Study of the State and Variability of Marine Environment in the Japan/East Sea in Cruise 58 of the R/V Akademik Oparin

Oceanology - Multiyear monitoring of the marine environment of the Japan/East Sea was continued by the joint Korean–Russian expedition of the R/V Akademik Oparin (cruise 58) in...     

Combining landslide susceptibility maps obtained from frequency ratio,logistic regression,and artificial neural network models using ASTER images and GIS

Landslide-related factors were extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, and integrated techniques were developed, applied, and verified for the analysis of landslide susceptibility in Boun, Korea, using a geographic information system (GIS). Digital elevation model (DEM), lineament, normalized difference vegetation index (NDVI), and land-cover factors were extracted from the ASTER images for analysis. Slope, aspect, and curvature were calculated from a DEM topographic database. Using the constructed spatial database, the relationships between the detected landslide locations and six related factors were identified and quantified using frequency ratio (FR), logistic regression (LR), and artificial neural network (ANN) models. These relationships were used as factor ratings in an overlay analysis to create landslide susceptibility indices and maps. Three landslide susceptibility maps were then combined and applied as new input factors in the FR, LR, and ANN models to make improved susceptibility maps. All of the susceptibility maps were verified by comparison with known landslide locations not used for training the models. The combined landslide susceptibility maps created using three landslide-related input factors showed improved accuracy (87.00% in FR, 88.21% in LR, and 86.51% in ANN models) compared to the individual landslide susceptibility maps (84.34% in FR, 85.40% in LR, and 74.29% in ANN models) generated using the six factors from the ASTER images.     

A Constitutive Model for Shear Behavior of Rock Joints Based on Three-Dimensional Quantification of Joint Roughness

A new constitutive model to describe the shear behavior of rock joints under constant normal stiffness (CNS) and constant normal load (CNL) conditions is proposed. The model was developed using an empirical approach based on the results of a total of 362 direct shear tests on tensile fractured rock joints and replicas of tensile joints and on a new quantitative roughness parameter. This parameter, the active roughness coefficient C _r, is derived from the features of the effective roughness mobilized at the contact areas during shearing. The model involves a shear strength criterion and the relations between stresses and displacements in the normal and shear directions, where the effects of the boundary conditions and joint properties are considered by the shape indices C _d and C _f. The model can be used to predict the shear behavior under CNS as well as CNL conditions. The shear behavior obtained from the experimental results is generally in good agreement with that estimated by the proposed model, and the effects of joint roughness, initial normal stress, and normal stiffness are reasonably reflected in the model.     

Toxicological impact assessment of heavy metal contamination on macrobenthic communities in southern coastal sediments of Korea

In the heavily industrialized Masan Bay of southern coast, Korea, the potential harmful effects of heavy metals (Cd, Co, Cu, Ni, Pb, Sn, Zn, and Hg) were evaluated in terms of the pollution load index (PLI) and ecological risk assessment index (ERI) methods, and the results obtained were considered alongside the health of the macrobenthic fauna communities. The results revealed that the bay sediments, especially in the inner bay and the outfall area of a sewage treatment plant, are exposed to moderate to serious levels of metal pollution. Hg and Cd contributed the most to the potential toxicity response indices in sediments recently deposited in the bay. The potential ecological risk assessment of heavy metals in the bay was highlighted by the use of the benthic biological pollution index (BPI), suggesting that the ERI is a useful toxicity response index, which can quantify the overall ecological risk level to a target environment.     

Influence of Pressure Change During Hydraulic Tests on Fracture Aperture

In a series of field experiments, we evaluate the influence of a small water pressure change on fracture aperture during a hydraulic test. An experimental borehole is instrumented at the Korea Atomic Energy Research Institute (KAERI) Underground Research Tunnel (KURT). The target fracture for testing was found from the analyses of borehole logging and hydraulic tests. A double packer system was developed and installed in the test borehole to directly observe the aperture change due to water pressure change. Using this packer system, both aperture and flow rate are directly observed under various water pressures. Results indicate a slight change in fracture hydraulic head leads to an observable change in aperture. This suggests that aperture change should be considered when analyzing hydraulic test data from a sparsely fractured rock aquifer.     

Biomagnification of persistent chlorinated and brominated contaminants in food web components of the Yellow Sea

Concentrations of polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), and polybrominated diphenyl ethers (PBDEs) were measured in 32 species inhabiting the Yellow Sea to assess their bioaccumulation potentials. The concentrations in these samples were lower than those reported for other countries or locations. Relatively high levels of BDE 209 in biota suggest an ongoing source of deca-BDE technical mixing within the Yellow Sea. The accumulation profiles of PCBs were uniform between species, but the concentrations of OCPs and PBDEs varied widely. Pelagic and benthic food-chain components were separated by their δ¹³C values. Significant positive correlations between δ¹⁵N and PCB 153, PCB 138, p,p′-DDE, oxy-chlordane, and trans-nonachlordane were found only for pelagic consumers, indicating that the pelagic food chain is an important bioaccumulation pathway for selected PCB and OCP compounds. The other compounds did not show any biomagnification through benthic and pelagic food chains, suggesting the lower bioaccumulation potentials of these contaminants.     

