草原生态系统模式中参数不确定性导致的模拟结果不确定性研究

基于五变量草原生态系统理论模式,应用与参数有关的条件非线性最优扰动(CNOP-P)方法,探讨了由参数不确定性导致的草原生态系统模式模拟结果的不确定性问题。参数的不确定性可能来源于观测和（或）对物理过程描述等的不确定性。选取了五变量草原生态系统模式中具有物理意义的32个模式参数进行数值试验。试验结果表明,对所考察的32个模式参数,在一定的不确定性和给定的优化时刻范围内,单独优化每个参数所得CNOP-Ps的联合模态与同时优化32个参数所得CNOP-P的模态并不相同。比较了上述两类参数误差以及随机参数误差对草原生态系统模拟的差异。随机参数误差与上述优化方法所得参数误差的不确定性范围大小相同。数值结果表明,同时优化32个参数所得 CNOP-P 类型参数误差使得草原生态系统模拟的不确定性程度最大。这种影响表现在使得草原生态系统转变为沙漠生态系统,或者使得草原生态系统转变为具有更多生草量的草原生态系统。上述数值结果不依赖于优化时间和参数不确定性程度的大小。这些数值结果建议我们应当考虑多参数的非线性相互作用来研究草原生态系统模式模拟的不确定性问题,并且揭示出CNOP-P方法是讨论上述问题的一个有用的工具。     

初值不确定性对暴雨数值预报影响的初步研究

为了研究初值不确定性对我国南方暴雨数值预报的影响,依据历史降水资料的统计分型,选取华南暴雨型、江淮暴雨型和黄淮暴雨型等三类型中具有代表性的暴雨过程,采用AREM模式以不同资料分析场(常规观测资料、NCEP和ERA40同化分析资料)作为初值进行暴雨预报对比试验。试验结果表明,对于各类型暴雨,不同资料初值的差异都会引起暴雨数值预报结果的较大差异;在此基础上,采用经验正交函数(EOF)分析方法,分析了各类暴雨初值误差及其变化信息,从中提取出主要的误差分量,并对这类误差的数值预报影响进行了敏感性试验和预报验证,结果显示,寻找和消除主要的初值误差,对改进暴雨数值预报结果具有重要作用。     

多模型方法在非点源污染负荷中的应用展望

对非点源污染进行定量化和有效控制的方法是通过非点源污染负荷模型对各类非点源的形成、迁移转化以及负荷量进行模拟。然而,流域非点源污染模型的不确定性是单一模型模拟污染负荷面临的重大挑战。借鉴多模型方法在降低水文模型不确定性方面的优越性,通过分析水文模型与非点源污染模型的相通性,提出多模型方法在非点源污染负荷中应用的基本思路并分析了多模型方法在非点源污染负荷估算中面临的挑战,总结了多模型方法在非点源污染负荷应用中的重点和难点问题。     

污染地下水治理过程不确定性的影响因素分析

污染含水层系统中地下水质的恢复之所以往往收效不大，在于地下水去除污染过程中存在诸多不确定性因素。文中把之分为两类：一类具有客观不确定性；另一类则具有主观不确定性。前一类中包括：(1)污染含水层介质的非均一性；(2)污染物的非平衡吸附作用；(3)污染物吸附分配系数的非均一性；(4)部分有机污染物的非水溶性；(5)PAT方案中非完整井以及水流的影响等。后一类则包括数值模拟中模型的概化以及参数的取值等。最后，概述了研究此类问题较为有效的方法，即应包括问题的定义、不确定性分析以及风险(或失效)评估等。     

电感耦合等离子体发射光谱法测定矿石中7种元素的结果不确定度评价

对电感耦合等离子体发射光谱法测定矿石中铜、铅、锌、钾、钠、钛、钒7种元素的整个实验过程可能引入的各种不确定度来源进行分析,并对各种不确定度分量进行量化计算,最后得出合成标准不确定度和扩展不确定度,给出测试结果。     

Method of Data Reduction and Uncertainty Estimation for Platinum-Group Element Data Using Inductively Coupled Plasma-Mass Spectrometry

A data reduction method is described for determining platinum-group element (PGE) abundances by inductively coupled plasma-mass spectrometry (ICP-MS) using external calibration or the method of standard addition. Gravimetric measurement of volumes, the analysis of reference materials and the use of procedural blanks were all used to minimise systematic errors. Internal standards were used to correct for instrument drift. A linear least squares regression model was used to calculate concentrations from drift-corrected counts per second (cps). Furthermore, mathematical manipulations also contribute to the uncertainty estimates of a procedure. Typical uncertainty estimate calculations for ICP-MS data manipulations involve: (1) Carrying standard deviations from the raw cps through the data reduction or (2) calculating a standard deviation from multiple final concentration calculations. It is demonstrated that method 2 may underestimate the uncertainty estimate of the calculated data. Methods 1 and 2 do not typically include an uncertainty estimate component from a regression model. As such models contribute to the uncertainty estimates affecting the calculated data, an uncertainty estimate component from the regression must be included in any final error calculations. Confidence intervals are used to account for uncertainty estimates from the regression model. These confidence intervals are simpler to calculate than uncertainty estimates from method 1, for example. The data reduction and uncertainty estimation method described here addresses problems of reporting PGE data from an article in the literature and addresses both precision and accuracy. The method can be applied to any analytical technique where drift corrections or regression models are used.     

不确定度评定及在产品符合性判定中的应用金属铟中锡的 ICP-AES 测定方法

建立了金属铟中锡的 ICP-AES 测定方法过程的数学模型,通过分析得到了对测定结果正确度影响的不确定度来源,评定了各个不确定度度分量、合成标准不确定度和扩展不确定度。并通过对标准方法的重复性、再现性等概念的讨论,说明了不确定度值在产品等级判定上的使用。     

X射线荧光光谱法检测Au质量分数不确定度的评定——以样品Au750为例

为了使测量结果更加科学,其不确定度的评定就越来越重要。在运用X射线荧光光谱法检测贵金属质量分数的过程中,测量系统以标准曲线法为基础,测量仪器直接给出测量结果,故可将该测量方法等同于直接测量。以样品Au750为例,探讨了测量不确定度的评定过程与步骤。结果显示,该方法测量结果的不确定度来源主要与测量系统有关,其主要的不确定度分量有标准样品的给定值与误差、仪器的分辨率、准确度以及校准不确定度等,忽略了环境及操作不当的人为影响因素。该评定过程简化,评定方法趋干合理。     

Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM) parameterization schemes, meteorological forcing, and land surface parameters on land surface hydrological simulations, and explore to what extent the quality can be improved, a series of experiments with different LSMs, forcing datasets, and parameter datasets concerning soil texture and land cover were conducted. Six simulations are run for the Chinese mainland on 0.1° × 0.1° grids from 1979 to 2008, and the simulated mon...     

大尺度水循环模拟系统不确定性研究进展(英文)

The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects:uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.