Access for all? Beach access and equity in the Detroit metropolitan area

Beaches are a unique type of recreation setting, offering a variety of water- and land-based opportunities that can meet residents’ diverse and complex recreation needs. Providing and improving equitable access to recreation amenities such as beaches have been recognized as essential responsibilities of public leisure agencies. This study assessed the degree of equity inherent in the distribution of public beaches in the Detroit metropolitan area; to account for spatial effects, phenomena rarely considered in prior equity analyses, geographically weighted regression was employed. Considerable local variations in the relationships between level of access to public beaches and population density, proportion of elderly population and educational attainment were identified. Such findings can help parks and recreation agencies better understand local patterns of equity, an important first step in facilitating the formulation of more efficient and effective planning and policy approaches.     

非线性回归法计算曝气设备清水氧传递系数

分析对比作图法、线性回归法和非线性回归法计算曝气设备清水氧传递系数(KLa)各自的优缺点。指出在实际测定曝气设备性能中,使用非线性回归法计算KLa更加可靠．而且可以使测试过程更加容易控制。所以在实际测试过程中,推荐使用非线性回归法计算KLa。     

ANALYZING CORRELATIONS BETWEEN STREAM AND WATERSHED ATTRIBUTES1

ABSTRACT: Bivariate correlation analysis has been widely used to explore relationships between stream and watershed attributes that have all been measured on the same set of watersheds or sampling locations. Researchers routinely test H₀: ρ= 0 for each correlation in a large table and then go on to discuss only those that are declared “significant.” Such test results are inaccurate because no allowance is made for multiple testing, and also because the tests are not mutually independent. This paper reviews the Bonferroni approach to controlling the overall error rate in multiple testing and shows how the approach becomes impractical for large correlation tables. The Hotelling/Williams test is introduced for comparing two dependent correlations that share a variable, and numerical constraints for two such correlations are illustrated. References are also given for testing other hypothesized patterns among dependent correlations, and links to dependent correlation software are provided. The methods are illustrated for watershed and stream variables sampled in 23 small agricultural watersheds of the Willamette Valley, Oregon.     

REGRESSION MODELS OF HERBICIDE CONCENTRATIONS IN OUTFLOW FROM RESERVOIRS IN THE MIDWESTERN USA, 1992–19931

ABSTRACT: Reservoirs are used to store water for public water supply, flood control, irrigation, recreation, hydropower, and wildlife habitat, but also often store undesirable substances such as herbicides. The outflow from 76 reservoirs in the midwestern USA, was sampled four times in 1992 and four times in 1993. At least one herbicide was detected in 82.6 percent of all samples, and atrazine was detected in 82.1 percent of all samples. Herbicide properties; topography, land use, herbicide use, and soil type in the contributing drainage area; residence time of water in reservoirs; and timing of inflow, release, and rainfall all can affect the concentration of herbicides in reservoirs. A GIS was used to quantify characteristics of land use, agricultural chemical use, climatic conditions, topographic character, and soil type by reservoir drainage basins. Multiple linear and logistic regression equations were used to model mean herbicide concentrations in reservoir outflow as a function of these characteristics. Results demonstrate a strong association between mean herbicide concentrations in reservoir outflow and herbicide use rates within associated drainage basins. Results also demonstrate the importance of including soils and basin hydrologic characteristics in models used to estimate mean herbicide concentrations.     

COMPARING METHODS OF HYDROLOGIC REGIONALIZATION1

ABSTRACT: Data splitting is used to compare methods of determining “homogeneous” hydrologic regions. The methods compared use cluster analysis based on similarity of hydrologic characteristics or similarity of characteristics of a stream's drainage basin. Data for 221 stations in Arizona are used to show that the methods, which are a modification of DeCoursey's scheme for defining regions, improve the fit of estimation data to the model, but that is is necessary to have an independent measure of predictive accuracy, such as that provided by data splitting, to demonstrate improved predictive accuracy. The methods used the complete linkage algorithm for cluster analysis and computed weighted average estimates of hydrologic characteristics at ungaged sites.     

AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.     

区域环境--经济协调发展定量分析方法研究

本文对目前常用的环境与经济协调发展分析方法的优劣和特点进行了具体分析，指出现在常用的进行可持续发展水平定量分析的层次分析法存在明显的缺陷，以及现有的几种评价环境与经济之间协调程度的方法的局限性。提出了较为客观实用的评估方法，即依据系统分析和数理统计的原理利用主成分分析进行环境——经济协调度分析，并对环境——经济协调度定量评估的步骤、方法包括测算方法的选择、数学模型的建构进行深入的探讨和研究，以南阳市为例对该方法进行了验证。     

Water Use by Thermoelectric Power Plants in the United States1

Abstract: Thermoelectric power generation is responsible for the largest annual volume of water withdrawals in the United States although it is only a distant third after irrigation and industrial sectors in consumptive use. The substantial water withdrawals by thermoelectric power plants can have significant impacts on local surface and ground water sources, especially in arid regions. However, there are few studies of the determinants of water use in thermoelectric generation. Analysis of thermoelectric water use data in existing steam thermoelectric power plants shows that there is wide variability in unitary thermoelectric water use (in cubic decimeters per 1 kWh) within and among different types of cooling systems. Multiple‐regression models of unit thermoelectric water use were developed to identify significant determinants of unit thermoelectric water use. The high variability of unit usage rates indicates that there is a significant potential for water conservation in existing thermoelectric power plants.     

DETERMINING SIGNIFICANCE AND PRECISION OF ESTIMATED PARAMETERS FOR RUNOFF FROM SEMIARID WATERSHEDS1

ABSTRACT Significant parameters for predicting thunderstorm runoff from small semiarid watersheds are determined using data from the Walnut Gulch watershed in southern Arizona. Based on these data, thunderstorm rainfall is dominant over watershed parameters for predicting runoff from multiple linear regression equations. In some cases antecedent moisture added significantly to the models. A technique is developed for estimating precision of predicted values from multiple linear regression equations. The technique involves matrix methods in estimating the variance of mean predicted values from a regression equation. The estimated variance of the mean predicted value is then used to estimate the variance of an individual predicted value. A computer program is developed to implement these matrix methods and to form confidence limits on predicted values based on both a normality assumption and the Chebyshev inequality.     

RIDGE REGRESSION TECHNIQUES APPLIED TO LANDSAT INVESTIGATION OF WATER QUALITY IN LAKE OKEECHOBEE1

ABSTRACT: Landsat radiance values were processed at two different (single and double) levels of accuracy to estimate chlorophyll a, turbidity, and suspended sediment in Lake Okeechobee, Florida. Both ordinary least square and ridge regression analyses were used to establish a relationship between water quality parameters and Landsat radiance. Radiance measurements made at greater precision (double level) gave a better solution in this application. The ridge regression analysis for double level not only can reduce the total mean square error about 13–20 percent and confidence interval about 6–28 percent as compared to ordinary least square analysis, but it can also change the interpretation of analysis results.