Development of a software package for trend detection in temporal series: Application to water and industrial effluent quality data for the St. Lawrence River

Despite the considerable amount of effort and resources involved in monitoring water quality, water quality assessment and environmental follow-up are sometimes carried out with simple statistics, the main reason being the lack of appropriate statistical methods adapted to the nature of sampled water quality data.A survey of the classical methods used for trend detection and of their limitations is first presented, including the most recent non-parametric techniques adapted to the structure of the sampled data and to the possible types of trends occuring. This paper then presents an interactive user-friendly software package developed for microcomputers making use of these latest adapted techniques. Afterwards, some applications of the software are described pertaining to the concentrations measured at long-term stations on the St. Lawrence River and to the mass loadings discharged by regulated industries. Finally, conclusions are drawn about the assumptions, performance and limitations of the package as well as about the research needs to improve the usefulness and applicability of the software.     

Robust graphical methods for diagnosing trend in irregularly spaced water quality time series

Graphical methods can play an important role in the reliable assessment of trends in typically ill behaved river quality data series both as diagnostic tools and as visual corroborative evidence when assumptions required for formal statistical tests are not met. Robust, graphically-oriented trend diagnosis procedures are presented for data series characterized by nonnormal populations, uneven time spacing, nonmonotonic trend and other factors which can create serious problems for standard parametric time series methods. Cleveland's robust locally weighted regression (RLWR) developed for investigating nonlinearity in x-y scatterplots is adapted as a robust/resistant smoothing filter for the analysis of irregular time series comprising quantitative observations. Low powered RLWR trend lines reveal temporally local phenomena, e.g. abrupt jumps (often associated with point source impacts) and periodicities, while higher powered RLWR yields smooth lines characterizing medium and longer term trends. Simple variants of Tukey smoothing concepts are developed for series with censored observations. Applications to Ontario river quality series reveal that graphical evidence is frequently sufficient to obviate the need for formal trend testing. The methods are generally applicable to most time series.     

Assessment of benthic changes during 20 years of monitoring the Mexican Salina Cruz Bay

In this work a non-parametric multivariate analysis was used to assess the impact of metals and organic compounds in the macro infaunal component of the mollusks benthic community using surface sediment data from several monitoring programs collected over 20 years in Salina Cruz Bay, Mexico. The data for benthic mollusks community characteristics (richness, abundance and diversity) were linked to multivariate environmental patterns, using the Alternating Conditional Expectations method to correlate the biological measurements of the mollusk community with the physicochemical properties of water and sediments. Mollusks community variation is related to environmental characteristics as well as lead content. Surface deposit feeders are increasing their relative density, while subsurface deposit feeders are decreasing with respect to time, these last are expected to be more related with sediment and more affected then by its quality. However gastropods with predatory carnivore as well as chemosymbiotic deposit feeder bivalves have maintained their relative densities along time.     

Spectral trend of vegetation with rainfall in events of El Niño-Southern Oscillation for Atlantic Forest biome,Brazil

This study aimed to analyze the spectral trend of vegetation with rainfall in El Niño-Southern Oscillation events (ENSO) in the Atlantic Forest, Brazil. Monthly rainfall data were collected from 85 conventional meteorological stations (EMC), data from the Enhanced Vegetation Index 2 (EVI2) and ENSO events (El Niño, La Niña, and Neutral) in the period from 2001 to 2013. Afterwards, state cluster analysis was performed using the results of non-parametric tests. The Mann-Kendall (MK) non-parametric test did not identify a trend pattern in rainfall distribution in the Atlantic Forest. The results for EVI2 by state and region showed that the trend is decreasing in the Northeast Region, except for the states of Alagoas and Pernambuco. Southeast region showed an increasing trend of EVI2 (except for Rio de Janeiro and São Paulo), while the South region showed a decreasing trend. In the Midwest, the trend was significantly decreasing. In the prognosis elaborated for the future, the regions with significant declines of the vegetation were the Northeast and Midwest. This study shows that the Atlantic Forest in some regions of Brazil has been suffering from the growing urbanization process and there is a trend of soil degradation.     

