• Smart Structures and Systems
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• v.20 no.1
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• pp.11-22
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• 2017

The long-term effect of ambient temperature on bridge strain is an important and challenging problem. To investigate this issue, one year data of strain and ambient temperature of a long-span cable-stayed bridge is studied in this paper. The measured strain-time history is decomposed into two parts to obtain the strains due to vehicle load and temperature alone. A linear regression model between the temperature and the strain due to temperature is established. It is shown that for every $1^{\circ}C$ increase in temperature, the stress is increased by 0.148 MPa. Furthmore, the extreme value distributions of the strains due to vehicle load, temperature and the combination effect of them during the remaining service period are estimated by the average conditional exceedance rate approach. This approach avoids the problem of declustering of data to ensure independence. The estimated results demonstrate that the 95% quantile of the extreme strain distribution due to temperature is up to $1.488{\times}10^{-4}$ which is 2.38 times larger than that due to vehicle load. The study also indicates that the estimated extreme strain can reflect the long-term effect of temperature on bridge strain state, which has reference significance for the reliability estimation and safety assessment.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.311-320
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• 2021

The agricultural water, which occupy about 61% of total water usage in the South Korea, is significantly objective to archieve effecitive water resources management. The objective of the study is to suggest a simple method in actual practice that could be used to estimate agricultural water usage in river considering hydrological condition. Historical record of agricultural water usage and runoff, which take account for hydrological condition of the basin, were obtained for totally 27 river basins. As the result, the high threshold value of the agricultural water usage rates compared to maximum usage amount has a particular correlations to the percent of normal year runoff for last 2 month, and threshold line of agricultural water usage rates was derived using the quantile regressions. Finally, two dimensionless threshold line and empirical formulas that described the correlation between the percent of normal year runoff for last 2 month and the agricultural water usage rate compared to maximum usage amount were derived. Also, the simple criteria to select which line and formula based on the characteristics of the basins was suggested but it need further studies. The result of the study could be used as an elemantary data in actual practice for water resoureces management.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.497-514
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• 2023

Purpose: This study aims to estimate the demand for various public parking lots in Seoul by clustering similar demand types of parking lots and predicting the demand for new public parking lots. Methods: We examined real-time parking information data and used time series clustering analysis to cluster public parking lots with similar demand patterns. We also performed various regression analyses of parking demand based on diverse heterogeneous data that affect parking demand and proposed a parking demand prediction model. Results: As a result of cluster analysis, 68 public parking lots in Seoul were clustered into four types with similar demand patterns. We also identified key variables impacting parking demand and obtained a precise model for predicting parking demands. Conclusion: The proposed prediction model can be used to improve the efficiency and publicity of public parking lots in Seoul, and can be used as a basis for constructing new public parking lots that meet the actual demand. Future research could include studies on demand estimation models for each type of parking lot, and studies on the impact of parking lot usage patterns on demand.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.383-391
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• 2015

As occurrence of gradually increasing extreme temperature events in Jeju Island, a hybrid downscaling technique that simultaneously applies by dynamical method and statistical method has implemented on design rainfall in order to reduce flood damages from severe storms and typhoons.As a result of computation, Case 1 shows a strong tendency to excessively compute rainfall, which is continuously increasing. While Case 2 showed similar trend as Case 1, low design rainfall has computed by rainfall in A1B scenario. Based on the design rainfall computation method mainly used in Preventive Disaster System through Pre-disaster Effect Examination System and Basic Plan for River of Jeju Island which are considering climatic change for selecting 50-year and 100-year frequencies. Case 3 selecting for Jeju rain gage station and Case 1 for Seogwipo rain gage station. The results were different for each rain gage station because of difference in rainfall characteristics according to recent climatic change, and the risk of currently known design rainfall can be increased in near future.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.747-759
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• 2018

Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.733-745
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• 2010

Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.29-35
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• 2011

This research proposes the suitable method for estimating the future probable rainfall based in 2100 on the observed rainfall data from main climate observation stations in Korea and the rainfall data from the A1B climate change scenario in the Korea Meteorological Administration. For all those, the frequency probable rainfall in 2100 was estimated by the relationship between average values of 24-hours annual maximum rainfalls and related parameters. Three methods to estimate it were introduced; First one is the regressive analysis method by parameters of probable distribution estimated by observed rainfall data. In the second method, parameters of probable distribution were estimated with the observed rainfall data. Also the rainfall data till 2100 were estimated by the A1B scenario of the Korea Meteorological Administration. Last method was that parameters of probable distribution and probable rainfall were estimated by the A1B scenario of the Korea Meteorological Administration. The estimated probable rainfall by the A1B scenario was smaller than the observed rainfall data, so it is required that the estimated probable rainfall was calibrated by the quantile mapping method. After that calibration, estimated probable rainfall data was averagely became approximate 2.3 to 3.0 times. When future probable rainfall was the estimated by only observed rainfall, estimated probable rainfall was overestimated. When future probable rainfall was estimated by the A1B scenario, although it was estimated by similar pattern with observed rainfall data, it frequently does not consider the regional characteristics. Comparing with average increased rate of 24-hours annual maximum rainfall and increased rate of probable rainfall estimated by three methods, optimal method of estimated future probable rainfall would be selected for considering climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• Journal of Korea Water Resources Association
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• v.52 no.4
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• pp.245-253
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• 2019

The objectives of this study are to estimate the return period of flash flood and evaluate its appropriateness based on the actual observation events for small mountainous watersheds in the Han River basin. For these goals, Flash Flood Guidance (FFG) was estimated from 1-hr duration Threshold Runoff (TR) and Saturation Deficit (SD) of soil moisture which was derived from Sejong University Rainfall Runoff (SURR) model. Then, the return period of flash flood was calculated by comparing the rainfall quantile to the 1-hr duration rainfall that exceeded the FFG during the past period (2002-2010). Moreover, the appropriateness of the estimated return period of flash flood was evaluated by using the observation events from 2011 to 2016. The results of the return period of flash flood ranged from 1.1 to 19.9 years with a mean and a standard deviation of 1.6 and 1.1 years, respectively. Also, the result of the appropriateness indicated that 83% of the return periods derived from observation events were within the return period of flash flood range. Therefore, the estimated return period of flash flood could be considered as highly appropriate.

• Journal of Korea Water Resources Association
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• v.33 no.4
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• pp.419-426
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• 2000

It is very important to establish sufficiently long and reliable annual maximum rainfall data in estimating areal rainfall quantiles of Han River Basin. The data from 9 gauging stations measured by Korea Meteorological Administration may meet such a requirement, however the number of these data sets is too small to estimate overall areal rainfall quantiles in large basin such as Han River Basin. In order to solve such a problem, the space correlations of many sites' data measured by Korea Ministry of Construction and Transportation and Korea Water Resources Corporation (the number of sites is 59) were used for modification of rainfall measure density. And areal rainfall quantiles according to each sub-basin were estimated based on regression analysis.