页岩气压裂作业人因失误结构化辨识方法研究

为提高页岩气压裂作业人因失误辨识结果的全面性和针对性,建立一种结构化的人因失误辨识方法。通过概括辨识阶段的作业流程,建立作业人员行为模型,概述作业人员的行为阶段。利用筛选出的引导词辨识行为阶段人因失误。将该方法应用于页岩气压裂过程的替液阶段。结果表明,用引导词能明确辨识方向,减少头脑风暴时间以及对专家知识的依赖;辨识过程的动态调整能改善认知可靠性,使更多人因失误模式(与传统CREAM方法相比)被辨识出来。     

Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS

This paper describes the utility of QUAL2E as a modelling package in the evaluation of a water quality improvement programme. In this study, QUAL2E was applied to determine the pollution loads in the river Yamuna during its course through the national capital territory of Delhi, India. The study aimed at examining the influence of different scenarios on river water quality. Four different pollution scenarios were analysed besides the 'business as usual' situation. The study revealed that it was necessary to treat the discharge from drains to the river Yamuna and diversion of a substantial load to the Agra canal for further treatment was also essential. It was also established through this study that maintaining a flow rate of more than 10 m(3)/s in the river could also help preserve the river's water quality. To clearly display the model outcomes and demarcate polluted zones in the river stretch, model results were interfaced with a Geographical Information System (GIS) to produce cartographic outputs. In addition, uncertainty analysis in the form of first-order error analysis and Monte Carlo analysis was performed, to realise the effect of each model parameter on DO and BOD predictions. The uncertainty analysis gave satisfactory results on simulated data.     

Rangeland dynamics of southern Ethiopia: (2). Assessment of woody vegetation structure in relation to land use and distance from water in semi-arid Borana rangelands

The structure and advancement of woody vegetation was studied in a semi-arid rangeland of southern Ethiopia under three land-use systems (communal land, a government ranch and a traditional grazing reserve enclosure) and along a distance gradient (near, middle and far) from water sources. A total of 54 woody plant species were identified. Based on the subjective opinions of the pastoralists, 85% of the identified woody plants have forage values to livestock. Cadaba farinsoa, Ormocarpum trichocarpum, Rhus natalensis, Acacia brevispica, Cordia gharaf and Hibiscus sparseaculeatus were reported to have fair to good palatability. Tree equivalent (TE) density of all woody plants combined was greater (P <0.01) in the government ranch (1) 188 TE ha(-1)) and the communal land (1083 TE ha(-1)) than in the traditional grazing reserve (419 TE ha(-1)), whereas this did not vary significantly (P >0.05) along the distance gradient from water. The most important encroaching woody plant species in the study areas were in descending order: Commiphora africana, Acacia drepanolobium, A. brevispica, Acacia. tortilis, Grewia tembensis and Lannea floccosa. The density of individual encroaching woody plant species along the distance gradient from water was not consistent. All encroaching woody species had the highest TE density in the communal land. The prevalence of these species followed the pattern of intensity of use within the communal grazing area. Most of the woody species had the highest abundance in the height class >0-2m regardless of land use and distance gradient from water. This study investigated the advance of severe woody encroachment in the communal and government sites as well as along the distance gradient from water. Some of the important contributing factors that can be suggested are heavy grazing pressure (in both the communal and government sites), expansion of cultivation and reduced mobility of livestock due to settlement of the pastoralists in the communal land.     

Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas

Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.     

重庆三峡库区非点源污染评价与影响因子分析

选取重庆三峡库区4个行政建制镇进行非点源污染监测与调查,以COD、TN、TP、Cu、Zn等指标为主要研究内容对库区农村环境进行污染特性分析并且利用等标污染负荷法对其生活污水、生活垃圾、畜禽养殖、水产养殖、化肥流失、农药流失、水土流失等污染源进行非点源污染评价。结果表明:COD、TN、TP、Cu、Zn的平均排放浓度分别为22.15 mg/L、6.37 mg/L、1.49 mg/L、47.73 g/kg、85.24 g/kg,库区主要污染物依次为TN、TP、COD、Cu、Zn等,主要污染源依次是畜禽养殖、化肥流失、生活污水、生活垃圾、农药流失、水土流失、水产养殖等。采用SPSS软件对影响库区环境污染的季节、收入水平、地域、畜禽养殖规模、环境基础设施完善程度等因子进行了分析,结果显示:COD主要影响因子是地域和畜禽养殖规模,TN主要影响因子是季节、地域和畜禽养殖规模,TP主要影响因子是环境基础设施完善程度、畜禽养殖规模和地域,Cu、Zn主要影响因子均是畜禽养殖规模。该研究可为重庆三峡库区生态修复、城乡统筹下的城乡规划及产业布局提供理论基础。     

