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.     

A deep-sea in-situ suspended sediment sampling system: Comment

A recent article by Beer et al. (1974) in Marine Geology describes an in-situ suspended sediment sampling system which utilizes a pump/motor unit, filter holders, and a lead-acid battery power source. Two aspects of their article may be misleading: the use of certain filter material as X-ray diffraction mounts, and the technique by which an oil-filled battery case may be operated.     

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 case study of warm air advection over a melting snow surface

When relatively warm, moist air moves over a snow surface, sensible heat and moisture are extracted from its lower layers and used to melt the snow. The depth of the cooled layer depends on horizontal wind speeds and the presence of high vertical wind shear. The mechanism for air mass modification appears to be turbulent mixing.     

A 2D finite volume model for bebris flow and its application to events occurred in the Eastern Pyrenees

FLATModel is a 2D finite volume code that contains several original approaches to improve debris-flow simulation. Firstly, FLATModel incorporates a ＂stop-and-go＂ technique in each cell to allow continuous collapses and remobilizations of the debris-flow mass. Secondly, flow velocity and consequently yield stress is directly associated with the type of rheology to improve boundary accuracy. Thirdly, a simple approach for entrainment is also included in the model to analyse the effect of basal erosion of debris flows. FLATMODEL was tested at several events that occurred in the Eastern Pyrenees and simulation results indicated that the model can represent rather well the different characteristics observed in the field.     

Rock-weathering rates as functions of time

The scarcity of documented numerical relations between rock weathering and time has led to a common assumption that rates of weathering are linear. This assumption has been strengthened by studies that have calculated long-term average rates. However, little theoretical or empirical evidence exists to support linear rates for most chemical-weathering processes, with the exception of congruent dissolution processes. The few previous studies of rock-weathering rates that contain quantitative documentation of the relation between chemical weathering and time suggest that the rates of most weathering processes decrease with time. Recent studies of weathering rinds on basaltic and andesitic stones in glacial deposits in the western United States also clearly demonstrate that rock-weathering processes slow with time. Some weathering processes appear to conform to exponential functions of time, such as the square-root time function for hydration of volcanic glass, which conforms to the theoretical predictions of diffusion kinetics. However, weathering of mineralogically heterogeneous rocks involves complex physical and chemical processes that generally can be expressed only empirically, commonly by way of logarithmic time functions. Incongruent dissolution and other weathering processes produce residues, which are commonly used as measures of weathering. These residues appear to slow movement of water to unaltered material and impede chemical transport away from it. If weathering residues impede weathering processes then rates of weathering and rates of residue production are inversely proportional to some function of the residue thickness. This results in simple mathematical analogs for weathering that imply nonlinear time functions. The rate of weathering becomes constant only when an equilibrium thickness of the residue is reached. Because weathering residues are relatively stable chemically, and because physical removal of residues below the ground surface is slight, many weathering features require considerable time to reach constant rates of change. For weathering rinds on volcanic stones in the western United States, this time is at least 0.5 my.     

Authigenic iron and titanium oxides in triassic red beds: (St. Bees Sandstone), Cumbria,Northern England

Authigenic iron and titanium oxides occur in three main textural varieties in the St. Bees Sandstone, a Triassic red bed succession in Cumbria. These are: (a) overgrowths of haematite, titaniferous haematite, anatase, and rutile which generally occur on detrital host grains of similar compositions. The overgrowths may occur as syntaxial rim cements or rhombohedral and prismatic projections and are always in optical continuity, (b) discrete crystals of anatase (including octahedrite) and haematite 10-40 μm in size occur in pore spaces, and (c) fine grained ( < 1 μm) pigmentary haematite occurs as grain coatings around detrital grains and in the interstitial matrix. The euhedral nature and pore-filling habit clearly indicate the authigenic origin of these iron- and titanium oxides. All three textural varieties are believed to have been precipitated from ground waters containing dissolved ferrous and titanium ions. These ions were derived from the intrastratal solution of detrital iron and titanium bearing grains including ferromagnesian silicates and iron-titanium oxides. The precipitation of iron oxides from migrating ground waters in the manner described here goes some way to explaining how thick, uniformly red successions can be formed.     

On the eigenvalues of kinematic α-effect dynamos

The kinematic α-effect dynamo problem is investigated in the case of an exterior perfect conductor. It is shown that certain approximate symmetries discovered in the numerical analysis of ROBERTS (1972) are exact for this case. As an illustration, an exact solution is given in a cylindrical geometry, where the equations can be written in terms of one variable. The implications for the earth's dynamo are discussed.     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.