基于社会科学统计程序(SPSS)回归性分析的尾矿库事故预测模型

基于社会科学统计程序(SPSS)软件的分析功能,对调查研究中获取的尾矿库案例进行数据提炼和分类编码,找出相关因子并进行回归性分析。最终目的是找出尾矿库各个因素的内在联系,建立简单的尾矿库事故模型,从而可以初步预测尾矿库事故发生的可能性。该预测模型为尾矿库事故的研究提出了新方法,对于防灾减灾以及保护人民生命财产安全起到了积极作用。     

水安全及城市水安全研究进展与趋势

归纳和总结国内外水安全及城市水安全相关研究实践及其所用的评价指标体系,并对几种常用模型与方法的应用情况及其各自的特点进行分析,针对目前水安全及城市水安全研究中存在的主要问题,指出水安全及城市水安全进一步研究的方向:从自然、生态环境、社会经济、人文4个基本方向,以系统性、持续性、动态性和层次性4个特征为基础,分析水安全及城市水安全的概念与内涵;根据研究区域特征及其主要水安全问题建立评价指标体系;以研究者对各个模型的理解程度及驾驭能力为准则选用或改造现有模型与方法;针对加强城市应急水源地建设、突发性水安全事件应急预案、湿润地区水安全等问题开展研究。     

Agricultural Chemicals in the Alluvial Aquifer of a Typical County of the Arkansas Delta

Statistical methods and a Geographic Information System (GIS) were used to investigate potential indicators of ground water vulnerability to agricultural chemical contamination in a representative area of the Mississippi River alluvial aquifer. A total of 47 wells were sampled for analysis of nitrate, phosphorus, potassium, and 13 pesticides commonly-used in the area. Ten soil and hydrogeologic variables and five ground water vulnerability indices were examined to explain the variations of chemical concentrations. The results showed that no individual soil or hydrogeologic variables or their linear combinations could explain more than 25% of the variation of the chemical concentrations. A quadratic response surface model with the values of confining unit thickness, slope, soil permeability, depth to ground water, and recharge rate accounted for 62% of the variation of nitrate, 43% of P, and 83% of K, suggesting that the interactions among soil and hydrogeologic variables were significant. Observed trends of decreasing nitrate and P concentrations with increasing well depth and/or depth to ground water seemed to correlate with carbonate equilibrium in the aquifer and more reduced environment with depth. In view of uncertainties involved, it was recognized that the limitations associated with input data resolution used in GIS and the formulation of leaching indices limited their use for predicting ground water vulnerability. Misuse of pesticides could be another factor that would complicate the relationships between pesticide concentrations and the vulnerability indices.     

Combining mapped and statistical data in forest ecological inventory and monitoring – supplementing an existing system

A forest ecological inventory and monitoring system combining information derived from maps and samples is proposed based on ecosystem regions (Bailey, 1994). The system extends the design of the USDA Forest Service Region 6 Inventory and Monitoring System (R6IMS) in the Pacific Northwest of the United States. The key uses of the information are briefly discussed and expected results are illustrated with examples. The system is flexible, allowing regions based on ecological considerations to be modified. Sampling intensities that are affordable are likely to be insufficient to provide meaningful estimates for key parameters relating to rare and endangered species, watersheds, and other ecological units. Methods are proposed for collecting additional information in follow-up surveys and combining it with relevant information obtained in R6IMS. Near-continuous information on weather and possible pollution variables recorded by instruments at sampling sites is needed to develop meaningful models to understand what is happening in the ecoregions. R6IMS and the proposed additions constitute a dynamic system which will be modified further as data are analyzed.     

