• Journal of Soil and Groundwater Environment
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• v.17 no.5
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• pp.56-67
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• 2012

In the present study, an enhanced subsurface prediction algorithm based on a non-parametric geostatistical model and a history matching technique through Gibbs sampler is developed and the iterative prediction improvement procedure is proposed. The developed model is applied to a simple two-dimensional synthetic case where domain is composed of three different hydrogeologic media with $500m{\times}40m$ scale. In the application, it is assumed that there are 4 independent pumping tests performed at different vertical interval and the history curves are acquired through numerical modeling. With two hypothetical borehole information and pumping test data, the proposed prediction model is applied iteratively and continuous improvements of the predictions with reduced uncertainties of the media distribution are observed. From the results and the qualitative/quantitative analysis, it is concluded that the proposed model is good for the subsurface prediction improvements where the history data is available as a supportive information. Once the proposed model be a matured technique, it is believed that the model can be applied to many groundwater, geothermal, gas and oil problems with conventional fluid flow simulators. However, the overall development is still in its preliminary step and further considerations needs to be incorporated to be a viable and practical prediction technique including multi-dimensional verifications, global optimization, etc. which have not been resolved in the present study.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.69-79
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• 2013

This paper presents a two-stage geostatistical integration approach that aims at downscaling of coarse scale remote sensing data. First, downscaling of the coarse scale sedoncary data is implemented using area-to-point kriging, and this result will be used as trend components on the next integration stage. Then simple kriging with local varying means that integrates sparse precise observation data with the downscaled data is applied to generate thematic information at a finer scale. The presented approach can not only account for the statistical relationships between precise observation and secondary data acquired at the different scales, but also to calibrate the errors in the secondary data through the integration with precise observation data. An experiment for precipitation mapping with weather station data and TRMM (Tropical Rainfall Measuring Mission) data acquired at a coarse scale is carried out to illustrate the applicability of the presented approach. From the experiment, the geostatistical downscaling approach applied in this paper could generate detailed thematic information at various finer target scales that reproduced the original TRMM precipitation values when upscaled. And the integration of the downscaled secondary information with precise observation data showed better prediction capability than that of a conventional univariate kriging algorithm. Thus, it is expected that the presented approach would be effectively used for downscaling of coarse scale data with various data acquired at different scales.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1047-1051
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• 2004

The design storm is a crucial element in urban drainage design and hydrological modeling. The total rainfall depth of a design storm is usually estimated by hydrological frequency analysis using historic rainfall records. The different geostatistical approaches (ordinary kriging, universal kriging) have been used as estimators and their results are compared and discussed. Variogram parameters, the sill, nugget effect and influence range, are analysis. Kriging method was applied for developing contour maps of design storm depths In bocheong stream basin. Effect to utilize weather radar data and grid-based basin model on the spatial variation characteristics of storm requires further study.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.252-258
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• 2007

We have studied the feasibility of geostatistics approach to enhancing analysis of sparsely obtained seismic data by combining with satellite gravity data. The shallow depth and numerous fishing nets in The Yellow Sea, west of Korea, makes it difficult to do seismic surveys in this area. Therefore, we have attempted to use geostatistics to integrate the seismic data along with gravity data. To evaluate the feasibility of this approach, we have extracted only a few seismic profile data from previous surveys in the Yellow Sea and performed integrated analysis combining with the results from gravity data under the assumption that seismic velocity and density have a high physical correlation. First, we analyzed the correlation between extracted seismic profiles and depths obtained from gravity inversion. Next, we transferred the gravity depth to travel time using non-linear indicator transform and analyze residual values by kriging with varying local means. Finally, the reconstructed time structure map was compared with the original seismic section given in the previous study. Our geostatistical approach demonstrates relatively satisfactory results and especially, in the boundary area where seismic lines are sparse, gives us more in-depth information than previously available.

• Environmental Engineering Research
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• v.22 no.4
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• pp.369-376
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• 2017

The trend analysis of the study was acquired by selecting multiyear monthly groundwater table data and monitors the wells in each sub-district under the study area. The intention of this research was to analyze the outcome of the non-parametric Mann-Kendall test at greater than the significance level which is 95% of groundwater level in Sylhet. The aptitude is effective at two conjunctures where the confidence bounds are 95% and it meets the estimate line of Sen's. To calculate and assess the spatial differences in the inanition of groundwater table, geostatistical methods was applied based on data from 27 groundwater wells during the period from January 1975 to December 2011 which were obtained from a secondary source, Bangladesh Water Development Board. The geographic information system was used to assess the spatial change in order to find the level of groundwater. Cross-validation errors were found within an advisable level in estimating the groundwater depth with different interpolation models of ordinary kriging methods. Finally, surface maps were generated with the best-fitted model. The southeast region was found highly vulnerable from groundwater level point of view. Northern region was detected highest hazard prone area for diverge groundwater using kriging method.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.29-38
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• 2010

