利用信息扩散模式对安徽及华东地区地震的风险分析

本文利用信息扩散模式,分别从年地震频次和年最大震级两个方面对安徽及华东地区的地震风险进行评估.结果显示:安徽地区ML≥3.0地震,年频次4次以上,约两年一遇;年发生ML≥3.9地震,则3年可能遇一次.而华东地区ML≥4.0地震,年频次4次以上,大约3年一遇;年发生ML≥4.9的地震,则可能2年遇一次.     

自然灾害风险区划图的一个潜在发展方向

由于自然灾害系统的复杂性及数据资料的不完备性,人们不可能精确估计任何自然灾害发生的概率,"概率值估不准"是现有超越概率风险区划图的致命弱点.简要回顾了针对这一问题已进行的提高估计精度和进行模糊风险计算的有关研究,并将模糊风险研究引入风险区划图的编制,给出了自然灾害软风险区划图的定义和一个初步的样式.讨论了这种风险图在体现风险值估不准方面,以及在为用户提供更多风险信息,为决策者提供调整余地等方面的优点.研究结果表明,软风险区划图是自然灾害风险区划图的一个潜在发展方向.为推进这一研究领域的发展,对今后的工作提出了一些建议.     

信息不对称下的金融风险机理研究

利用信息不对称理论对市场交易中的道德风险和逆向选择进行了解释。对国家同商业银行及中介机构的信息不对称,商业银行同工商企业的信息不对称,国家金融机构信息获取方面存在的困难的原因进行了分析。研究了由于信息不对称利率、汇率、管理及决策在金融行业的风险,以及操作过程中,贷款对象选择,对中小企业贷款的风险。只要充分重视金融风险,采取得当的防范对策,风险是可以防范的。     

数字消防--消防信息化的开放模式

针对当前消防信息化建设中存在的开放性不足的问题,提出了一种开放的建设模式--数字消防.在探讨数字消防的性质和特点的基础上,对我国数字消防的功能需求进行了系统分析,并对实践中出现的"由总队主导的数字消防模式"和"由民防主导的数字消防模式"进行了探讨分析.最后,针对需要进一步解决的问题提出了相应的建议.     

基于GIS技术的海塘防洪减灾信息系统

海塘工程的规划、设计、建设、维护和管理,对沿海省份经济发展和人民生命财产的安全十分重要,历来受到政府和沿海居民的高度重视.介绍了基于GIS技术的海塘防洪减灾信息系统的主要功能及逻辑结构,分析了海塘数据库的特点,详细讨论了海塘属性和空间数据库的建库内容及方法.最后通过应用实例,验证了系统技术路线的合理性、正确性和实用性.     

我国油气企业环境会计核算及信息披露的探讨

在国民经济中占有主导地位的油气企业同时也是造成环境污染的主体之一。因此,建立油气企业环境会计制度有极其重要的现实意义。文章针对我国油气企业环境会计制度应用现状,运用环境会计基本理论,对企业环境会计核算方法及信息传播模式进行了探讨,以期为油气企业环境会计制度的实施提供一些理论依据和具体方法,推动油气企业环境会计制度的发展。     

MODELING THE DISTRIBUTION OF DIFFUSE NITROGEN SOURCES AND SINKS IN THE NEUSE RIVER BASIN OF NORTH CAROLINA,USA1

This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km² Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).     

采油厂HSE监督检查管理系统创建实践研究

本文根据采油厂生产过程风险特点,以生产单元为对象,通过建立全员参与的HSE监督检查体系,实现对采油厂HSE监督检查标准的统一规范,利用开发的HSE监督检查信息集成平台,创建完成采油厂HSE监督检查管理系统。在大庆油田第五采油厂的应用实践显示,其能为采油厂带来巨大的风险管理效益,是全面落实直线与属地HSE责任的有效载体。对于采油厂有效实施HSE监督检查具有重大意义,是HSE管理制度的一种创新。     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

Environmental cost of using poor decision metrics to prioritize environmental projects

Conservation decision makers commonly use project‐scoring metrics that are inconsistent with theory on optimal ranking of projects. As a result, there may often be a loss of environmental benefits. We estimated the magnitudes of these losses for various metrics that deviate from theory in ways that are common in practice. These metrics included cases where relevant variables were omitted from the benefits metric, project costs were omitted, and benefits were calculated using a faulty functional form. We estimated distributions of parameters from 129 environmental projects from Australia, New Zealand, and Italy for which detailed analyses had been completed previously. The cost of using poor prioritization metrics (in terms of lost environmental values) was often high—up to 80% in the scenarios we examined. The cost in percentage terms was greater when the budget was smaller. The most costly errors were omitting information about environmental values (up to 31% loss of environmental values), omitting project costs (up to 35% loss), omitting the effectiveness of management actions (up to 9% loss), and using a weighted‐additive decision metric for variables that should be multiplied (up to 23% loss). The latter 3 are errors that occur commonly in real‐world decision metrics, in combination often reducing potential benefits from conservation investments by 30–50%. Uncertainty about parameter values also reduced the benefits from investments in conservation projects but often not by as much as faulty prioritization metrics.