大数据环境下企业安全绩效管理的基础性问题*

为明晰大数据对安全绩效管理的影响,把握信息时代下企业安全绩效管理的研究方向,基于大数据时代下安全绩效管理内容,阐述数据驱动下安全绩效管理的应用优势,探讨数据驱动下安全绩效管理的研究变革,剖析大数据环境下企业安全绩效管理的数据流向,构建数据驱动下安全绩效管理的框架模型,并提出数据驱动下企业安全绩效管理应用对策。结果表明:基于大数据的安全绩效管理有助于提升企业安全管理水平,也为安全生产系统优化提供理论依据。     

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

Importance of Sediment–Water Interactions in Coeur d’Alene Lake,Idaho, USA: Management Implications

A field study at Coeur dAlene Lake, Idaho, USA, was conducted between October 1998 and August 2001 to examine the potential importance of sediment–water interactions on contaminant transport and to provide the first direct measurements of the benthic flux of dissolved solutes of environmental concern in this lake. Because of potential ecological effects, dissolved zinc and orthophosphate were the solutes of primary interest. Results from deployments of an in situ flux chamber indicated that benthic fluxes of dissolved Zn and orthophosphate were comparable in magnitude to riverine inputs. Tracer analyses and benthic-community metrics provided evidence that solute benthic flux were diffusion-controlled at the flux-chamber deployment sites. That is, effects of biomixing (or bioturbation) and ground-water interactions did not strongly influence benthic flux. Remediation efforts in the river might not produce desired water-quality effects in the lake because imposed shifts in concentration gradients near the sediment–water interface would generate a benthic feedback response. Therefore, development of water-quality models to justify remediation strategies requires consideration of contaminant flux between the water column and underlying sediment in basins that have been affected by long-term (decadal) anthropogenic activities.     

新常态下要科学认识环境管理六个量的关系

针对新常态下环境管理面临的机遇与挑战,本文提出了环境管理工作要树立新的思维,并在此基础上深入剖析了总量与质量、容量与流量、存量与增量的关系。现行的总量控制制度在实施过程中带来的污染减排潜力越来越小,因此,环境管理的目标应从以污染排放控制为主向以环境质量改善为主转变,通过采取具有针对性的差异化容量总量控制管理手段,实现污染排放流量管控,同时,应充分考虑现有环境本底负荷的问题,实现污染存量和可能增量的协同控制,这对于推进环境管理工作的战略转型具有借鉴意义。     

Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition

Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base‐flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite‐nitrate (NO₂‐NO₃), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO₂‐NO₃ concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed‐use and heavily impacted watersheds.     

长庆油田质量安全环保巡察实践

质量安全环保巡察是长庆油田分公司QHSE管理体系的重要组成部分,是升级版的管理体系审核方式,在长庆油田已初见成效。推行“六个三”运行模式,坚持问题导向,紧盯问题突出单位、关键技术和管理岗位,深察管理渎职、监督失职、岗位失责和承包商失信等问题,突出风险管控、质量管理、承包商管理等方面,正向查落实,查压力传导、责任落实,逆向追责任,追溯问题根源,查找管理症结,准确追责问责,倒逼责任归位,达到持续改进QHSE管理的目的。     

Evaluating Infiltration Requirements for New Development Using Extreme Storm Transposition: A Case Study from Dane County,WI

Changes in land use and extreme rainfall trends can lead to increased flood vulnerability in many parts of the world, especially for urbanized watersheds. This study investigates the performance of existing stormwater management strategies for the Upper Yahara watershed in Dane County, WI to determine whether they are adequate to protect urban and suburban development from an extreme rainfall. Using extreme storm transposition, we model the performance of the stormwater infiltration practices required for new development under current county ordinances. We find during extreme rainfall the volume of post‐development runoff from impervious surfaces from a typical site would increase by over 55% over pre‐development conditions. We recommend the ordinance be strengthened to reduce vulnerability to flooding from future urban expansion and the likely increase in the magnitude and frequency of extreme storms.     

THE VULNERABILITY OF WETLANDS TO CLIMATE CHANGE: A HYDROLOGIC LANDSCAPE PERSPECTIVE1

ABSTRACT: The vulnerability of wetlands to changes in climate depends on their position within hydrologic landscapes. Hydrologic landscapes are defined by the flow characteristics of ground water and surface water and by the interaction of atmospheric water, surface water, and ground water for any given locality or region. Six general hydrologic landscapes are defined; mountainous, plateau and high plain, broad basins of interior drainage, riverine, flat coastal, and hummocky glacial and dune. Assessment of these landscapes indicate that the vulnerability of all wetlands to climate change fall between two extremes: those dependent primarily on precipitation for their water supply are highly vulnerable, and those dependent primarily on discharge from regional ground water flow systems are the least vulnerable, because of the great buffering capacity of large ground water flow systems to climate change.     

基于环境地理信息平台的预警系统的构建

随着经济的高速发展,环境污染事故也呈现出上升的势头,环境污染事故不仅造成了环境危害,而且对人民群众的安全产生了重大威胁。鉴于环境污染事故的多发性、危害性,应急处置显然非常重要,而构建强大的应急处置信息系统有助于应急处置和分析决策的顺利进行。本文分析了环境应急处置需求,提出了建立环境污染应急管理信息系统的设计框架。     

Development of categorical mapping for quantitative assessment of eutrophication

Spatial distribution of nutrient and phytoplankton variables is often illustrated using categorical mapping for each variable. However, the assessment of eutrophication cannot be derived from a single parameter since a synthesis of the environmental variables related to eutrophication is required. These shortcomings are further complicated since it is difficult to discriminate between distinct trophic states along natural environmental gradients. In the present work, a methodological procedure for quantitative assessment of eutrophication at a spatial scale was examined in the Gulf of Saronicos, Greece, based on a thematic map generated from the synthesis of four variables characterising eutrophication. The categorical map of each variable was developed using the Kriging interpolation method and four trophic levels were indicated (eutrophic, upper-mesotrophic, lower-mesotrophic and oligotrophic) based on nutrient and phytoplankton concentration scaling. Multi-criteria choice methods were applied to generate a final categorical map showing the four trophic levels in the area. This synthesis of categorical maps for assessing eutrophication at a spatial scale is proposed as a methodological procedure appropriate for coastal management studies.