Karst database development in Minnesota: design and data assembly

The Karst Feature Database (KFD) of Minnesota is a relational GIS-based Database Management System (DBMS). Previous karst feature datasets used inconsistent attributes to describe karst features in different areas of Minnesota. Existing metadata were modified and standardized to represent a comprehensive metadata for all the karst features in Minnesota. Microsoft Access 2000 and ArcView 3.2 were used to develop this working database. Existing county and sub-county karst feature datasets have been assembled into the KFD, which is capable of visualizing and analyzing the entire data set. By November 17 2002, 11,682 karst features were stored in the KFD of Minnesota. Data tables are stored in a Microsoft Access 2000 DBMS and linked to corresponding ArcView applications. The current KFD of Minnesota has been moved from a Windows NT server to a Windows 2000 Citrix server accessible to researchers and planners through networked interfaces.     

Changes in American urban floodplain occupancy since 1958: the experiences of nine cities

In 1958, researchers from the University of Chicago documented increases in the number of structures in the floodplains of 17 American cities, a phenomenon attributed to the prevalence of flood control structures. Because federal policies have shifted to managing floodplains, this paper updates the 1958 study for nine of the cities. Several trends are apparent. Development pressures determine flood-plain encroachment; floodplain management regulations have been implemented where it was easiest to do so. Further, structural measures continue to dominate. Thus, while many local officials are becoming more aware of advantages of flood-plain regulation, implementation and enforcement are inconsistent and uneven.     

Improved Petrological Modal Analyses from X-ray Powder Diffraction Data by use of the Rietveld Method I. Selected Igneous, Volcanic, and Metamorphic Rocks

Mineral modes have been determined for specimens of eight rocktypes from CuK X-ray powder diffraction data using the Rietveldmethod. The samples include two granites, a granodiorite, adamellite,gabbro, basalt, trachyte, and two granulite-facies metamorphicrocks. Up to eight individual mineral components have been measuredin each sample (no glassy phases were observed), with a detectionlimit of {small tilde}1 wt.%, depending on the mineral assemblage.Marked variations in grain size (i.e., granite vs. trachyte)provide no difficulties for the X-ray method. The X-ray resultscompare very favourably with (1) optical modes determined forthe medium–coarse-grained samples by point counting, (2)normative calculations obtained using locally enhanced catanormand mesonorm software, and (3) corresponding Rietveld modesdetermined, for two samples, from neutron powder data. Wheredifferences occur, these are discussed in relation to the limitationsof each of the methods. The improved accuracy of the X-ray method is due primarily tothe incorporation of the full diffraction profile in the Rietveldanalysis calculations, and the elimination of preferred orientationby collecting the data from samples packed in glass capillaries(i.e., Debye–Scherrer mode). The good agreement of theX-ray and neutron modes shows that the usual problems encounteredwith microabsorption, extinction, and sampling are of littleconcern in these rocks. The results highlight one of the majoradvantages provided by Rietveld modal analysis over the moretraditional ‘reference intensity’ X-ray methods,namely, that the crystal chemistry (and thus the calibrationconstants) of the individual phases can be adjusted dynamicallyduring each individual analysis. This not only provides moreaccurate phase abundances, but also gives important supplementaryinformation about the mineralogy of the major components.     

A Model of Magmatic Crystallization

A computer model simulating fractional crystallization at oneatmosphere pressure incorporates nine broadly-defined minerals—magnetite,olivine, hypersthene, augite, quartz, plagioclase, orthoclase,leucite, and nepheline. The crystallization temperature of eachmineral is considered to be a smooth function of the compositionof the magmatic liquid. These mineral temperature equationsare obtained by multiple linear regression analysis of informationfrom published silicate systems and rock melting experiments.The nine equations are solved for any primary liquid, withinthe broad range of common magma types, to select the crystallizingmineral or minerals. Partition ratios from published experimentsand analyses of lavas and phenocrysts permit calculation ofthe composition of the crystallizing mineral assemblage. Subtractionof a small amount of that composition from the primary liquidyields a new liquid, which may be recycled to yield a sequenceof liquids during fractional crystallization. The crystallizationmodel handles assemblages of co-precipitating minerals, andcan trace progressive saturation in new minerals, substitutionof a new mineral for an old mineral, and cessation of crystallizationof a mineral. The sequences of minerals and liquids derivedfrom a broad set of primary liquids are geologically realistic,so the model is useful in predicting phenocrysts in volcanicrocks and events during crystallization of shallow intrusions.     

Island shadow effects and the wave climate of the Western Tuamotu Archipelago (French Polynesia) inferred from altimetry and numerical model data

To implement a numerical model of atoll lagoon circulation, we characterized first the significant wave height (Hs) regime of the Western Tuamotu Archipelago and the local attenuation due to the protection offered by large atolls in the south Tuamotu. Altimetry satellite data and a WAVEWATCH III two-way nested wave model at 5km resolution from 2000 to 2010 were used. Correlation between altimetry and model was high (0.88) over the period. According to the wave model, the archipelago inner seas experienced attenuated Hs year-long with a yearly average Hs around 1.3m vs a minimum of 1.6m elsewhere. The island shadow effect is especially significant in the austral winter. In contrast with southern atolls, Western Tuamotu experienced only few days per year of Hs larger than 2.5m generated by very high Hs southern swell, transient western local storms, strong easterly winds, and during the passage of distant hurricanes.