Marine Eutrophication: A Proposed Data Analysis Procedure For Assessing Spatial Trends

A methodology for the discrimination of the different trophic levels at a spatial scale in the marine environment is proposedusing spatial analysis methods and non-parametric statistics. Phytoplankton cell number, being a representative parameter to express trophic trends in the marine ecosystem is selected forthe methodology development; Saronicos Gulf, Greece is used for the case study. The proposed stepwise methodology includes interpolation for assessing the spatial distribution of phytoplankton cell number, division of the Gulf into a number of quadrates, development of a scale characterising trophic levels and finally characterisation of the trophic state ofeach quadrate using non-parametric statistics. The advantages of this methodology and the potential applications in coastal management studies are also discussed.     

Spatiotemporal trend analysis of recent river water quality conditions in Japan

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.     

Some comments on analysis techniques for censored water quality data

When investigating trace substances in ambient water, a proportion of water sample concentrations is usually below limits of detection. In medical and industrial reliability studies, comparisons are often made of time to event data which includes right censored observations indicating only that an observation is greater than a specified value. In this paper consideration is given to the application of non-parametric procedures, widely used in the analysis of time to event data, to water quality data which is left censored.A non-parametric estimate of the cumulative distribution function for left censored water quality data can be generated quite easily. For the comparison of levels of trace substances it is necessary to combine an unconditional likelihood for the proportion of observations below a detection limit with a partial likelihood for the portion of the distribution above the detection limit in order to make use of regression methodology. The details of this are outlined and an example is given which compares levels of toxic substances at the head and mouth of the Niagara river.When comparisons are based on matched pair data, further modifications are necessary. A development paralleling that for time to event data is given. Consideration is also given to model extensions which allow for a dependence between observations at the same location over a period of time.The presentation is introductory and designed to illustrate the potential of some available methodology for use in the analysis of water quality data.     

中国海域赤潮发生趋势的年际变化

回顾了中国海域的赤潮发生频次等数据的年际变化,尤其是进入21世纪的赤潮发生趋势,以期为赤潮灾害分析和防治提供帮助。数据表明,赤潮问题已不容忽视。总体上,赤潮发生的频次和累计面积呈现增长趋势,尤其是21世纪前10年的赤潮发生频次和规模是20世纪后50年的2倍多。与20世纪不同,东海的赤潮问题最严重,远远超过了南海;而渤海的赤潮规模也明显增加,此2海区成为赤潮的重灾区。赤潮多发生在5、6月份,但有延长的态势,对赤潮监测和预防提出了新的要求。赤潮生物,特别是有毒藻类不断增加,对渔业和人类健康造成威胁。同时也看到,赤潮的发生并非持续上涨,赤潮是可以防治的。     

Long-term seasonal changes of the Danube River eco-chemical status in the region of Serbia

Seasonal spatial and temporal changes of selected eco-chemical parameters in section of the Danube River flowing through Serbia were analyzed. Data for electrical conductivity (EC), dry and suspended matter, residue on ignition, chemical oxygen demand (COD), biochemical oxygen demand (BOD-5), ultraviolet extinction, dissolved oxygen (DO), oxygen saturation, pH, nitrates, total phosphorus, and nitrogen were collected between 1992 and 2006. The use of monthly medians combined with linear regression and two-sided t test has been proven to be the best approach for resolving trends from natural variability of investigated parameters and for determining trend significance. Patterns of temporal changes between different months were examined. It was also determined that spatial trends of some parameters oscillate in predictable manner, increasing in one part of the year and declining in the other. Regression slope coefficients, an excellent indicator for determining when the water quality is changing the most along the course of the Danube, reach their maximum during summer for temperature (t), electric conductivity, nitrates, and total N, while in the same season suspended matter, COD, BOD-5, DO, and oxygen saturation coefficients reach their minimum. Correlations for used data sets of selected parameters were analyzed for better understanding of their behavior and mutual relations. It was observed that as Danube flows through Serbia, its general eco-chemical status either stagnates or improves, but the rate of river self-purification often depends on the season of the year.     

