ON THE MISMATCH BETWEEN DATA AND MODELS OF HYDROLOGIC AND WATER RESOURCE SYSTEMS1

ABSTRACT: Many difficulties exist in the matching of models with data. This paper identifies elements of this problem and discusses considerations involved in model evaluation. The well known multivariate linear regression model is used to illustrate the distinctions between accuracy and precision and between estimation and prediction (because the model is commonly misused.) No amount of additional data will improve the accuracy of a poor model. A high R², while indicative of a good matching between the observed data and model estimates, is a poor criterion for judging adequacy of the model to make good predictions of future events. Model evaluation also includes the problem of introducing secondary data and proxy variables into a model. Secondary data frequently enter, for example, the mass, energy and water budget equations because of difficulties in measuring the primary variables. Proxy variables arise because of a desire to collapse a vector of incomparable values, say, of water quality into a single number. Review of the above issues indicates that model evaluation is a multi-criterion problem, often imbedded in a larger framework where models are intended to meet multiple objectives. The mismatch of models and data has increasing legal and social consequences.     

DATA REQUIREMENTS OF A WATER QUALITY MANAGEMENT PROGRAM1

ABSTRACT: Routine data collection currently consumes a large amount of the total resources devoted to water quality management. All too often data collection becomes an end in itself, with little thought given to the purpose of the data collection. The problem generally stems from a lack of proper routine surveillance system design and a failure on the part of the designers to initially identify the data needs of the management program. This study attempts, in a general way, to delineate the data needs of a water quality management program. This first required an identification of the activities involved in water quality management. The activities were then discussed in terms of the types of information needed to successfully complete their assigned tasks. Several detailed examples are given. The results of the discussion are summarized and several strategies are proposed to relate the results to surveillance system design.     

ON PRECIPITATION SENSOR NETWORK DENSITIES FOR EVALUATING WINTERTIME OROGRAPHIC CLOUD SEEDING EXPERIMENTS1

Principal component analysis is used to investigate density requirements of wintertime orographic cloud seeding experiment precipitation sensor networks. Three passes in the vicinity of Climax, Colorado are studied. The eighteen or more evenly spaced precipitation sensors of each pass are almost completely described by three principal components. These three principal components appear to represent (i) mean precipitation, (ii) slope orientation to storm systems, and (iii) elevation. Evaluation of these principal components is implemented with two distribution-free tests, a proportionality test and the runs test. The results of this study suggest that the loss of experimental information caused by low density precipitation sensor networks may be of little consequence.     

卫星云图资料同化中的质量控制及其在暴雨预报中的应用

以1996年7月3—4日发生在江淮流域的暴雨过程为例，依据统计特征分别以常规分析场、正涡度高值区、高低空急流为标准，设计了三套方案对卫星反演湿度场进行质量控制。利用中尺度MM5模式进行的数值试验表明：经质量控制后预报场得到较大改善；质量控制方案的优劣对预报效果有直接影响，选择合理的控制标准是重要的。     

灾害等级的综合评价

灾害等级被用来表示灾害所造成的社会损失大小。主成分分析法能够在保证原始数据信息损失最小的情况下，以少数的综合变量取代原有的多维变量，使数据结构大为简化，并且客观地确定权数，避免了主观随意性，因而是灾害等级综合评价的一种简单易行的有效方法。通过主成分分析，可以为减灾和分区和分级管理提供重要的理论依据。     

基于灰色预测理论的瓦斯传感器自校正技术

笔者提出了将灰色预测理论与单片机技术相结合 ,对瓦斯传感器的非线性进行自校正的新思路 ;采用了灰色预测理论中GM(1,1)模型和单片机技术相结合 ,将预测误差值对传感器的实测值进行分段补偿的方法 ,实现对瓦斯传感器的非线性自校正 ;该方法克服了灰色预测理论对波动较大的随机序列的预测精度低的缺陷。其研究结果表明 ,应用该方法得到的预测值与真值的拟合程度好 ,预测值与真值之间最大的差值为 0 .15 0 1% ,而该处校正前的差值为 0 .30 0 0 % ,提高了传感器的测量精度。     

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.