• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.29-29
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• 2015

수자원의 지속적인 관리 및 효율적인 활용을 위하여 수문량의 예측과 분석은 필수적인 과정이라 할 수 있으며 이에 따라 다양한 수문 모형이 구축되고 강우, 유량 등 대표적인 수문량의 예측이 수행되어져 왔다. 그 중에서도 수문 시계열 모형은 시간의 흐름에 따라 일정하게 기록되어온 수문 자료를 확률적인 과정을 통하여 모형을 구축하고 이를 바탕으로 미래 수문량을 예측하는 데활용되는 모형으로, 과거에 기록된 수문 패턴이 미래에도 지속된다는 가정 하에 구축된다. 일반적으로 시계열 모형은 하나의 자료계열로 모형을 구축하는 단변량 모형과 원 자료계열 외에 다른 자료계열을 고려하여 모형을 구축하는 다변량 모형이 있으며, 다변량 모형은 원 자료계열에 영향을 미치는 외부변수를 고려함으로써 두 자료계열간의 상관성을 모형에 반영할 수 있는 장점을 가지고 있다. 또한 자료계열의 계절성을 고려하여 시계열 모형을 구축할 경우, 수문 시계열이 가지고 있는 계절적 영향을 잘 반영할 수 있다. 따라서 본 연구에서는 계절성을 고려한 다변량 시계열 모형인 SARIMAX(Seasonal AutoRegressive Integrated Moving Average with eXogenous) 모형을 이용하여 대표적인 수공구조물인 댐의 유입량 예측을 수행하였다. 일반적으로 댐 유입량 예측에는 댐의 유입량과 상관성이 높은 강우가 외부변수로 사용되어져 왔으나, 이 외에도 영향을 미칠 수 있는 지점특성치를 고려하여 모형을 구축한 후 비교하였다.

• Journal of Wellbeing Management and Applied Psychology
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• v.4 no.3
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• pp.23-33
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• 2021

Purpose: In the course of the domestic environmental impact assessment, the current status survey was improperly conducted, and the issue of false and inaccurate environmental impact assessment reports has been raised several times recently through media reports. Research design, data and methodology: There is a continuous demand for improvement measures for the current status measurement method, such as having difficulties in securing a normal measurement date in consideration of equipment operation and rainfall days in the field. Results: In addition, in order to grasp the general air quality status of the evaluation target area, it is necessary to check the various current status concentrations by season and time series per year. However, there is a problem that is currently being carried out based on limited results such as measurement for 1 day or 3 days. Conclusions: Therefore, in this study, based on the national atmospheric measurement network, an inverse distance weighted (IDW) interpolation method was applied to calculate the current state concentration. This study suggested a method to use it in preparing the air quality item in the environmental impact assessment report.

• Geomechanics and Engineering
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• v.35 no.1
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• pp.13-27
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• 2023

The model production for large-scale (lateral length ≥ 2.0 m) capillary barrier (CB) model tests is time and cost-intensive. To address these limitations, the framework of a small-scale CB (SSCB) model test under the lateral no-flow condition has been established. In this study, to validate the experimental methodology of the SSCB model test, a series of seepage analyses on the SSCB model test and engineered slopes in the same and additional test conditions was performed. First, the seepage behavior and diversion length (L_D) of the CB system were investigated under three rainfall conditions. In the seepage analysis for the engineered slopes with different slope angles and sand layer thicknesses, the L_D increased with the increase in the slope angle and sand layer thickness, although the increase rate of the L_D with the sand layer thickness exhibited an upper limit. The L_D values from the seepage analysis agreed well with the results estimated from the laboratory SSCB mode test. Therefore, it can be concluded that the experimental methodology of the SSCB model test is one of the promising alternatives to efficiently evaluate the water-shielding performance of the CB system for an engineered slope.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.263-274
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• 2013

