Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

中小企业的安全投入行为研究

在分析安全事故的"外部性"和"不确定性"特征的基础上,探讨安全事故的特征对企业安全投入行为的影响。我国中小企业安全投入不足的原因甚多:员工生命价值低估导致人员伤亡赔偿偏低、我国劳动力供大于求的现状、中小企业安全投资决策缺乏科学性等。我国劳动力市场供大于求的状况短期内无法改变,只能通过强化政府的激励和监管作用,促进中小企业建立科学的安全投资决策支持系统,以提高中小企业安全投入水平。     

一种湿度计的校准方法——测量不确定度分析校准法

本文提出了校准湿度计的一种新方法一测量不确定度分析校准法,以利用5121湿度发生器校准可输出（0-5）V的湿度传感器的基本误差为例,介绍了其校准方法确定了该方法校准湿度计的置信度和准确葭：     

An approach to optimise nutrient management in environmental sanitation systems despite limited data

The material flow analysis method can be used to assess the impact of environmental sanitation systems on resource consumption and environmental pollution. However, given the limited access to reliable data, application of this data-intensive method in developing countries may be difficult. This paper presents an approach allowing to develop material flow models despite limited data availability. Application of an iterative procedure is of key importance: model parameter values should first be assessed on the basis of a literature review and by eliciting expert judgement. If model outputs are not plausible, sensitive input parameters should be reassessed more accurately. Moreover, model parameters can be expressed as probability distributions and variable uncertainty estimated by using Monte Carlo simulation. The impact of environmental sanitation systems on the phosphorus load discharged into surface water in Hanoi, Vietnam, is simulated by applying the proposed approach.     

低温试验能力验证中的不确定度分析评估

本文简述电气领域如何评定测量不确定度过程,并结合CNAS T0346低温试验能力验证计划,识别和具体分析低温试验中各测量不确定度的来源,对各种影响因素进行评价,论述人、机、料、法、环、测各环节对测量结果的影响,给出了低温试验测量结果不确定度的评估过程。     

电源变压器温升试验中（绕组法）的影响因素及不确定度的评估

本文中探讨的是根据绕组法计算电源变压器绕组温升的试验方法,以及对整个试验过程中环境、仪器设备、仪表、人为因素所引起的误差等对最终试验结果的影响,并对其测量不确定度进行评估。     

污染源排气自动监测氮氧化物的不确定度分析

使用烟气排放连续监测系统自动监测仪器测定污染源排气中氮氧化物,按照最新的《测量不确定度评定与表示》(JJF1059.1—2012)的要求,测量不确定度评定的要求,首次对其氮氧化物自动监测的不确定度进行分析,得出不确定度报告。     

Factors affecting the quantitative uncertainty of the estimated short-term intake. Part I—Calculation methods

ABSTRACT

The calculation of the combined uncertainty of the international estimated short-term intake (IESTI) of ethephon residues in apples is shown as an example. The ethephon residues in apples were reported by the Joint FAO (Food and Agriculture Organization of the United Nations)/WHO (World Health Organization) Meeting on Pesticide Residues (JMPR). The apple consumption data were taken from the IESTI (international short-term intake) calculation template used by the JMPR. The IESTI was calculated with the currently used method (case 2a) and a proposed one recommended by the EFSA (European Food Safety Authority)/RIVM (Dutch National Institute for Public Health) Scientific Workshop co-sponsored by FAO and WHO. In this example, the ratio of IESTI_proposed/IESTI_current and their combined relative uncertainty are about 2.8, and 1.7, respectively. The larger IESTI and uncertainty obtained with the proposed equation are the consequence of calculation only with the large portion (LP) instead of its combination with unit mass, and the MRL instead of the highest residue (HR). The LP is the major contributor to the combined uncertainty. Both the calculated IESTI and its combined uncertainty depend on the actual food – pesticide residue combination, and should be calculated for each case.     

Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Estimation of sampling uncertainty for determination of pesticide residues in plant commodities

In order to provide residue data for refining the estimated sampling uncertainty, a coordinated research program was initiated for performing field studies on residues in individual items of leafy vegetables, small and large crops. The trials were carried out in 13 countries with 3 small fruits, 5 large crops, 2 medium/large crops and 3 leafy vegetables. The 25 pesticide active ingredients applied represented the dicarboximide (3), organophosphorus (8), synthetic pyrethroids (5), phthalimides (2), organochlorine (1) and other types of pesticides (6). In addition, 11 supervised field trials were performed in grapes and lettuce by the pesticide manufacturers, and their results were provided for evaluation. The studies represented actual agriculture practice around the world, and provide reliable data for estimation of sampling uncertainty. Based on the 12346 residue data, the best estimate for the relative sampling uncertainty for composite samples, assuming sample size of 10 for small crops and leafy vegetables and 5 for large crops, with 95% confidence limits in brackets are: small commodities: 0.25 (0.20–0.29); Brassica leafy vegetables: 0.20 (0.16–0.24); large commodities: 0.33 (0.29–0.38).