碳酸岩Sr、Nd、Pb 同位素地球化学研究评述

碳酸岩是出露相对较少的幔源岩石，其中Sr与Nd是研究地幔物质组成的主要对象之一。本文统计了世界上主要碳酸岩的锶、钕、铅同位素组成特征；研究显示，碳酸岩源区主要是洋岛玄武岩高U／Pb的HIMU端员和富集端员(EM1或EM2)的混合作用；此外大部分碳酸岩的锶、钕同位素落在大洋玄武岩范围内；这些均表明其成因与地慢柱有密切联系。碳酸岩及与之共生的硅酸岩的同源或独立源区模式部很难充分解释两者同位素组成特征，逭反映碳酸岩的演化模式涉及更复杂的过程。可能是俯冲作用使碳酸岩源区经历不同时间和程度的富集、亏损过程导致地幔源区成分不均一。     

Velocity field in the spiral-wave pattern observed in rotating shallow-water experiments

The paper presents the first quantitative results of a laboratory study of the velocity field in a two-arm spiral-wave pattern generated in a steady-state fashion by a hydrodynamical instability in a differentially rotating, thin layer of liquid. The liquid layer has a free surface, and the rotational profile includes an interval where the velocity drops abruptly, as in the gaseous disks of spiral galaxies. The properties of anticyclonic vortices observed between the arms of this pattern at the corotation radius are considered.     

Groundwater vulnerability mapping: A GIS and fuzzy rule based integrated tool

Contamination of groundwater has become a major concern in recent years. Since testing of water quality of all domestic and irrigation wells within large watersheds is not economically feasible, one frequently used monitoring strategy is to develop contamination potential maps of groundwater, and then prioritize those wells located in the potentially highly contaminated areas for testing of contaminants. However, generation of contamination potential maps based on groundwater sensitivity and vulnerability is not an easy task due inherent uncertainty. Therefore, the overall goal of this research is to improve the methodology for the generation of contamination potential maps by using detailed landuse/pesticide and soil structure information in conjunction with selected parameters from the DRASTIC model. The specific objectives of this study are (i) to incorporate GIS, GPS, remote sensing and the fuzzy rule-based model to generate groundwater sensitivity maps, and (ii) compare the results of our new methodologies with the modified DRASTIC Index (DI) and field water quality data. In this study, three different models were developed (viz. DI_fuzz, VI_fuzz and VI_{fuzz_ped}) and were compared to the DI. Once the preliminary fuzzy logic-based (DI_fuzz) was generated using selected parameters from DI, the methodology was further refined through VI_fuzz and VI_{fuzz_ped} models that incorporated landuse/pesticide application and soil structure information, respectively. This study was conducted in Woodruff County of the Mississippi Delta region of Arkansas. Water quality data for 55 wells were used to evaluate the contamination potential maps. The sensitivity map generated by VI_{fuzz_ped} with soil structure showed significantly better coincidence results when compared with the field data.