TILE RATIONALE FOR OHIO'S DETERGENT PHOSPHORUS BAN1

ABSTRACT: Ohio signed into law a detergent phosphorus ban on March 26, 1988. This law limits the elemental phosphorus content of household laundry detergents to 0.5 percent in all 35 Lake Erie counties in Ohio by 1990. Ohio's detergent phosphorus ban will help non-compliant municipal wastewater treatment plants achieve compliance with the 1 mg/L effluent phosphorus standard. By limiting the phosphorus content of household laundry detergents, Ohio will also benefit from less phosphorus entering surface waters from combined sewer overflows, communities with treatment plant bypasses, and riparian homes with septic tanks. This is important because most of the phosphorus in laundry detergents is in the bioavailable form and Ohio's Lake Erie shoreline is particularly sensitive to Cladophora problems. When viewed in conjunction with reduced chemical costs for phosphorus removal and savings in sludge disposal costs, Ohio's detergent phosphorus ban is a pragmatic component of an international phosphorus management strategy to protect the Great Lakes.     

NEW ZEALAND'S NATIONAL WATER QUALITY MONITORING NETWORK - DESIGN AND FIRST YEAR'S OPERATION1

ABSTRACT: The design and implementation of a national surface water quality monitoring network for New Zealand are described. Some of the lessons learned from the first year of operation are also addressed. Underpinning the design, and specified in advance, are the goal and objectives, the data quality assurance system, and the mechanism for data interpretation and reporting. Because of the difficulties associated with the use of a multitude of different agencies, only one agency is involved in field work and one laboratory undertakes the analysis. Staff training has been given a high priority. The network has been designed to give good trend detectability for regular sampling over a 5–10 year period.     

The environmental audit. I. Concepts

Extensive criticism of water quality monitoring programs has developed as costs are compared with the benefits produced by monitoring efforts. Collecting water quality data while developing understanding of the functional character of the environment will improve water quality monitoring data utility in environmental management. The environmental audit characterizes the attributes of the natural environment (that is, attribute type, intensity, and variability), providing a theoretical as well as practical foundation for data interpretation. In the view proposed here, traditional monitoring means the very narrow activity of collecting samples and perhaps analyzing them and storing the analyses. In the environmental audit, these activities are a mechanism to systematically improve environmental monitoring and assessment by improving the design and implementation of environmental programs. Major reasons why existing programs fail to meet the needs of legislators, regulators, and conservationists are identified.     

APPROACHES TO MULTIVARIATE MODELING OF WATER RESOURCES TIME SERIES1

ABSTRACT: Alternative approaches suggested for modeling multiseries of water resources systems are reviewed and compared. Most approaches fall within the general framework of multivariate ARMA models. Formal modeling procedures suggest a three-stage iterative process, namely: model identification, parameter estimation and diagnostic checks. Although a number of statistical tools are already available to follow such modeling process, in general, it is not an easy task, especially if high order vector ARMA models are used. However, simpler ARMA models such as the contemporaneous and the transfer-function models may be sufficient for most applications in water resources. Two examples of modeling bivariate and trivariate streamflow series are included. Alternative modeling procedures are used and compared by using data generation techniques. The results obtained suggest that low order models, as well as contemporaneous ARMA models, reproduce quite well the main statistical characteristics of the time series analyzed. It is assumed that the same conclusions apply for most water resources time series.     

TREND ASSESSMENT OF WATER QUALITY TIME SERIES1

ABSTRACT A general methodology is described for identifying and statistically modeling trends which may be contained in a water quality time series. A range of useful exploratory data analysis tools are suggested for discovering important patterns and statistical characteristics of the data such as trends caused by external interventions. To estimate the entries in an evenly spaced time series when data are available at irregular time intervals, a new procedure based upon seasonal adjustment is described. Intervention analysis is employed at the confirmatory data analysis stage to rigorously model changes in the mean levels of a series which are identified using exploratory data analysis techniques. Furthermore, intervention analysis can be utilized for estimating missing observations when they are not too numerous. The effects of cutting down a forest upon various water quality variables and also the consequences of acid rain upon the alkalinity in a stream provide illustrative applications which demonstrate the effectiveness of the methodology.     

