IMPACT OF VARIED DATA RESOLUTION ON HYDRAULIC MODELING AND FLOODPLAIN DELINEATION1

ABSTRACT: Current data collection technologies such as light detection and ranging (LIDAR) produce dense digital terrain data that result in more accurate digital terrain models (DTMs) for engineering applications. However, such data are redundant and often cumbersome for hydrologic and hydraulic modeling purposes. Data filtering provides a means of eliminating redundant points and facilitates model preparation. This paper demonstrates the impact of varied data resolution on a case study completed for a 2.3 mi² area with mild slopes (about 001 ft/ft) along Leith Creek near Laurinburg, North Carolina. For the original data set and seven filtered data sets, filtering induced changes in elevation, area, and hydraulic radius were determined for 10 water depths at 23 cross sections. Water surface elevations resulting from HEC‐RAS (Hydrologic Engineering Center‐River Analysis System) models for each data set were then compared. A hydraulic model sensitivity analysis was also conducted to compare filtering error to error introduced by variation in flow rates and roughness values. Finally, automated floodplain delineation was performed for each filter level based on the computed hydraulic model results and the filtered LIDAR elevations. Data filtering results indicate that significant time savings are achieved throughout the modeling process and that filtering to four degrees can be performed without compromising cross‐sectional geometry, hydraulic model results, or floodplain delineation results.     

A FRAMEWORK FOR QUANTITATIVE SMART GROWTH IN LAND DEVELOPMENT1

ABSTRACT: Increasing awareness about the problems brought on by urban sprawl has led to proactive measures to guide future development. Such efforts have largely been grouped under the term “Smart Growth.” Although not widely recognized as such, the “smart” in Smart Growth implies an optimization of some quantity or objective while undertaking new forms of urban development. In this study, we define Smart Growth as that development plan that leads to the optimal value of a precisely defined measure identified by a stakeholder or stakeholders. To illustrate a formal, quantitative framework for Smart Growth, this study develops definitions of optimal development from the perspectives of four different types of stakeholders: a government planner, a land developer, a hydrologist, and a conservationist subject to certain development constraints. Four different objective functions are posed that are consistent with each of these stakeholders’perspectives. We illustrate the differences in consequences on future development given these different objective functions in a stylized representation for Montgomery County, Maryland. Solutions to Smart Growth from the individual perspectives vary considerably. Tradeoff tables are presented that illustrate the consequences experienced by each stakeholder depending on the viewpoint that has been optimized. Although couched in the context of an illustrative example, this study emphasizes the need to apply rigorous, quantitative tools in a meaningful framework to address Smart Growth. The result is a tool that a range of parties can use to plan future development in ways that are environmentally and fiscally responsible and economically viable.     

林业企业信息系统中数据库的安全性研究

本文对林业企业信息系统中数据库安全的重要性、数据库的主要安全特点等进行了分析，并列举了数据库安全性控制的三种方法：即口令保护、数据加密和存取控制。     

Soil emissions of NO, N2O and CO2 from croplands in the savanna region of central Brazil

In the last 40 years, a large area of savanna vegetation in Central Brazil (Cerrado) has been converted to agriculture, with intensive use of fertilizers, irrigation and management practices. Currently, the Cerrado is the main region for beef and grain production in Brazil. However, the consequences of these agricultural practices on NO, N₂O and CO₂ emissions from soil to atmosphere are still poorly investigated. The objectives of this study were to quantify soil emissions of NO-N, N₂O-N and CO₂-C in different no-till cultivation systems in comparison with native savanna vegetation. The agricultural areas included: (a) the maize and Brachiaria ruzizienses intercropping system followed by irrigated bean in rotation; (b) soybean followed by natural fallow; and (c) cotton planting over B. ruzizienses straw. The study was performed from August 2003 to October 2005 and fluxes were measured before and after planting, after fertilizations, during the growing season, before and after harvesting. NO-N fluxes in the soybean field were similar to those measured in the native vegetation. In the cornfield, higher NO-N fluxes were measured before planting than after planting and pulses were observed after broadcast fertilizations. During Brachiaria cultivation NO-N fluxes were lower than in native vegetation. In the irrigated area (bean cultivation), NO-N fluxes were also significantly higher after broadcast fertilizations. Most of the soil N₂O-N fluxes measured under cultivated and native vegetation were very low (<0.6 ng N₂O-N cm⁻² h⁻¹) except during bean cultivation when N₂O-N fluxes increased after the first and second broadcast fertilization with irrigation and during nodule senescence in the soybean field. Soil respiration values from the soybean field were similar to those in native vegetation. The CO₂-C fluxes during cultivation of maize and irrigated bean were twice as high as in the native vegetation. During bean cultivation with irrigation, an increase in CO₂-C fluxes was observed after broadcast fertilization followed by a decrease after the harvest. Significantly lower soil C stocks (0-30 cm depth) were determined under no-tillage agricultural systems in comparison with the stocks under savanna vegetation. Fertilizer-induced emission factors of N oxides calculated from the data were lower than those indicated by the IPCC as default.     

