SELECTING TREND TESTS FOR WATER QUALITY SERIES WITH SERIAL CORRELATION AND MISSING VALUES1

ABSTRACT: The use of nonparametric tests for monotonic trend has flourished in recent years to support routine water quality data analyses. The validity of an assumption of independent, identically distributed error terms is an important concern in selecting the appropriate nonparametric test, as is the presence of missing values. Decision rules are needed for choosing between alternative tests and for deciding whether and how to pre-process data before trend testing. Several data pre-processing procedures in conjunction with the Mann-Kendall tau and the Seasonal Kendall test (with and without serial correlation correction) are evaluated using synthetic time series with generated serial correlation and missing data. A composite test (pre-testing for serial correlation followed by one of two trend tests) is evaluated and was found to perform satisfactorily.     

NONPARAMETRIC TESTS FOR TREND DETECTION IN WATER QUALITY TIME SERIES1

ABSTRACT: A review of nonparametric tests for trend leads to the conclusion that Mann-Whitney, Spearman, and Kendall tests are the best choice for trend detection in water quality time series. Recently these tests have been adapted to account for dependence and seasonality in such series (Lettenmaier, 1976; Hirsch, et al., 1972; Hirsch and Slack, 1984). For monotonic trends, a procedure allowing to select the pertinent tests considering the characteristics of time series is proposed and the practical limitations of the tests are also brought out. This procedure has been applied to identify the appropriate trend detection test for the time series of nine water quality parameters at Lake Laflamme (Québec). When a time series can be tested with the Mann-Whitney, Kendall, Spearman, or Lettenmaier (1976) test, the number of observations required to detect trends of a given magnitude, for selected significance and power levels can be calculated with the power function of the t test. When the test proposed by Hirsch, et al. (1984), Hirsch and Slack (1984), or Farrell (1980) need to be used, the number of observations can only be estimated approximately from the results of empirical power studies.     

DATA ANALYSIS OF WATER QUALITY TIME SERIES IN LAKE ERIE1

ABSTRACT: A comprehensive data analysis study is carried out for detecting trends and other statistical characteristics in water quality time series measured in Long Point Bay, Lake Erie. In order to glean an optimal amount of useful information from the available data, the exploratory and confirmatory data anslysis stages are adhered to. To test a range of hypotheses regarding the statistical properties of the time series, a wide variety of both parametric and nonparametric techniques are employed. A particularly useful nonparametric method for discovering trends is the seasonal Mann-Kendall test.     

Trends and applications of multi-criteria decision analysis in environmental sciences: literature review

Approximately 3000 papers concerning multi-criteria decision analysis (MCDA) in the environmental field were identified through a series of queries in the Web of Science database and classified by MCDA method and environmental application using text mining in R. Stemming and stop word removal techniques were used to remove irrelevant text from the literature. Trends in MCDA methods (AHP/ANP, TOPSIS, outranking, MAUT/MAVT) associated with specific environmental applications (water, air, energy, natural resources, and waste management) or interventions/tools applications (stakeholders, strategies, sustainability, and GIS) were identified. The results show a linear growth in the share of MCDA papers in environmental science across all application areas. Furthermore, the results show that AHP/ANP and MAUT/MAVT are the most frequently mentioned MCDA methods in the literature. For environmental applications, the results showed that natural resource and waste management keywords were, respectively, the most and least commonly discussed applications within the MCDA papers. For intervention/tool applications, we found that keywords associated with ‘strategy’ and ‘GIS’ applications are, respectively, the most and least commonly discussed keywords within the MCDA papers. The authors found that MCDA method keywords were evenly distributed across the environmental and intervention/tool applications, indicating a lack of preference in the environmental field for use of specific MCDA methods. This paper demonstrates that text mining is an applicable tool to assess specific textual trends and patterns when analyzing larger bodies of MCDA literature.     

Development of environmental thresholds for streams in agricultural watersheds

Global increases in consumption of chemical nutrients, application of pesticides, and water withdrawal to enhance agricultural yield have resulted in degraded water quality and reduced water availability. Efforts to safeguard or improve environmental conditions of agroecosystems have usually focused on managing on-farm activities to reduce materials loss and conserve habitat. Another management measure for improving environmental quality is adoption of environmental performance standards (also called outcome-based standards). This special collection of six papers presents the results of four years of research to devise scientifically credible approaches for setting environmental performance standards to protect water quantity and quality in Canadian agriculturally dominated watersheds. The research, conducted as part of Canada's National Agri-Environmental Standards Initiative, aimed to identify Ideal Performance Standards (the desired environmental state needed to maintain ecosystem health) and Achievable Performance Standards (the environmental conditions achievable using currently available and recommended best available processes and technologies). Overviews of the papers, gaps in knowledge, and future research directions are presented. As humans, livestock, and wildlife (both terrestrial and aquatic) experience greater pressures to share the same limited water resources, innovative research is needed that incorporates a landscape perspective, economics, farm practices, and ecology to advance the development and application of tools for protecting water resources in agricultural watersheds.     

A statistical study of the quality of surface water intended for human consumption near Valencia (Spain)

Water quality in the European Union is subject to legislation through directives that are applicable in all Member States. The directives specify a set of physical and chemical parameters that should be regularly controlled using a network of sampling points, with sampling based on the intended use of the water. This paper presents the results of a statistical comparison of the quality of water intended for human consumption at two different locations (the Canal de Benagéber and the Canal Júcar-Turia) near the town of Valencia (Spain). These are currently the only canals that could supply Valencia and other nearby towns with drinking water. The parameters considered in this paper are the ones specified in the European directives for determining the quality of water intended for human consumption. These directives specify that the 95th percentile of the distribution of each parameter should be used to assess water quality, so accurate estimation of these percentiles was essential in this paper. We found statistically significant differences among locations in chlorides, sulfates, temperature, coloration, and manganese, but the results varied depending on the statistical tests that we used; parametric methods gave better results than nonparametric methods.     

TIME SERIES ANALYSIS IN PERSPECTIVE1

ABSTRACT: By employing a set of criteria for classifying the capabilities of time series models, recent developments in time series analysis are assessed and put into proper perspective. In particular, the inherent attributes of a wide variety of time series models and modeling procedures presented by the authors of the 18 papers contained in this volume are clearly pointed out. Additionally, it is explained how these models can address many of the time series problems encountered when modeling hydrologic, water quality and other kinds of time series. For instance, families of time series models are now available for modeling series which may contain nonlinearities or may follow nonGaussian distributions. Based upon a sound physical understanding of a problem and results from exploratory data analyses, the most appropriate model to fit to a data set can be found during confirmatory data analyses by following the identification, estimation and diagnostic check stages of model construction. Promising future research projects for developing flexible classes of time series models for use in water resources applications are suggested.     

Scenario analysis: a review of methods and applications for engineering and environmental systems

Changing environment, uncertain economic conditions, and socio-political unrest have renewed interest in scenario analysis, both from theoretical and applied points of view. Nevertheless, neither the processes for scenario analysis (SA) nor evaluation criteria and metrics have been regularized. In this paper, SA-reported applications and implementation methodology are discussed in the context of an extensive literature review covering papers published between 2000 and 2010. Over 340 papers were identified through a series of queries in the web of science database. The papers were classified based on the North American Industrial Classification System and SA application goals (environmental, business, and social). SA methodology used in each paper was assessed based on four main criteria: coverage, consistency, uncertainty assessment, and efficiency. We find a significant increase in SA applications, especially in the environmental field. Theoretical developments in the field represent a small fraction of published studies and do not increase in time. The methods used to develop different scenarios vary widely across the academic literature and applications reviewed. Similarly, the methods and data used to characterize the scenarios and develop response strategies are extremely diverse and are limited by factors such as computational tractability and available time and resources. Based on this review, we recommend a regular process for scenario analysis that includes the steps of analysis, scenario definition, and evaluation.     

TESTING FOR TREND IN LAKE AND GROUND WATER QUALITY TIME SERIES1

ABSTRACT: The detection of gradual trends in water quality time series is increasing in importance as concern grows for diffuse sources of pollution such as acid precipitation and agricultural non-point sources. A significant body of literature has arisen dealing with trend detection in water quality variables that exhibit seasonal patterns. Much of the literature has dealt with seasonality of the first moment. However, little has been mentioned about seasonality in the variance, and its effect upon the performance of trend detection techniques. In this paper, eight methods of trend detection that arise from both the statistical literature as well as the water quality literature have been compared by means of a simulation study. Varying degrees of seasonality in both the variances and the means have been introduced into the artificial data, and the performances of these procedures are analyzed. Since the focus is on lake and ground water quality monitoring, quarterly sampling and short to moderate record lengths are examined.     

地下水弥散实验研究

本文通过野外实验的方法,确定了地下水含水层的弥散参数,为建立准确可靠的地下水污染预测模型提供依据,对地下水环境质量研究和环境影响评价具有实际意义。     

Maximum permissible and negligible concentrations for some organic substances and pesticides

The aim of the paper is to provide interested parties the methods that were used for generic hazard assessment in The Netherlands, and the resulting so-called maximum permissible concentrations (MPCs) and the negligible concentrations (NCs) for approximately 150 organic substances and pesticides. The MPCs and NCs were derived for water, sediment, and soil. The concentration in the environment above which the risk of adverse effects was considered unacceptable to ecosystems is called the MPC. The MPCs take into account that the substances are distributed among the different environmental compartments, and are harmonized accordingly. The MPCs served as a basis for the Dutch government to set generic environmental quality standards (EQS) in The Netherlands (IWINS,[15]). EQS in turn are used by the Dutch Government to assess the environmental quality and for other environmental policy purposes. Concentrations in the environment below which the occurrence of adverse effects is considered to be negligible are called NCs. Hazards must be reduced when the environmental concentration of a substance exceeds its MPC. In-between this limits reduction of hazards is preferable. The MPC is a scientifically derived hazard limit. The NC is simply defined as 1% of the MPC. In general, there is a great demand for ecotoxicological data that currently limits a more reliable estimate of many MPCs. For water, approximately half of the MPCs are derived on the basis of four or more NOECs (no observed effect concentrations). For the other half, MPCs are based on only a few chronic or acute tests. For soil and sediment, however, almost no ecotoxicological data are available, and MPCs for those compartments have, in many cases, been derived from MPCs in water applying the equilibrium partitioning method (EqP-method), resulting in MPCs with greater uncertainty. Some of the methods and underlying assumptions that have been used may need improvement. For example, the factor between MPC and NC, the statistical extrapolation method, the method that is used for secondary poisoning, the role of the background concentrations of ‘naturally’ occurring substances, and the bioavailability and the EqP-method. There is a great need for hazard limits, and the present compilation tries to provide those as well as identifying research gaps.     

Nonpoint source pollution, environmental quality, and ecosystem health in China: introduction to the special section

The rapid economic and industrial growth of China, exemplified by a 10-fold increase in its gross domestic product in the past 15 years, has lifted millions of its citizens out of poverty but has simultaneously led to severe environmental problems. The World Health Organization estimates that approximately 2.4 million deaths in China per year could be attributed to degraded environmental quality. Much of China's soil, air, and water are polluted by xenobiotic contaminants, such as heavy metals and organic compounds. In addition, soil quality is degraded by erosion, desertification, and nutrient runoff. Air quality is further compromised by particulates, especially in heavily populated areas. Research shows that 80% of urban rivers in China are significantly polluted, and poor water quality is a key contributor to poverty in rural China. Economic and industrial growth has also greatly expanded the demand for water sources of appropriate quality; however, pollution has markedly diminished usable water resource quantity. Desertification and diminishing water resources threaten future food security. In recent years, China's government has increased efforts to reverse these trends and to improve ecosystem health. The Web of Science database showed that the percentage of articles on China devoting to environmental sciences increased dramatically in recent years. In addition, the top 25 institutes publishing the papers in environmental sciences were all in China. This special issue includes seven articles focusing on nonpoint source pollution, environmental quality, and ecosystem health in China. The major issues, and results of these studies, are discussed in this introduction.     

TECHNIQUES FOR DETECTING TRENDS IN LAKE WATER QUALITY1

ABSTRACT: With the advent of standards and criteria for water quality variables, there has been an increasing concern about the changes of these variables over time. Thus, sound statistical methods for determining the presence or absence of trends are needed. A Trend Detection Method is presented that provides: 1) Hypothesis Formulation - statement of the problem to be tested, 2) Data Preparation - selection of water quality variable and data, 3) Data Analysis - exploratory data analysis techniques, and 4) Statistical Tests - tests for detecting trends. The method is utilized in a stepwise fashion and is presented in a nonstatistical manner to allow use by those not well versed in statistical theory. While the emphasis herein is on lakes, the method may be adopted easily to other water bodies.     

NONPARAMETRIC TEST PERFORMANCE FOR TRENDS IN WATER QUALITY WITH SAMPLING DESIGN APPLICATIONS1

ABSTRACT: In this paper four nonparametric tests for monotonic trend detection are compared with respect to their power and accuracy. The importance of comparing powers at equal empirical significance levels rather than nominal levels is stressed. Therefore, an appropriate graphical method is presented. The effect of the sampling frequency is also assessed using Monte Carlo simulations and a trajectory representation that visualizes the dynamics of the trade-off between the type I and type II errors. These methods are applied to compare four nonparametrical tests (seasonal Mann. Kendall, modified seasonal Mann-Kendall, covariance eigenvalue and covariance inversion) under several conditions. It is concluded with respect to the power that it is not worthwhile for the modified seasonal Mann-Kendall test applied to the AR(1) process considered in this paper to increase the sampling frequency from monthly to biweekly for detecting a monotonic trend of 5 percent, 10 percent, or 15 percent of the process variance. Under these conditions the seasonal Mann-Kendall test is highly liberal, while the covariance inversion and the covariance eigenvalue test are conservative. This research is situated in the development of an efficient sampling design for the Flemish water quality monitoring network.     

Developing a sustainable energy strategy for a water utility. Part II: A review of potential technologies and approaches

Environmental legislation is increasing the amounts of bought-in electricity required for sewage treatment, and generating larger volumes of sewage sludge to be treated and disposed of. Concurrently, concerns over global warming and food safety from sewage sludge recycling on agricultural land is augmenting the costs of conventional sewage and sludge treatment technologies and practices. This paper reviews some emerging technologies and practices that may assist in mitigating these problems in the future. In addition, a number of potential renewable energy technologies available to water companies are reviewed. Results suggest that through the take-up of new technologies, current and future water quality standards could be delivered in a more sustainable way. However, this series of papers also highlights that institutional and political conflicts may have inadvertently failed to recognise the wider effects of improving water quality and lessened the financial support necessary for their widespread take-up. It is also suggested that through the use of a Strategic Environmental Assessment (SEA) approach, stakeholders could gain a better understanding of the broader environmental effects of achieving certain water quality standards and develop policy and long-term investment strategies accordingly. However, to fulfill the information requirements of an SEA, an appropriate appraisal tool that considers many of these factors in unison is required, and a possible technique is suggested.     

石油化工废碱液在造纸厂的应用

为使中原乙烯生产过程中产生的废碱液得到有效利用,采用合理的工艺流程,麦草经粉碎后与用废碱液配置好的蒸煮液装入蒸球,经升温、升压蒸煮后,进入洗涤工艺,其间废碱液中有效成分被充分利用。从产品纸张的质量来看,利用废碱液制浆生产的纸张质量完全能够达到或超过国家纸张质量标准。此项废物利用有可观的经济效益和环境效益。     

构建流域水质综合监测体系的初探

流域水质监测是流域水环境改善与污染防治的重要前提,为流域水环境管理提供了必要的技术支撑。目前环保、水利、流域管理等众多部门均承担了一定范围内的流域水质监测工作,但由于监测方法、取样断面等方面的差异,各监测机构的数据往往存在较大差异,不利于流域水质现状评价、预警预报和水环境的综合管理。本文以长江流域的跨省界断面为研究对象,对构建流域水质综合监测体系进行初探研究,对于确保流域水质安全具有重要意义。     

用模糊数学对大连湾水质的评价研究

由于海域水环境系统的不确定性、随机性以及海域水质分级的模糊性,传统的海域水质评价方法如单因子评价法、综合污染指数法往往不能客观地反映海域水资源的质量状况。用模糊数学的方法对大连湾的水质环境质量进行评价,能够客观地分析出大连湾的污染状况,为合理规划、控制大连湾沿岸污染企业的污水排放提供科学依据,从而达到有计划地控制和治理海域污染,改善海域环境质量的目的。     

A COMPARATIVE STUDY OF LINEAR AND NONLINEAR TIME SERIES MODELS FOR WATER QUALITY1

ABSTRACT: Surface water quality data are routinely collected in river basins by state or federal agencies. The observed quality of river water generally reflects the overall quality of the ecosystem of the river basin. Advanced statistical methods are often needed to extract valuable information from the vast amount of data for developing management strategies. Among the measured water quality constituents, total phosphorus is most often the limiting nutrient in freshwater aquatic systems. Relatively low concentrations of phosphorus in surface waters may create eutrophication problems. Phosphorus is a non-conservative constituent. Its time series generally exhibits nonlinear behavior. Linear models are shown to be inadequate. This paper presents a nonlinear state-dependent model for the phosphorous data collected at DeSoto, Kansas. The nonlinear model gives significant reductions in error variance and forecasting error as compared to the best linear autoregressive model identified.     

ESTIMATING MEAN AND VARIANCE FOR ENVIRONMENTAL SAMPLES WITH BELOW DETECTION LIMIT OBSERVATIONS1

ABSTRACT: Left-censoring of data sets complicates subsequent statistical analyses. Generally, substitution or deletion methods provide poor estimates of the mean and variance of censored samples. These substitution and deletion methods include the use of values above the detection limit (DL) only, or substitution of 0, DL/2 or the DL for the below DL values during the calculation of mean and variance. A variety of statistical methods provides better estimators for different types of distributions and censoring. Maximum likelihood and order statistics methods compare favorably to the substitution or deletion methods. Selected statistical methods applicable to left-censoring of environmental data sets are reviewed with the purpose of demonstrating the use of these statistical methods for coping with Type I (and Type II) left-censoring of normally and log-normally distributed environmental data sets. A PC program (UNCENSOR) is presented that implements these statistical methods. Problems associated with data sets with multiple DLs are discussed relative to censoring methods for life and fatigue tests as recently applied to water quality data sets.