城市地下水饮用水水源地安全评价体系研究

随着饮用水质量标准的提高,水源地安全评价指标体系也应随之完善.从水源地安全的内涵出发,构建了包括水量、质量、脆弱性和生态环境4项一级指标、11项二级指标的地下水饮用水水源地安全评价体系,并提出了相应的分析计算方法,从而为新标准实施后地下水源地安全评价提供了科学依据.     

Remote sensing of grassland–shrubland vegetation water content in the shortwave domain

This study compares the ability of spectral approaches operating in the shortwave optical domain to predict absolute and relative vegetation water content (AWC and RWC, respectively) across northern prairie grassland–shrubland. We collected vegetation water content and spectral radiometer data over plots of comparable ground resolution (0.5 m) at seven field sites in the Canadian mixed grass prairie in June 2004. We then aggregated observations to scale these data “up” to an observational scale consistent with that of Landsat-TM satellite imagery (30 m). This allowed us to assess abilities of three spectral approaches to predict AWC and RWC at both observational scales. These approaches were: individual vegetation indices, a combination of spectral bands and a combination of spectral derivatives. Our results showed that (a) the band-combination approach provides the most accurate and precise estimates of AWC and RWC at both 0.5 and 30 m sampling resolutions; (b) the combination of bands providing the greatest predictive abilities are those that emphasize the contrast in reflectance between the NIR and SWIR spectral regions; (c) the band-combination approach predicts AWC with much greater accuracy and precision than RWC and (d) the predictive ability of the band-combination approach decreases only slightly when plot-level data are aggregated to a 30 m sampling resolution. These results are generally consistent with the results of other studies and with theory. While our results suggest that simple spectral methods (e.g. linear band-combinations or indices) are good predictors of AWC over grazed and ungrazed grassland–shrubland landscapes at plot- and Landsat spatial resolutions, they are less encouraging for the estimation of RWC. Despite their good predictive abilities, the temporal and geographical portabilities of the spectral approaches for estimating AWC must be further assessed before they can be considered reliable and robust predictive tools. Thus, the further testing of these techniques over larger geographical extents is required.     

亚洲夏季风指数的重新评估与季风的长期变化

使用NCEP/NCAR再分析资料对Webster与Yang的季风指数(WYI)进行计算和修改。WYI定义为850与200 hPa的纬向风差,但通过分析150—100 hPa和200 hPa的环流场、散度场与垂直运动场,发现200 hPa层并不能真正反映亚洲季风系统上层环流的变化,尤其是其最主要的环流特征即热带东风急流的变化,其核心位于150—100 hPa。纬向风切变U850-U(150 100)的值比U850-U200的值远大得多,更能真实反映季风的强度,并且与低层辐合耦合在一起的高层辐散最大位于150 hPa,在对流层高层取150 hPa比200 hPa更能反映季风系统的耦合关系。因此,在对流层上层选择150—100 hPa重新定义季风指数(DHI)为IDH=U8*50-U(*150 100),不但可以更好地表征亚洲纬向风切变中心的强度变化,也可以代表对流层上下层季风系统的变率。分别用季风指数DHI和WYI对亚洲夏季风的长期变化进行研究,发现DHI比WYI更合适。DHI的变化表明亚洲夏季风存在明显的年代际变化及突变,20世纪70年代末之后显著减弱,这主要是由于150—100 hPa层东风的减弱,但这种东风的减弱现象在200 hPa不明显。突变后总的来说:亚洲地区高层东风减弱,表明夏季风减弱;海陆气压差和海陆温差的减小导致季风减弱;相应高空辐散和水汽输送在印度半岛、中南半岛中部、中国华北与东北地区都是减弱的,也表明夏季风减弱。最后比较NCEP/NCAR和ERA-40两种再分析资料研究亚洲夏季风的强度及其长期变化的差异,以作参考。     

西秦岭三叠纪沉积盆地演化

笔者在概要介绍了西秦岭三叠系的分布与建造特征、沉积环境、生物区系特征，三叠系的构造形变特征以及与相邻地质体的形变差异性的基础上，论述了该区在中三叠世短暂的地质发展演化过程中，由扬子型稳定浅海碳酸盐岩沉积快速演变为特提斯型深海巨厚复理石沉积的演化历史，讨论了特提斯型裂陷槽由裂开接受沉积—关闭结束沉积。快速关闭并褶皱形变这一完整演化过程中的构造特征，总结了三叠系的盆地演化规律。     

过去76年来射阳湖湖沼环境的动态变化

选用不同年代的地形图、以及遥感图象数据等信息源,用地理信息系统以及景观指数分析方法对射阳湖湖沼环境的动态变化进行了初步研究。结果表明,射阳湖的面积逐年减少,从1958年到1974年,射阳湖的面积减少了153.245km2,年均递减9.578km2,这两个时期的年均面积递减率是最大的。景观指数分析表明射阳湖湖沼湿地的破碎化程度和空间异质性越来越高。大量水利工程的修建导致上游来水减少是射阳湖面积减小的主要原因,滩地围垦、水产养殖业以及居民地扩展等是其变化的主要因素。     

中国地磁台网的K指数测量结果分析

Ｋ指数以０,１,……,９的数字分为１０级,以３小时为一时段,简单、直观、清晰地表示出地磁场受太阳微粒辐射而形成的扰动变化的程度。Ｋ指数测量是地磁台日常工作的重要内容之一。正确地区别Ｋ变化与非Ｋ变化是测量Ｋ指数的基本要求和关键所在。我国地磁台站从１９８９年开始用规则日变化ＳＲ代替“铁曲线”来识别Ｋ变化与非Ｋ变化,使测量方法与国际上的通行做法相一致。本文通过对我国地磁台站的Ｋ频次分布统计指出,在采用新     