Stakeholders and environmental management systems: a synergistic influence on environmental imbalance

This article analyzes the combined effects of stakeholder pressure and the implementation of environmental management systems on organizations’ environmental behaviors. Beyond their individual effects, the implementation of an environmental management system should enhance the effect of stakeholder pressure on environmental imbalance, defined as the divergence between what the organization does and what it should do. Information collected from 3748 industrial plants in seven countries provides empirical evidence that supports the study propositions. Therefore, this study contributes to both the debate about the effectiveness of environmental management systems and the effort to explain the complex relationship between organizations and their stakeholders in environmental matters.     

物流与安全

论述了物流与安全的发展过程,研究了物流与安全的密切关系,物流被誉为企业的"第三利润源",安全就能使其实现"第四利润",良好的物流系统工程应该是安全的系统工程,提出了促进物流与安全协调发展的策略.     

计算机辅助故障模式影响分析与事件序列图综合分析方法研究

故障模式影响分析(Failure Mode Effect Analysis, FMEA)和事件序列图(Event Sequence Diagram, ESD)是分析系统故障因果关系的两种常用技术,在分别独立应用时,既有各自的优点,也存在着一定的缺陷和不足,主要体现为: FMEA不能展示故障模式到故障后果的推演过程; ESD模型的合理性很大程度上取决于初始事件的确定,而该方法本身不能实现这一功能.本文综合FMEA与ESD的优点,阐述了复杂动态系统FMEA与ESD综合分析的思路,对现有FMEA进行了一定的改进,并进一步分析计算机辅助FMEA和ESD综合方法建模的原理和实现技术.     

基于群集动力学模型的密集场所人群疏散问题研究

密集场所人群疏散问题直接关系到大型公共场所的安全保障能力.应用群集动力学理论方法,在密集人群群体流动过程和个体流动过程分析的基础上,对已有的人群疏散数学模型进行改造,使之更加符合实际意义.以实际人群密集场所为例,进行数值仿真,寻求一定人流密度和疏散时间约束下的最佳疏散通道宽度以及关于开放疏散出口数量的最佳疏散策略,以达到最佳的疏散效果.为有效解决应急环境下密集场所人群疏散问题提供了理论依据,可用于指导密集场所建筑物的结构设计改进,以及疏散过程中的调度管理优化等.     

Methodological issues in forestry mitigation projects: a case study of Kolar district

There is a need to assess climate change mitigation opportunities in forest sector in India in the context of methodological issues such as additionality, permanence, leakage and baseline development in formulating forestry mitigation projects. A case study of forestry mitigation project in semi-arid community grazing lands and farmlands in Kolar district of Karnataka, was undertaken with regard to baseline and project scenario development, estimation of carbon stock change in the project, leakage estimation and assessment of cost-effectiveness of mitigation projects. Further, the transaction costs to develop project, and environmental and socio-economic impact of mitigation project was assessed. The study shows the feasibility of establishing baselines and project C-stock changes. Since the area has low or insignificant biomass, leakage is not an issue. The overall mitigation potential in Kolar for a total area of 14,000 ha under various mitigation options is 278,380 t C at a rate of 20 t C/ha for the period 2005–2035, which is approximately 0.67 t C/ha/year inclusive of harvest regimes under short rotation and long rotation mitigation options. The transaction cost for baseline establishment is less than a rupee/t C and for project scenario development is about Rs. 1.5–3.75/t C. The project enhances biodiversity and the socio-economic impact is also significant.

Modelling farm structural change for integrated ex-ante assessment: review of methods and determinants

This paper provides a literature review of methods and determinants relevant for modelling farm structural change within an integrated modelling chain. Environmental and economic impacts at farm level and individual farm responses to agricultural and agri-environmental policies strongly depend on characteristics like farm size, specialisation, and production intensity. Consequently, up-scaling results of corresponding farm type models in ex-ante assessment exercises requires comprehensive and valid predictions of the farm types’ future relevance under different scenarios. The paper reviews methods relevant to forecasting farm numbers in classes defined by farm typologies with the objective to identify (1) a preferable modelling approach and (2) empirically relevant determinants. Despite the literature's considerable size, even recent studies are rather limited in scope and typically restricted to a subset of farm types and one or very few regions. With regard to data availability, computational complexity and statistical validation procedures, Markov chain models are identified as the only generally suitable method for a broadly scoped modelling approach across European regions and a differentiated farm typology. However, other research on determinants of farm growth, the number of farm holders, farm succession as well as new multi-agent based simulation approaches hint at relevant explanatory variables previously not considered in Markov chain analyses. Their impact seems testable in more ambitious cross-regional and cross-farm type setups.