洪泽湖渔业水质监测点位优化布设

基于2001—2011年洪泽湖水质溶解氧、高锰酸盐指数、总氮、氨氮和总磷长期定位监测数据,采用物元分析法研究洪泽湖渔业水质监测站位的优化布设。结果表明,用物元分析法将原来的21个监测站位优化为14个,监测点位优化后对监测结果无明显影响。     

秦淮河水质监测点位的优化

采用模糊数学“最大树”聚类分析法,对秦淮河水系的监测点位进行了优化.检验证明,经优化组合不仅保留了具有不同功能的监测点位,而且能够较好地反映秦淮河水质状况,其结果是令人满意的.     

入太湖河道大型底栖动物群落结构及水质生物学评价

于2020年9月在太滆运河、漕桥河、徐家大塘和竺山湾布设14个监测点位，调查入太湖河道底栖动物群落结构，并采用Goodnight修正指数（GBI）、生物学污染指数（BPI）和多样性指数（H）进行水质生物学评价。结果表明，研究区域共检出底栖动物6纲18种，霍甫水丝蚓（Limnodrilus hoffmeisteri）和中国长足摇蚊（Tanypus chinensis）为优势种，生物多样性由高到低为竺山湾（H=1.20）＞徐家大塘（H=1.09）＞太滆运河（H=0.67）＞漕桥河（H=0.33）。典范对应分析显示，总氮、正磷酸盐等因子与寡毛类生物量呈正相关，叶绿素a、IMn与摇蚊幼虫生物量呈正相关。生物学评价表明，太滆运河处于中重度污染状态，漕桥河、徐家大塘和竺山湾处于中度污染状态。     

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。     

应用水质标识指数法评价太湖湖滨带水质

以2009年12月和2010年4、8月的全太湖湖滨带水质监测数据为基础,以TN、TP、NH₃-N、COD_Mn、DO为评价指标,采用水质标识指数评价法对太湖湖滨带水质进行评价。水质指标基本信息显示,NH₃-N冬季、春季空间变异较大,TP夏季空间变异较大;单因子标识指数评价结果显示,太湖湖滨带水体水质因子污染风险时空差异显著,TN冬季、春季全区域污染风险均较大,NH₃-N冬季和夏季在竺山湾、西部沿岸区域污染风险较大,TP三季在竺山湾、西部沿岸区域污染风险较大;综合标识指数评价结果显示,东太湖、东部沿岸、贡湖区域水质较好,为Ⅲ类水,竺山湾和西部沿岸水体水质最差,为Ⅴ类水,且竺山湾和西部沿岸水体三季均处于重度污染状态。该研究可为太湖湖滨带水环境的生态恢复和标识指数应用的推广提供一定的科学依据。     

基于灰色聚类方法的湖泊营养状态综合评价

将湖泊水体的营养状态看作一个灰色系统，建立用于识别湖泊营养状态属性的灰色聚类综合评价模型，将水质级别作为一个灰类，水质状态作为灰色变量，根据灰色白化权函数聚类方法来确定水体营养状况归类。以太湖为例，基于分布全湖的20个监测点数据，运用灰色聚类法对其进行富营养状态综合评价，结果表明，监测时段太湖大部分水体基本处于中营养水平，局部湖面达到中度富营养状态，客观地反映了太湖湖区水体营养状况。     

登沙河流域水质监测断面优化研究

基于大连市登沙河监测断面的水质数据,采用系统聚类法、模糊聚类法和物元分析法进行优化,筛选代表性断面。结果表明,优化后的监测断面个数减少了40%,相关性较高的相邻断面个数由优化前的71%减少为54%,优化前、后的样本方差齐且均值无显著性差异。优化后的监测断面在显著提高效率的同时也确保了数据的代表性,使得断面重复布设情况得到明显改善。     

模糊数学在大气优化布点方面的应用

本文采用最大最小法标定、求传递闭包、动态聚类等聚类分析法;用贴近度及择近原则的优选方法进行优化布点;并经三种不同方法检验,证明四个监测点完全能代表原设九个点。     

改进的模糊综合评价法在某煤矿区水质评价中的应用

基于熵权法和相对标准偏差法组合评价因子权重，综合最大隶属度原则与加权平均原则，建立改进的模糊综合评价法，应用该方法评价某煤矿区浅层地下水水质，并与其他评价方法作比较。结果表明：在研究区33个浅层地下水监测点中，属于Ⅰ类、Ⅱ类、Ⅲ类水的监测点分别有4个、16个、13个，Ⅱ类水最多，占比48.5%，无Ⅳ类、Ⅴ类水，水质状况总体较好；对比发现，工业园水质相对较差，煤矿区及工业广场次之，农田和居民区水质相对较好；改进后的模糊综合评价法综合考虑了评价因子间的内在联系，既减小了主观因素对评价过程的影响，也规避了单一评判原则对水质等级判定带来的局限性，评价结果更符合实际情况。     

