汉丹江(陕西段)水质变化特征分析

基于2008—2012年陕西省境内汉江、丹江干流14个断面的水质监测数据,采用单因子评价法、平均综合污染指数法和秩相关系数法等对该段水体的水质变化特征进行研究。结果表明,汉丹江(陕西段)断面水质以Ⅱ类、Ⅲ类为主,水质总体为优;水质综合污染状况呈下降趋势,其中汉江下降趋势显著;水质综合污染状况空间差异和区域分布特征明显,城区段污染大于郊区,各行政区段河流下游污染大于上游。流域水质主要受有机污染和营养盐因子影响,水体污染源主要来自城镇生活源和农业面源,工业源占比不大且排放行业较为集中。     

汉江襄阳城区段水质变化规律及特征分析

为全面掌握汉江襄阳城区段沿程水质变化情况,合理制定相应保护措施,基于2018—2022年汉江襄阳城区段出入境断面及支流水质监测数据,对汉江襄阳城区段水环境质量、变化趋势和相关特征开展综合分析评价。结果表明,2018—2022年汉江襄阳城区段入境与出境断面水质状况总体为优,但出境断面氨氮、总磷、总氮的质量浓度较入境断面均有明显增高,主要支流唐白河、清河及南渠的汇入对出境断面水质影响较大。2018—2021年汉江襄阳城区段出入境断面主要监测指标质量浓度分布表现为丰水期＞枯水期,2022年表现为枯水期＞丰水期。汉江襄阳城区段水质氮污染贡献明显高于磷污染,仍以氮污染为主,水质中氮主要以游离氨和铵盐以外的形式存在。相关性分析结果表明,入境断面与出境断面中氨氮、总氮与各指标相关性差别较大,总磷、溶解氧与各参数间的相关性基本一致。研究结果可为制定汉江水环境改善及污染防治措施提供科学依据。     

代表性水质评价方法的比较研究

从太湖流域国控断面常规监测数据出发,利用代表性水质评价方法对各断面进行评价,系统分析比较这些方法的优缺点。结果显示:①单因子指数法评价结果比较保守;②内梅罗指数法将"1"作为清洁与污染的分界点,指数偏小;③灰色关联分析法水质指标权重系数的确定较模糊综合评判法合理,结果也更接近于综合水质标志指数法;④综合水质标志指数法评价结果与其它评价方法结果重合度最高,且模糊评判法、灰色关联分析法和BP-ANN法的评价结果均向综合水质标志指数法逼近。综合水质标志指数法以单因子指数法为基础,对劣Ⅴ类水进行细化,将恶臭对水质的不利影响考虑其中,其指数组成合理,且易于操作施行。     

模糊-主成分分析综合评价法在地下水水质评价中的应用

主成分分析法可以在保留数据原始信息的基础上有效地降低数据维度，从而将影响地下水质的多因子简化为几个综合因子，但对地下水的综合水质状况无法直接表达；模糊综合评价法能直接给出水体综合水质情况结论，但评价因子多为人为选取，存在较强的主观性。以辽宁思山岭矿区地下水水质现状评价为例，利用主成分分析法选取影响各断面水质的关键因子，将其作为模糊综合评价的评价因子，建立了模糊?主成分分析综合评价法的地下水水质耦合评价模型。研究结果表明，该模型能很好地体现分析因子对评价结果带来的影响，使得评价结果更科学、合理。     

因子分析法在金泉工业园区地下水水质评价中的应用

根据金泉工业园水源地8个不同监测断面的地下水水质监测数据,采用R型因子分析法对园区水源地地下水水质进行综合评价,在研究地下水中13种化学成分间相关关系的基础上,提取4个主因子进行分析计算。结果表明,Cl-、SO24-、总硬度和可溶性固体对第一主因子贡献明显;第二主因子代表指标是Zn;第三主因子代表指标是As;NO3-、氨氮、NO2-对第四主因子贡献显著。对水质进行综合评价后发现,人民渠、海流图河和乌拉壕监测断面处水质类别为V类,其他断面均为IV类。因子分析法从整体上评价了园区水源地地下水的水质现状,分析结果清晰明确,为日后地下水资源的管理与保护提供科学依据。     

北京市妫水河水质现状评价

2017年分3个时期(丰水期、平水期、枯水期)采集妫水河及其支流12个断面表层水样,分析了COD、氨氮、TP、DO、pH值等水质指标,采用单因子评价法、水污染指数法、主成分分析法和模糊综合评价法对水质进行评价,根据4种水质评价方法的评价结果,分析4种方法在小流域河流评价中的适用性。结果表明:目前妫水河12个断面中S2、S10和Z2 3个断面水质较差,基本属于地表Ⅴ类水,污染程度为重度污染;其他9个断面水质等级为地表Ⅳ类水,污染程度为中度污染;中段世园会段水质较好,优于上段和下段,主要污染指标为COD;妫水河主要污染源于农业和生活,枯水期水质优于平水期和丰水期。水污染指数法更适合小流域水体水质的定性定量评价,且计算方便简单。     

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。     

不同水质评价方法在丹江口流域水质评价中应用比较

采用合理的水质评价方法,准确地描述河流水质状况,才能为水质管理提供治理方案。以丹江口水源地为例,选用单因子指数评价方法、综合污染指数评价方法、模糊综合评判法、主成分分析法、水污染指数法对丹江口水源地7个河流断面进行水质评价并对比评价效果。结果表明,水污染指数法操作简便、评价结果直观明了,具有广泛的应用范围。     

