基于GIS空间插值方法的长湖水质评价

通过对各插值方法选择后取反距离加权法与克立格法对长湖的污染现状进行分析,结果表明大部分水域水质处于Ⅴ类和劣Ⅴ类,只有主要出水口习家口和刘岺闸附近的部分水域的水质可以达到Ⅳ类水质标准.同时发现反距离加权法与克立格法均具有较高的精度,但克立格法优于反距离加权法,这两种方法评价湖泊水质都能取得比较好的效果.     

AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.     

有机磷农药二元混合物联合效应评价新方法的研究

以敌敌畏、乐果联合作用于线虫的毒理学实验为基础,基于FH插值法理论,通过较少的实验数据建立有机磷农药二元混合物联合效应模型,求解作用效应表达式并绘制联合效应三维曲面图;基于合并用药分析公式,计算联合作用评价q值并绘制农药浓度与q值的联合作用评价三维曲面图,结果表明敌敌畏与乐果混合物联合作用不仅表现为相加作用,而且还在局部低浓度表现为拮抗作用,与多元统计分析结果一致。上述研究表明FH插值法理论可作为二元有机磷农药联合效应分析及评价的一种新方法。     

基于GIS和LUR模型的西安市PM2.5浓度空间分布模拟研究

基于地理信息系统GIS和土地利用回归LUR模型,模拟西安市PM2.5浓度空间动态分布,结果表明:与PM2.5浓度相关性最高的分别为缓冲区为2 km的水域面积、人口密度和距离水域距离,R 2分别为0.501,0.393和0.280;与PM2.5浓度相关性最低的分别为缓冲区为4 km的水域面积、未利用地面积和耕地面积,R 2分别为0.039、0.021和0.017.未考虑风速建立的LUR模型多元回归的相关系数为0.856,R 2为0.733,考虑风速的相关系数为0.892,R 2为0.796,表明风速对于污染物的分布影响较大,LUR模型模拟效果较好.模拟的PM2.5年均浓度高风险区分布于中部,中风险区分布于中西部,低风险区分布于东南部和西部.     

基于GIS的海洋底栖生物栖息密度空间插值方法

在地理信息系统即GIS的支持下,分别采用反距离加权(inverse distance weighted,IDW)、普通克里格(ordinary krig-ing,OK)、规则样条(regularize spline,RS)和张力样条(tension spline,TS)4种插值方法对2006年7月获得的大连湾底栖生物栖息密度的数据进行空间插值处理,并对插值结果的精确度进行交叉验证,分析和比较不同插值方法获得的分布图。结果表明,插值精确度普通克里格>反距离加权>张力样条>规则样条;4种方法均能较客观的模拟出底栖生物栖息密度的分布趋势,但是在整体趋势和局部趋势两方面的综合考虑下,普通克里格的表现效果更好。文章进一步指出,在确定站位数量及分布前提下,插值结果的精确度可以通过选择空间插值方法得以改善,但其根本还是取决于站位布置的数量和其分布合理性。     

城市表层土壤重金属污染分析研究

根据某城市土壤表层中的8种重金属Cu、Pb、Cd、Hg、As、Cr、Ni、Zn的浓度数据,利用地统计学原理方法,研究了不同功能区土壤重金属的污染特征。结果表明Cd、Cu、Hg、Pb和Zn在工业区和主干道路区浓度超标,并且这几种元素的富集系数偏高,说明污染来源主要是工业生产、汽车尾气排放及汽车轮胎磨损等。此研究对城市土壤重金属污染治理及修复、重金属污染重点行业污染控制等提供参考。     

OPEN CHANNEL INTERPOLATION OF CROSS SECTIONAL PROPERTIES1

ABSTRACT: This paper confirms the use of interpolated data to refine water surface profiles. Sources of error within these computations are due to truncation error, inaccuracies in geometric data, and improper modeling. Confirmation includes the development of an equation that models the effect of data measurement error on the computed water surface profile. A review of interpolation procedures includes a proposed method based upon geometric properties.     

燃气爆炸作用下房屋裂缝开展的分形模拟

烯气爆炸灾害下房屋裂纹开展有的模式与受均布压力破坏时的相同，在参照实验所得混凝土裂缝的分形维数资源的基础上编制了相应的软件，利用分形插值的方法实现裂缝开展的模拟，模拟结果较好地反映了裂缝发展的真实情况，且较以往的模拟方法节约了大量存储空间。     

基于BP人工神经网络的城市PM2.5浓度空间预测

针对PM2.5日均质量浓度,采用BP人工神经网络模型,预测研究区空气中PM2.5浓度的空间变异,通过与普通克里格(Ordinary Kriging)插值方法对比验证BP人工神经网络预测模型的精度.结果表明:BP人工神经网络预测模型下研究区检验样本点位置的PM2.5仿真浓度与观测浓度之间的均方差、平均绝对误差、平均相对偏差和相关系数分别为0.296 μg2/m6、0.412 μg/m3、1.650％和0.851;而与此同时,普通克里格插值方法下的对应结果分别为1.041 μg2/m6、0.689 μg/m3、11.910％、0.638.研究成果在肯定BP人工神经网络预测模型可用于揭示PM2.5浓度空间变异特征的同时,也证实了其相对于普通克里格插值方法在固定空间点位准确预测PM2.5浓度方面的优势.     

Comparison of Point Estimation Techniques in the Spatial Analysis of Radium-226, Radium-228 and Potassium-40 in Soil

Many environmental surveys require the implementation of estimation techniques to determine the spatial distribution of the variable being investigated. Traditional methods of interpolation and estimation, for example, inverse distance squared and triangulation often ignore features of the data set such as anisotropy which may have a significant impact on the quality of the estimates produced. Geostatistical techniques may offer an improved method of estimation by modelling the spatial continuity of the variable using semi-variogram analysis. The theoretical model fitted to the semi-variogram is then used in the assignation of weighting factors to the samples surrounding the location to be estimated. This paper outlines the results of a comparison between three common estimation methods, polygonal, triangulation and inverse distance squared and a geostatistical method, in the estimation of soil radionuclide activities. The geostatistical estimation method known as kriging performed best over a range of parameters used to test the performance of the methods. Kriging exhibited the best correlation between actual and estimated values, the narrowest error distribution and the lowest overall estimation error. Polygonal estimation was best at reproducing the data set distribution. Conditional bias was evident in all the methods, low values being over-estimated and high values being under-estimated.