• Water Engineering Research
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• v.1 no.2
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• pp.147-158
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• 2000

In this study, we characterized the seasonal variation of rainrate fields in the Han river basin using the WGR multi-dimensional precipitation model (Waymire, Gupta, and Rodriguez-Iturbe, 1984) by estimating and comparing the parameters derived for each month and for the plain area, the mountain area and overall basin, respectively. The first-and second-order statistics derived from observed point gauge data were used to estimate the model parameters based on the Davidon-Fletcher-Powell algorithm of optimization. As a result of the study, we can find that the higher rainfall amount during summer is mainly due to the arrival rate of rain bands, mean number of cells per cluster potential center, and raincell intensity. However, other parameters controlling the mean number of rain cells per cluster, the cellular birth rate, and the mean cell age are found invariant to the rainfall amounts. In the application to the downstream plain area and upstream mountain area of the Han river basin, we found that the number of storms in the mountain area was estimated a little higher than that in the plain area, but the cell intensity in the mountain area a little lower than that in the plain area. Thus, in the mountain area more frequent but less intense storms can be expected due to the orographic effect, but the total amount of rainfall in a given period seems to remain the same.

• Journal of Korea Water Resources Association
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• v.39 no.8 s.169
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• pp.717-726
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• 2006

In this study, we developed a rainfall forecasting model using data from radiosonde and rain gauge network and neural networks. The primary hypothesis is that if we can consider the moving direction of the rain generating weather system in forecasting rainfall, we can get more accurate results. We assume that the moving direction of the rain generating weather system is same as the wind direction at 700mb which is measured at radiosonde networks. Neural networks are consisted of 8 different modules according to 8 different wind directions. The model was verified using 350 AWS data and Pohang radiosonde data. Correlation coefficient is improved from 0.41 to 0.73 and skill score is 0.35. Statistical performance measures of the Quantitative Precipitation Forecast (QPF) model show improved output compared to that of rainfall forecasting model using only AWS data.

• Journal of Wetlands Research
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• v.12 no.1
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• pp.51-61
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• 2010

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, it is important to understand the spatial-temporal features of rainfall. In this study, RADAR rainfall was used to calculate gridded areal rainfall which reflects the spatial-temporal variability. In addition, Kalman-filter method, a stochastical technique, was used to combine ground rainfall network with RADAR rainfall network to calculate areal rainfall. Thiessen polygon method, Inverse distance weighting method, and Kriging method were used for calculating areal rainfall, and the calculated data was compared with adjusted areal RADAR rainfall measured using the Kalman-filter method. The result showed that RADAR rainfall adjusted with Kalman-filter method well-reproduced the distribution of raw RADAR rainfall which has a similar spatial distribution as the actual rainfall distribution. The adjusted RADAR rainfall also showed a similar rainfall volume as the volume shown in rain gauge data. Anseong-Cheon basin was used as a study area and the RADAR rainfall adjusted with Kalman-filter method was applied in $Vflo^{TM}$ model, a physical-based distributed model, and ModClark model, a semi-distributed model. As a result, $Vflo^{TM}$ model simulated peak time and peak value similar to that of observed hydrograph. ModClark model showed good results for total runoff volume. However, for verifying the parameter, $Vflo^{TM}$ model showed better reproduction of observed hydrograph than ModClark model. These results confirmed that flood runoff simulation is applicable in domestic settings(in South Korea) if highly accurate areal rainfall is calculated by combining gauge rainfall and RADAR rainfall data and the simulation is performed in link to the distributed hydrological model.

• Korean Journal of Hydrosciences
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• v.3
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• pp.31-44
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• 1992

Precise run-off forecasting depends on the ability to predict quantitative rainfall intensity. The purpose of this study is to develop a stochastic model for the shori-term rainfall prediction. It is required for the model to predict rainfall intensities at all the telemetered rain-gauge locations simultaneously. All the model parameters, which are used in this work ; velocity and direction of storm movement, radial spectrum, and dimensionless time distribution of rainfall, are the results of the previous study. We formulated the model and operated it, so that in this study was analyzed particulary the influence of 4 dimensionless time distributions on the prediction and the influence of the model on run-off.

• Water for future
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• v.23 no.3
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• pp.341-350
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• 1990

Precise run-off forecasting depends on the ability to predict quantitative rainfall intensity. This study suggests a stochastic model for 1 hour order rainfall prediction. The model simultaneously predicts rainfall intensity at all telemetered rain-gauge locations. All model parameters, velocity and direction of storm movement, radial spectrum, dimensionless time distribution of rainfall, are estimated from telemetered and historical data for the basin being predicted. Also the estimated parameters are based on the previous study. The results are the influence of dimensionless time distributions on the prediction and the model on run-off.

• Journal of Environmental Science International
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• v.33 no.1
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• pp.43-57
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• 2024

The possible experimental time for cloud seeding was analyzed in South Korea. Rain gauge and radar precipitation data collected from September 2017 to August 2022 in from the three main target stations of cloud seeding experimentation (Daegwallyeong, Seoul, and Boryeong) were analyzed. In this study, the assumption that rainfall and cloud enhancement originating from the atmospheric updraft is a necessary condition for the cloud seeding experiment was applied. First, monthly and seasonal means of the precipitation duration and frequency were analyzed and cloud seeding experiments performed in the past were also reanalyzed. Results of analysis indicated that the experiments were possible during a monthly average of 7,025 minutes (117 times) in Daegwallyeong, 4,849 minutes (81 times) in Seoul, and 5,558 minutes (93 times) in Boryeong, if experimental limitations such as the insufficient availability of aircraft is not considered. The seasonal average results showed that the possible experimental time is the highest in summer at all three stations, which seems to be owing to the highest precipitable water in this period. Using the radar-converted precipitation data, the cloud seeding experiments were shown to be possible for 970-1,406 hours (11-16%) per year in these three regions in South Korea. This long possible experimental time suggests that longer duration, more than the previous period of 1 hour, cloud seeding experiments are available, and can contribute to achieving a large accumulated amount of enhanced rainfall.