It is necessary to develop an integration model which can account for various data acquired at different measurement scales in environmental thematic mapping with high-resolution ground survey data and relatively low-resolution remote sensing data. This paper presents and applies a multi-scale geostatistical methodology for downscaling of thematic maps generated from lowresolution remote sensing data. This methodology extends a traditional ordinary kriging system to a block kriging system which can account for both ground data and remote sensing data which can be regarded as point and block data, respectively. In addition, stochastic simulation based on block kriging is also applied to describe spatial uncertainty attached to the downscaling. Two downscaling experiments including SRTM DEM and MODIS Leaf Area Index (LAI) products were carried out to illustrate the applicability of the geostatistical methodology. Through the experiments, multi-scale geostatistics based on block kriging successfully generated relatively high-resolution thematic maps with reliable accuracy. Especially, it is expected that multiple realizations generated from simulation would be effectively used as input data for investigating the effects of uncertain input data on GIS model outputs.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.168-178
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• 2006

In recent years, an ingress of mass jellyfish into cooling water intake system causes interruption of electric power production at the Uljin nuclear power plant. Therefore, monitering and forecast on the mass ingress of marine organisms are demanded as one of the early preventing measurements. Sea water movement is a major factor on the ingress of marine organisms like Moon jellyfish which has weak self-mobile ability. When sea surface flow direction adjacent to the Uljin is the northwest, the jellyfish on the Tsushima warm currents move to the Uljin power plant. To detect the direction of sea surface warm flows, the spatial range with $25km{\times}25km$ is set up and NOAA sea surface temperature(SST) data are collected in this area. For the statistical analysis, the SST data are made as GIS point data and geostatistical analysis of ArcGIS is used. Analyzing directional semivariogram, the anisotropy of the SST point data are calculated and warm flow direction is detected. This experimental results are expected to use as an element technology for the early warning system development of mass jellyfish ingress in power plant.

• Environmental Analysis Health and Toxicology
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• v.31
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• pp.6.1-6.10
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• 2016

Objectives This study examined the spatial distribution and the extent of soil contamination by heavy metals resulting from primitive, unconventional informal electronic waste recycling in the Agbogbloshie e-waste processing site (AEPS) in Ghana. Methods A total of 132 samples were collected at 100 m intervals, with a handheld global position system used in taking the location data of the soil sample points. Observing all procedural and quality assurance measures, the samples were analyzed for barium (Ba), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn), using X-ray fluorescence. Using environmental risk indices of contamination factor and degree of contamination ($C_{deg}$), we analyzed the individual contribution of each heavy metal contamination and the overall $C_{deg}$. We further used geostatistical techniques of spatial autocorrelation and variability to examine spatial distribution and extent of heavy metal contamination. Results Results from soil analysis showed that heavy metal concentrations were significantly higher than the Canadian Environmental Protection Agency and Dutch environmental standards. In an increasing order, Pb>Cd>Hg>Cu>Zn>Cr>Co>Ba>Ni contributed significantly to the overall $C_{deg}$. Contamination was highest in the main working areas of burning and dismantling sites, indicating the influence of recycling activities. Geostatistical analysis also revealed that heavy metal contamination spreads beyond the main working areas to residential, recreational, farming, and commercial areas. Conclusions Our results show that the studied heavy metals are ubiquitous within AEPS and the significantly high concentration of these metals reflect the contamination factor and $C_{deg}$, indicating soil contamination in AEPS with the nine heavy metals studied.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.59-64
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• 2005

Although experimental analysis for groundwater sample at wells located systematically are very effective to delineate seawater intrusion region at coastal area, this method is restricted in few wells and time. We have conducted electrical resistivity sounding at 30 points in the study areas to analyze the region of seawater intrusion and found the boundary between salt wedge and fresh water lens from the analysis results of geostatistical method using variogram for one-dimensional inversion results. The methodology adopted in this study would be useful for finding the seawater intrusion region and evaluating quantitatively.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.285-290
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• 2006

To access the volume of sediments deposited after construction of the Soyang Dan and to understand their distribution in the Soyang lake, acoustic profiling using a 10-20 kHz system was conducted along profiles of 227 km length. Profile intervals are approximately 50 and 500 m for longitudinal and cross lines, respectively. The data were gain-controlled and then migrated using the f-k algorithm. After digitization of boundaries of the sediments, the acoustic interpretation was verified through correlating with 38 core samples. Thickness of the sediments averages 0.25 m and reaches to 8.25 m at maximum. Estimated total volume of the sediments based on anisotropic models in geostatistical methods is approximately $5.9{\times}10^6\;m^3$, which is more than twice greater than the earlier estimation based on an isotropic model.