Proceedings of the Korean Institute of Navigation and Port Research Conference
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2002.03a
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pp.197-203
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2002
The estimation of pile bearing capacity is important since the design details are determined from the result. There are numerous ways of determining the pile design load, but only few of them are chosen in the actual design. According to the recent investigation in Korea, the formulas proposed by Meyerhof based on the SPT N values are most frequently chosen in the design stage. In the study, various static and dynamic formulas have been used in predicting the allowable bearing capacity of a pile. Further, the reliability of these formulas has been verified by comparing the perdicted values with the static and dynamic load test measurements. Also in cases, these methods of pile bearing capacity determination do not take the time effect consideration, the actual allowable load as determined from pile load test indicates severe deviation from the design value. The principle results of this study are summarized as follows : A a result of estimate the reliability in criterion of the Davisson method, in was showed that Terzaghi & Peck > Chin > Meyerhof > Modified Meyerhof method was the most reliable method for the prediction of bearing capacity. Comparisons of the various pile-driving formulas showed that Modified Engineering News was the most reliable method. However, a significant error happened between dynamic bearing capacity equation was judged that uncertainty of hammer efficiency, characteristics of variable , time effect etc... was not considered. As a result of considering time effect increased skin friction capacity higher than end bearing capacity. It was found out that it would be possible to increase the skin friction capacity 1.99 times higher than a driving. As a result of considering 7 day's time effect, it was obtained that Engineering News. Modified Engineering News. Hiley, Danish, Gates, CAPWAP(CAse Pile Wave Analysis Program ) analysis for relation, respectively, $Q_{u(Restrike)}$$Q_{u(EOID)}$ = 0.971 $t_{0.1}$, 0.968 $t_{0.1}$, 1.192 $t_{0.1}$, 0.88 $t_{0.1}$, 0.889 $t_{0.1}$, 0.966 $t_{0.1}$, 0.889 $t_{0.1}$, 0.966 $t_{0.1}$
KSCE Journal of Civil and Environmental Engineering Research
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v.33
no.2
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pp.529-536
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2013
The semi-distributed rainfall runoff model of SWAT is applied to the Seom-river experimental watershed. The simulations of various antecedent periods before the targeted simulation periods of 2002 to 2009 are not necessary despite of the slight appearance of corresponding changes in simulated total runoff. The simulated results of total runoff by using various numbers of soil layer maps have little differentiated nevertheless the slight changes in simulated results have been appeared. The 7 parameters of CANMX, $CN_2$, ESCO, GW_REVAP, SOL_ALB, SOL_AWC, and SOL_K greatly govern the rainfall runoff are confirmed and their sensitivity analyses have been carried out. The optimal parameters used in SWAT are derived by SUFI-2 of SWAT-CUP. The NS and $R^2$ are 0.99 and 0.98, respectively which is shown the good agreement between the observed and the simulated results. The uncertainty factors of P-factor and R-factor are 0.85 and 0.06, respectively which is also shown the high efficiency of the model. The high applicability is also shown with improving the RMSE in SWAT model simulation using the parameters estimated by SUFI-2 of SWAT-CUP.
KSCE Journal of Civil and Environmental Engineering Research
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v.37
no.1
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pp.29-41
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2017
Design rainfalls are one of the most important hydrologic data for river management, hydraulic structure design and risk analysis. The design rainfalls are first estimated by a point frequency analysis and the IDF (intensity-duration-frequency) curve is then constructed by a nonlinear regression to either interpolate or extrapolate the design rainfalls for other durations which are not used in the frequency analysis. It has been widely recognised that the more reliable approaches are required to better account for uncertainties associated with the model parameters under circumstances where limited hydrologic data are available for the watershed of interest. For these reasons, this study developed a hierarchical Bayesian based GLM (generalized linear model) for a regional frequency analysis in conjunction with a scaling function of the parameters in probability distribution. The proposed model provided a reliable estimation of a set of parameters for each individual station, as well as offered a regional estimate of the parameters, which allow us to have a regional IDF curve. Overall, we expected the proposed model can be used for different aspects of water resources planning at various stages and in addition for the ungaged basin.
