Risk communication in emergency response to a simulated extreme flood

Risk communication in flood incident management can be improved through developing hydrometeorological and engineering models used as tools for communicating risk between scientists and emergency management professionals. A range of such models and tools was evaluated by participating flood emergency managers during a 4-day, real-time simulation of an extreme event in the Thamesmead area in the Thames estuary close to London, England. Emergency managers have different communication needs and value new tools differently, but the indications are that a range of new tools could be beneficial in flood incident management. Provided they are communicated large model uncertainties are not necessarily unwelcome among flood emergency managers. Even so they are cautious about sharing the ownership of weather and flood modelling uncertainties.     

Assessing Uncertainty in Estimates of Nitrogen Loading to Estuaries for Research, Planning, and Risk Assessment

Parametric (propagation for normal error estimates) and nonparametric methods (bootstrap and enumeration of combinations) to assess the uncertainty in calculated rates of nitrogen loading were compared, based on the propagation of uncertainty observed in the variables used in the calculation. In addition, since such calculations are often based on literature surveys rather than random replicate measurements for the site in question, error propagation was also compared using the uncertainty of the sampled population (e.g., standard deviation) as well as the uncertainty of the mean (e.g., standard error of the mean). Calculations for the predicted nitrogen loading to a shallow estuary (Waquoit Bay, MA) were used as an example. The previously estimated mean loading from the watershed (5,400 ha) to Waquoit Bay (600 ha) was 23,000 kg N yr⁻¹. The mode of a nonparametric estimate of the probability distribution differed dramatically, equaling only 70% of this mean. Repeated observations were available for only 8 of the 16 variables used in our calculation. We estimated uncertainty in model predictions by treating these as sample replicates. Parametric and nonparametric estimates of the standard error of the mean loading rate were 12–14%. However, since the available data include site-to-site variability, as is often the case, standard error may be an inappropriate measure of confidence. The standard deviations were around 38% of the loading rate. Further, 95% confidence intervals differed between the nonparametric and parametric methods, with those of the nonparametric method arranged asymmetrically around the predicted loading rate. The disparity in magnitude and symmetry of calculated confidence limits argue for careful consideration of the nature of the uncertainty of variables used in chained calculations. This analysis also suggests that a nonparametric method of calculating loading rates using most frequently observed values for variables used in loading calculations may be more appropriate than using mean values. These findings reinforce the importance of including assessment of uncertainty when evaluating nutrient loading rates in research and planning. Risk assessment, which may need to consider relative probability of extreme events in worst-case scenarios, will be in serious error using normal estimates, or even the nonparametric bootstrap. A method such as our enumeration of combinations produces a more reliable distribution of risk.     

燃气泄漏风险评价中不确定性问题的探讨

讨论了燃气泄漏事故风险评价中泄漏的发生、泄漏源强度、扩散模式的不确定性问题。提供了确定瞬时泄漏和连续泄漏的方法 ,以及判定重气扩散时转变为中性阶段的准则。最后介绍了不确定性问题的研究方法。     

Importance of scientific uncertainty in decision making

Uncertainty in environmental decision making should not be thought of as a problem that is best ignored. In fact, as is illustrated in a simple example, we often informally make use of awareness of uncertainty by hedging decisions away from large losses. This hedging can be made explicit and formalized using the methods of decision analysis. While scientific uncertainty is undesirable, it can still be useful in environmental management as it provides a basis for the need to fund additional monitoring, experimentation, or information acquisition to improve the scientific basis for decisions.     

Assessing and communicating data quality in policy-relevant research

The quality of scientific information in policy-relevant fields of research is difficult to assess, and quality control in these important areas is correspondingly difficult to maintain. Frequently there are insufficient high-quality measurements for the presentation of the statistical uncertainty in the numerical estimates that are crucial to policy decisions. We propose and develop a grading system for numerical estimates that can deal with the full range of data quality—from statistically valid estimates to informed guesses. By analyzing the underlying quality of numerical estimates, summarized as spread and grade, we are able to provide simple rules whereby input data can be coded for quality, and these codings carried through arithmetical calculations for assessing the quality of model results. For this we use the NUSAP (numeral, unit, spread, assessment, pedigree) notational system. It allows the more quantitative and the more qualitative aspects of data uncertainty to be managed separately. By way of example, we apply the system to an ecosystem valuation study that used several different models and data of widely varying quality to arrive at a single estimate of the economic value of wetlands. The NUSAP approach illustrates the major sources of uncertainty in this study and can guide new research aimed at the improvement of the quality of outputs and the efficiency of the procedures.     

Uncertainty analysis framework for tubular connection sealability of underground gas storage wells

The seal failure of tubing and casing connections compromises underground gas storage well safety. This work proposes a systematic uncertainty analysis framework for connection sealability assessment. The framework covers reliability analysis and reliability sensitivity analysis and attempts to provide more effective support for the reliability design of connection seals. The reliability analysis introduces an adaptive Kriging with stopping criterion P-Monte Carlo simulation (AKP-MCS) method, which can provide a satisfactory estimate of failure probability with a small number of performance function evaluations. This metamodeling technology can effectively reduce the numerical efforts required for the reliability assessment of connection sealability. In the reliability sensitivity analysis, the refined metamodel obtained from the reliability analysis is coupled into a single-loop Monte Carlo simulation (MCS) method. The classifier attribute of this metamodel can meet the requirement of the single-loop MCS method to classify the signs of sampling points. This attribute enables sample matrices to be evaluated on this metamodel instead of the performance function, making the reliability sensitivity assessment more feasible. The proposed method is first demonstrated with four academic examples with promising results. Next, an illustrative tubular connection case is provided. The proposed scheme gives estimates of the failure probability and reliability sensitivity close to the classical model but requires less computational cost. The results of the analysis can provide useful information for the scheme decision-making and reliability optimization of connection seal design.     

原子荧光光度法同时测定水中砷、硒的不确定度分析

对原子荧光光度法测定水样中砷、硒浓度的影响因素进行分析,对各因素的不确定度进行计算和评估。结果表明,影响其测量不确定度主要因素是原子荧光强度值带来的不确定度,其它因素是次要的。     

不确定性校正对地震危险性分析结果的影响

对现行地震危险性分析模型中的不确定性校正方法所涉及到的一些问题进行了讨论．以地震烈度的危险性分析为例,说明危险性曲线的衰减系数及不确定性大小是影响校正结果的主要因素．总的趋势是：对低烈度,校正后危险性有所降低,降低幅度达50％以上;对高烈度,校正后危险性有所提高,提高幅度可达数倍以上。     

4-氨基安替比林分光光度法测定挥发性酚的不确定度分析

测量不确定度是近年兴起的一种对测量结果可信程度的表示方式，这种方式将会在环境监测分析中推广和应用。依据《测量不确定度评定与表示指南》，在挥发性酚测量时找出影响测量的各个因素（分量），建立满足测量不确定度所需的数学模型。并对其进行评定，再将这些分量的不确定度合成，最终估算出挥发性酚的总不确定度。其结果能如实反应测量的置信度和准确度。     

水样中铵氮测量的不确定度评定

通过对铵氮测定过程的分析,找出了影响测定结果的各个分量。影响测定结果的分量主要有:标准溶液、回归曲线、试样平行试验、纳氏试剂分光光度法、分光光度计,取样等。在此基础上对测量的不确定度进行了评定,并按照计量技术规范,给出了标准的表示法。