Rb-Sr and K-Ar systems of biotite in surface environments regulated by weathering processes with implications for isotopic dating and hydrological cycles of Sr isotopes

Biotite is widely used for Rb-Sr and K-Ar isotopic dating and influences Sr isotope geochemistry of hydrological regimes. The isotopic system of biotite behaves diversely in response to surface weathering; i.e. the complete preservation of original Rb-Sr and K-Ar isotopic ages or dramatic reduction. In this study, we have explored the relation between the behavior of isotopic systems and complex weathering processes of biotites in the weathering profiles distributed on the Mesozoic granitoids in South Korea. In the lower parts of the profiles, biotite in the early stages of weathering was transformed into either oxidized biotite or hydrobiotite, with a mass release of ⁸⁷Sr and ⁴⁰Ar forced by the rapid oxidation of ferrous iron. During the transformation to oxidized biotite, ⁸⁷Sr and ⁴⁰Ar were preferentially released relative to Rb and K, respectively, via solid-state diffusion through the biotite lattice, resulting in a drastic reduction of original isotopic age. The reduction of Rb-Sr age was greater than that of K-Ar age because K was preferentially released over Rb whereas ⁸⁷Sr and ⁴⁰Ar were released proportionally to each other. However, during the transformation of biotite to hydrobiotite (i.e., to regularly interstratified biotite-vermiculite), ⁸⁷Sr, Rb, ⁴⁰Ar, and K were completely retained in the alternating biotite interlayer, and thus the original isotopic age can be preserved. In the upper parts of the profiles, where iron oxidation was almost completed, ⁸⁷Sr, Rb, ⁴⁰Ar, and K were gradually and proportionally released, with no further significant change in isotopic age during the gradual transformation of the early-formed oxidized biotite into hydrobiotite and vermiculite or during their final decomposition to kaolinite. The ratios and amounts of isotopes released from weathered biotites are dependent upon the degree of iron oxidation and the pathways of mineralogical transformation. Regional and local variations in isotopic systems affected by particular weathering processes should be considered when dating biotite or biotite-bearing rocks in weathering environments, modeling the transfer of Sr isotopes to hydrologic regimes, and tracking the provenance of sediments.     

Optimal design of viscoelastic dampers using eigenvalue assignment

In this study a procedure for determining the optimum size and location of viscoelastic dampers is proposed using the eigenvalue assignment technique. Natural frequencies and modal damping ratios, required to realize a given target response, are determined first by the convex model. Then the desired dynamic structural properties are realized by optimally distributing the damping and stiffness coefficients of viscoelastic dampers using non‐linear programming based on the gradient of eigenvalues. This optimization method provides information on the optimal location as well as the magnitude of the damper parameters. The proposed procedure is applied to the retrofit of a 10‐story shear frame, and to a three‐dimensional structure with an asymmetric plan. The analysis results confirm that the responses of model structures retrofitted by the proposed method correspond well with the given target response. Copyright © 2003 John Wiley & Sons, Ltd.     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.     

A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

In the present work, climate change impacts on three spring (March–June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak–volume, peak–duration and volume–duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970–1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970–1999) and future (2041–2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties.     

Impact of vegetation feedback on the temperature and its diurnal range over the Northern Hemisphere during summer in a 2 × CO2 climate

This study examines the potential impact of vegetation feedback on the changes in the diurnal temperature range (DTR) due to the doubling of atmospheric CO₂ concentrations during summer over the Northern Hemisphere using a global climate model equipped with a dynamic vegetation model. Results show that CO₂ doubling induces significant increases in the daily mean temperature and decreases in DTR regardless of the presence of the vegetation feedback effect. In the presence of vegetation feedback, increase in vegetation productivity related to warm and humid climate lead to (1) an increase in vegetation greenness in the mid-latitude and (2) a greening and the expansion of grasslands and boreal forests into the tundra region in the high latitudes. The greening via vegetation feedback induces contrasting effects on the temperature fields between the mid- and high-latitude regions. In the mid-latitudes, the greening further limits the increase in T _max more than T _min, resulting in further decreases in DTR because the greening amplifies evapotranspiration and thus cools daytime temperature. The greening in high-latitudes, however, it reinforces the warming by increasing T _max more than T _min to result in a further increase in DTR from the values obtained without vegetation feedback. This effect on T _max and DTR in the high latitude is mainly attributed to the reduction in surface albedo and the subsequent increase in the absorbed insolation. Present study indicates that vegetation feedback can alter the response of the temperature field to increases in CO₂ mainly by affecting the T _max and that its effect varies with the regional climate characteristics as a function of latitudes.     