太原汾河景区跨桥断面水体污染的时空变化模式研究

选取太原汾河景区跨桥断面8个监测点,在2012年3月—2013年10月期间对河流8项水质参数进行监测,并结合派生的水体综合污染指数及主成分分析方法分析和评价景区水污染时空变化特征。结果表明,景区水质污染变化时空差异明显,上游污染相对较小,下游污染较重;春季溶解氧和p H值变化幅度最大,夏季除总氮和氨氮外,其他各污染物均有显著变化特征,秋季则以氨氮、总氮和总磷变化最为显著。主成分分析结果显示,虽然各监测点水体污染的关键影响因子不同,但总磷是太原市河流水体污染的共同解释因子。     

西藏生活垃圾填埋场周边地表水环境质量调查评价

采用标准指数法、综合评价法和灰色关联分析法对西藏地区4个典型垃圾填埋场周边地表水环境质量进行分析和评价。结果表明：各填埋场各评价因子均满足《地表水环境质量标准》（GB 3838—2002）Ⅲ类标准；各填埋场临近地表水环境综合水质均呈现上游监测点优于下游监测点；综合水质现状为尚清洁—清洁；灰色关联分析法评价结果为工布江达县生活垃圾填埋场下游监测点水质为Ⅱ类，其他填埋场各监测点水质均为Ⅰ类。各填埋场临近地表水水质现状满足其水域功能区要求，受填埋场污染环境影响较小。     

汉江下游干支流浮游植物群落特征及其对水质的指示评价

浮游植物群落的动态变化可以全面、真实地反映水质的优劣,有利于了解水体污染状况的发展趋势.为及时掌握汉江下游水质变化,基于2019年3—12月汉江下游干流及主要支流浮游植物和水体理化指标监测数据,分析了浮游植物群落结构特征,并通过冗余分析研究了影响浮游植物群落结构的主要环境因子,同时运用浮游植物群落特征对汉江下游水质进行...     

新疆某县河流水质现状评价及其变化趋势分析

利用新疆某县境内主要河流的水质监测资料,依据水质评价标准《地表水环境质量标准》(GB 3838-2002),评价了某县境内主要河流的环境质量,采用季节性肯达尔法进行趋势分析检验。结果表明,新疆某县境内河流水质总体优良,水质级别为Ⅰ、Ⅱ类,可以作为饮用水源地、农田灌溉用水、一般工业用水的水源。从趋势分析检验结果看,水质基本稳定,没有受到明显的人为污染。     

杭州市钱塘江干支流水质多元统计分析

运用多元统计方法分析了杭州市钱塘江干支流上26个断面的水质监测指标。利用系统聚类分析方法将断面所在河流分为3组,与钱塘江流域污染空间分布现状基本一致。对各组水质的主成分分析表明,第1组河流水质以有机污染为主,水体中氮、磷营养盐浓度较高,水体污染程度较轻,污染来源相对单一;第2组河流水体受有机物、重金属、石油类等多个污染指标的影响,水体水质较第1组差,污染来源相对复杂;第3组河流水体既有一般有机污染,也有重金属、有毒有害物质的污染,水体水质污染严重。     

Application and validation of a new biotic index using data from several water systems

Protozoans of Lake Donghu were collected from five stations using the PFU method. The sampling was conducted for one year and two times a month. The aim of this research was to test the applicability of a new protozoa biotic index, species pollution value (SPV) and community pollution value (CPV), established by the authors using data from the River Hanjiang. Each station's CPV was calculated from the SPV and the correlation analysis between the CPV and the comprehensive chemical index of stations I, II, III showed a significant correlation between them. The pollution status of the five stations was correctly evaluated by the CPV. These results suggested that the biotic index could be applied in water systems other than the River Hanjiang. The SPV of some protozoa species in Lake Donghu, not observed in the River Hanjiang were established. In order to further test the applicability of the biotic index, protozoan and chemistry data from the Rivers Torrente Stirone and Parma of Italy were used. The results showed that the CPV for the two rivers had a close relationship with the chemical water quality, which indicated that the biotic index could be applied in other parts of the world for the monitoring and estimating of water quality. Since the results of testing and verifying the biotic index in some other water systems in China were also satisfactory, this indicated that the biotic index has an extensive suitability for freshwater ecosystems. As long as more than 50% of the species in a sample have a SPV, the CPV calculated from the SPV is reliable for monitoring and evaluating water quality.     

2016—2021年上海市杨浦区黄浦江流域水质变化与污染特征分析

为全面了解并跟踪上海市杨浦区黄浦江流域的水质情况，于2016年1月—2021年12月对杨浦区黄浦江流域的6个监测断面的地表水质量进行调查。采用单因子污染指数分析法和水质综合污染指数分析法，探究了杨浦区内黄浦江流域水质的污染变化特征。结果表明，自2017年杨浦区开展河道整治以来，流域总体水质明显改善，出口水质从重度污染提升到良好水平；居民区密集的虬江断面水质相对较差，后续需加强对虬江流域的污染排放管理；水质污染特征分析结果发现河道的主要污染物种类从氨氮（NH₃-N）转换为总磷(TP)，说明河道整治提升了河道的自净能力，水质改善效果显著；水质在非汛期优于汛期，气温、降雨、泵站放江和污水排放是影响水质的主要原因。     

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 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.     

一种建立北方季节性河流水体净化模型的新方法

应用回归分析法研究了北方河流在迳流量季节与年度变化较大的情况下河流水体的自净规律 ,对确定北方季节性河流水污染物总量控制目标与水质保护目标 ,具有重要的现实意义 ,在实际工作中已得到应用并具有较强的推广价值     

河流水环境质量综合评价方法比较研究

提出了对河流水环境质量综合评价方法的基本要求，对水环境质量评价方法的现状进行了研究，并通过对各种方法的 比较，探讨了今后水环境质量综合评价方法的发展方向。