• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.617-625
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• 1999

Global warming has begun since the industrial revolution and it is getting worse recently. Even though the increase of greenhouse gases such as $CO_2$ is thought to be the main cause for global warming, its impact on global climate has not been revealed clearly in rather quantitative manners. However, researches using General Circulation Models(GCMs) has shown the accumulation of greenhouse gases increases the global mean temperature, which in turn impacts on the global water circulation pattern. This changes in global water circulation pattern result in abnormal and more frequent meteorological events such as severe floods and droughts, generally more severe than the normal ones, which are now common around the world and is referred as a indirect proof of global warming. Korean peninsula also cannot be an exception and have had several extremes recently. The main objective of this research is to analyze the impact of global warming on the change of flood and drought frequency. Based on the assumption that now is a point in a continuously changing climate due to global warming, we analyzed the observed daily rainfall data to find out how the increase of annual rainfall amount affects the distribution of daily rainfall. Obviously, the more the annual rainfall depth, the more frequency of much daily rainfall, and vice versa. However, the analysis of the 17 points data of Keum river basin in Korea shows that especially the number of days of under 10mm or over 50mm daily rainfall depth is highly correlated with the amount of annual rainfall depth, not the number of dry days with their correlation coefficients quite high around 0.8 to 0.9.

• The Journal of Engineering Geology
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• v.34 no.3
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• pp.459-471
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• 2024

Landslide risk is influenced by internal factors such as terrain, geology, soil composition, and forest cover, and external factors such as rainfall and seismic activity. In particular, changes in rainfall patterns due to climate change and changes in terrain due to urban sprawl result in increased landslide risk, both directly and indirectly. This study analyzes internal factors that influence landslide risk using existing spatial data and examines changes in rainfall under the SSP5-8.5 climate change scenario. Rainfall intensity was evaluated across different frequencies and durations, and the landslide risk was assessed by applying rainfall infiltration models to mountain slopes. The analysis reveals that with increasing rainfall duration (1, 6, 12, 18, and 24 h) for an event with a recurrence interval of 10 yr rainfall intensity decreases. However, for shorter rainfall durations (1 h), the intensity increases with the event frequency (10, 20, 50, and 100 yr). Infiltration analysis further shows that with prolonged rainfall, the proportion of areas with a safety factor of 1.3 or higher decreases, thereby raising the landslide risk.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.449-457
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• 2011

Recently, increasing heavy rainfalls due to climate change and/or variability result in hydro-climatic disasters being accelerated. To cope with the extreme rainfall events in the future, hydrologic frequency analysis is usually used to estimate design rainfalls in a design target year. The rainfall data series applied to the hydrologic frequency analysis is assumed to be stationary. However, recent observations indicate that the data series might not preserve the statistical properties of rainfall in the future. This study incorporated the residual analysis and the hydrologic frequency analysis to estimate design rainfalls in a design target year considering the non-stationarity of rainfall. The residual time series were generated using a linear regression line constructed from the observations. After finding the proper probability density function for the residuals, considering the increasing or decreasing trend, rainfalls quantiles were estimated corresponding to specific design return periods in a design target year. The results from applying the method to 14 gauging stations indicate that the proposed method provides appropriate design rainfalls and reduces the prediction errors compared with the conventional rainfall frequency analysis which assumes that the rainfall data are stationary.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.747-757
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• 2021

Quantification of extreme rainfall is very important in establishing a flood protection plan, and a general measure of extreme rainfall is expressed as an T-year return level. In this study, a method was proposed for quantifying spatial distribution and uncertainty of daily rainfall depths with various return periods using a hierarchical Bayesian model combined with climate and geographical information, and was applied to the Seoul-Incheon-Gyeonggi region. The annual maximum daily rainfall depth of six automated synoptic observing system weather stations of the Korea Meteorological Administration in the study area was fitted to the generalized extreme value distribution. The applicability and reliability of the proposed method were investigated by comparing daily rainfall quantiles for various return levels derived from the at-site frequency analysis and the regional frequency analysis based on the index flood method. The uncertainty of the regional frequency analysis based on the index flood method was found to be the greatest at all stations and all return levels, and it was confirmed that the reliability of the regional frequency analysis based on the hierarchical Bayesian model was the highest. The proposed method can be used to generate the rainfall quantile maps for various return levels in the Seoul-Incheon-Gyeonggi region and other regions with similar spatial sizes.

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.4
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• pp.72-80
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• 1989

Various analyses were made to investigate the stochastic structure of the daily rainfall in Korea. Records of daily rainfall amounts from 1951 to 1984 at Chinju Metesrological Station were used for this study. Obtained results are as follows : 1. Time series of the daily rainfall at Chinju were positively, serially correlated for the lag as large as one day. 2. Rainfall events, defined as a sequence of consecutive wet days separated by one or more dry days, showed a seasonal variation in the occurrence frequency. 3. The marginal distribution of event characteristics of each month showed significant dif- ferences each other. Events occurred in summer had longer duration and higher magnitude with higher intensity than those of events occurred in winter. 4. There were significant positive correlations among four event characteristics ; dura- tion, magnitude, average intensity, and maximum intensity. 5. Correlations among the daily rainfall amounts within an event were not significant in general. 6. There were no consistant significancy in identity or difference between the distribu- tions of daily rainfall amounts for different days within events. 7. Above mentioned characteristics of daily rainfall time series must be considered in building a stochastic model of daily rainfall.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.47-56
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• 2004

