基于观测数据空间化的北京市PM_(2.5)时空分异

PM2.5在地球表面上的变化是连续的,但由于地面海拔起伏和站点分布的相对稀疏,直接内插法很难顾及这种情况。文章运用反距离权重(IDW)、Kriging、经验贝叶斯克里金法(EBK)、多元回归+残差内插的综合空间化手段,对北京市2015年1月的PM2.5数据进行分析。结果表明:利用多元回归+残差内插方法空间化更优,且PM2.5存在显著的正局部空间自相关,中度以上污染主要分布在北京市东南部和房山区。时间上,PM2.5质量浓度逐时均值呈"W"型。3 h尺度上,PM2.5质量浓度与相对湿度和露点温度正相关,与能见度、大气压和风速负相关,与温度不相关。     

改进AHP-DRASTIC模型用于地下水U(Ⅵ)污染风险评价及回归分析

以某铀尾矿库为例,应用层次分析法(AHP)对DRASTIC进行了改进,并增加两个新的指标,得出改进后的AHPDRASTICLL模型。分别采用常规DRASTIC模型、改进DRASTICLL模型、AHP-DRASTICLL模型对某铀尾矿库区地下水受U(Ⅵ )污染风险进行了评价。结果表明:尾矿库周围与砂卵砾石层区风险较高,丘陵地带风险较低。采集监测井U(Ⅵ )浓度样本数据,与3个模型标准化综合评分值建立线性回归关系,常规DRASTIC模型相关系数R2=0.7795;改进DRASTICLL模型相关系数R2=0.8278;AHP-DRASTICLL模型相关系数R2=0.8581。分析结果表明AHPDRASTICLL模型能更加准确地反映地下水受污染的可能性。     

太子河流域硅藻群落与驱动因子的定量关系

定量研究水生生物对水环境参数的适宜值是评估栖息地质量和维持生物完整性的主要途径. 以辽宁省太子河流域为研究范例,选择Y(优势度指数)大于0.000 1的硅藻为研究对象,结合水环境参数,采用CCA(典范对应分析)、CART(分类回归树)和WA(加权平均回归分析)等方法,分析硅藻与水环境因子的关系,并计算硅藻对驱动因子的最适值. CCA结果表明,IOS(底质指数)、ρ(TDS)(TDS为总溶解固体)和ρ(COD_Mn)是硅藻群落的驱动因子;CART预测结果表明,IOS高的水环境硅藻密度高于IOS低的水环境,ρ(TDS)和ρ(COD_Mn)低的水环境硅藻密度高于ρ(TDS)和ρ(COD_Mn)高的水环境;WA结果显示,96种硅藻对IOS、ρ(TDS)和ρ(COD_Mn)的最适值范围分别为1.00~6.44、60.29~820.30 mg/L和0.46~2.89 mg/L. 钝端菱形藻解剖刀变种和尖端菱形藻适宜栖息于IOS较低而ρ(COD_Mn)较高的水环境, Gomphonema trancatum和肿大桥弯藻则适宜栖息于IOS较高的水环境;缠结异极藻二叉变种和尖细异极藻适宜栖息于ρ(TDS)较高的水环境,弧形峨眉藻和克洛钝脆杆藻则适宜栖息于ρ(TDS)较低的水环境;弧形峨眉藻和隐头舟形藻威蓝变种适宜栖息于ρ(COD_Mn)较低的水环境. 针杆藻和桥弯藻对IOS的最适值高于舟形藻和菱形藻以及其他藻种,96种硅藻对ρ(TDS)和ρ(COD_Mn)的最适值均表现为菱形藻和异极藻较高、针杆藻和桥弯藻较低.      

A Water Allocation Decision‐Support Model and Tool for Predictions in Ungauged Basins in Northeast British Columbia,Canada

Pressures on water resources due to changing climate, increasing demands, and enhanced recognition of environmental flow needs result in the need for hydrology information to support informed water allocation decisions. However, the absence of hydrometric measurements and limited access to hydrology information in many areas impairs water allocation decision‐making. This paper describes a water balance‐based modeling approach and an innovative web‐based decision‐support hydrology tool developed to address this need. Using high‐resolution climate, vegetation, and watershed data, a simple gridded water balance model, adjusted to account for locational variability, was developed and calibrated against gauged watersheds, to model mean annual runoff. Mean monthly runoff was modeled empirically, using multivariate regression. The modeled annual runoff results are within 20% of the observed mean annual discharge for 78% of the calibration watersheds, with a mean absolute error of 16%. Modeled monthly runoff corresponds well to observed monthly runoff, with a median Nash–Sutcliffe statistic of 0.92 and a median Spearman rank correlation statistic of 0.98. Monthly and annual flow estimates produced from the model are incorporated into a map‐ and watershed‐based decision‐support system referred to as the Northeast Water Tool, to provide critical information to decision makers and others on natural water supply, existing allocations, and the needs of the environment.     

Access for all? Beach access and equity in the Detroit metropolitan area

Beaches are a unique type of recreation setting, offering a variety of water- and land-based opportunities that can meet residents’ diverse and complex recreation needs. Providing and improving equitable access to recreation amenities such as beaches have been recognized as essential responsibilities of public leisure agencies. This study assessed the degree of equity inherent in the distribution of public beaches in the Detroit metropolitan area; to account for spatial effects, phenomena rarely considered in prior equity analyses, geographically weighted regression was employed. Considerable local variations in the relationships between level of access to public beaches and population density, proportion of elderly population and educational attainment were identified. Such findings can help parks and recreation agencies better understand local patterns of equity, an important first step in facilitating the formulation of more efficient and effective planning and policy approaches.     

基于支持向量机的巢湖富营养化程度评价研究

由于湖泊富营养化程度影响因素多,评价因素与富营养化等级之间关系复杂而且具有非线性特征。支持向量机是由Vapnik等人提出的建立在统计学习理论基础上的一种新的机器学习方法,由于其使用结构风险最小化原则代替经验风险最小化原则,解决了一些神经网络遗留的问题,又由于其应用了核函数思想,它可以较好地解决非线性问题,利用支持向量机多类分类算法,构建巢湖富营养化程度评价模型,取得较好的结果。     

大气污染总量控制规划智能决策支持系统的开发与研究

对大气污染总量控制规划智能决策支持系统的开发步骤和总体结构做了介绍。并描述了该系统中的知识库系统、模型库系统、数据库系统和图形库系统的设计思想,特别是对知识库的构造进行了较详细的叙述。还介绍了神经网络技术在该系统中的应用。指出大气污染总量控制规划智能决策支持系统将为大气污染总量控制提供更科学、更合理、更有效的规划方案。     

中国省级环境决策支持系统的系统分析

中国省级环境决策支持系统(DSS)是基于GIS和各种模型的空间决策支持系统?该文介绍了DSS系统的系统分析方法和内容,包括软件需求说明?数据需求说明和总体设计      

复杂河流系统水污染的计算机图形模拟

讨论在河流系统水污染规划中应用交互式计算机图形技术。通过对复杂河流系统水污染的图形模拟,提出建立图模型的一般理论和方法,并就浑太流域河流水污染案例给出实际模拟结果。