• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.831-838
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• 2018

This paper presents a method to estimate the flow discharge in a backwater affected river junction. First, unsteady HEC-RAS model was simulated and calibrated using 2 recent real flood and then HPG (Hydraulic Performance Graph) was created by plotting the relationship between upstream and downstream stages and discharge in the reach and performing kriging interpolation. During a flood, the discharge through the reach can be estimated based on the stages at its ends and the developed HPG. These discharge data were in good agreement with the automatic discharge measurements such as ADVM. This study could provide an economical and practical method for estimating discharge in a junction with a high hysteresis of stage-discharge relationships.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.23-33
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• 2011

In this study, the data that examined the chloride ion concentration of ground water wells in the west coast of Jeollabukdo applying the GIS spatial estimation method were analyzed. In particular, through the designation of a validation point among ground water wells and then the analysis of error characteristics of the chloride ion concentration by each method of IDW (Inverse Distance Weight), Spline, and Kriging Interpolation method which is proper for estimating salt water intrusion was selected. The main conclusion from this study is as follows. First, as a result of analyzing the error characteristics of various spatial estimation methods by using the data from the chloride ion concentration of 485 ground water wells, the IDW method was found to be the most appropriate for estimating chloride ion concentration by salt water intrusion. Second, analyzing the average chloride ion concentration of the targeted regions has revealed that Gunsan-si with the record of $541mg/{\ell}$ did not meet water quality standards even for industrial use. Both Gimje-si and Gochang-gun satisfied drinking water quality standards and Buan-gun with $272mg/{\ell}$ was slightly below the standards for drinking water. Third, concerning the results of analysis according to administrative districts, as the areas adjacent to the west coast such as Daemyeong-dong, Joong-dong, Jangjae-dong and Guemam-dong in Gunsan-si are found to have very high chloride ion concentration, and both Hoehyeon-myeon and Daeya-myeon bounded by the Mankeong river did not meet water quality standards even for industrial use. From these facts, it is concluded that salt water intrusion has a great effect on Gunsan-si generally.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.74-81
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• 2019

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.21-33
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• 2019

This study performed to simulate the watershed storm runoff using data of S-band dual-polarization radar rain, GPM (Global Precipitation Mission) satellite rain, and observed rainfall at 21 ground stations operated by KMA (Korea Meteorological Administration) respectively. For the 3 water level gauge stations (Sancheong, Changchon, and Namgang) of NamgangDam watershed ($2,293km^2$), the KIMSTORM2 (KIneMatic wave STOrm Runoff Model2) was applied and calibrated with parameters of initial soil moisture contents, Manning's roughness of overland and stream to the event of typhoon CHABA (82 mm in watershed aveprage) in $5^{th}$ October 2016. The radar and GPM data was corrected with CM (Conditional Merging) method such as CM-corrected Radar and CM-corrected GPM. The CM has been used for accurate rainfall estimation in water resources and meteorological field and the method combined measured ground rainfall and spatial data such as radar and satellite images by the kriging interpolation technique. For the CM-corrected Radar and CM-corrected GPM data application, the determination coefficient ($R^2$) was 0.96 respectively. The Nash-Sutcliffe efficiency (NSE) was 0.96 and the Volume Conservation Index (VCI) was 1.03 respectively. The CM-corrected data of Radar and GPM showed good results for the CHABA peak runoff and runoff volume simulation and improved all of $R^2$, NSE, and VCI comparing with the original data application. Thus, we need to use and apply the radar and satellite data to monitor the flood within the watershed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Journal of the Korean GEO-environmental Society
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• v.15 no.3
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• pp.65-74
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• 2014

Borehole investigation which is mainly used to figure out geotechnical characterizations at construction work has the benefit that it provides a clear and convincing geotechnical information. But it has limitations to get the overall information of the construction site because it is performed at point location. In contrast, geophysical measurements like seismic survey has the advantage that the geological stratum information of a large area can be characterized in a continuous cross-section but the result from geophysics survey has wide range of values and is not suitable to determine the geotechnical design values directly. Therefore it is essential to combine borehole data and geophysics data complementally. Accordingly, in this study, a three-dimensional spatial interpolation of the cross-sectional distribution of seismic refraction was performed using digitizing and geostatistical method (krigring). In the process, digital map were used to increase the trustworthiness of method. Using this map, errors of ground height which are broken out in measurement from boring investigation and geophysical measurements can be revised. After that, average seismic velocity are derived by comparing borehole data with geophysical speed distribution data of each soil layer. During this process, outlier analysis is adapted. On the basis of the average seismic velocity, integrated analysis techniques to determine the three-dimensional geological stratum information is established. Finally, this analysis system is applied to dam construction field.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.379-394
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• 2021

Air pollution data in South Korea is provided on a real-time basis by Air Korea stations since 2005. Previous studies have shown the feasibility of gridding air pollution data, but they were confined to a few cities. This paper examines the creation of nationwide gridded maps for PM10 concentration using 333 Air Korea stations with variogram optimization and ordinary kriging. The accuracy of the spatial interpolation was evaluated by various sampling schemes to avoid a too dense or too sparse distribution of the validation points. Using the 114,745 matchups, a four-round blind test was conducted by extracting random validation points for every 365 days in 2019. The overall accuracy was stably high with the MAE of 5.697 ㎍/m³ and the CC of 0.947. Approximately 1,500 cases for high PM10 concentration also showed a result with the MAE of about 12 ㎍/m³ and the CC over 0.87, which means that the proposed method was effective and applicable to various situations. The gridded maps for daily PM10 concentration at the resolution of 0.05° also showed a reasonable spatial distribution, which can be used as an input variable for a gridded prediction of tomorrow's PM10 concentration.

• Journal of the Korean Geotechnical Society
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• v.20 no.2
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• pp.131-141
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• 2004

For geotechnical applications, engineers use data obtained from a site investigation to interpret the structure and potential behavior of the subsurface. In most cases, these data consist of samples that represent 1/100,000 or less of the total volume of soil. These samples and associated field and lab testing provide the information used to estimate soil parameter values. The resulting values are estimated ones and there exists some likelihood that actual soil conditions are significantly different from the estimates. This may be the case even if the sampling and interpretation procedures are performed in accordance with standard practice. Although these efforts have been made to characterize the uncertainty associated with geotechnical parameters, there is no commonly accepted method to evaluate quantitatively the quality of an investigation plan as a whole or the relative significance of individual sampling points or potential sampling points.

• Journal of the Korean earth science society
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• v.31 no.7
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• pp.681-690
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• 2010

Inversion result of geophysical data given as a block type was geostatistically simulated with borehole observation given as a point type and was applied to the rock classifying map. The geophysical data generally involved secondary information for the target material and were obtained for overall region. In contrast, borehole data provided direct information for the target material, but tended to be effective only for a narrow range of region and were dealt as a point type. Integrated simulation or kriging interpolation of these two different kinds of information required the covariance for point-point, point-block and block-block. Using the Bssim module included in SGeMS software, integrated result of geophysical data and borehole data were obtained. The results were then compared with the method of geostatistical inversion proposed by authors. Downscaling method used in this study showed relatively more flexible than the geostatistical inversion.