Assessment of the water quality and identification of pollution sources of Kaduna River in Niger State (Nigeria) using exploratory data analysis

Exploratory data analysis such as hierarchical cluster analysis and principal component analysis were applied to water quality dataset of the Kaduna River, obtained during 3 years (2008–2010), monthly monitoring of eight key different sampling sites for 19 parameters to extract correlations and similarities between variables and to classify river sampling sites in groups of similar quality. Hierarchical cluster analysis grouped eight sampling sites into three statistically significant clusters of similar water composition. Six varifactors were obtained after varimax rotation of initial principal components using principal component analysis. These techniques gave an insight into the sources of pollution. Anthropogenic influence (municipal, industrial wastewater and agricultural run‐off) was the major source of river water pollution.     

再生水水质综合评价的主成分分析方法

采用主成分分析方法评价再生水综合水质,利用R软件强大的统计功能,对某再生水厂供水实测数据进行了定量化评价。结果表明,主成分分析方法是一种切实可行的水质综合评价方法,值得进一步研究,并能为其他相关行业的质量评价提供参考。     

Assessment of seasonal variations in surface water quality

Assessment of seasonal changes in surface water quality is an important aspect for evaluating temporal variations of river pollution due to natural or anthropogenic inputs of point and non-point sources. In this study, surface water quality data for 16 physical and chemical parameters collected from 22 monitoring stations in a river during the years from 1998 to 2001 were analyzed. The principal component analysis technique was employed to evaluate the seasonal correlations of water quality parameters, while the principal factor analysis technique was used to extract the parameters that are most important in assessing seasonal variations of river water quality. Analysis shows that a parameter that is most important in contributing to water quality variation for one season may not be important for another season except for DOC and electrical conductance, which were always the most important parameters in contributing to water quality variations for all four seasons.     

Evaluation of river water quality monitoring stations by principal component analysis

The development of a surface water monitoring network is a critical element in the assessment, restoration, and protection of stream water quality. This study applied principal component analysis (PCA) and principal factor analysis (PFA) techniques to evaluate the effectiveness of the surface water quality-monitoring network in a river where the evaluated variables are monitoring stations. The objective was to identify monitoring stations that are important in assessing annual variations of river water quality. Twenty-two stations used for monitoring physical, chemical, and biological parameters, located at the main stem of the lower St. Johns River in Florida, USA, were selected for the purpose of this study. Results show that 3 monitoring stations were identified as less important in explaining the annual variance of the data set, and therefore could be the non-principal stations. In addition, the PFA technique was also employed to identify important water quality parameters. Results reveal that total organic carbon, dissolved organic carbon, total nitrogen, dissolved nitrate and nitrite, orthophosphate, alkalinity, salinity, Mg, and Ca were the parameters that are most important in assessing variations of water quality in the river. This study suggests that PCA and PFA techniques are useful tools for identification of important surface water quality monitoring stations and parameters.     

基于主成分分析和综合指数法的饮用水水源地水质评价

将主成分分析和综合指数评价法相结合,对绵阳市饮用水水源地的水质现状进行了评价。结果表明,2006--2010年饮用水水源地水质呈下降趋势,特别是2010年水质污染程度严重,主成分载荷值最大者为BOD5,重金属汞的单因子指数为2,无法满足II级水源地（III类地表水）标准要求,并根据水质污染现状,提出了相应的保护水源地水质的措施。     

Analysis of long-term and seasonal river water quality changes in Latvia

An analysis of long-term historical records of the concentrations of major ions, TDS and nutrients for 20 river sites in Latvia is reported. Periods of water quality observations ranged from 15 to 43 years. A study of the quarterly adjusted time series showed that characteristic features of the data are non-normal distributions, seasonality, serial correlation and presence of significant trends that are mostly positive. The application of state-of-the-art software, based on non-parametric statistics such as the Seasonal Kendall slope estimator and the Seasonal Hodges-Lehmann estimator, made it possible to investigate these water quality records more accurately than other methods allow.Typical seasonal variations and concentration-discharge relationships were analyzed for different constituents. It was shown that fertilizer application and marsh land reclamation can cause widespread and intensive river water quality changes. Concentration increases of as much as 5–10 times that of background values were detected for NO₃⁻, Cl⁻, Na⁺ + K⁺ and SO₄²⁻. The main water quality changes took place in the 1960s and the early 1970s when fertilizer applications and reclamation works increased. After that, concentration increases for constituents other than NO₃⁻ and SO₄²⁻ were statistically insignficiant. The significant increases for NO₃⁻ and SO₄²⁻ were probably due to the additional impact of increased atmospheric deposition. The results of long-term changes of river loads entering the Baltic Sea and the Gulf of Riga from Latvian territory are examined.     