This study is to develop digital leadership in a field of national defense. Today, korean society is facing the crisis of national security. But national defense leadership is not show in the circumstance of national security crisis. As you know, national defense leadership is a process that make use of influence. Which means it converges people's interest and demands well and also show people the right vision of national defense and make them to comply the policy about national security. Because of the environmental change, our national defense leadership is having a new turning point. First, international order, which is under post-cold war, raises possibility of guarantee of peace and security in international society but also, cause the increase of multiple uncertainty and small size troubles in security circumstance. In addition, Korean society is rushing into democratization and localization period by success in peaceful change of political power went through about three times. The issue of political neutralization of military is stepping into settlement but still, negative inheritance of old military regime is worrying about it. In this situation, we can't expect rise in estimation about the importance of security and military's reason for being. So, military have to give their concern to not only internal maintenance of order and control and growth of soldiers but also developing external leadership to strength influence to society and military's the reason for being. So for these alternative I'm suggesting a digital leadership of national defense which fits digital era. This digital leadership is the leadership which can accept and understand digital technology and lead the digital organization. To construct digital national defense we need a practical leadership. The leadership has to be digital leadership with digital competence that can direct vision of digital national defense and carry out the policy. A leader who ha s digital leadership can lead the digital society. The ultimate key to construct digital government, digital corporate and digital citizen depends on digital leader with digital mind. To be more specific, digital leadership has network leadership, next generation leadership, knowledge driven management leadership, innovation oriented leadership. A leader with this kind of leadership is the real person with digital leadership. From now on, to rise this, we have to build up human resource development strategy and develop educational training program.
This study was intended to investigate the rainfall-runoff relationship with spatially distributed rainfall data, and then, to analyze and quantify the uncertainty induced by spatially averaging rainfall data. For constructing spatially distributed rainfall data, several historical rainfall events were extended spatially by simple kriging method based on the semivariogram as a function of the relative distance. Runoff was computed by two models; one was the modified Clark model with spatially distributed rainfall data and the other was the conventional Clark model with spatially averaged rainfall data. Rainfall errors and discharge errors occurred through this process were defined and analyzed with respect to various rain-gage network densities. The following conclusions were derived as the results of this work; 1) The conventional Clark parameters could be appropriate for translating spatially distributed rainfall data. 2) The parameters estimated by the modified Clark model are more stable than those of the conventional Clark model. 3) Rainfall and discharge errors are shown to be reduced exponentially as the density of rain-gage network is increased. 4) It was found that discharge errors were affected largely by rainfall errors as the rain-gage network density was small.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.2
/
pp.412-424
/
2019
In this study, the changes of the streamflow characteristics of the watershed were analysed depending on the infiltration methods of CAT. The study area, Boryeong-dam watershed located in Chungcheongnam-do area, has been suffered from severe drought in recent years and stabilized regarding on the storage rate through efforts such as constructing a channel connecting the upstream of Boryeong-dam from the downstream of the Geum river. In this study, the effects of soil infiltration parameters on the watershed streamflow characteristics were analyzed by the infiltration methods of CAT such as Rainfall Excess, Green&Ampt and Horton. And the parameter calibrations were conducted by SCEUA-P, a global optimization technique module of the PEST, the package for parameter optimization and uncertainty analysis, to compare the yearly variations of soil parameters for infiltration methods of CAT. In addition, the streamflow characteristics were analyzed for three infiltration methods by applying three different scenarios, such as applying calibrated parameters for every years to simulate the model for each years, applying calibrated parameters for the entire period to simulate the model for entire period, and applying the average value of yearly calibrated parameters to simulate the model for entire period.
Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.
Kim, Hye Rim;Kim, Seung Do;Hong, Yu Deok;Lee, Su Bin;Jung, Ju Young
Journal of Climate Change Research
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v.2
no.3
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pp.203-219
/
2011
Greenhouse gas(GHG) inventories were reported recently in various fields. It, however, has been rarely to mention about the accuracy and reliability of the GHG inventory results. Some reliable assessment methods were introduced to judge the accuracy of the GHG inventory results. It is, hence, critical to develop an evaluation methodology. This project was designed 1) to develop evaluation methodology for reliability of inventory results by GHG-CAPSS, 2) to check the feasibility of the developed evaluation methodology as a result of applying this methodology to two emission sources: liquid fossil fuel and landfill, and 3) to construct the technical roadmap for future role of GHG-CAPSS. Qualitative and quantitative assessment methodologies were developed to check the reliability and accuracy of the inventory results. Qualitative assessment methodology was designed to evaluate the accuracy and reliability of estimation methods of GHG emissions from emission and sink sources, activity data, emission factor, and quality management schemes of inventory results. On the other hand, quantitative assessment methodology was based on the uncertainty assessment of emission results. According to the results of applying the above evaluation methodologies to two emission sources, those seem to be working properly. However, it is necessary to develop source-specific rating systems because emission and sink sources exhibit source-specific characteristics of GHG emissions and sinks.
Proceedings of the Korea Water Resources Association Conference
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2015.05a
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pp.217-217
/
2015
The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.
Journal of Korean Society of Disaster and Security
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v.13
no.4
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pp.25-36
/
2020
An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.
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