HYDROLOGIC UNCERTAINTY MEASURE AND NETWORK DESIGN1

ABSTRACT: This paper presents a simple methodology, using the entropy concept, to estimate regional hydro logic uncertainty and information at both gaged and ungaged grids in a basin. The methodology described in this paper is applicable for (a) the selection of the optimum station from a dense network, using maximization of information transmission criteria, and (b) expansion of a network using data from an existing sparse network by means of the information interpolation concept and identification of the zones from minimum hydrologic information. The computation of single and joint entropy terms used in the above two cases depends upon single and multivariable probability density functions. In this paper, these terms are derived for the gamma distribution. The derived formulation for optimum hydrologic network design was tested using the data from a network of 29 rain gages on Sleeper River Experimental Watershed. For the purpose of network reduction, the watershed was divided into three subregions, and the optimum stations and their locations in each subregion were identified. To apply the network expansion methodology, only the network consisting of 13 stations was used, and feasible triangular elements were formed by joining the stations. Hydrologic information was calculated at various points on the line segments, and critical information zones were identified by plotting information contours. The entropy concept used in this paper, although derived for single and bivaviate gamma distribution, is general in type and can easily be modified for other distributions by a simple variable transformation criterion.     

Risk communication in the internet age: The rise of disorganized skepticism

Communicating risks has become a core ingredient in the regulatory functions of government, interest group advocacy, public health, and corporate relations. The channels of risk communication have grown in complexity along with the development and expansion of the Internet and the birth of personalized blogging. This paper discusses three stages in the development of risk communication as an area of study and research. It examines the way risk is framed in three channels of communication, newsprint, the Expanded Academic Index, and Google using the example of the controversial chemical perfluorooctanoic acid (PFOA). The paper concludes that the Internet, as illustrated by the Google search engine, has created more opportunities for citizen learning and expanded the breadth and channels of risk communication, while also providing new opportunities for stakeholders to influence the message. Democritization of information does not necessarily create greater concordance between the cultural and technical assessment of risk.     

The Role of Mineral Weathering Rate Determinations in Generating Uncertainties in the Calculation of Critical Loads of Acidity and their Exceedance

Current legislation within Europe aimed at limitingecosystem damage resulting from inputs of atmosphericpollution is based on the critical load concept. Mineralweathering rates are central to the calculation ofcritical loads (acceptable levels) of acid deposition.The authors have undertaken a number of studies whichillustrate the complications and limitations inherent inpredicting mineral weathering rates and the implicationswhich these have for critical loads calculations andmapping. Calculated weathering rates and critical loadsfor two acid-sensitive parent materials (greywackes andgranites) are presented and are used to illustrate theimpact that uncertainty can have on critical loadexceedances. The results have obvious implications forportraying the uncertainties of critical loads to policy makers.     

An uncertain energy planning model under carbon taxes

In this study, an interval fuzzy mixed-integer energy planning model (IFMI-EPM) is developed under considering the carbon tax policy. The developed IFMIEPM incorporates techniques of interval-parameter programming, fuzzy planning and mixed-integer programming within a general energy planning model. The IFMIEPM can not only be used for quantitatively analyzing a variety of policy scenarios that are associated with different levels of carbon tax policy, but also tackle uncertainties expressed as discrete intervals and fuzzy sets in energy and environment systems. Considering low, medium and high carbon tax rates, the model is applied to an ideal energy and environment system. The results indicate that reasonable solutions have been generated. They can be used for generating decision alternatives and thus help decision makers identify desired carbon tax policy.     

环境风险评价中的不确定性研究

在环境风险评价中经常会遇见不确定性问题,以无水氢氟酸储罐泄漏为例,分别研究了在计算事故发生概率、确定泄漏源、应用扩散模式、评价事故损伤结果等工作中遇到的不确定性问题。并以此分析了造成这些不确定性因素的原因,同时提出相应的解决方法,最后介绍了环境风险评价中不确定性问题的研究现状和方向。     

巢湖塘西河河口湿地重金属污染风险不确定性评价

基于污染风险评价系统多种不确定性共存的特点,采用盲数描述和表征重金属污染风险评价模型的各项参数,在对采自巢湖塘西河河口湿地24个表层沉积物柱状样中Cu,Zn,Pb,Cd和Cr等指标分析测试的基础上,采用Matlab工具软件编制的潜在生态风险指数盲数评价模型程序,对巢湖塘西河河口湿地重金属污染风险进行定量评估. 结果表明:巢湖塘西河河口湿地处于中等污染至较高污染状态,其相应的可信度分别为0.589和0.411;潜在生态风险等级属较低至中等水平,其相应可信度分别为0.755和0.245. 5种重金属污染程度排序依次为Cu＞Cd＞Zn＞Pb＞Cr;潜在生态风险水平排序依次为Cd＞Cu＞Pb＞Cr＞Zn.      

Comparing model averaging with other model selection strategies for benchmark dose estimation

Model averaging (MA) has been proposed as a method of accommodating model uncertainty when estimating risk. Although the use of MA is inherently appealing, little is known about its performance using general modeling conditions. We investigate the use of MA for estimating excess risk using a Monte Carlo simulation. Dichotomous response data are simulated under various assumed underlying dose–response curves, and nine dose–response models (from the USEPA Benchmark dose model suite) are fit to obtain both model specific and MA risk estimates. The benchmark dose estimates (BMDs) from the MA method, as well as estimates from other commonly selected models, e.g., best fitting model or the model resulting in the smallest BMD, are compared to the true benchmark dose value to better understand both bias and coverage behavior in the estimation procedure. The MA method has a small bias when estimating the BMD that is similar to the bias of BMD estimates derived from the assumed model. Further, when a broader range of models are included in the family of models considered in the MA process, the lower bound estimate provided coverage close to the nominal level, which is superior to the other strategies considered. This approach provides an alternative method for risk managers to estimate risk while incorporating model uncertainty.

Dealing with uncertainty in the assessment of human exposure to radioactivity in food and the environment

This paper presents an overview of the approach used to assess radiation dose and risk to members of the public from radioactivity in food and the environment. It describes uncertainties in the process and suggests ways of dealing with them to improve the risk assessment process. It also explains how uncertainty in the assessed dose/risk can be communicated to non-expert audiences such as members of the public. The issues covered in this paper apply to risk assessment of any contaminant and not only radioactivity.     

Minimax regret discounting

The paper considers an environmental policy decision in which the appropriate approach for discounting future costs and benefits is unknown. Uncertainty about the discount rate is formulated as a decision under Knightian uncertainty. To solve this, we employ minimax regret, a decision criterion that is much less conservative then the related criterion maximin—in particular, it can be shown to implement a “proportional response” in that it equally balances concern about the mistake of doing too little with that of doing too much. Despite the criterion's balanced nature, the minimax regret solution mimics a policy that maximizes the present discounted value of future net benefits with an effective (certainty-equivalent) discount rate that declines over time to the lowest possible rate. In addition to reinforcing Weitzman's (1998) original limiting result, the approach generates concrete policy advice when decision makers are unable to specify a prior over possible discount rates. We apply it to the Stern–Nordhaus discounting debate and find that the effective discount rate converges to the Stern rate in just under 200 years.