Empirical evaluation of river basin sustainability affected by inter‐basin water transfer using composite indicators

In this study, a practical approach to evaluate the sustainability of river basins subjected to an inter‐basin water transfer project is developed. Selection of appropriate evaluation indicators is pivotal to such approach. To make use of huge amount of data, composite indicators of sustainability (CIS) should be utilised. The proposed approach relies on 15 sustainability indicators (SI) that cover three major criteria namely (economic, social and environmental), and aggregates them into eight different types of sustainability indices for a more robust outcome. Two scenarios were considered within the source and recipient basins. Furthermore, multivariate principal component analysis (PCA) was applied to determine principal and non‐principal indicators for the two river basins. The ability of CIS and PCA methods were verified via correlation and simple regression methods respectively. The results demonstrated that inter‐basin water transfer may improve sustainability, provided that a proper water resource management is enforced.     

应用综合水质指数法评价沙澧河漯河段的水质

以沙澧河漯河段3个断面2006-2009年的水质监测数据为基础,应用综合水质指数法,对沙澧河漯河段水质状况进行了分析与评价.将参与评价的项目分为3类:对人体危害严重且难以消除的污染物(第一类)、处理后容易达标的污染物(第二类)、其他污染物(第三类).评价结果表明,澧河水质优良并保持相对稳定;沙河水质稍差,但由尚好逐渐向...     

Assessment of the surface water quality in Northern Greece

The application of different multivariate statistical approaches for the interpretation of a large and complex data matrix obtained during a monitoring program of surface waters in Northern Greece is presented in this study. The dataset consists of analytical results from a 3-yr survey conducted in the major river systems (Aliakmon, Axios, Gallikos, Loudias and Strymon) as well as streams, tributaries and ditches. Twenty-seven parameters have been monitored on 25 key sampling sites on monthly basis (total of 22,350 observations). The dataset was treated using cluster analysis (CA), principal component analysis and multiple regression analysis on principal components. CA showed four different groups of similarity between the sampling sites reflecting the different physicochemical characteristics and pollution levels of the studied water systems. Six latent factors were identified as responsible for the data structure explaining 90% of the total variance of the dataset and are conditionally named organic, nutrient, physicochemical, weathering, soil-leaching and toxic-anthropogenic factors. A multivariate receptor model was also applied for source apportionment estimating the contribution of identified sources to the concentration of the physicochemical parameters. This study presents the necessity and usefulness of multivariate statistical assessment of large and complex databases in order to get better information about the quality of surface water, the design of sampling and analytical protocols and the effective pollution control/management of the surface waters.     

Hydrochemical characteristics and water quality assessment of surface water and groundwater in Songnen plain, Northeast China

Water quality is the critical factor that influence on human health and quantity and quality of grain production in semi-humid and semi-arid area. Songnen plain is one of the grain bases in China, as well as one of the three major distribution regions of soda saline-alkali soil in the world. To assess the water quality, surface water and groundwater were sampled and analyzed by fuzzy membership analysis and multivariate statistics. The surface water were gather into class I, IV and V, while groundwater were grouped as class I, II, III and V by fuzzy membership analysis. The water samples were grouped into four categories according to irrigation water quality assessment diagrams of USDA. Most water samples distributed in category C1-S1, C2-S2 and C3-S3. Three groups were generated from hierarchical cluster analysis. Four principal components were extracted from principal component analysis. The indicators to water quality assessment were Na, HCO₃, NO₃, Fe, Mn and EC from principal component analysis. We conclude that surface water and shallow groundwater are suitable for irrigation, the reservoir and deep groundwater in upstream are the resources for drinking. The water for drinking should remove of the naturally occurring ions of Fe and Mn. The control of sodium and salinity hazard is required for irrigation. The integrated management of surface water and groundwater for drinking and irrigation is to solve the water issues.     

