Critical Steps for Continuing Advancement of Satellite Rainfall Applications for Surface Hydrology in the Nile River Basin1

Gebremichael, Mekonnen, Emmanouil N. Anagnostou, and Menberu M. Bitew, 2010. Critical Steps for Continuing Advancement of Satellite Rainfall Applications for Surface Hydrology in the Nile River Basin. Journal of the American Water Resources Association (JAWRA) 46(2):361-366. DOI: 10.1111/j.1752-1688.2010.00428.x. Abstract: Given the increasingly higher resolution and data accessibility, satellite precipitation products could be useful for hydrological application in the Nile River Basin, which is characterized by lack of reasonably dense hydrological in situ sensors and lack of access to the existing dataset. However, in the absence of both extreme caution and research results for the Nile basin, the satellite rainfall (SR) products may not be used, or may even be used erroneously. We identify two steps that are critical to enhance the value of SR products for hydrological applications in the Nile basin. The first step is to establish representative validation sites in the Nile basin. The validation site will help to quantify the errors in the different kinds of SR products, which will be used to select the best products for the Nile basin, include the errors in decision making, and design strategies to minimize the errors. Using rainfall measurements collected from the unprecedented high-density rain gauge network over a small region within the Nile basin, we indicate that SR estimates could be subject to significant errors, and quantification of estimation errors by way of establishing validation sites is critically important in order to use the SR products. The second step is to identify the degree of hydrologic model complexity required to obtain more accurate hydrologic simulation results for the Nile basin when using SR products as input. The level of model complexity may depend on basin size and SR algorithm, and further research is needed to spell out this dependence for the Nile basin.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

工业企业厂界环境噪声监测中背景噪声监测及修正探讨

针对测量结果修正的相关要求,本文对新颁布的《工业企业厂界环境噪声排放标准》（GB12348-2008）和旧标准《工业企业厂界噪声测量方法》（GB／T12349-1990）在实际工作中的运用进行了比对、分析和探讨,并根据实际工作经验,提出了在背景噪声难以测量的一些特殊情况下的几种解决途径,主要提出噪声源声值与背景声值相差小于3dB（A）时的解决方案。     

Risk assessment tools incorporating human error probabilities in the Japanese small-sized establishment

Although it has been estimated that as many as 80% of all occupational accidents have human errors as a cause, no risk assessment tools incorporating human-related elements have been developed for small companies. Human error probability (HEP) and human error analysis (HEA) have been used for large-scale, safety-critical industries for last three decades, but these tools are not suitable for smaller, more general industries that comprise the majority of accident settings.Here, we describe and verify a risk assessment tool that includes human-related elements for small companies. The tool expands on traditional risk assessment methods, such as matrix, risk graph and numerical scoring method, by adding human-related elements. The tool is easy-to-use in occupational environments, and includes assessments of human behavior and potentially outdated machinery at work place.     

人-机系统事故预防理论研究

分析人-机系统事故发生原因,剖析经典以人失误为主因的事故致因模型存在的不足,在该模型基础上增加"刺激"形成的原因,构建了改进事故致因模型。对两模型进行比较研究,指出人机工程学与防止事故的关系,提出了人机工程学防止事故的方法,并给出人机界面合理性主观评价检查表。研究及论证表明:预防人-机系统事故的本质在于有效防止人失误的发生,除安全管理措施以外,最重要的是人机工程学问题,笔者提出的基于人机工程学的人-机系统事故预防理论,对人-机系统事故的预防起到积极的指导作用。     

综合环境可靠性试验中加速度传感器灵敏度的修正

在综合环境可靠性试验中,加速度传感器的灵敏度会随不同的试验温度产生确定的、可逆的变化,而灵敏度的变化会导致振动控制系统产生系统误差.通过在不同温度下对传感器灵敏度的校准,获得了几种传感器灵敏度的温度变化特性,并提出了通过对变换器设置的传感器灵敏度进行修正,消除试验环境温度引起的系统误差的方法.     

航空维修人为差错影响因素分析中的模糊层次分析法

航空维修中的人为差错影响因素分析对于预防事故发生至关重要,如何定量分析及辨识出主要影响因素是亟待解决的问题。为此,结合航空维修实际,提出运用群组模糊层次分析法对人为差错影响因素进行量化排序和分类,归纳细化了影响因素层次体系,并给出了分析计算流程。以一起由维修人为差错所引发的航空事故为例进行了实证分析,结果表明:该方法能够辨识出航空维修中人为差错产生的主要影响因素,进而对制订最优事故预防方案,控制和减少该类事故的发生有积极意义。同时该方法对其他行业中的人为差错主要影响因素辨识有着一定的参考价值。     

基于层次分析法的Pedersen人因失误模型研究

科技的发展,使机器设备可靠性有了显著提高,工作环境也得到了改善,但由于人的复杂性,人因失误成为主要的致因因素,如何预防和控制人的失误就成为一个非常重要的课题.运用层次分析法的基本原理,结合Pedersen人因失误模型,构建了导致人因失误的层次分析模型,计算结果显示,人在某种状态下承受负荷的能力大小是影响其失误的主要原因.通过实例,证明了计算结果的可靠性,并提出了减少人因失误的建议.     

基于人工神经网络理论的建筑物火灾安全评价研究

依据建筑物火灾危险性的影响因素,应用人工神经网络理论及系统安全方法,建立了建筑物火灾危险性的评价指标体系,该方法摆脱了评价过程中的随机性和参评人员主观上的不确定性及其认识上的模糊性等缺点,大大提高了准确性。为了验证评价模型的准确性,将该理论应用到某高校图书馆火灾危险性评价中,快速、准确地得到了安全评价结果,取得了满意效果,为建筑物防火设计以及安全管理提供了可行的依据。