Potential and Shortcomings of Numerical Weather Prediction Models in Providing Meteorological Data for Urban Air Pollution Forecasting

The last decade progress in numericalweather prediction (NWP) modelling and studies of urbanatmospheric processes for providing meteorological data forurban air pollution forecasting is analysed on examples ofseveral European meteorological centres. Modern nested NWP models are utilising land-use databasesdown to 1 km resolution or finer, and are approaching thenecessary horizontal and vertical resolution suitable forcity scale. The recent scientific developments in the fieldof urban atmospheric physics and the growing availabilityof high-resolution urban surface characteristics datapromise further improvements of the capability of NWPmodels for this aim. A strategy to improve NWP data forthe urban air pollution forecasting is suggested.     

环境保护及可持续发展需要加强现代化档案工作

新世纪可持续发展思想成为主流,中国处于社会转型时期,在西部大开发、环境保护、城市建设等许多领域,环境档案具有不可替代的重要功能。但是目前的环境档案工作还亟待强化高科技化、法制化和提高人才素质,特别需要强化档案的资源开发观念。     

四川省科技人力资源潜力与结构变化

通过对四川省科技人力资源的潜力、结构变化的分析,提出建立统一规范的科技人才培养经费投入政策,加强科技人才资源的再开发,不拘一格引进科技人才,建立四川省科技人力资源监测系统等对策。     

城市旅游环境承载力及其旅游资源空间管理

UTECC主要充当控制旅游需求的功能。UTECC的降低最明显的后果就是损害了城市的生态环境质量,紧接着会导致旅游需求的降低。为了实现城市旅游可持续发展,城市的旅游需求不能超过旅游环境承载力。通常对城市旅游资源过度需求的空间管理方法主要有5种。本文在AlanCollins(1999年)研究的基础上提出了城市旅游环境承载力的概念,并借助城市旅游资源过度需求管理方面的理论对如何使用及防止滥用城市旅游环境承载力作了初步研究。     

区域性旱涝灾害序列的信息量及分维的研究

本文依据 C· E· Shannon的信息量概念 ,定义了旱涝灾害序列的信息量公式。以安徽省长江、淮河流域的旱 (涝 )灾害序列为例进行了研究 ,初步计算出相应的信息量、信息维 ,并得出如下结论 :1旱 (涝 )序列的信息量随时间是波动的、衰减的 ;2大旱 (大涝 )前信息量增加 ,信息维降低 ;3区域性旱 (涝 )序列的信息维一般在 0 .70～ 0 .90之间     

天津市城区暴雨沥涝仿真模拟系统的研究

天津市位于黄河水系尾闾，是我国北方重要的工业和港口城市。该市历史上一直遭受洪涝灾害的威胁，加之近几年市区范围不断扩大，不透水面积增加，排水能力远远不能适应城市的发展要求，城市沥涝问题日趋严重。为了掌握天津市暴雨沥涝的规律，减轻洪涝灾害对该市的影响，作者利用二维不恒定流水动力学模型和计算机信息管理及图形技术，采用Power Station Fortran 4.0和Visual Basic5.0编程语言，在Widows98环境下开发了天津市暴雨沥涝仿真模拟系统。该系统首次实现了从城市暴雨预报、监测到城市暴雨沥涝仿真模拟的研究， 不仅能够处理实时的不均匀的降雨信息，还能处理数值预报模型的预报降雨信息。系统的信息前后处理模块用图形方式管理仿真模型的各类信息，方便用户显示、查询和修改，使系统更加完整、实用。     

基于洪水灾害快速评估的承灾体易损性信息管理系统

洪水灾害易损性信息管理系统是为了开展洪水灾害快速评估,对不同洪水灾害流域和同一洪水灾害流域中的不同地区、不同承灾体(财产分类)、不同致灾因子(水深和历时等)条件,以财产的损失率为核心的综合信息管理系统。本文介绍了洪水灾害易损性信息管理系统的开发与设计的基本原理,阐述了系统的总体结构框架和功能模块划分,并且在系统数据流程图的基础上,对损失率数据库等几个重要的模块进行了详细的分析与设计,给出了系统的部分运行结果。本系统在与GIS、遥感等空间技术结合后,能够高效地完成各种洪水灾害损失的快速评估与预测分析工作,同时,本系统亦可独立作为对区域洪水灾害易损性研究的数据基础和理论支撑。     

A comparative study of risk perception in small and large communities where chemical industries are present

Opinion polls were conducted to assess the level of risk perceived by the citizens in communities of different sizes where chemical industries were present. The aim of the study was to relate the risk perceived to variables such as the nature of risks, the specific information received regarding the industrial activity and the economic impact of this activity in the community.     

MULTISCALE RIVER ENVIRONMENT CLASSIFICATION FOR WATER RESOURCES MANAGEMENT1

ABSTRACT: River Environment Classification (REC) is a new system for classifying river environments that is based on climate, topography, geology, and land cover factors that control spatial patterns in river ecosystems. REC builds on existing principles for environmental regionalization and introduces three specific additions to the “ecoregion” approach. First, the REC assumes that ecological patterns are dependent on a range of factors and associated landscape scale processes, some of which may show significant variation within an ecoregion. REC arranges the controlling factors in a hierarchy with each level defining the cause of ecological variation at a given characteristic scale. Second, REC assumes that ecological characteristics of rivers are responses to fluvial (i.e., hydrological and hydraulic) processes. Thus, REC uses a network of channels and associated watersheds to classify specific sections of river. When mapped, REC has the form of a linear mosaic in which classes change in the downstream direction as the integrated characteristics of the watershed change, producing longitudinal spatial patterns that are typical of river ecosystems. Third, REC assigns individual river sections to a class independently and objectively according to criteria that result in a geographically independent framework in which classes may show wide geographic dispersion rather than the geographically dependent schemes that result from the ecoregion approach. REC has been developed to provide a multiscale spatial framework for river management and has been used to map the rivers of New Zealand at a 1:50,000 mapping scale.     

SUBWATERSHED SPATIAL ANALYSIS TOOL: DISCRETIZATION OF A DISTRIBUTED HYDROLOGIC MODEL BY STATISTICAL CRITERIA1

ABSTRACT: Complex hydrologic models, designed for simulating larger watersheds, require a huge amount of input data. Most of these models use spatially distributed data as inputs. Spatial data can be aggregated or disaggregated for use as input to a model, which can impact model outputs. Although, it is efficient to minimize data redundancy by aggregating the spatial data, upscaling reduces the detail/resolution of input information and increases model uncertainty. On the other hand, a large number of model inputs with high degrees of disaggregation take more computer time and space to process. Hence, a balance between striving for a maximum level of aggregation and a minimum level of information loss has to be achieved. This study presents a definition of an appropriate level of discretization, derived by establishing a relationship between a model's efficiency and the number of subwater‐sheds modeled. An entropy based statistical approach/tool called Subwatershed Spatial Analysis Tool (SUSAT) was developed to find an objective choice of an appropriate level of discretization. The new approach/tool was applied to three watersheds, each representing different hydrologic conditions, using a hydrologic model. Coefficients of efficiency and entropy estimated at different levels of discretization were used to validate the success of the new approach.