Measurement of biochemical oxygen demand of the leachates

Biochemical oxygen demand (BOD) of the leachates originally from the different types of landfill sites was studied based on the data measured using the two manometric methods. The measurements of BOD using the dilution method were carried out to assess the typical physicochemical and biological characteristics of the leachates together with some other parameters. The linear regression analysis was used to predict rate constants for biochemical reactions and ultimate BOD values of the different leachates. The rate of a biochemical reaction implicated in microbial biodegradation of pollutants depends on the leachate characteristics, mass of contaminant in the leachate, and nature of the leachate. Character of leachate samples for BOD analysis of using the different methods may differ significantly during the experimental period, resulting in different BOD values. This work intends to verify effect of the different dilutions for the manometric method tests on the BOD concentrations of the leachate samples to contribute to the assessment of reaction rate and microbial consumption of oxygen.     

Assessment of temporal and spatial water quality in international Gomishan Lagoon,Iran, using multivariate analysis

Coastal lagoon ecosystems are vulnerable to eutrophication, which leads to the accumulation of nutrients from the surrounding watershed over the long term. However, there is a lack of information about methods that could accurate quantify this problem in rapidly developed countries. Therefore, various statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least square (PLS), principal component regression (PCR), and ordinary least squares regression (OLS) were used in this study to estimate total organic matter content in sediments (TOM) using other parameters such as temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), nitrite (NO₂), nitrate (NO₃), biological oxygen demand (BOD), phosphate (PO₄), total phosphorus (TP), salinity, and water depth along a 3-km transect in the Gomishan Lagoon (Iran). Results indicated that nutrient concentration and the dissolved oxygen gradient were the most significant parameters in the lagoon water quality heterogeneity. Additionally, anoxia at the bottom of the lagoon in sediments and re-suspension of the sediments were the main factors affecting internal nutrient loading. To validate the models, R², RMSECV, and RPDCV were used. The PLS model was stronger than the other models. Also, classification analysis of the Gomishan Lagoon identified two hydrological zones: (i) a North Zone characterized by higher water exchange, higher dissolved oxygen and lower salinity and nutrients, and (ii) a Central and South Zone with high residence time, higher nutrient concentrations, lower dissolved oxygen, and higher salinity. A recommendation for the management of coastal lagoons, specifically the Gomishan Lagoon, to decrease or eliminate nutrient loadings is discussed and should be transferred to policy makers, the scientific community, and local inhabitants.     

季节性Kendall检验分析湘江长沙段水质变化趋势

季节性Kendall检验是一种广泛应用于河流水质变化趋势分析的非参数检验。以湘江长沙段三汊矶断面2001—2011年水质监测结果为样本,运用季节性Kendall检验分析湘江长沙段水质变化趋势及影响因素,结果表明:氨氮浓度呈显著上升趋势,总磷浓度呈高度显著上升趋势,总镉、总砷浓度呈高度显著下降趋势,湘江长沙段水质主要受城市生活、工业和农业面源污染物排放的影响,河水流量对水质的影响相对较小。     

Contamination of Oxygen-Consuming Organics in the Yellow River of China

Contamination of oxygen-consuming organics (OCOs) was one of the most serious problems in the Yellow River of China. This study was conducted to analyze monitoring of the data on OCOs contamination for the river in 1980 and during 1992–1999 as well as examining the effect of suspended solids (SS) on chemical oxygen demand (COD_Mn) and biochemical oxygen demand (BOD₅) of river water. Several significant results have arisen from the study. First, COD_Mn and BOD₅ of the river water showed an increasing trend from the upper to the lower reaches of the mainstream. BOD₅ values of river water in 1992 were significantly higher than those in 1980 and showed an increasing trend during 1992–1999. Second, OCOs in river water of the mainstream was attributed mainly to point sources; the ratio of point to non-point sources of BOD₅ was about 2.81. The load from point sources showed an increasing trend during 1992–1998. In contrast, the load from non-point sources manifested a decreasing trend during this period; this was caused by the decreasing trend of SS content in river water. The total load of BOD₅ from point and non-point sources displayed an increasing trend during 1992–1998. Third, as the humic substances in SS can hardly be biologically oxidized in natural conditions but can be oxidized by chemical oxidants such as potassium permanganate, COD_Mn was not suitable for being regarded as a parameter reflecting the pollution degree of OCOs in river water with a high SS content.     

