• 한국환경과학회지
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• 제23권1호
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• pp.25-37
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• 2014

In the present study, we analyzed precipitation patterns and diurnal variation trends of hourly precipitation intensity due to climate change. To that end, we used the hourly precipitation data obtained from 26 weather stations around South Korea, especially Busan, from 1970 to 2009. The results showed that the hourly precipitation was concentrated on a specific time of day. In particular, the results showed the so-called "morning shift" phenomenon, which is an increase in the frequency and intensity of hourly precipitation during the morning. The morning shift phenomenon was even more pronounced when a higher level of hourly precipitation intensity occurred throughout the day. Furthermore, in many regions of Korea, including Busan, this morning shift phenomenon became more prevalent as climate change progressed.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.247-247
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• 2015

Global Climate Model (GCM) is too coarse to apply at a basin scale. The spatial downcsaling is needed to used to permit the assessment of the hydrological changes of a basin. Furthermore, temporal downscaling is required to obtain hourly precipitation to analyze a small or medium basin because only few or several hours are used to determine the peak flows after it rains. In the current study, the spariotemporal distribution of downscaled hourly precipitation for RCP4.5 and RCP8.5 scenarios over South Korea is presented as well as its implications over hydrologica responses. Mean hourly precipitation significantly increases over the southern part of South Korea, especially during the morning time, and its increase becomes lower at later times of day in the RCP8.5 scenario. However, this increase cannot be propagated to the mainland due to the mountainous areas in the southern part of the country. Furthermore, the hydrological responses employing a distributed rainfall-runoff model show that there is a significant increase in the peak flow for the RCP8.5 scenario with a slight decrease for the RCP4.5 scenario. The current study concludes that the employed temporal downscaling method is suitable for obtaining the hourly precipitation data from daily GCM scenarios. In addition, the rainfall runoff simulation through the downscaled hourly precipitation is useful for investigating variations in the hydrological responses as related to future scenarios.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.497-500
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• 2008

The typhoon is provoking huge damage attacking in Korea periodically every year. Therefore, in this study, the analysis of 24 hourly maximum precipitation change related to typhoon events achieved based on Mann-Whitney U test, T test, Modified T test, Sign test, F test, and Modified F test. At the results, the 24 hourly maximum precipitation was expose that average and standard deviation are increasing recently. Therefore, hydorlogical structures have to be prepared of extreme rainfall events by typhoons.

• 한국수자원학회논문집
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• 제35권6호
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• pp.763-777
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• 2002

본 연구의 목적은 간헐 수문사상인 시간강수계열의 구조적 특성을 고찰하여 강수량 모의발생을 위한 추계학적 모형을 개발하는 것이다. 이를 위하여 본 연구에서는 강수발생과정에 대한 추계학적 모형은 이재준과 이정식(2002)이 개발한 추계학적 모형을 이용하였으며, 강수량과정을 위하여 사상내의 시간강수량을 비정상 1차 자기회귀모형으로 기술하였다. 시간강수계열의 강수발생과정과 강수량과정을 조합하면 시간강수사상의 발생패턴과 사상기간내의 강수의 종속구조를 모의할 수 있는 시간강수계열에 대한 모의모형이 얻어지며, 이 모형의 적합성을 구명하기 위해 서울을 대상으로 하여 실적강수자료를 분석하였다. Monte Carlo 모의결과는 모형이 사상기간내의 강수강도, 지속 기간, 크기의 주변 및 조건부 분포를 잘 재현하고 있음을 보여주었다. 실적 및 모의 자료에 대한 자기상관함수도 비교적 작은 시간지체에서는 유사하였다

• 한국수자원학회논문집
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• 제35권1호
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• pp.109-124
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• 2002

본 연구는 간헐 수문사상인 시간강수계열의 구조적 특성을 고찰하여 강수발생의 군집성을 고려한 강수발생과정에 대한 추계학적 모의발생 모형을 개발한 것이다. 먼저 강수사상의 발생패턴을 기술하기 위해 Poisson 군집과정을 사용하였고, 이 과정에서 군집간의 시간과 군집내의 사상 수는 지수분포로 기술하였다. 둘째로 사상의 지속기간과 군집내에서 사상간의 시간은 음대수혼합분포로 기술하였다. 마지막으로 이상과 같은 시간강수사상의 발생패턴과 사상기간내의 강수의 종속구조를 구명하기 위해 서울을 대상으로 하여 실적강수자료를 분석하였다. Monte Carlo 모의결과는 모형이 강수발생의 계절적 패턴, 사상특성의 주변 및 조건부 분포를 잘 재현하고 있음을 보여주었다.