Satellite-derived vegetation index and cover type maps for estimating carbon dioxide flux for arctic tundra regions

The spatial variability and co-variability of two different types of remote sensing derivatives that portray vegetation and geomorphic patterns are analyzed in the context of estimating regional-scale CO₂ flux from land surfaces in the arctic tundra. For a study area encompassing the Kuparuk River watershed of the North Slope of Alaska, we compare satellite-derived maps of the normalized difference vegetation index (NDVI) generated at two different spatial resolutions to a map of vegetation types derived by image classification of data from the Landsat multispectral scanner (MSS). Mean values of NDVI for each cover type stratum are unique (with the exception of moist acidic tundra and shrubland types). Based on analysis of semi-variograms generated for SPOT-NDVI data, most of the vegetation cover and landform features of this arctic tundra landscape have spatial dimensions of less than 1 km. Thaw lakes on the coastal plain and glacial depositional landforms, such as moraines in the foothills, seem to be the largest features, with vegetation units having dimensions no larger than 700 m. Frequency distributions of NDVI and vegetation types extracted for sampling transects flown by an aircraft sensing CO₂ flux, relative to distributions for the entire Kuparuk River watershed, suggest a slight sampling bias towards greater cover of mesic wet sedge tundra and thaw lakes and associated lower NDVI values. The regional pattern of NDVI for the North Slope of Alaska corresponds primarily to differences between the two major physiographic provinces of this region.     

SZGC—93型数字工程地震仪

ＳＺＧＣ－９３型数字工程地震仪是专为工程地震勘探而研制的。经过两年多的实际生产使用表明：该仪器精度高、性能稳定、操作方便。是一种实用性较好的野外专用设备。本文介绍了它的组成：论述了其各个单元电路的工作原理及主要技术指标;最后说明了该设备两年多来的实际应用成果。     

Integrative Monitoring Analysis Aiming at the Detection of Spatial and Temporal Trends of Metal Accumulation in Mosses

Goal and Scope. The UNECE heavy metals in Mosses Surveys provide data on the accumulation of metals in naturally growing mosses throughout Europe. Using Germany as an example, this article concentrates on the elaboration and application of methods of data analysis that are necessary for a comprehensive interpretation of spatial and temporal trends in metal accumulation.Methods and Results. The sampling of mosses, and the chemical analysis of Cr, Cu, Fe, Ni, Pb, Ti, V and Zn in 1990, 1995 and 2000 are summarized briefly. The variogram analyses detect distinct autocorrelation structures in the sample data which may consequently be estimated for all sites in Germany without monitoring metal accumulation by means of ordinary kriging. A procedure for the geostatistical detection of spatial outliers was developed and applied and, after the elimination of the spatial outliers, several measurements were seen to indicate an adequate quality of the geostatistical estimations. The cluster analyses of the z-transformed estimation data result in a nominal multi-element index that indicates regional metal accumulation types over time. Percentile statistics serve for computation of an ordinal, scaled, multi-element accumulation index which is spatially differentiated over time in terms of multivariate, statistically defined ecoregions. The integrative statistical analysis reveals, from 1990 to 2000, that the metal accumulation declines up to 80% in some of the ecoregions. Hot spots of metal accumulation are mapped and interpreted by means of metadata analysis.Conclusions. Dot maps depict the spatial structure of the metal accumulation without spatial bias. This information, detailed with respect to metal species and space, should be generalized for better supporting the interpretation. The combination of geostatistical analysis and estimation, percentile and multivariate statistics is suitable for the calculation of indices that serve for a comprehensive mapping of metal accumulation in the ecoregions over time, for quantifying the bias of the surface estimation, and for mapping spatial outliers and hot spots of metal accumulation.     

Drought Monitoring Using Data Mining Techniques: A Case Study for Nebraska, USA

Drought has an impact on many aspects of society. To help decision makers reduce the impacts of drought, it is important to improve our understanding of the characteristics and relationships of atmospheric and oceanic parameters that cause drought. In this study, the use of data mining techniques is introduced to find associations between drought and several oceanic and climatic indices that could help users in making knowledgeable decisions about drought responses before the drought actually occurs. Data mining techniques enable users to search for hidden patterns and find association rules for target data sets such as drought episodes. These techniques have been used for commercial applications, medical research, and telecommunications, but not for drought. In this study, two time-series data mining algorithms are used in Nebraska to illustrate the identification of the relationships between oceanic parameters and drought indices. The algorithms provide flexibility in time-series analyses and identify drought episodes separate from normal and wet conditions, and find relationships between drought and oceanic indices in a manner different from the traditional statistical associations. The drought episodes were determined based on the Standardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI). Associations were observed between drought episodes and oceanic and atmospheric indices that include the Southern Oscillation Index (SOI), the Multivariate ENSO Index (MEI), the Pacific/North American (PNA) index, the North Atlantic Oscillation (NAO) Index, and the Pacific Decadal Oscillation (PDO) Index. The experimental results showed that among these indices, the SOI, MEI, and PDO have relatively stronger relationships with drought episodes over selected stations in Nebraska. Moreover, the study suggests that data mining techniques can help us to monitor drought using oceanic indices as a precursor of drought.