Effect of spatial variation characteristics on contouring of design storm depth

The ordinary kriging method, a geostatistical interpolation technique, was applied for developing contour maps of design storm depth in northern Taiwan using intensity–duration–frequency (IDF) data. Results of variogram modelling on design storm depths indicate that the design storms can be categorized into two distinct storm types: (i) storms of short duration and high spatial variation and (ii) storms of long duration and less spatial variation. For storms of the first category, the influence range of rainfall depth decreases when the recurrence interval increases, owing to the increasing degree of their spatial independence. However, for storms of the second category, the influence range of rainfall depth does not change significantly and has an average of approximately 72 km. For very extreme events, such as events of short duration and long recurrence interval, we do not recommend usage of the established design storm contours, because most of the interstation distances exceed the influence ranges. Our study concludes that the influence range of the design storm depth is dependent on the design duration and recurrence interval and is a key factor in developing design storm contours. Copyright © 2003 John Wiley & Sons, Ltd.     

Modeling X-Ray Photoionized Plasmas Produced at the Sandia Z-Facility

In experiments at the high-power Z-facility at Sandia National Laboratory in Albuquerque, New Mexico, we have been able to produce a low density photoionized laboratory plasma of Fe mixed with NaF. The conditions in the experiment allow a meaningful comparison with X-ray emission from astrophysical sources. The charge state distributions of Fe, Na and F are determined in this plasma using high resolution X-ray spectroscopy. Independent measurements of the density and radiation flux indicate unprecedented values for the ionization parameter ξ = 20–25 erg cm s⁻¹ under nearly steady-state conditions. First comparisons of the measured charge state distributions with X-ray photoionization models show reasonable agreement, although many questions remain.     

Development and application of a GIS-based tool for earthquake-induced hazard prediction

An integrated GIS-based tool (GTIS) was constructed to estimate site effects related to the earthquake hazards in the Gyeongju area of Korea. To build the GTIS for the study area, intensive site investigations and geotechnical data collections were performed and a walk-over site survey was additionally carried out to acquire surface geo-knowledge data in accordance with the procedure developed to build the GTIS. For practical applications of the GTIS used to estimate the site effects associated with the amplification of ground motion, seismic microzoning maps of the characteristic site period and the mean shear wave velocity to a depth of 30 m were created and presented as a regional synthetic strategy addressing earthquake-induced hazards. Additionally, based on one-dimensional site response analyses, various seismic microzoning maps for short- and mid-period amplification potentials were created for the study area. Case studies of seismic microzonations in the Gyeongju area verified the usefulness of the GTIS for predicting seismic hazards in the region.     

He–Ar and Nd–Sr isotopic compositions of late Pleistocene felsic plutonic back arc basin rocks from Ulleungdo volcanic island, South Korea: Implications for the genesis of young plutonic rocks in a back arc basin

We report analyses of noble gases and Nd–Sr isotopes in mineral separates and whole rocks of late Pleistocene (< 0.2 Ma) monzonites from Ulleungdo, South Korea, a volcanic island within the back arc basin of the Japan island arc. A Rb–Sr mineral isochron age for the monzonites is 0.12 ± 0.01 Ma. K–Ar biotite ages from the same samples gave relatively concordant ages of 0.19 ± 0.01and 0.22 ± 0.01 Ma. ⁴⁰Ar/³⁹Ar yields a similar age of 0.29 ± 0.09 Ma. Geochemical characteristics of the felsic plutonic rocks, which are silica oversaturated alkali felsic rocks (av., 12.5 wt% in K₂O + Na₂O), are similar to those of 30 alkali volcanics from Ulleungdo in terms of concentrations of major, trace and REE elements. The initial Nd–Sr isotopic ratios of the monzonites (⁸⁷Sr/⁸⁶Sr = 0.70454–0.71264, ¹⁴³Nd/¹⁴⁴Nd = 0.512528–0.512577) are comparable with those of the alkali volcanics (⁸⁷Sr/⁸⁶Sr = 0.70466–0.70892, ¹⁴³Nd/¹⁴⁴Nd = 0.512521–0.512615) erupted in Stage 3 of Ulleungdo volcanism (0.24–0.47 Ma). The high initial ⁸⁷Sr/⁸⁶Sr values of the monzonites imply that seawater and crustally contaminated pre-existing trachytes may have been melted or assimilated during differentiation of the alkali basaltic magma.A mantle helium component (³He/⁴He ratio of up to 6.5 RA) associated with excess argon was found in the monzonites. Feldspar and biotite have preferentially lost helium during slow cooling at depth and/or during their transportation to the surface in a hot host magma. The source magma noble gas isotopic features are well preserved in fluid inclusions in hornblende, and indicate that the magma may be directly derived from subcontinental lithospheric mantle metasomatized by an ancient subduction process, or may have formed as a mixture of MORB-like mantle and crustal components. The radiometric ages, geochemical and Nd–Sr isotopic signatures of the Ulleungdo monzonites as well as the presence of mantle-derived helium and argon, suggests that these felsic plutonic rocks evolved from alkali basaltic magma that formed by partial melting of subcontinental lithospheric mantle beneath the back arc basin located along the active continental margin of the southeastern part of the Eurasian plate.     