Influence of water and sediment quality on benthic biota in an acidified river

Water and sediment quality and benthic biota were investigated in all seasons during three years in the River Akagawa that receives the effluent from a mine drainage treatment plant at its upstream site. The upper reaches kept the low pH, the comparatively high concentrations of metals and a large amount of iron deposited on the riverbed. The predominant macroinvertebrates were Protonemura sp., Capnidae, Nemoura sp. and Chironomidae in the upper and middle reaches. In the lowest reaches, the community structure of the macroinvertebrate changed into Chironomidae, Trichoptera (Hydropsychidae) and Ephemeroptera (Baetis sp.) as the pH was increased. From the results of multivariate analyses, it was found that the restoration of pH and attached algae and the increase in the concentrations of nutrients and organic matter promoted the inhabitation of Chironomidae and Hydropsychidae, whereas the dissolved metals in the river water inhibited the inhabitation of these families. Moreover, the sedimentation of metals would cause a severe damage to the inhabitation of Hydropsychidae compared with that of Chironomidae.     

基于主成分分析的松花江流域黑龙江段水质评价

对松花江流域黑龙江控制区段13个监测断面不同水期的水质指标进行主成分分析,以鉴别主要的污染源,进而提出有针对性的水污染控制对策。结果表明,BOD5、COD、TP、TN为主要污染指标,合计贡献率为49. 529%,首要污染源为生活污水与农业废水。第二大污染指标主要为石油类、阴离子表面活性剂、氰化物,主要来源于工业废水。总污染最严重的主要是阿什河口内平水期与龙安桥平水期。龙安桥平水期等对应的河流区段受生活污水及农业废水污染较为严重,苗家平水期等对应的河流区段受工业污染较为严重。     

Static-based early-damage detection using symbolic data analysis and unsupervised learning methods

A large amount of researches and studies have been recently performed by applying statistical and machine learning techniques for vibration-based damage detection. However, the global character inherent to the limited number of modal properties issued from operational modal analysis may be not appropriate for early-damage, which has generally a local character. The present paper aims at detecting this type of damage by using static SHM data and by assuming that early-damage produces dead load redistribution. To achieve this objective a data driven strategy is proposed, consisting of the combination of advanced statistical and machine learning methods such as principal component analysis, symbolic data analysis and cluster analysis. From this analysis it was observed that, under the noise levels measured on site, the proposed strategy is able to automatically detect stiffness reduction in stay cables reaching at least 1%.     

主成分分析法识别岩溶多重介质含水系统水化学和水动力特性——以贵州后寨岩溶典型小流域为例

基于主成分分析,以贵州后寨典型岩溶含水系统为例,对该区1995年8月到1996年8月的10个代表性站点的20个变量进行分析,结果表明,前两个主成分综合携带了全部信息的89．3％。从变量的主成分判别平面图上得出第一主成分F1主要由Ca^2＋、SIc（方解石饱和指数）、SId（白云石饱和指数）、HCO3^-、总硬度、Mg^2＋决定,第二主成分F2主要由K^＋＋Na^＋、Cl^-、SO4^2-、HCO3^-,SO4^2-、TOD、水温等决定;水流流经地层的岩性是后寨流域内岩溶含水系统水化学类型和各种水化学参数在空间和时间上变化的主要控制因素,次要因素是地下水的水动力条件特别是地下水的径流深度。水文地球化学信息对地下水系统的水动力特征分析具有指示意义,而主成分分析法耦合水动力和水化学方面的信息,为深入了解岩溶含水系统水动力化学特征提供了一种途径。     