The purpose of this study is to estimate soil loss amount according to the rainfall-runoff erosivity factor frequency and to analyze the hazard zone that has high possibilities of soil erosion in the watershed. RUSLE was used to analyze soil loss quantity. The study area is Gwanchon that is part of Seomjin river basin. To obtain the frequency rainfall-runoff erosivity factor, the daily maximum rainfall data for 39 years was used. The probability rainfall was calculated by using the Normal distribution, Log-normal distribution, Pearson type III distribution, Log-Pearson type III distribution and Extreme-I distribution. Log-Pearson type III was considered to be the most accurate of all, and used to estimate 24 hours probabilistic rainfall, and the rainfall-runoff erosivity factor by frequency was estimated by adapting the Huff distribution ratio. As a result of estimating soil erosion quantity, the average soil quantity shows 12.8 and $68.0ton/ha{\cdot}yr$, respectively from 2 years to 200 years frequency. The distribution of soil loss quantity within a watershed was classified into 4 classes, and the hazard zone that has high possibilities of soil erosion was analyzed on the basis of these 4 classes. The hazard zone represents class IV. The land use area of class IV shows $0.01-5.28km^2$, it ranges 0.02-9.06% of total farming area. Especially, in the case of a frequency of 200 years, the field area occupies 77.1% of total fanning area. Accordingly, it is considered that soil loss can be influenced by land cover and cultivation practices.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.937-942
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• 2005

It is necessary to estimate the runoff hydrograph and peak flood discharge using law of probability for synthetic flood control policy and design of hydraulic structures. Rainfall analysis is needed in the process of peak flood discharge estimation and the time distribution of a design rainfall is a very important process in the analysis. In this study, we estimate design flood for a small urban basin and a rural basin of medium scale which have different travel times. The Huff method is widely used in Korea for the time distribution of design rainfall to estimate design flood. So, we use Huff method and a conceptual method which is suggested in this study for the comparative purpose. The 100-year frequency rainfall is used to estimate design flood for each basin and the design flood is compared with the existing design flood. As the result, the design flood is overestimated $14.6m^3/sec$ by Huff method and is underestimated $70.9m^3/sec$ by a conceptual method for the rural basin. For the small urban basin, the design flood is excessively overestimated $294.65m^3/sec$ by Huff method and is overestimated $173m^3/sec$ by a conceptual method. The reason of excessive overestimation by Huff method in the small urban basin is that the increased rate of rainfall intensity according to the decrease of duration is large and the duration exceeds the time of concentration when the increased rainfall intensity is concentrated in a quartile. Therefore, we suggested a conceptual method for the time distribution of design rainfall by considering the rainless period and duration. Especially, the conceptual method might be useful for the small urban basin with short concentration time which the design flood is overestimated by Huff method.

• The Journal of Engineering Geology
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• v.31 no.4
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• pp.631-646
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• 2021

Increasing incidences of landslides in Korea are endangering life and damaging property. To ascertain the cause of the rapid increase in landslides in 2020, this study analyzed the correlation between frequency of their occurrence and persistence of rainfall. The study area comprised seven areas in Gangwon-do, Gyeonggi-do, Gyeongsangnam-do, Gyeongsangbuk-do, Jeollanam-do, Jeollabuk-do, and Chungcheongnam-do. The used rainfall factors were monthly rainfall in June, July, and August, rainfall during the summer (June-August), rainfall during the monsoon season, and number of precipitation days during the summer and during the monsoon season. The effect of these factors on landslides was identified by comparing them with the occurrence of landslides in the year of increased landslide occurrence in each area. The results confirmed that not only rainfall but also the number of precipitation days during the monsoon season affect the occurrence of landslides. The rapid increase in landslide occurrence in 2020 was attributed to increases in both the number of precipitation days during the monsoon season and rainfall during the monsoon season in 2020. These results are expected to be used as basic data for future landslide warning standards that consider the effect of the persistence of rainfall.

• Journal of Wetlands Research
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• v.5 no.2
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• pp.1-13
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• 2003

In Korea, most of the rainfalls have been concentrated in the flood season and the flood study has received more attention than low flow analysis. One of the reasons that the analysis of low flows has less attention is the lacks of the required data like daily rainfall and so we have used the stochastic processes such as pulse noise, exponential distribution, and state model of Markov chain for the rainfall simulation in short term such as daily. Especially this study will pay attention to the state model of Markov chain. The previous study had performed the simulation study by the state model without considerations of the flood and non-flood periods and without consideration of the frequency of rainfall for the period of a state. Therefore this study considers afore mentioned two cases and compares the results with the known state model. As the results, the RMSEs of the suggested and known models represent the similar results. However, the PRE(relative percentage error) shows the suggested model is better results.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.499-499
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• 2018

Hydro-meteorological extremes are trivial in these days. Therefore, it is important to identify extreme hydrological events in advance to mitigate the damage due to the extreme events. In this context, exploring temporal distribution of sub-daily extreme rainfall at multiple rain gauges would informative to identify different states to describe severity of the disaster. This study proposehidden Markov chain model (HMM) based rainfall analysis tool to understand the temporal sub-daily rainfall patterns over South Korea. Hourly and daily rainfall data between 1961 and 2017 for 92 stations were used for the study. HMM was applied to daily rainfall series to identify an observed hidden state associated with rainfall frequency and intensity, and further utilized the estimated hidden states to derive a temporal distribution of daily extreme rainfall. Transition between states over time was clearly identified, because HMM obviously identifies the temporal dependence in the daily rainfall states. The proposed HMM was very useful tool to derive the temporal attributes of the daily rainfall in South Korea. Further, daily rainfall series were disaggregated into sub-daily rainfall sequences based on the temporal distribution of hourly rainfall data.