基于最优分割理论的酸雨监控点位的分类研究

Fisher最优分割法是用离差平方和来表示同类样本之间的差异程度,通过简便的计算步骤和作图,确定最优分类数,使同类样本间的差异最小,各类别样本间的差异最大,并用F检验法检验最优分类数的合理性。文章根据Fisher最优分割法的理论内涵,研究其应用于酸雨环境监测优化布点的可行性。以漳州市沿海区域监测点为研究实例,用Fisher最优分割法确定最优的分类情况和最优的优化布点方案。结果表明,原布设的9个监测点用Fisher最优分割法优化为3个典型点位,可客观地反映漳州市酸雨控制区的整体污染状况和污染趋势,该方法理论内涵直观、计算简便、重复性好,对环境质量监测有重要的意义。     

纳米二氧化钛与镉对斜生栅藻(Scenedesmus obliquus)生长的拮抗效应及其作用机制

人工纳米材料（MNMs）进入水环境将改变传统环境污染物的环境归趋及其毒性作用,两者的相互作用及其机制一直是环境科学领域的热点问题.迄今为止,已有大量MNMs与现存污染物联合毒性作用的研究成果发表,但其潜在的作用机制,尤其是联合作用下的生物响应机制仍未清楚.本文以典型MNMs——纳米二氧化钛（nTiO₂）与重金属镉（Cd²⁺）为研究目标,以斜生栅藻（Scenedesmus obliquus）为受试生物,考察在等效剂量（毒性比1 ∶1）下不同浓度组合nTiO₂和Cd²⁺对斜生栅藻的联合毒性作用模式及其分子机制.结果表明,等效剂量下Cd²⁺和nTiO₂的72h EC₅₀值对比单独暴露时均有显著升高,呈拮抗效应.进一步开展转录组学分析发现,nTiO₂存在下斜生栅藻能量代谢所涉及的光合作用、叶绿素代谢以及淀粉与蔗糖代谢通路发生了显著上调,与藻细胞抗逆效应相关的精氨酸与脯氨酸代谢通路同样呈正向刺激表现.本文首次报道了nTiO₂与Cd²⁺等效剂量联合暴露下,浮游植物通过改变藻细胞抗逆能力与加强能量代谢来降低毒性的生物响应机制.本研究结果为深入理解MNMs与现存污染物的复合环境健康效应提供重要参考和研究基础.     

THE IMPORTANCE OF ACCURATE CURVE NUMBERS IN THE ESTIMATION OF STORM RUNOFF1

ABSTRACT: Storm runoff as calculated by the runoff curve number method is shown to be of varying sensitivity to both input rainfall and curve number. Using an assumed input error of 10%, a runoff error chart is given. Up to about 9 inches of rainfall, runoff is more sensitive to curve number than to rainfall. The importance of accurate curve number selection in this range is stressed.     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

A taxonomy of performance influencing factors for human reliability analysis of emergency tasks

This paper introduces the process for, and the result of, the selection of performance influencing factors (PIFs) for the use in human reliability analysis (HRA) of emergency tasks in nuclear power plants. The approach taken in this study largely consists of three steps. First, a full-set PIF system is constructed from the collection and review of existing PIF taxonomies. Secondly, PIF candidates are selected from the full-set PIF system, considering the major characteristics of emergency situations and the basic criteria of PIF for use in HRA. Finally, a set of PIFs is established by structuring representative PIFs and their detailed subitems from the candidates. As a result, a set of PIFs comprised of the 11 representative PIFs and 39 subitems was developed.