基于主成分-聚类分析法的建筑节能气候区划

通过分析影响建筑冷热耗量的气候指标,提出了以采暖度日数HDD18、空调度日数CDD26、最冷月平均温度、最热月平均温度、冬季太阳辐射热量、夏季太阳辐射热量、冬季含湿量和夏季含湿量8个气候指标作为建筑节能气候区划指标,采用主成分分析与聚类分析相结合的区划方法对我国270个城市进行了建筑节能气候区划,划分为严寒干热高辐区、严寒凉爽高辐区、严寒无夏区、寒冷微热区、温和炎热湿润区、温和凉爽区和阴冷湿热区,介绍了这7个气候区的主要气候特征和主要的地理范围,明确了各区的建筑节能重点和适宜的技术策略。     

Influence of water quality on the presence of off-flavour compounds (geosmin and 2-methylisoborneol)

Geosmin and 2-methylisoborneol are off-flavour compounds related to poor organoleptics and a decrease in consumer satisfaction with drinking water. The relationship between these off-flavour compounds and 39 parameters of water quality (chemical, physical and biological) for three different surface waters from lotic systems that supply potable water to Quebec City and Lévis (Canada) was studied using principal component analysis. The objective of this study was to show that a multidimensional approach with principal component analysis using the component matrix serves to differentiate the processes involved in the appearance of the olfactory compounds from those not involved or little involved and to extract the most representative data of these processes. Our study shows that the presence of geosmin can be explained, in the case of the water studied, by a process associated primarily with the eutrophication of water and, to a lesser degree, by an allochthonous origin. However, the presence of 2-methylisoborneol may be linked to two processes with different origins, but of equal importance: a winter origin – most likely allochthonous – involving anthropic contributions and an autochthonous bacterial origin.     

Influence of temperature and river discharge on water quality of the western scheldt estuary

Dissolved oxygen concentrations and information on the nitrification process collected respectively during a 14- and a 5-year period in the self-purifying part of the Western Scheldt estuary have been studied. In the polluted part of the stream, ammonium concentrations over the period 1967–1977 have been considered as well.This paper demonstrates the high variability of these 3 parameters (oxygen, start of the nitrification process, ammonium) owing to the hydrological conditions: temperature and river discharge.Neither the levels of ammonium in the polluted upper part of the stream, nor the concentrations of nitrate and dissolved oxygen in the recuperation part of the Scheldt estuary have changed significantly during the periods studied (respectively 5, 10 and 14 years). A relation between these parameters and time could be hidden by hydrological factors.Water quality of a stream can be assessed by interpreting oxygen, nitrate, and ammonium concentrations, only if all environmental and hydrodynamical parameters are known simultaneously.     

云龙天池水库季节性蓝绿藻水华成因及其对水质的影响研究

全球变暖背景下湖库发生蓝绿藻水华的成因及其对水质的影响是充满争议的热点环境问题。云龙天池水库是云龙天池国家级自然保护区的主要水源地,开展其水质变化研究具有重要战略意义。本研究利用多参数水质监测浮标系统(AMT—FB301)对该水库开展了连续四个月(2022.1.14—5.11)的高分辨率(时间间隔30 s)蓝绿藻和水质监测工作。结果显示,蓝绿藻在3月早春时节发生水华现象。在月间、月际和日际尺度上,水体中的氨氮含量均与蓝绿藻丰度高度正相关,表明在这类尚未发生明显富营养化的水体中,营养条件仍然是调控蓝绿藻水华发生的最主要因素。突然的升温也可能成为诱发蓝绿藻暴发的关键因素,但充足的营养供应是前提条件。蓝绿藻水华的发生导致了水库的水质明显下降(浊度增加,溶解氧降低)。所以,在未来持续升温背景下,控制外源营养输入仍然是改善这类水库水质和防控蓝绿藻水华发生的最有效途径。     

斑马鱼生物学效应的研究进展及在水质监测中的应用

主要从不同污染物胁迫介绍了斑马鱼的呼吸行为、运动行为、群体行为等行为学效应,以及个体、器官、细胞、分子等多种水平的毒理效应,同时对斑马鱼行为学和毒理效应在水质监测和水环境评价方面的应用做出介绍和展望,得出综合斑马鱼的行为变化和毒理效应两个方面能更准确地表征水体污染类型及污染程度。