Evaluation of GPS orbit prediction strategies for the IGS Ultra-rapid products

The International GNSS Service (IGS) provides Ultra-rapid GPS & GLONASS orbits every 6 h. Each product is composed of 24 h of observed orbits with predicted orbits for the next 24 h. We have studied how the orbit prediction performance varies as a function of the arc length of the fitted observed orbits and the parameterization strategy used to estimate the empirical solar radiation pressure (SRP) effects. To focus on the dynamical aspects of the problem, nearly ideal conditions have been adopted by using IGS Rapid orbits and known earth rotation parameters (ERPs) as observations. Performance was gauged by comparison with Rapid orbits as truth by examining WRMS and median orbit differences over the first 6-h and the full 24-h prediction intervals, as well as the stability of the Helmert frame alignment parameters. Two versions of the extended SRP orbit model developed by the Centre for Orbit Determination in Europe (CODE) were tested. Adjusting all nine SRPs (offsets plus once-per-revolution sines and cosines in each satellite-centered frame direction) for each satellite shows smaller mean sub-daily, scale, and origin translation differences. On the other hand, eliminating the four once-per-revolution SRP parameters in the sun-ward and the solar panel axis directions yields orbit predictions that are much more rotationally stable. We found that observed arc lengths of 40–45 h produce the most stable and accurate predictions during 2010. A combined strategy of rotationally aligning the 9 SRP results to the 5 SRP frame should give optimal predictions with about 13 mm mean WRMS residuals over the first 6 h and 50 mm over 24 h. Actual Ultra-rapid performance will be degraded due to the unavoidable rotational errors from ERP predictions.     

Landslide susceptibility mapping using GIS and the weight-of-evidence model

The weights-of-evidence model (a Bayesian probability model) was applied to the task of evaluating landslide susceptibility using GIS. Using landslide location and a spatial database containing information such as topography, soil, forest, geology, land cover and lineament, the weights-of-evidence model was applied to calculate each relevant factor's rating for the Boun area in Korea, which had suffered substantial landslide damage following heavy rain in 1998. In the topographic database, the factors were slope, aspect and curvature; in the soil database, they were soil texture, soil material, soil drainage, soil effective thickness and topographic type; in the forest map, they were forest type, timber diameter, timber age and forest density; lithology was derived from the geological database; land-use information came from Landsat TM satellite imagery; and lineament data from IRS satellite imagery. Tests of conditional independence were performed for the selection of factors, allowing 43 combinations of factors to be analysed. For the analysis of mapping landslide susceptibility, the contrast values, W ⁺ and W ^-, of each factor's rating were overlaid spatially. The results of the analysis were validated using the previous landslide locations. The combination of slope, curvature, topography, timber diameter, geology and lineament showed the best results. The results can be used for hazard prevention and land-use planning.     

Uncertainty of snow water equivalent retrieved from AMSR‐E brightness temperature in northeast Asia

Accurate estimation of snow water equivalent (SWE) has been significantly recognized to improve management and analyses of water resource in specific regions. Although several studies have focused on developing SWE values based on remotely sensed brightness temperatures obtained by microwave sensor systems, it is known that there are still a number of uncertainties in SWE values retrieved from microwave radiometers. Therefore, further research for improving remotely sensed SWE values including global validation should be conducted in unexplored regions such as Northeast Asia. In this regard, we evaluated SWE through comparison of values produced by the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR‐E) from December 2002 to February 2011 with in situ SWE values converted from snow‐depth observation data from four regions in the South Korea. The results from three areas showed similarities which indicated that the AMSR‐E SWE values were overestimated when compared with in situ SWE values, and their Mean Absolute Errors (MAE) by month were relatively small (1.1 to 6.5 mm). Contrariwise, the AMSR‐E SWE values of one area were significantly underestimated when compared with in situ SWE values and the MAE were much greater (4.9 to 35.2 mm). These results were closely related to AMSR‐E algorithm‐related error sources, which we analyzed with respect to topographic characteristics and snow properties. In particular, we found that snow density data used in the AMSR‐E SWE algorithm should be based on reliable in situ data as the current AMSR‐E SWE algorithm cannot reflect the spatio‐temporal variability of snow density values. Additionally, we derived better results considering saturation effect of AMSR‐E SWE. Despite the demise of AMSR‐E, this study's analysis is significant for providing a baseline for the new sensor and suggests parameters important for obtaining more reliable SWE. Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluation of multiple surface soil moisture for Korean regional flux monitoring network sites: Advanced Microwave Scanning Radiometer E,land surface model,and ground measurements

In the past few decades, there have been great developments in remotely sensed soil moisture, with validation efforts using land surface models (LSMs) and ground‐based measurements, because soil moisture information is essential to understanding complex land surface–atmosphere interactions. However, the validation of remotely sensed soil moisture has been very limited because of the scarcity of the ground measurements in Korea. This study validated Advanced Microwave Scanning Radiometer E (AMSR‐E) soil moisture data with the Common Land Model (CLM), one of the most widely used LSMs, and ground‐based measurements at two Korean regional flux monitoring network sites. There was reasonable agreement regarding the different soil moisture products for monitoring temporal trends except National Snow and Ice Data Centre (NSIDC) AMSR‐E soil moisture, albeit there were essential comparison limitations by different spatial scales and soil depths. The AMSR‐E soil moisture data published by the National Aeronautics and Space Administration and Vrije Universiteit Amsterdam (VUA) showed potential to replicate temporal variability patterns (root‐mean‐square errors = 0·10–0·14 m³ m^?3 and wet BIAS = 0·09 ? 0·04 m³ m^?3) with the CLM and ground‐based measurements. However, the NSIDC AMSR‐E soil moisture was problematic because of the extremely low temporal variability and the VUA AMSR‐E soil moisture was relatively inaccurate in Gwangneung site characterized by complex geophysical conditions. Additional evaluations should be required to facilitate the use of recent and forthcoming remotely sensed soil moisture data from Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive missions at representative future validation sites. Copyright © 2011 John Wiley & Sons, Ltd.