Trend evaluation of water quality parameters in the Niagara and St. Lawrence Rivers

Physical and chemical (nutrients and major ions) indicators of water quality monitored by Environment Canada between 1977 and 1987 in the Niagara River at Niagara-on-the-Lake and in the St. Lawrence River at Wolfe Island are analyzed for seasonal and annual variations. Parametric methods such as moving averages and linear regression and nonparametric methods (Spearman's rank coefficient) are used to test for the existence of trends in these data. The results indicate that specific conductivity, sodium and chloride have decreased significantly over the period of study. During the same period there is no significant trend for either discharge and nutrients.     

Methods for determination of elemental carbon in ambient air

A few analytical methods of elemental carbon determination are described. The purpose of the work is to choose the best method for determination of its content in dust suspended in air in industrial regions. The reflectance and chromatographic methods were investigated. It was shown that the reflectance methods could be used only when the particle size and form of elemental carbons constant. The chromatographic method, which includes the step of combustion of the sample in oxygen and chromatographic determination of evolved CO₂ is recommended, since it is independent of the form of carbon. Organic carbon is removed from dust samples by extraction with benzene-methanol mixture.     

Statistical trends in ground-water monitoring data at a landfill Superfund site: A case study

This paper describes the use of statistical regression models to characterize temporal trends in groundwater monitoring data collected between 1980 and 1990 on 15 wells and 13 parameters (195 cases in all) at the KL Avenue landfill site in Kalamazoo County, Michigan. This site was used as a municipal landfill prior to 1980, then was placed on the Superfund site list in 1982 after ground-water contamination was found.Six temporal regression trend models were defined using linear and quadratic regression models. These trends were used to classify each of the 195 cases as: improving, deteriorating, or stable over the 1980–1990 time period. Using these classifications it was determined that there were more than twice as many improving cases as deteriorating conditions at the KL site during this time period. These models provide a method for visualizing and interpreting trends in ground-water quality at individual well locations within the contaminant plume and for assessing the chemical trend behavior of the overall plume. The improving, deteriorating, and stable trend categories were developed for two purposes. The first purpose is to facilitate comprehension of information contained in large amounts of water quality data. The second is to assist communication among the many different groups of people who recommend actions, including remediation responsibilities at Superfund sites, like the KL site.A normal probability model was used in the trend classifications. This model contained provisions to accommodate nondetect data and other abnormal laboratory determinations which can influence the trend selection process. The robustness of this classification procedure was examined using a lognormal probability model. The overall conclusions about the KL site using the lognormal model were similar to those obtained using the normal model. However, some individual trend indications were different using the lognormal model. The Shapiro-Wilk test was used to check the adequacy of both the normal and lognormal models. The lognormal model was found to be a somewhat more adequate model for fitting the KL site data, but was not found to be superior to the normal model for each case.The normal and lognormal models were both found to be suitable for determining overall trend conditions at this site. Both models are recommended for these purposes assuming an understanding of the statistical constraints and hydrochemical context. However, it is recommended that the search for more adequate trend models continues.     

New insight into defining the lakes of the southern Baltic coastal zone

There exist many classification systems of hydrographic entities such as lakes found along the coastlines of seas and oceans. Each system has its advantages and can be used with some success in the area of protection and management. This paper aims to evaluate whether the studied lakes are only coastal lakes or rather bodies of water of a completely different hydrological and hydrochemical nature. The attempt to create a new classification system of Polish coastal lakes is related to the incompleteness of lake information in existing classifications. Thus far, the most frequently used are classifications based solely on lake basin morphogenesis or hydrochemical properties. The classifications in this paper are based not only on the magnitude of lake water salinity or hydrochemical analysis but also on isolation from the Baltic Sea and other sources of water. The key element of the new classification system for coastal bodies of water is a departure from the existing system used to classify lakes in Poland and the introduction of ion-“tracking” methods designed to identify anion and cation distributions in each body of water of interest. As a result of the work, a new classification of lakes of the southern Baltic Sea coastal zone was created. Featured objects such as permanently brackish lakes, brackish lakes that may turn into freshwater lakes from time to time, freshwater lakes that may turn into brackish lakes from time to time, freshwater lakes that experience low levels of salinity due to specific incidents, and permanently freshwater lakes. The authors have adopted 200 mg Cl^? dm^?3 as a maximum value of lake water salinity. There are many conditions that determine the membership of a lake to a particular group, but the most important is the isolation lakes from the Baltic Sea. Changing a condition may change the classification of a lake.     

Scaling the trophic index (TRIX) in oligotrophic marine environments

The TRIX index used for the assessment of trophic status of coastal waters has been applied in many European seas (Adriatic, Tyrrhenian, Baltic, Black Sea, and North Sea). However, all these waters are characterized by high nutrient levels and phytoplankton biomass; index calibration based on systems that are principally eutrophic may introduce bias to the index scaling. In the present work the TRIX trophic index is evaluated using three standard sets of data characterizing oligotrophy, mesotrophy, and eutrophication in the Aegean (Eastern Mediterranean) marine environment. A natural eutrophication scale based on the TRIX index that is suitable to characterize trophic conditions in oligotrophic Mediterranean water bodies is proposed. This scale was developed into a five-grade water quality classification scheme describing different levels of eutrophication. It is questionable whether this index can form a universal index of eutrophication or the scaling of TRIX should be region specific.     

Multivariate analyses of the effect of an urban wastewater treatment plant on spatial and temporal variation of water quality and nutrient distribution of a tropical mid-order river

Freshwater resources are increasingly scarce due to human activities, and the understanding of water quality variations at different spatial and temporal scales is necessary for adequate management. Here, we analyze the hypotheses that (1) the presence of a wastewater treatment plant (WWTP) and (2) a polluted tributary that drains downstream from the WWTP change the spatial patterns of physicochemical variables (pH, turbidity, dissolved oxygen, and electrical conductivity) and nutrient concentrations (reactive soluble phosphorus, total phosphorus, nitrogen series, total nitrogen, and total dissolved carbon) along a mid-order river in SE Brazil and that these effects depend on rainfall regime. Six study sites were sampled along almost 4 years to evaluate the impacts of human activities, including sites upstream (1–3) and downstream (5–6) from the WWTP. The impacts were observed presenting an increasing trend from the source (site 1) towards Água Quente stream (site 4, the polluted tributary), with signs of attenuation at site 5 (downstream from both WWTP and site 4) and the river mouth (site 6). Input of nutrients by rural and urban runoff was observed mainly at sites 2 and 3, respectively. At sites 4 and 5, the inputs of both untreated and treated wastewaters increased nutrient concentrations and changed physicochemical variables, with significant impacts to Monjolinho River. Seasonal variations in the measured values were also observed, in agreement with the pluviometric indexes of the region. Univariate analyses suggested no effect of the WWTP for most variables, with continued impacts at sites downstream, but non-parametric multivariate analysis indicated that these sites were recovering to chemical characteristics similar to upstream sites, apparently due to autodepuration. Therefore, multivariate methods that allow rigorous tests of multifactor hypotheses can greatly contribute to determine effects of both point and non-point sources in river systems, thus contributing to freshwater monitoring and management.     

湘江流域永州段水质和水文气象因素变化规律及其相关分析

为推进湘江流域永州段水资源保护,加强水质预测,利用2014—2018年冷水滩断面水文气象和水质监测数据,基于相关分析、主成分分析等多元统计方法,研究分析了湘江冷水滩断面水质、水文气象因素变化规律以及两者的相关关系、量化关系。结果表明:该地区水文气象因素对水质影响最大,水质与水文气象因素之间的相关关系显著,水文气象因素是影响湘江流域水质的重要因素;溶解氧与水温、降水量呈线性回归关系,高锰酸盐指数与水位呈线性回归关系,高锰酸盐指数拟合回归方程的精度略低于溶解氧拟合回归方程。