In this study we evaluated the hydrological applicability of multi-satellite precipitation estimates. Three high-resolution global multi-satellite precipitation products, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), the Global Satellite Mapping of Precipitation (GSMaP), and the Climate Precipitation Center (CPC) Morphing technique (CMORPH), were applied to the Coupled Routing and Excess Storage (CREST) model for the evaluation of their hydrological utility. The CREST model was calibrated from 2002 to 2005 and validated from 2006 to 2009 in the Chungju Dam watershed, including two years of warm-up periods (2002-2003 and 2006-2007). Areal-averaged precipitation time series of the multi-satellite data were compared with those of the ground records. The results indicate that the multi-satellite precipitation can reflect the seasonal variation of precipitation in the Chungju Dam watershed. However, TMPA overestimates the amount of annual and monthly precipitation while GSMaP and CMORPH underestimate the precipitation during the period from 2002 to 2009. These biases of multi-satellite precipitation products induce poor performances in hydrological simulation, although TMPA is better than both of GSMaP and CMORPH. Our results indicate that advanced rainfall algorithms may be required to improve its hydrological applicability in South Korea.

• Economic and Environmental Geology
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• v.4 no.4
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• pp.225-234
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• 1971

With the advance of civilization and steadily increasing population rivalry and competition for the use of the sewage, culverts, farm irrigation and control of various types of flood discharge have developed and will be come more and more keen in the future. The author has tried to calculated a formula that could adjust these conflicts and bring about proper solutions for many problems arising in connection with these conditions. The purpose of this study is to find out effective sewage, culvert, drainage, farm irrigation, flood discharge and other engineering needs in the Taegu area. If demands expand further a new formula will have to be calculated. For the above the author estimated methods of control for the probable expected rainfall using a formula based on data collected over a long period of time. The formula is determined on the basis of the maximum daily rainfall data from 1921 to 1971 in the Taegu area. 1. Iwai methods shows a highly significant correlation among the variations of Hazen, Thomas, Gumbel methods and logarithmic normal distribution. 2. This study obtained the following major formula: ${\log}(x-2.6)=0.241{\xi}+1.92049{\cdots}{\cdots}$(I.M) by using the relation $F(x)=\frac{1}{\sqrt{\pi}}{\int}_{-{\infty}}^{\xi}e^{-{\xi}^2}d{\xi}$. ${\xi}=a{\log}_{10}\(\frac{x+b}{x_0+b}\)$ ($-b<x<{\infty}$) ${\log}(x_0+b)=2.0448$ $\frac{1}{a}=\sqrt{\frac{2N}{N-1}}S_x=0.1954$. $b=\frac{1}{m}\sum\limits_{i=1}^{m}b_s=-2.6$ $S_x=\sqrt{\frac{1}{N}\sum\limits^N_{i=1}\{{\log}(x_i+b)\}^2-\{{\log}(x_0+b)\}^2}=0.169$ This formule may be advantageously applicable to the estimation of flood discharge, sewage, culverts and drainage in the Taegu area. Notation for general terms has been denoted by the following. Other notations for general terms was used as needed. $W_{(x)}$ : probability of occurranec, $W_{(x)}=\int_{x}^{\infty}f_{(n)}dx$ $S_{(x)}$ : probability of noneoccurrance. $S_{(x)}=\int_{-\infty}^{x}f_(x)dx=1-W_{(x)}$ T : Return period $T=\frac{1}{nW_{(x)}}$ or $T=\frac{1}{nS_{(x)}}$ $W_n$ : Hazen plot $W_n=\frac{2n-1}{2N}$ $F_n=1-W_x=1-\(\frac{2n-1}{2N}\)$ n : Number of observation (annual maximum series) P : Probability $P=\frac{N!}{{t!}(N-t)}F{_i}^{N-t}(1-F_i)^t$ $F_n$ : Thomas plot $F_n=\(1-\frac{n}{N+1}\)$ N : Total number of sample size $X_l$ : $X_s$ : maximum, minumum value of total number of sample size.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.517-524
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• 2022

