Monitoring, assessment and modelling using water quality data in the Saale River Basin, Germany

The European Water Framework Directive (WFD) is the overall driver for this environmental study and currently requires the identification of patterns and sources of pollution (monitoring) to support objective ecological sound decision making and specific measures to enhance river water quality (modelling). The purpose of this paper is to demonstrate in a case study the interrelationship between (1) hydrologic and water quality monitoring data for river basin characterization and (2) modelling applications to assess resources management alternatives. The study deals with monitoring assessment and modelling of river water quality data of the main stem Saale River and its principal tributaries. For a period of 6 years the data, which was sampled by Environmental Agencies of the German states of Thuringia, Saxony and Saxony-Anhalt, was investigated to assess sources and indicators of pollution. In addition to the assessment a modelling exercise of the routing of different pollutants was carried out in the lower part of the test basin. The modelling is a tool to facilitate the evaluation of alternative measures to reduce contaminant loadings and improve ecological status of a water body as required by WFD. The transport of suspended solids, salts and heavy metals was modelled along a selected Saale reach under strong anthropogenic influence in terms of contaminants and river morphology between the city of Halle and the confluence with the Elbe River. The simulations were carried out with the model WASP5 which is a dynamic flood-routing and water quality model package developed by the US Environmental Protection Agency.     

基于多元统计的宁夏典农河水质演替特征探究

宁夏典农河是黄河宁夏段的主要入黄排水沟之一,其水质状况对黄河宁夏-内蒙古段跨省流域水质安全至关重要。选取典农河2011—2020年10个监测点位的16项水质参数,采用综合污染指数(WPI)法,结合相关性分析、主成分分析、聚类分析等分析方法,综合分析该流域水污染特征,并对污染程度进行评估,对污染因子和污染原因进行解析,最终提出管控建议。研究结果表明：2011—2020年,影响典农河水质的主要污染因子为COD_Cr、NH₃-N、TP、TN,对应的年均浓度范围分别为22.3～71.5、0.64～9.09、0.173～0.662、2.89～21.52 mg/L,超标率分别为46%、8%、13%、85%。典农河2011—2020年WPI范围为0.59～1.74,重金属含量一直维持在较低水平。流域TN与TP年均浓度比值范围为20～84,整体呈下降趋势,且各监测点的差异性逐渐减小;BOD₅与COD_Cr浓度比值范围为0.02～0.19,反映出典农河流域水体可生化性较差。各监测断面污染物之间存在较强相关性,其中：流域C...     

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.     

2001-2015年松花江流域水污染变化特征研究

利用2001-2015年松花江流域国家监测网30个可比断面监测数据,从流域和断面水质变化、各项指标超标情况和浓度变化、污染负荷等方面分析了松花江流域水质变化情况。结果表明,松花江流域水质总体呈好转趋势,特别是2007年以来有比较明显的改善。该流域长期以来主要污染指标为高锰酸盐指数、石油类、五日生化需氧量和氨氮。高锰酸盐指数、石油类和五日生化需氧量污染均有明显改善,但氨氮污染改善不明显。在继续加强COD排放总量控制的基础上,有效削减氨氮排放是促进松花江水质改善的重点。     

Evaluation of the impacts of road runoff in a Mediterranean reservoir in Portugal

Road runoff is a linear diffuse source of pollution, with very specific characteristics. This study intends to improve the understanding of road runoff impacts in water bodies in Portugal. The chosen case study is S. Domingos reservoir catchment. The study analyzed land uses, the presence of pollution sources, and gathered temporal water quality data and performed site measurements and sample collection. The water quality data for the reservoir was provided by the national water quality monitoring system from the Portuguese Water Institute. The parameters selected were TSS, COD, NO₃ ^?, Cl^?, and Cu. The results obtained revealed that the presence of IP6 highway at S. Domingos catchment affects the water quality; however, the impacts are not significant due to the high dilution effect of the reservoir volume. Agriculture, the main land use of the catchment, is responsible for introducing pollutants such as TSS, Cl^?, COD, N, and P in the local water streams and at the reservoir. TSS, COD, and Cu are pollutants generated by the road. The success of the study was very much dependent on the availability of 12 years of historic water quality data for S. Domingos reservoir, and the use of the moving average method. Taking into consideration the high variability of hydrological variables in Mediterranean climates, the concentration of pollutants in the water bodies must always be assessed in a significant time period.     

流域水污染监测与溯源技术研究进展

水污染特征识别和溯源是实施水污染精准治污的关键一步,也是流域水污染防治工作的前提。该文概述了不同分析监测技术、传统溯源方法与人工智能在水污染监测与溯源中的应用进展。光谱分析由于灵敏度高、准确度好,在实现水污染快速监测中应用最为广泛。传统溯源方法在复杂多样的水污染事故中不能准确快速地确定其污染源类型,而人工智能技术由于可以解决动态环境问题中的不确定性和复杂性,能够准确、智能地识别水质特征和追踪污染源。将人工智能与传统技术相结合是流域水污染溯源的发展趋势。展望了人工智能在水污染溯源方面的应用前景,为实现流域水污染全面监管提供了新的思路。     

沱江流域主要污染负荷预测及时空分布特征

耦合社会-经济因子探究工业点源和生活污染源污染负荷未来变化趋势,可为优化水环境规划和管理方案提供理论依据。选取沱江流域为研究区域,采用经济增长预测法、工业点源传统统计法、人口趋势灰色模型预测法和排污系数法分别计算了2020-2025年该区域28个县(市、区)的工业GDP值,工业点源废水排放量及主要污染负荷(COD、NH₃-N、TN、TP),农村与城镇人口及生活污染源的主要污染负荷,并利用ArcGIS技术探究了工业点源和生活污染源主要污染负荷空间分布特征。结果表明:2020-2025年,工业GDP值总体呈逐年增加趋势,而工业废水排放量总体呈逐年减少趋势,预计到2025年,流域工业GDP值将增加至2.52×10¹²元,而工业废水排放量将减少至0.64×10⁸ t。工业点源主要污染负荷表现为COD>NH₃-N>TN>TP。沱江流域总人口数与生活污染源污染负荷呈逐年增加趋势,其中城镇人口与生活污染源污染负荷呈逐年增加趋势,农村人口与生活污染源污染负荷呈逐年减少趋势,且城镇人口及生活污染源污染负荷增加量大于农村人口及生活污染源污染负荷减少量。城镇、农村生活污染源的主要污染负荷表现为COD>NH₃-N>TN>TP。工业点源和生活污染源主要污染负荷在空间上存在高度异质性。2025年,来自工业点源的主要污染负荷均呈上游较少,中、下游较多的特征;来自城市生活污染源的主要污染负荷均呈中、上游较多,下游较少的特征;来自农村生活污染源的主要污染负荷均呈中游较多,上、下游较少的特征。笔者提出耦合社会-经济因子预测流域污染负荷的方法可以推广到其他与社会经济指标相关联的流域工业点源、生活污染源污染负荷的预测研究中,以期为未来流域水环境管理与治理提供科学参考。     

汛期连云港市重点断面污染来源调查研究

长期以来汛期江苏省部分重点断面水质下降明显,是当地水环境质量提升的难点之一.选取连云港市重点断面为研究对象,应用手工监测和卫星遥感监测方法,分析4个典型断面水质变化特点;通过三维荧光溯源分析方法,确定农业源和生活源是主要污染源;结合现场核查,发现秸秆还田沤水和雨污分流不到位是导致典型断面水质下降的主要原因.研究提出,手...     

Chemical monitoring of river water bodies in an EU outermost region: examples from the Azores archipelago (Portugal)

Chemical monitoring of water quality on a total of 16 rivers in the Azores archipelago (Portugal), since 2003, made it possible to identify the major pressures and spatial geochemical variations along main course of the rivers. River water pollution is to a large extent associated to point sources, namely domestic wastewater discharges, especially in urban areas, and diffuse sources, associated with pasture land, and explain the high values on BOD(5) and nutrients (P and N). Heavy metals and metalloids, as well as hydrocarbons and pesticides, are generally under the detection limits of the analytical methods. Generally, river water reflects pollution loads according to a simple model, derived from land use in the watershed: in the upper part conditions are pristine, in the intermediate portion of the basin pasture land dominates and near the coast urban discharges are increasingly important. Results stress the role that an approach based on the watershed scale, coupled with land use management measures, are crucial to water management procedures and a successful WFD implementation in small river basin districts like the Azores. The paper also shows the need for full compliance regarding EU directives on urban wastewater and nitrate pollution due to agriculture.     