Statistical prediction of heavy rain in South Korea

1. Introduction In recent decades, extreme weather events seem to be growing in frequency and risk due to water-related disasters. According to the World Meteorological Or- ganization report (ISDR and WMO, 2004) on World Water Day, 22 March 2004, the economic losses caused by water-related disasters, including floods, droughts and tropical cyclones, are on an increasing trend as follows: the yearly mean in the 1970s was about 131 billion US dollars, 204 billion dollars in the 1980s, and …     

Assessing Winter Wheat Responses to Climate Change Scenarios: A Simulation Study in the U.S. Great Plains

Hard red winter wheat (Triticum aestivum L.) is a major crop in the Great Plains region of the U.S. The goal of this assessment effort was to investigate the influence of two contrasting global climate change projections (U.K. Hadley Center for Climate Prediction and Research and Canadian Centre for Climate Modelling and Analysis) on the yield and percent kernel nitrogen content of winter wheat at three locations in Nebraska. These three locations represent sub-humid and semi arid areas and the transition between these areas and are also representative of major portions of the winter wheat growing areas of the central Great Plains. Climate scenarios based on each of the projections for each location were developed using the LARS-WG weather generator along with data from automated weather stations. CERES-Wheat was used to simulate the responses for two contrasting cultivars of wheat using two sowing dates. The first sowing date represented current sowing dates appropriate for each location. The second sowing date was later and represents the approximate date when the mean air temperature from the climate scenarios is the same as the mean air temperature from the actual climate data at the current sowing dates. The yield and percent kernel nitrogen content using the two climate scenarios generally decrease going from the sub-humid eastern to the semi arid western parts of Nebraska. Results from these simulations indicate that yield and percent kernel nitrogen content using the two climate scenarios could not both be maintained at levels currently simulated. Protein content (directly related to kernel nitrogen content) and end-use quality are the primary determinants for the use of hard red winter wheat in baked goods. Nitrogen management and new cultivars, which can enhance the uptake and translocation of nitrogen, will be proactive steps to meet the challenges of global climate change as represented by these climate scenarios.     

Vertical distribution of giant jellyfish, <Emphasis Type="Italic">Nemopilema nomurai</Emphasis> using acoustics and optics

Nemopilema nomurai jellyfish, which are believed to complete their development in the East China Sea, have started migrating into the Yellow Sea in recent years. We obtained biomass estimates of this species in the Yellow Sea using bottom trawl fishing gear and sighting surveys over a 5-year period. These methods are effective for obtaining N. nomurai jellyfish density estimates and information about the community distribution near the bottom or surface of the sea. To verify the vertical distributions of giant jellyfish between, we used hydroacoustic equipment, including an optical stereo camera system attached to a towed sledge and an echo counting method with scientific echosounder system. Acoustic and optical data were collected while the vessel moved at 3 knots, from which the distribution and density of N. nomurai jellyfish were analyzed. Subsequently, the camera system was towed from a 7 m mean depth to sea level, with the detection range of the acoustic system extending from an 8 m depth to the bottom surface. The optical and acoustic methods indicated the presence of vertical distribution of 0.11³ (inds/m³) and 0.064 (inds/m3), respectively. However, the vertical distribution indicated that around 93% of individuals occurred at a depth range of 10–40 m; thus, a 2.4-fold greater density was estimated by acoustic echo counting compared to the optical method.