REGIONAL SCALE TREND MONITORING OF INDICATORS OF TROPHIC CONDITION OF LAKES1

ABSTRACT: The U.S. Environmental Protection Agency has proposed a sample survey design to answer questions about the ecological condition and trends in condition of U.S. ecological resources. To meet the objectives, the design relies on a probability sample of the resource population of interest (e.g., a random sample of lakes) each year on which measurements are made during an index period. Natural spatial and temporal variability and variability in the sampling process all affect the ability to describe the status of a population and the sensitivity for trend detection. We describe the important components of variance and estimate their magnitude for indicators of trophic condition of lakes to illustrate the process. We also describe models for trend detection and use them to demonstrate the sensitivity of the proposed design to detect trends. If the variance structure that develops during the probability surveys is like that synthesized from available databases and the literature, then the trends in common indicators of trophic condition of the specified magnitude should be detectable within about a decade for Secchi disk transparency (0.5–1 percentiyear) and total phosphorus (2–3 percent/year), but not for chlorophyll-a (> 3–4 percent/year), which will take longer.     

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.     

MONITORING STRATEGIES TO DETERMINE COMPLIANCE WITH WATER QUALITY OBJIECTIVES1

ABSTRACT: Two sampling strategies designed to test for compliance with water quality objectives are examined. For objectives based on long-term mean requirements, fixed frequency sampling at frequent intervals is most advantageous regardless of the underlying distribution of the data. For objectives that are based on maximum allowable concentrations, effective sampling strategies increase the likelihood of detecting noncompliance. If data are highly autocorrelated or sharply seasonal in distribution, an exceedance-driven sampling strategy is more effective and efficient for detecting violations than fixed frequency sampling. However, data generated by exceedance-driven sampling provide biased estimates of mean and standard deviation.     

PARAMETRIC AND NONPARAMETRIC TESTS FOR DEPENDENT DATA1

ABSTRACT: Simulation and analytical results show that ignoring serial dependence can have serious effects on the performance of the t, sign, and Wilcoxen tests. In particular, the true significance levels of these tests are altered significantly from the intended nominal levels. Modifications for these tests are given and shown to have the correct significance levels. Furthermore, an estimate of serial correlation is suggested for binary data and evaluated by simulation. An application to the toxic contaminants data from the Niagara River concludes the paper.     

共沉淀—原子吸收法分析铁强化盐中的铁

本文采用原子吸收分光光度法,测定铁强化盐中微量铁。用数理统计方法检证了方法的可靠性。     

数理统计方法在岷沱江水环境背景值计算中的应用

统计单元的划分，异常值的剔除，分布类型检验及背景值的表征是环境背景值计算中的四个关键环节，本文就其应用进行了较为系统地讨论。     

2002年9-12月国内环境事件数据

简要统计了2002年9－12月国内发生的各种环境事件57件，包括沙尘天气（3件），污染事件（10件），山体滑坡和泥石流（12件），虫害（2件）以及其他自然灾害（30件），最后对自然灾害进行了讨论。     

2003年5-8月国内环境事件数据

简要统计了2003年5—8月国内发生的各种环境事件127件，包括沙尘天气(1件)、污染事件(18件)、山体滑坡和泥石流(39件)、地震(15件)、虫害(9件)以及其他自然灾害(45件)。最后对洪涝、地质灾害和旱灾进行了讨论。     

SPATIAL ANALYSIS FOR MONTHLY RAINFALL IN SOUTH FLORIDA1

ABSTRACT: Several methods have been developed to interpolate point rainfall data and integrate areal rainfall data from any network of stations. From previous studies, it can be concluded that models for spatial analysis of rainfall are dependent on topography, area of analysis, type of rainfall, and density of gauging network. The purpose of this study is to evaluate a set of six appropriate models for point and areal rainfall estimations over a 4000 square mile area in South Florida. In this study, a case of developing spatial continuity model for monthly rainfall from a database that had various lengths of records and missing data is documented. The spatial correlation and variogram models for monthly rainfall were developed. Six methods of spatial interpolation were applied and the results validated with historical observations. The results of the study indicate that the multiquadric, kriging, and optimal interpolation schemes are the best three methods for interpolation of monthly rainfall within the study area. The optimal and kriging methods have the advantage of providing estimates of the error of interpolation. The optimal interpolation method uses the spatial correlation function and the kriging method uses the variogram function. The two spatial functions are related. Either of the two methods provide good estimates of monthly point and areal rainfall in the study area.