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).     

基于3S技术的桂林市南溪河污染现状调查

城区小流域常是水污染较重的区域,又是污染源密集的地方,其非点源污染的监测与评估,需要实用方法。本调查基于3S技术,开展流域的监测与评价,包括空间定位的精度控制、非点源的遥感分类解译、采用排污系数对非点源污染评估、对污染源及污水管网做GIS空间分析。结合水质监测进行污径比和水环境容量的评价。重点讨论了城区人口解译方法和污染源评估方法,探讨典型城区非点源污染监测的思路。     

南水北调中线陕西水源区污染源排放时空变化特征

基于2008—2012年污染源环境统计数据,采用Spearman秩相关系数法等分析南水北调中线陕西水源区污废水及污染物年排放总量变化趋势,借助ArcGIS空间分析功能表征水源区污染源排放的空间分布特征。结果表明:2008—2012年水源区污废水和NH_3-N年排放总量呈显著上升趋势,COD、As、Pb、Cd、Cr和Hg年排放总量呈抛物线型变化,总体上COD、Pb、Cd年排放总量增加,As、Cr和Hg年排放总量降低。水源区污废水及污染物排放量空间差异明显,污废水、COD和NH_3-N排放涉及流域所有区县,其排放量从干流到流域边缘呈现较明显的梯度变化,即位于流域中心或地级市行政中心的区县排放量明显高于位于流域边缘的区县;As、Pb、Cd、Cr和Hg排放量呈现明显的区域分布,主要分布在勉县等8个区县。     

中国农村饮用水水源地水质状况研究

为了系统评估中国农村饮用水水源地水质变化情况,根据2009—2018年农村饮用水水源地水质监测数据,综合评价和分析了中国农村地表和地下饮用水达标情况、空间分布和主要超标因子等。监测结果表明：10年来,农村饮用水水源地达标率不断提高,这主要得益于地表饮用水水质整体改善;地下饮用水水质达标率持续偏低,且略有变差趋势,与城市地区的差距逐年加大。农村饮用水水源地超标断面和点位在空间上分布较广,主要超标因子相对集中,且表现出与农村和农业面源污染较强的相关性。建议进一步重视农村饮用水水源地（特别是地下饮用水）的保护,加强农村饮用水水源地水质监测,加快农业面源污染防治。     

黄河流域甘肃段面源污染估算与空间分析

采用遥感分布式面源污染评估模型（DPeRS）,对2018年黄河流域(甘肃段)面源污染空间分布特征进行分析,具体包括多类型污染量产排特征解析和流域优先管控单元识别。结果表明,污染量上,2018年黄河流域（甘肃段）总氮(TN)、总磷(TP)、氨氮(NH₃^-N)、化学需氧量(COD_Cr)的面源污染排放负荷分别为65.6,11.8,19.1和77.2 kg/km²,入河量分别为836.7,33.3,220.2和1 353.3 t;空间分布上,氮型(TN和NH₃^-N)排放负荷高值区主要分布在流域中部和东部局部地区,流域大部分地区TP排放负荷均较高,COD_Cr面源污染排放负荷高值区分布较为零散。与排放负荷相比,黄河流域（甘肃段）面源污染入河负荷并不突出,这与该地区水资源量少有密切关系。筛选出黄河流域（甘肃段）面源污染优先控制单元15个,面积占比为85.2%,I类优控单元主要分布在庆阳市、天水市、兰州市和白银市等地区,II类优控单元主要分布在甘南藏族自治州,且TN、TP、NH₃^-N和COD_Cr面源污染优控单元识别结果的平均精度达到80%。     