Nutrient transfer functions: the site of integration between feeding behaviour and nutritional physiology

Summary. We describe and extend a graphical approach to quantitative nutrition that focuses on the interplay between behavioural and physiological components of nutritional regulation. The site of integration is the nutrient transfer function, which is the function describing the time course of nutrient transfer between serially connected nutritional compartments (e.g., from the gut to the blood). The relationship between the shape of the nutrient transfer function and the temporal patterns of feeding determines the values of two key quantitative parameters of nutrition: the rate ('power') and the efficiency of nutrient acquisition. The approach can be extended to consider, in addition to the short-term behavioural and physiological decisions made by animals, some ecological determinants and longer-term, life history consequences of such decisions. Most importantly, this category of models can provide insights into the interplay among the various nutrients in an animal's diet. We illustrate this using hypothetical examples, and also present preliminary data for the power-efficiency relationships of protein and digestible carbohydrates in locusts. Finally, we consider existing evidence for the various means available to these and other insects for regulating such relationships. Received 24 September 1997; accepted 9 December 1997.     

Natural control mechanisms in models of aquatic ecosystems

Based on cybernetic categories of natural control mechanisms, four generations of ecosystem models are distinguished: feed-forward, feedback, self-adaptation and self-organization models. The analysis of the natural control mechanisms in aquatic ecosystems suggests that different processes are controlled in different ways, and, although the four mechanisms were identified in historical sequence, they all operate simultaneously. The concept of self-organization of an ecosystem is introduced and specified for a model of an aquatic pelagic ecosystem. The concept of the ecosystem as a multilayer, multigoal and multiechelon hierarchical system with hierarchy of the levels of biological organization is also introduced.     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

Calculating losses of crops in Denmark caused by high ozone levels

In order to help guide air pollution legislation at the European level, harmful air pollution effects on agriculture crops and the consequent economic implications for policy have been studied for more than a decade. Ozone has been labeled as the most serious of the damaging air pollutants to agriculture, where growth rates and consequently yields are dramatically reduced. Quantifying the effects has formed a key factor in policymaking. Based on the widely held view that AOT40 (Accumulated exposure Over Threshold of 40 ppb) is a good indicator of ozone-induced damage, the Danish Eulerian Model (DEM) was used to compute reduced agriculture yields on a 50 km×50 km grid over Europe. In one set of scenarios, a ten year meteorological time series was combined with realistic emission inventories. In another, various idealized emission reduction scenarios are applied to the same meteorological time series. The results show substantial inter-annual variability in economic losses, due in most part to meteorological conditions which varied much more substantially than the emissions during the same period. It is further shown that, taking all uncertainties into account, estimates of ozone-induced economic losses require that a long meteorological record is included in the analysis, for statistical significance to be improved to acceptable levels for use in policy analysis. In this study, calculations were made for Europe as a whole, though this paper presents results relevant for Denmark.     

A New Approach to Plant Diversity Assessment Combining HPLC Data, Simplex Mixture Design and Discriminant Analysis

The quantitative assessment of plant diversity and its monitoring with time represent a key environmental issue for management and conservation of natural resources. Assessment of plant diversity could be based on chemical analyses of secondary metabolites (e.g. flavonoids, terpenoids), because of the substantial quantitative and qualitative between-individual variability in such compounds. At a geographical scale, the plant populations become widely dispersed, and their monitoring from numerous routine individual analyses could become restricting. To overcome such constraint, this study develops a multivariate calibration model giving the relative frequency of a particular taxon from a simple high-performance liquid chromatography (HPLC) analysis of a plant mixture. The model was built from a complete set of mixtures combining different taxons, according to an experimental design (Scheffé’s matrix). For each mixture, a reference HPLC pattern was simulated by averaging the individual HPLC profiles of the constitutive taxons. The calibration models, based on Bayesian discriminant analysis (BDA), gave statistical relationships between the contributions of each taxon in mixtures and reference HPLC patterns of these mixtures. Finally, these models were validated on new mixtures by using outside plants. This new biodiversity survey approach is illustrated on four chemical taxons (four chemotypes) of Astragalus caprinus (Fabaceae). The more differentiated the taxon, the better predicted its contributions (in mixtures) were by BDA calibration model. This new approach could be very useful for a global routine survey of plant diversity.