• Journal of Wetlands Research
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• v.4 no.2
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• pp.43-56
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• 2002

About 12 rain gauge stations of Korea, annual maximum rainfall series of before and after 1980 whose durations are 1, 2, 3, 6, 12, 24, 48, 72 hours respectively were composed and statistical characteristics of those time series were calculated and probability rainfall were estimated by L-moment frequency analysis method and compared each other in order to investigate the recent quantitative rainfall variations. And also, distribution curves of each statistical variations for each duration were constructed by using Kigging method to look into spacial rainfall variation aspects. As a result, We could confirm recent rainfall increase in the South Korea. And spatial increase pattern of standard deviation and frequency rainfall appeared analogously each other. 1n the cases of comparatively short rainfall duration, we could see relatively low increase or decrease tendency in Chungchong Province, Cholla-bukdo, Cholla-namdo eastern part, Kyongsang-namdo western part area. While, variations happened great1y in seaside district of east coast, southwest seashore, Inchon area etc. In the cases of longer durations relatively low increase was showed in southern seashore such as Yeosoo area and as distance recedes from this area, showed gradually augmented tendency. The aspect of mean looks similar tendency of above except that the variation rate of almost seaside district are big in the case of shorter durations. In addition, rainfall increases of short durations which became the center of hydrologist and meteorologist are unconfirmed in this study.

• Atmosphere
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• v.25 no.4
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• pp.719-734
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• 2015

Korea is one of the country with the world's oldest meteorological observation records. Starting with first meteorological record of fog in Goguryeo in the year of 34 BC, Korea had left a great deal of quantitative observation records, from the Three Kingdoms Period to Goryeo to Joseon. During the Joseon Dynasty, with a great attention by kings, efforts were particularly made to measure rainfall in a systematic and scientific manner. In the 23rd year of King Sejong (1441), the world's first rain gauge called "Chugugi" was invented; in the following year (1442), a nationwide rainfall observation network was established. The King Sejong distributed Chugugi to 350 observation stations throughout the state, even to small towns and villages, for measuring and recording rainfall. The rainfall observation using Chugugi, initiated by King Sejong, had been in place for about 150 years, but halted during national disturbances such as Japanese invasion of Korea in 1592. Since then, the observation had been forgotten for a long time until the rainfall observation by Chugugi was resumed in the 48th year of King Yeongjo (1770). King Yeongjo adopted most of the existing observation system established by King Sejong, including the size of Chugugi and observation rules. He, however, significantly reduced the number of Chugugi observation stations to 14, and commanded the 352 local authorities such as Bu, Gun, Hyeon to conduct "Wootaek", a method of measuring how far the moisture had absorbed into the soil when it rains. Later on, six more Chugugi stations were established. If the number of stations of Chugugi and Wootaek are combined together, the total number of rainfall observation station in the late period of Joseon Dynasty was 372. The rainfall observation with Chugugi during the Joseon Dynasty is of significance and excellence in three aspects: 1) the standard size of Chugugi was so scientifically designed that it is as great as today's modern rain gauge; 2) rainfall was precisely measured, even with unit of Bun (2 mm); and 3) the observation network was distributed on a nationwide basis.

• Atmosphere
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• v.22 no.1
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• pp.129-135
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• 2012

This study restores rainfall measurements taken with the Chugugi (rain gauge) at Wonju, Hamheung, and Haeju from the Deungnok (government records from the Joseon Dynasty). We restored rainfall data corresponding to a total of 9, 13, and 18 years for Wonju, Hamheung, and Haeju, respectively. Based on the restored data, we reconstructed monthly rainfall data. Restoration was most successful for the rainy season months of June, July and August. The restored rainfall data were compared with the summer rainfall data for Seoul as recorded by the Seungjeongwon (Royal Secretariat). In June, the variation in the restored rainfall data was similar to that of the Seungjeongwon data for Seoul. In July and August, however, the variations in the reconstructed data were markedly different from those in the Seoul data (Seungjeongwon). In the case of the worst drought in the summer of 1888, a substantial shortage of rainfall was found in both the Seungjeongwon data for Seoul and the restored data for the three regional locations.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.256-261
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• 2004

Due to the problems of global warming, the frequency of meteorological extremes such as droughts, floods and the annual rainfall amount are suddenly increasing. Even though the increase of greenhouse gases, for example, is thought to be the main factor for global warming, its impact on global climate has not yet been revealed clearly in rather quantitative manners. Therefore, tile objective of this study is to inquire the change of precipitation condition due to climate change by global warming. In brief, this study want to see its assumption if rainfall quantile estimates are really changing. In order to analyze the temporal change, the rainfall quantile estimates at the Seoul rain gauge stations are estimated for the 21-year data period being moved from 1908 to 2002 with 1-year lag. The main objective of this study is to analyze the variability of rainfall quantile estimates using four methods. Next, The changes in confidence interval of rainfall quantile are evaluated by increasing the data period. It has been found that confidence interval of rainfall quantile estimates is reduced as the data period increases. When the hydraulic structures are to be designed, it is important to select the data size and to re-estimate the flood prevention capacity in existing river systems.