松花江流域水生态环境中生物与生境和化学要素间的关联 性研究

利用2012年松花江流域生物、生境和水质的调查数据,采用生物完整性指数(IBI)评价松花江流域的水生态环境质量,并着重对IBI评价结果与生境质量、水质间的关系及生物与生境和化学参数间的相关关系进行了分析。结果表明,松花江流域IBI评价结果与其生境质量存在显著正相关,与水质评价结果基本一致。生境质量及大多数生境参数均与多项生物参数间存在显著/极显著的相关关系;其次,COD、CODMn、BOD5、TN、TP等超标化学因子也与多项生物参数存在显著/极显著的相关关系,说明生境受损和有机污染压力是引起松花江流域水生态环境质量变化的主要压力。为恢复和改善松花江流域的水生态质量,研究建议针对流域生境质量和超标化学污染开展相应的保护和控制措施。     

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.     

基于遥感影像的木兰溪水质参数反演

水质监测对水环境评价及污染预防至关重要,但地面监测成本高、监测面积有限等,难以满足实时、大范围监测的要求。为了更好地解决该问题,基于遥感影像的空中监测技术越来越得到研究人员的青睐。以木兰溪为研究区,利用和地面监测数据同步的Landsat-8卫星遥感影像数据,对木兰溪的典型水质参数总磷、总氮、溶解氧、高锰酸盐指数的反演问题进行研究。首先,根据Landsat-8的水体敏感波段,分别选取总磷、总氮、溶解氧、高锰酸盐指数的反演特征波段组合为(b1-b2)/(b2+b3),(b1-b2)/(b3-b4),b2/(b1+b4),b1/b2;其次,利用反演特征波段组合分别构建总磷、总氮、溶解氧、高锰酸盐指数浓度的SVR(Support Vector Regression)反演模型,通过IPSO算法对SVR模型的参数进行优选;然后,将IPSO-SVR反演模型和统计回归反演模型、广义回归神经网络(GRNN)反演模型在验证集上进行评估,以平均绝对误差和均方根误差作为评价指标进行对比分析,结果表明IPSO-SVR反演模型的平均绝对误差和均方根误差最小,说明IPSO-SVR反演模型具有较高的精度和较好的实用性...     

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.     

黄河流域水质和工业污染源研究

为科学评价黄河流域的水质状况及工业企业污染源现状,根据黄河流域2018—2019年地表水和饮用水水源地水质监测数据,建立了综合反映流域水环境质量和可定量分析排名的城市水质指数;利用大数据技术分析工业企业水污染物排放数据,研究建立了企业环境信用动态评价体系。研究结果表明:2018—2019年,黄河流域城市水环境质量得到一定程度的改善,城市地表水环境质量优和良等级数量从17个增加到19个,饮用水水源地优等级城市数量从7个增加到11个;但黄河流域中游地区水污染问题较为严重,需要重点加强水污染控制。水质污染主要以点源工业污染为主,COD和氨氮排放量较多,COD和氨氮年日均排放浓度平均值分别为51.1、3.1 mg/L,工业废水处理率偏低;山西、陕西、河南等"高"风险企业数量较多,分别达到3 047、1 630、1 442家。建议加强黄河流域上下游、左右岸、干支流协同配合,加大水污染防治工作的深度和力度。     

中国中东部一次大范围重污染过程特征分析

采用嵌套网格空气质量预报模式(NAQPMS)模拟与气象、污染物观测资料相结合的方式,分析了2016年12月影响中国中东部地区的一次重污染过程中PM_(2.5)时空分布特征及来源成因。结果表明,重污染过程中PM_(2.5)具有较明显的时空变化规律,污染呈现一定程度的区域性分布特点,不同地理位置条件下,污染物浓度的累积和传输方式表现出不同的特征,细颗粒物快速二次生成及不利扩散条件下的持续积累可能是此次污染过程的主要原因,不利于污染物扩散的高低空天气形势的配合抑制了污染物的快速消散,为大气污染的形成及维持提供了稳定的大气环境背景,形成了此次污染过程污染浓度高、影响范围大的态势。