几种土壤质量评价方法的比较

分别用Ｔ值分级法，综合指数法，模糊数学综合评判法，灰色聚类法，等斜率灰色聚类法，宽域灰色聚类法对湖南某地１０个监测点的土壤质量现状进行评价，通过比较，认为宽域灰色聚类法较好。     

太湖蓝藻水华时空分布与预警监测响应的分析

选择2007和2008年200幅EOS/MODIS太湖蓝藻监测遥感影像,统计分析了梅梁湾、竺山湾宜兴段、贡湖湾、东太湖胥口湾和湖州方向湖体蓝藻水华爆发的空间和时间分布规律。并在得出全太湖蓝藻水华空间和时间分布规律的基础上,从环境监测部门蓝藻预警监测工作的实际出发,将蓝藻水华预警监测的响应划分为常规监测和应急监测,提出了具体的监测要求,为环太湖地区的相关部门更好地开展蓝藻预警监测工作提供了科学依据。     

长江南京段水质自动监测点位优化

简述了长江南京段监测断面现状，用相关分析与聚类分析方法对水质监测数据进行了统计分析，对长江南京段水质自动监测优化布点提出了相关建议。     

太湖湖滨带浮游植物群落特征及指示种筛选

针对太湖湖滨带,均匀布设49个点位,分别于2009年12月、2010年4、8月开展浮游植物及水质监测。结果显示,湖滨带浮游植物群落多样性整体较低,优势种从枯水期到丰水期呈"鱼腥藻-鱼腥藻-微囊藻"的演变趋势;西北部湖区(竺山湖、梅梁湾、西部沿岸)浮游植物密度明显高于东南部湖区(东部沿岸、东太湖、南部沿岸);湖滨带浮游植物群落结构与湖体相似,密度比湖体高1个数量级;RDA排序筛选出在显著水平上解释浮游植物分布的最小变量组合为TN、CODMn、SS、p H、SD,且方差分解指出TN是相对最重要的变量;当物种适合度为50%~100%时,与TN具有较好梯度响应关系的是四尾栅藻及弓型藻,并且这2个种与TN、TP及综合营养状态指数的组合变量也有较好的梯度响应关系,具备指示太湖湖滨带富营养化的可能,但定量指示意义尚待进一步研究。     

Analysis of long-term water quality for effective river health monitoring in peri-urban landscapes—a case study of the Hawkesbury–Nepean river system in NSW, Australia

The Hawkesbury–Nepean River (HNR) system in South-Eastern Australia is the main source of water supply for the Sydney Metropolitan area and is one of the more complex river systems due to the influence of urbanisation and other activities in the peri-urban landscape through which it flows. The long-term monitoring of river water quality is likely to suffer from data gaps due to funding cuts, changes in priority and related reasons. Nevertheless, we need to assess river health based on the available information. In this study, we demonstrated how the Factor Analysis (FA), Hierarchical Agglomerative Cluster Analysis (HACA) and Trend Analysis (TA) can be applied to evaluate long-term historic data sets. Six water quality parameters, viz., temperature, chlorophyll-a, dissolved oxygen, oxides of nitrogen, suspended solids and reactive silicates, measured at weekly intervals between 1985 and 2008 at 12 monitoring stations located along the 300 km length of the HNR system were evaluated to understand the human and natural influences on the river system in a peri-urban landscape. The application of FA extracted three latent factors which explained more than 70 % of the total variance of the data and related to the ‘bio-geographical’, ‘natural’ and ‘nutrient pollutant’ dimensions of the HNR system. The bio-geographical and nutrient pollution factors more likely related to the direct influence of changes and activities of peri-urban natures and accounted for approximately 50 % of variability in water quality. The application of HACA indicated two major clusters representing clean and polluted zones of the river. On the spatial scale, one cluster was represented by the upper and lower sections of the river (clean zone) and accounted for approximately 158 km of the river. The other cluster was represented by the middle section (polluted zone) with a length of approximately 98 km. Trend Analysis indicated how the point sources influence river water quality on spatio-temporal scales, taking into account the various effects of nutrient and other pollutant loads from sewerage effluents, agriculture and other point and non-point sources along the river and major tributaries of the HNR. Over the past 26 years, water temperature has significantly increased while suspended solids have significantly decreased (p?<?0.05). The analysis of water quality data through FA, HACA and TA helped to characterise the key sections and cluster the key water quality variables of the HNR system. The insights gained from this study have the potential to improve the effectiveness of river health-monitoring programs in terms of cost, time and effort, particularly in a peri-urban context.     