我国双车道公路事故预测模型研究中数据采集

事故预测模型的研究可为公路设计人员提供有效的安全设计工具。该研究需要大量基础数据的支撑,数据采集量的大小、数据质量和数据分析水平直接决定研究成果的优劣。笔者在双车道公路事故预测模型研究过程中,对我国双车道公路安全影响要素进行分析,确定基于现有条件下比较理想的数据采集对象,总结了数据采集的方法及其不足之处。具体包括数据采集的范围,样本量的需求,事故数据、交通组成数据、路侧、接入口和路线数据采集的方法、数据处理方式等。     

《中国安全生产科学技术》期刊发展分析

《中国安全生产科学技术》是我国安全科学领域一本学术性、技术性比较强的科技期刊,定位于国家级安全生产科学研究领域的权威性期刊,学术性与实用性兼顾。本文以2005～2006年《中国安全生产科学技术》的有关统计数据为基础进行分析,有关数据说明《中国安全生产科学技术》期刊涉及安全生产各个领域,作者所在地涵盖全国27个省市及海外3个国家和地区,在安全科学领域有较大的影响;发文数量稳中有升,注意刊发不同领域和机构的论文,发展平衡,有稳定的发展潜力;基金论文多,期刊学术水平比较高;版式编排规范、标准,既注重刊物质量,也注意期刊的外在表现。     

Hydrologic Model Framework for Water Resources Planning in the Santa Cruz River,Southern Arizona1

Abstract: The authors develop a model framework that includes a set of hydrologic modules as a water resources management and planning tool for the upper Santa Cruz River near the Mexican border, Southern Arizona. The modules consist of: (1) stochastic generation of hourly precipitation scenarios that maintain the characteristics and variability of a 45‐year hourly precipitation record from a nearby rain gauge; (2) conceptual transformation of generated precipitation into daily streamflow using varied infiltration rates and estimates of the basin antecedent moisture conditions; and (3) surface‐water to ground‐water interaction for four downstream microbasins that accounts for alluvial ground‐water recharge, and ET and pumping losses. To maintain the large inter‐annual variability of streamflow as prevails in Southern Arizona, the model framework is constructed to produce three types of seasonal winter and summer categories of streamflow (i.e., wet, medium, or dry). Long‐term (i.e., 100 years) realizations (ensembles) are generated by the above described model framework that reflects two different regimes of inter annual variability. The first regime is that of the historic streamflow gauge record. The second regime is that of the tree ring reconstructed precipitation, which was derived for the study location. Generated flow ensembles for these two regimes are used to evaluate the risk that the regional four ground‐water microbasins decline below a preset storage threshold under different operational water utilization scenarios.     

基于DEA技术的污水处理定价模型

应用DEA方法评价污水处理厂相对效率，并将评价结果用于污水处理定价，得到了基于DEA方法的污水处理定价模型。该模型克服了现有定价模型的不足，体现了政府对污水处理厂生产效率的要求，能够促使企业提高效率并降低成本。     

A GENETIC ALGORITHM TO REDUCE STREAM CHANNEL CROSS SECTION DATA1

A genetic algorithm (GA) was used to reduce cross section data for a hypothetical example consisting of 41 data points and for 10 cross sections on the Kootenai River. The number of data points for the Kootenai River cross sections ranged from about 500 to more than 2,500. The GA was applied to reduce the number of data points to a manageable dataset because most models and other software require fewer than 100 data points for management, manipulation, and analysis. Results indicated that the program successfully reduced the data. Fitness values from the genetic algorithm were lower (better) than those in a previous study that used standard procedures of reducing the cross section data. On average, fitnesses were 29 percent lower, and several were about 50 percent lower. Results also showed that cross sections produced by the genetic algorithm were representative of the original section and that near‐optimal results could be obtained in a single run, even for large problems. Other data also can be reduced in a method similar to that for cross section data.