Simulations of Annual Cycle of Phytoplankton Production and the Utilization of Nitrogen in the Yellow Sea

A nutrient dynamic model coupled with a 3D physical model has been developed to study the annual cycle of phytoplankton production in the Yellow Sea. The biological model involves interactions between inorganic nitrogen (nitrate and ammonium), phosphate and phytoplankton biomass. The model successfully reproduces the main features of phytoplankton-nutrient variation and dynamics of production. 1. The well-mixed coastal water is characterized by high primary production, as well as high new production. 2. In summer, the convergence of tidal front is an important hydrodynamic process, which contributes to high biomass at frontal areas. 3. The evolution of phytoplankton blooms and thermocline in the central region demonstrate that mixing is a dominant factor to the production in the Yellow Sea. In this simulation, nitrate- and ammonium-based productions are estimated regionally and temporally. The northern Yellow Sea is one of the highly ranked regions in the Yellow Sea for the capability of fixing carbon and nitrogen. The annual averaged f-ratio of 0.37 indicates that regenerated production prevails over the Yellow Sea. The result also shows that phosphate is the major nutrient, limiting phytoplankton growth throughout the year and it can be an indicator to predict the bloom magnitude. Finally, the relative roles of external nutrient sources have been evaluated, and benthic fluxes might play a significant role in compensating 54.6% of new nitrogen for new production consumption.     

Characterization of Estuarine Marine Clays for Coastal Reclamation in Pusan, Korea

Large scale reclamation works in coastal areas of the Nakdong River plain are at various stages of progress, since early 1990's on in-situ soft marine clay deposits. These deposits are of the order of 30 to 40 m thick. A realistic rapid characterization of soft ground would ensure success of any reclamation work in this area. In order to cope with the work carried out with different agencies, it is desirable to evolve a systematic methodology. In this study, engineering properties of clays at three coastal areas, Gadukdo, Noksan and Shinho, have been generated. The analysis of data has been done within the framework of classical developments in soil mechanics. Analysis has also been made by making use of the recent developments in dealing with soft clays. The dominant factors, namely, stress, time, and environment influencing the response of clay to loading are identified.     

Estimation of covariance matrix from geochemical data with observations below detection limits

Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances, , , , and forY andZ: (ii) defining new variables by and and lettingA=C+D andB=C–D, and obtaining MLE for variances, and forA andB; (iii) estimating the correlation coefficient _YZ by and the covariance _YZ by . The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada.     

Experimental validation of the wavefield transform of electromagnetic fields

The wavefield transform is a mathematical technique for transforming low-frequency electromagnetic (EM) signals to a non-diffusive wave domain. The ray approximation is valid in the transform space and this makes traveltime tomography for 3D mapping of the electrical conductivity distribution in the subsurface possible. The transform, however, imposes stringent frequency bandwidth and signal-to-noise ratio requirements on the data. Here we discuss a laboratory scale experiment designed to collect transform quality EM data, and to demonstrate the practical feasibility of transforming these data to the wavefield domain.
We have used the scalable nature of EM fields to design a time-domain experiment using graphite blocks to simulate realistic field conditions while leaving the time scale undisturbed. The spatial dimensions have been scaled down by a factor of a thousand by scaling conductivity up by a factor of a million. The graphite blocks have two holes drilled into them to carry out cross-well and borehole-to-surface experiments. Steel sheets have been inserted between the blocks to simulate a conductive layer.
Our experiments show that accurate EM data can be recorded on a laboratory scale model even when the scaling of some features, such as drill-hole diameters, is not maintained. More importantly, the time-domain EM data recorded in cross-well and surface-to-borehole modes can be usefully and accurately transformed to the wavefield domain. The observed wavefield propagation delay is proportional to the direct distance between the transmitter and receiver in a homogeneous medium. In a layered medium, data accuracy is reduced and, hence, our results are not so conclusive. On the basis of the experimental results we conclude that the wavefield transform could constitute a valid approach to the interpretation of accurate, undistorted time-domain data if further improvement in the transform can be realized.