美国地表水环境监测管理体系及对我国的启示

简述了美国地表水监测管理体系,指出其健全的环境监测体系、完善的标准体系以及充分的信息公开和数据共享是保障水环境质量的基石、关键和枢纽。结合我国水环境监测管理的现状,提出,应加强水环境质量监测的立法工作,进一步完善水污染物排污许可证制度,建立以水环境质量为目标的水环境管理制度体系,进一步加大监测信息公开和数据共享力度,修订更适合我国的水环境质量监测指标。     

Identification of spatiotemporal nutrient patterns in a coastal bay via an integrated k-means clustering and gravity model

This study presents an integrated k-means clustering and gravity model (IKCGM) for investigating the spatiotemporal patterns of nutrient and associated dissolved oxygen levels in Tampa Bay, Florida. By using a k-means clustering analysis to first partition the nutrient data into a user-specified number of subsets, it is possible to discover the spatiotemporal patterns of nutrient distribution in the bay and capture the inherent linkages of hydrodynamic and biogeochemical features. Such patterns may then be combined with a gravity model to link the nutrient source contribution from each coastal watershed to the generated clusters in the bay to aid in the source proportion analysis for environmental management. The clustering analysis was carried out based on 1 year (2008) water quality data composed of 55 sample stations throughout Tampa Bay collected by the Environmental Protection Commission of Hillsborough County. In addition, hydrological and river water quality data of the same year were acquired from the United States Geological Survey's National Water Information System to support the gravity modeling analysis. The results show that the k-means model with 8 clusters is the optimal choice, in which cluster 2 at Lower Tampa Bay had the minimum values of total nitrogen (TN) concentrations, chlorophyll a (Chl-a) concentrations, and ocean color values in every season as well as the minimum concentration of total phosphorus (TP) in three consecutive seasons in 2008. The datasets indicate that Lower Tampa Bay is an area with limited nutrient input throughout the year. Cluster 5, located in Middle Tampa Bay, displayed elevated TN concentrations, ocean color values, and Chl-a concentrations, suggesting that high values of colored dissolved organic matter are linked with some nutrient sources. The data presented by the gravity modeling analysis indicate that the Alafia River Basin is the major contributor of nutrients in terms of both TP and TN values in all seasons. With this new integration, improvements for environmental monitoring and assessment were achieved to advance our understanding of sea-land interactions and nutrient cycling in a critical coastal bay, the Gulf of Mexico.     

Spatial distribution and temporal variation of chemical properties of drainage watercourses in rural and peri-urban areas of Novi Sad (Serbia)—a case study

Waters are among to the most vulnerable environmental resources exposed to the impact of various point and non-point pollutants from rural/urban activities. Systematic and long-term monitoring of hydro-resources is therefore of crucial importance for sustainable water management, although such practice is lacking across many (agro-)hydro-ecosystems. In the presented study, for the first time, the spatial distribution (covering almost 9000 ha) and temporal variation (2006–2013) in certain quality parameters was characterized in drainage watercourses Tatarnica and Subic, whose catchment is rural and suburban areas close to the city of Novi Sad, Republic of Serbia. Based on majority of observed parameters, both watercourses belonged to I and II water quality classes, with occasional presence of certain parameters (e.g., suspended solids, total phosphorus; ammonium) at extreme values exacerbating both watercourses to classes IV and V. The value of the synthetic pollution index (i.e., a combined effect of all considered parameters) showed a higher degree of water pollution in watercourse Subic (on average 2.00) than Tatarnica (on average 0.72). Also, cluster analysis for watercourse Tatarnica detected two groups of parameters (mostly related to nutrients and organic matter), indicating more complex impacts on water quality during the observed period, in which elucidation thus established water quality monitoring program would be of great importance.     

洮滆水系湖库富营养化生态风险的特点与比较

茅东水库、长荡湖、涌湖、太湖竺山湾是洮滆水系从上游到下游排列的4大典型湖库,2008年的监测分析表明,氮、磷是该水系湖库富营养化的主要污染因子,并沿流域呈加剧趋势,上下游TP质量浓度为0.081～0.296 mg/L,差异小,而TN质量浓度为0.314～5.67 mg/L,差异大,长荡湖到涌湖是洮滆水系首要污染物TN快...     

农业面源污染对我国农村地表水的影响与对策研究

基于2015—2021年我国农村地表水环境质量监测数据,分析了农村地表水环境质量状况特征;选取农业农村社会经济活动相关参数,与农村地表水中主要超标因子的超标比例进行了相关性分析;以2020年为基准年,对全国31个行政区,涵盖农村地表水水质状况、农业农村活动水平和污染压力、环境容量3个方面的9个指标进行了聚类分析。结果表明,我国农村地表水的变化趋势、季节特点和主要超标因子等表现出明显的农业面源污染特征;乡村人口、农业投入品使用量和经济作物种植比例等参数与主要超标指标具有较强的相关性（R＞0.9）;聚类分析将全国31个行政区划分为7种不同的农业面源污染类型。提出,应根据不同地区农业面源污染特点,因地制宜地推进标准化规模养殖、畜禽粪污资源化利用、化肥减量行动、高效低风险农药推广等农业面源污染治理措施,进一步加大农村生活污水处理设施建设,同时,完善农村环境质量监测网络,加强农业面源污染监测和评估。