖...