ISSN:1180-4009    

DOI:10.1002/env.3770020103

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractThe focal point of this paper is the concept:the environmental unit is Earth itself. To analyze and predict global environmental phenomena, the dimensions of our domain of concern must match those of the planet's dynamic fluid envelope: atmospheric and oceanic. Traditional techniques of statistical diagnostic analysis and prediction must be cast in the natural coordinates of earth‐oriented systems and computer technology tasked to its present limits to handle global scale data bases.A notation is presented in which various approaches to estimating variables in large domains can be seen as adaptations to a common estimation objective. Their differences arise from differences in the scope and extent of information available to describe the system under study. The “universal estimator notation” serves to identify areas for significant further development. Examples are given which illustrate the potential impacts on spatial estimation algorithms of using available data to tune them to location and current

ISSN:1180-4009    

DOI:10.1002/env.3770020104

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractA pollution rose consists of selective averages of concentrations of an air pollutant for all sectors of the wind rose. Generally the sectors are 10 or 20 degrees wide and one‐hour averages of concentrations and wind directions are used. Complications arise when daily averages of concentrations have to be used. The number of data is much smaller and the variability of the wind direction over 24 hours is large. In this paper, a linear regression model is presented and applied to a real set of data. The standard solution of the regression problem is shown to give useless results; this is a consequence of the ill‐conditioning (multicollinearity) of the data. Large improvements are achieved with ridge regression and other forms of penalized least squares estimation. Cross‐validation is used for obtaining good values of the penalty parameter automati

ISSN:1180-4009    

DOI:10.1002/env.3770020105

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractAn outline of some central methodological steps in an ecometric analysis to develop load diagrams is given. This is done within the framework of an Expert system for environmental consequence analysis for natural aquatic ecosystems. Examples focus on nutrient emissions/eutrophication in coastal areas. The analysis is based on a number of fundamental concepts (effect, dose, sensitivity, area and time compatibility, ecometric analysis, load diagrams, etc.). The paper addresses questions concerning the basic set‐up of the Expert system, how to establish representative empirical data for entire coastal areas for various types of substances, e.g., nutrients, and parameters expressing eutrophication (e.g., Secchi depth, chlorophyll) and internal correlations among dose and sensitivity parameters. Limitations and advantages with the ecometric approach are stresse

ISSN:1180-4009    

DOI:10.1002/env.3770020106

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractFull scale tests were performed to determine the effects of transient and return flows on the clarification process of activated sludge treatment. An ARIMA‐intervention model and a feedback‐feedforward control scheme for return flow was developed. Computer simulation runs were used to test the effectiveness of the control algorithm. The paper describes and discusses the model identification, the controller development and the controller's potential in applicat

ISSN:1180-4009    

DOI:10.1002/env.3770020107

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractThis paper investigates the fit of the lognormal model and Box and Cox (BC) family of transformation models to several data sets that arise in environmental contexts where the data may be heavily left‐censored with multiple detection limits. A model fitting protocol is described that selects an optimal BC model, identifies outlying observations, and verifies the final model using a normal probability plot correlation statistic. This protocol is used to fit these models to data collected on seventeen groundwater chemistry variables in Ingham County, Michigan in 1986‐1987 as part of the Michigan Groundwater Survey. Six of these variables are adequately modelled by an optimally‐chosen BC model and five of these six are adequately modelled by the lognormal model. Ten of the study variables are marginally modelled by a BC model, whereas only six of the study variables are marginally fit by the lognormal model. The remaining variables fail the fitting criteria due to the significance of the probability plot correlation statistic or because of the presence of outlying observations in the final model.On the basis of these results, the data analyst is cautioned against the automatic use of the lognormal model for fitting environmental data in every circumstance. What is recommended is checking the adequacy of the lognormal model prior to use. If the lognormal model is not an adequate model, then perhaps some other member of the Box and Cox family will provide an adequate

ISSN:1180-4009    

DOI:10.1002/env.3770020108

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractAn empirical technique for determining sample size during ongoing, non‐probability, haphazard sampling is described in the present paper. While there are many techniques for determining sample sizea priori, all of them require a knowledge of the population parameters (or at least their variance). Moreover, thesea priorimethods are based on assumptions of probability sampling such as simple random, stratified random, cluster, and so on. It is common in psychological, biological, social, environmental and medical research, however, to employ non‐probability samples of unknown representativeness and with virtually no knowledge of the parameters in question. Thusa prioritechniques are quite impractical and limited in their usefulness.The procedure described in the present paper is an empirical method which does not require assumptions of probability sampling. The method involves determining the point of convergence of Sums of Squares and Cross Products (SSCP) matrices in sequential sampling using Wilk's lambda as a criterion with Rao's approximateFas a test statistic. When the SSCP matrices of two sample sequences converge at the α = .10 level of significance, the sample size is determined to be adequate as the estimators have stabilized. Further sampling would produce redundant data. An application of the present technique to a large scale study is given as a practical exa

ISSN:1180-4009    

DOI:10.1002/env.3770020109

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractIn many problems of regulation of water quantity and quality, a process of fundamental importance is that of cumulative sums — weighted or otherwise — of random variables forming a stochastic process. It is commonly believed that in such situations, the structure of the stochastic process is not important as long as the most important parameters remain the same. This means, for example, for a Markov process, with the same stationary distribution and the same serial correlation coefficient, the behaviour of the cumulative sums would be nearly the same. In this paper we show, by analytical methods and by simulation that this belief is erroneous, and that the structure of the input model has a significant effect, and that this effect increases with the serial correlation coeffici

ISSN:1180-4009    

DOI:10.1002/env.3770020110

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

ISSN:1180-4009    

DOI:10.1002/env.3770020102

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY