Analysing the sensitivity behaviour of two hydrology models

Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects) and the extent these parameters interact with each other (second-order effects). This method requires the specification of two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock.     

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建立了固相萃取、毛细柱气相色谱-电子捕获检测器定量分析水中硝基苯类化合物的分析方法。通过对固相萃取柱的选择、固相萃取条件(样品溶液的pH值、上样速度、上样体积、洗脱液选择及配比)的优化,得出了最佳实验条件。穿透体积可达1.5L,回收率在80%~105%,最小检出浓度在0.00037~0.072μg/L之间,均大大低于GB13194-91的规定。相对标准偏差在0.7%~5.3%之间。该方法准确、简单,重现性好、回收率高,污染小。     

在线自动监测仪与实验室国标方法测定地表水中总氮的比对分析

随着监测技术的发展,地表水中越来越多的污染物可采用自动监测仪器实现实时监测。采用自动监测与实验室国标方法测定地表水中总氮的结果是否可比以及造成差异的原因,文章根据实际样品比对实验对此进行了探讨。     

沈阳市大气可吸入颗粒物水溶性组分的因子分析

选取沈阳市6个监测点位,采集2005年冬、春、夏、秋大气可吸入颗粒物样本。用安捷伦7500型电感耦合等离子体质谱仪分析PM10中19种水溶性组分。用因子分析法分析了沈阳市大气可吸入颗粒物水溶性组分的来源。     

玄武湖沉积物中磷的形态分布特征

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盐酸萘乙二胺比色法测定大气中硝基苯、苯胺浓度的改进

本文探讨了盐酸萘乙二胺比色方法测定大气中硝基苯、苯胺浓度的最佳反应条件,如酸度、试剂加入量、反应温度、反应时间等。简化了过滤、洗涤操作,精密度高、显色稳定。     

环境影响预测中基准值问题的探讨

鉴于目前环境影响预测中基准值取法存在的问题,提出了结合目前通用做法与灰色预测的灰靶方案,该方案使得环境影响预测结果在一定范围内变化,从而更为切合评价实际。     

B—P网络逐步聚类法在环境测点优选中的应用

将Ｂ－Ｐ网络原理与逐步聚类分析思想相结合,用于环境测点聚类优选。该方法用于水清河几个监测断面的优选结果是符合客观实际的。     

城市空气质量周报效用分析

介绍了世界上一些发达国家的空气污染预报的做法和采取的措施,阐述了我国开展空气质量预报的方针和方法,指出了周报是预报的基础工作。叙述了我国空气质量周报的污染参数的选取、污染指数的分级及其浓度限值和污染指数计算及确定,分析并总结了开展城市空气质量周报所发挥的效用是提高公众的环保意识,加大了治理污染的力度,转变了环境监测的职能,促进了环境监测事业的发展     

大气颗粒物样品中有机碳和元素碳的测定

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