• 대기
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• 제29권5호
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• pp.615-626
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• 2019

To find any effects of precipitation climate on the forecast verification methods, we processed the hourly records of precipitation over South Korea. We examined their relationship between the climate and the methods of verification. Precipitation is an intermittent process in South Korea, generally less than an hour or so. Percentile ratio of precipitation period against the entire period of the records is only 14% in the hourly amounts of precipitation. The value of the forecast verification indices heavily depends on the climate of rainfall. The direct comparison of the index values might force us to have a mistaken appraisal on the level of the forecast capability of a weather forecast center. The size of the samples for verification is not crucial as long as it is large enough to satisfy statistical stability. Our conclusion is still temporal rather than conclusive. We may need the amount of precipitation per minute for the confirmation of the present results.

• 한국수자원학회논문집
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• 제41권3호
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• pp.265-276
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• 2008

수공구조물의 설계를 위해서는 충분한 기간의 관측자료가 필요하지만, 우리나라의 수문자료는 대부분 충분한 수의 관측자료를 보유하고 있지 못하는 실정이다. 따라서 본 연구에서는 핵밀도함수를 이용한 비동질성 Markov 모형을 통해 시간강수량 자료를 모의하였다. 첫 번째로 시간강수량 자료에 변동핵밀도함수를 이용하여 천이확률을 산정하였으며, 두 번째로 난수와 천이확률을 통해 강수가 발생하는 시간을 결정하였다. 세 번째로 강수가 발생한 시간의 강수량의 크기를 핵밀도함수를 통해 추정하였다. 분석결과에서 모의된 시간강수량은 관측시간강수량과 비슷한 통계적 특성을 보이고 있는 것으로 나타났다. 또한, 시간강수량의 모의발생을 위하여 산정한 천이확률을 이용해 강수의 무차원시간분포곡선을 유도하였다.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.501-504
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• 2008

A non-homogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrological variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase.

• 한국환경과학회지
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• 제6권5호
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• pp.461-472
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• 1997

This study was carried out to investigate the characteristics of chemical components and precipitation at Kimhae area from March, 1992 to June, 1994. The pH values, concentration of soluble ions($Cl^-$, $NO_2^-}$ $NO_3^-}$, $NO_4^{2-}$-, $PO_4^{3-}$. $F^-$, $Mg^{2+}$, $Ca^{2+}$, $Mn^{2+}$, $K^+) and non-soluble metals(Cr.Si. Zn, Pb, Cu, Fe, Mn, Mg, Ad. V. Cal were measured by pH meter, IC (ion Chromatography) and ICP(Inductively Coupled Plasma). The data were analyzed by the dally. hourly distribution characteristics of acidity and chemical components, as well as the correlation between them. The results are as follows. 1. The pH range of precipitation was from 3.45 to 6.80 in Kimhae area. and average value was pH 4.62 and main chemical components were $SO_4^{2-}$, $Cl^-$, $NO_3^-$. The highest pH value and concentration appeared in initial rain, which might result from urbanlzation and industrialization in this area and long term transportation from China. 2. The hourly correction distribution of main anions related to pH value In the rainwater showed $SO_4^{2-}$ > $NO_3^-$ > $Cl^-$. Hourly concentration of heavy metal and each ion was highly correlated with pH in the precipitation.

• 한국농공학회논문집
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• 제66권4호
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• pp.51-57
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• 2024

This study was conducted on how to simulate runoff, which was done using existing physical models, using an LSTM (Long Short-Term Memory) model based on deep learning. Tancheon, the first tributary of the Han River, was selected as the target area for the model application. To apply the model, one water level observatory and four rainfall observatories were selected, and hourly data from 2020 to 2023 were collected to apply the model. River water level of the outlet of the Tancheon basin was simulated by inputting precipitation data from four rainfall observation stations in the basin and average preceding 72-hour precipitation data for each hour. As a result of water level simulation using 2021 to 2023 data for learning and testing with 2020 data, it was confirmed that reliable simulation results were produced through appropriate learning steps, reaching a certain mean absolute error in a short period time. Despite the short data period, it was found that the mean absolute percentage error was 0.5544~0.6226%, showing an accuracy of over 99.4%. As a result of comparing the simulated and observed values of the rapidly changing river water level during a specific heavy rain period, the coefficient of determination was found to be 0.9754 and 0.9884. It was determined that the performance of LSTM, which aims to simulate river water levels, could be improved by including preceding precipitation in the input data and using precipitation data from various rainfall observation stations within the basin.