This paper analyzes wave measurement using X-band navigation (ship) radar, changes in radar signal due to snowfall and precipitation, and factors that obstruct wave measurement. Data obtained from the radar installed at Sokcho Beach were used, and data from the Korea Meteorological Administration and the Korea Hydrographic and Oceanographic Agency were used for the meteorological data needed for comparative verification. Data from the Korea Meteorological Administration are measured at Sokcho Meteorological Observatory, which is about 7km away from the radar, and data from the Korea Hydrographic and Oceanographic Agency are measured at a buoy about 3km away from the radar. To this point, changes in radar signals due to rainfall or snowfall have been transmitted empirically, and there is no case of an analysis comparing the results to actual weather data. Therefore, in this paper, precipitation, snowfall data, CCTV, and radar signals from the Korea Meteorological Administration were comprehensively analyzed in time series. As a result, it was confirmed that the wave height measured by the radar according to snowfall and rainfall was reduced compared to the actual wave height, and a decrease in the radar signal strength according to the distance was also confirmed. This paper is meaningful in that it comprehensively analyzes the decrease in the signal strength of radar according to snowfall and rainfall.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1934-1938
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• 2008

In this study, the landuse pattern at the Gab river is analyzed using time-series aerial images. This study area is divided by two zones like as inland and floodplain. To begin with, in inland, the landuse area of items such as residential, road, industrial, public facilities is increased by following the urbanization. On the other hand, the area of the other items such as agricultural, forest and river is decreased. Also, the inclination of those two groups is reversed around 1988. Form the results, it is clarified that the Gab river is urbanized around 1988. In floodplain, the area of river is decreased as time goes by. This result means that the area of landuse factors such as level-upped riverside land, bridge, head work is increased conversely. Also, the proportion of the water to the river considering the hydrologic factor like rainfall is increased as time goes by. Overall, it is concluded that aerial image can be applied to get a landuse information that is needed in river management and planning.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.86-97
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• 2007

The principal component analysis was performed to identify the general characteristics of groundwater level changes from 202 deep and 112 shallow wells monitoring data, respectively, which came from the National Groundwater Monitoring Stations operated by KWATER with time spans of 156 continuous weeks from 2003 to 2005. Eight principal components, which accounted for 80% of the variability of the original time series, were extracted for water levels of shallow and deep monitoring wells. As a result of cluster analysis using the loading value of three principal components for shallow wells, shallow monitoring wells were divided into 3 groups which were characterized with a response time to rainfall (Group 1: 4.6 days, Group 2: 24.1 days, Group 3: 1.4 days), average long-term trend of water level (Group 1: $2.05{\times}10^{-4}$ m/day, Group 2: $-7.85{\times}10^{-4}$ m/day, Group 3: $-3.51{\times}10^{-5}$ m/day) and water level difference (Group 1 < Group 2 < Group 3). Additionally, they showed significant differences according to a distance to the nearest stream from well (Group 3 < Group 2 < Group 1), topographic slope of well site (Group 3: plain region, Group 1: mountainous region) and groundwater recharge rate (Group 3 < Group 2 < Group 1) with a p-value of 0.05.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.644-653
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• 2018

Landslides occur frequently due to the effects of heavy rainfall and typhoons caused by climate change. Erosion control measures are needed to effectively prevent landslide damage. In order to improve their efficiency, it is necessary to quantitatively measure the sediment discharge from the mountain stream. In this study, a load cell sensor was installed in a mountain stream and the measured values were compared according to the applicability and load test type in the mountain stream. The result of the load test showed that the effect of the loading type (load test 1, 2) was low at average (loadings) of 0.4kgf and 0.6kgf at sites 1 and 2, respectively. The load factor was also derived by regression analysis to increase the accuracy of the measured values. According to the results of the load factor (normalized) to the load-cell measurement value, the output value increased by 14.8% and 24.6% in sites 1 and 2, respectively, and was calculated to be similar to the reference value. The load cell sensor enabled us to quantitatively estimate the amount of sediment discharge in the mountain stream through time series analysis with the water level and rainfall information. If the monitoring is carried out for a long time, it can be used to find the sediment discharge mechanism for the mountain stream. In addition, applying sensors such as load-cells to a mountain stream is expected to contribute to the development of related industries, such as the manufacturing of measurement sensors.