• Water for future
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• v.14 no.4
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• pp.53-72
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• 1981

In this study, South Korea is divided into 5 zones and is studied about the analysis of time-regional distribution of previpitation frequency and rainfall intensity in Korea. In the previpitation frequency analysis, the basic data groups of 39 stations were selected. The diagram of previpitation frequency was drawn, and the time-regional distribution of precipitation frequency was analized. In the rainfall intensity analysis, the basic data groups of 36 stations were selected. The probable rainfall, I-D-F curve, and regression equation between 24hr. and 10min.-18hr. areal depth were obtained. The results of this study are following; 1) The precipitation class of max. recurrence probability in every season except summer was commonly (1) 1-5mm, (2) 0.1-1mm, (3) 5-10mm in order. 2) The zone of max. recurrence frequency owing to the precipitation class was zone II in precipitation frequency of below 20mm, zone IV in precipitation frequency of 30-40mm, zone I in precipitation frequency of above 70mm for a year. 3) The recurrence probability of precipitation in Korea can be represented to the equation of exponential function; $$W(x)=e^{\alpha+\beta}$$ 4) The first and third zones were expected heavy rain for the short and long duration. 5) The I.D.F. curves were drawn, and established that the time interval for the least deviation of I.D.F curve is 10~40min., 40min. -4hr., 4~24hr. 6) The regression equations of areal mean depth between 24hr. and 10min.-18hr. for each zone were obtained. 7)The probable rainfall of 36 points were calculated.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1053-1064
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• 2022

The Thiessen method, which is the current area average precipitation method, has serious structural limitations in accurately calculating the average precipitation in the watershed. In addition to the observation accuracy of the precipitation meter, errors may occur in the area average precipitation calculation depending on the arrangement of the precipitation meter and the direction of the heavy rain. When the watershed is small and the station density is sparse, in both simulation and observation history, the Thiessen method showed a peculiar tendency that the average precipitation in the watershed continues to increase and decrease rapidly for 10 minutes before and after the peak. And the average precipitation in the Thiessen basin was different from the rainfall radar at the peak time. In the case where the watershed is small but the station density is relatively high, overall, the Thiessen method did not show a trend of sawtooth-shaped over-peak, and the time-dependent fluctuations were similar. However, there was a continuous time lag of about 10 minutes between the rainfall radar observations and the ground precipitation meter observations and the average precipitation in the basin. As a result of examining the ground correction effect of the rainfall radar watershed average precipitation, the correlation between the area average precipitation after correction is rather low compared to the area average precipitation before correction, indicating that the correction effect of the current rainfall radar ground correction algorithm is not high.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.3
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• pp.122-134
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• 1994

The objective of this study is to provide with the hydrometeological and probabilistic characteristics of the storms and winds of typhoons that have been passed through the Korea peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall and wind data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. Wind data were also analysed for their probabilistic distributions. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that have passed through the Korean peninsula was type E, which was followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, that was followed by A, super A, and C types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution for typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution. 5. The most frequent probabilistic distribution for typhoon wind events was Type-I xtremal distribution, followed by Two-parameter lognormal distribution, and Normal distribution.

• Water for future
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• v.28 no.1
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• pp.133-144
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• 1995

The subject of the paper is the selection of the number and location of rainguage stations among existing ones, which will be part of real-time data collection system, for the computation of mean areal precipitation and for use as input of real-time flow forecasting models. The weighted average method developed by National Weather Service was used to compute MAP. Two different searching methods were used to find local optimal solutions as a function of the number of rainguages. An operational rainfall-runoff model was used to determine the optimal location and number of stations for flow prediction.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1427-1430
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• 2009

The amount and the continuity of the precipitation data used in a hydrological analysis may exert a big influence on the reliability of the analysis. It is a fundamental process to estimate the missing data caused by such as a breakdown of the rainfall recording machine or to expand a short period of rainfall data. In this study the eight methods widely used as methods for estimating are compared. The data used in this research is the annual precipitation amount during 17 years at the Cheolwon station including an ungauged period of 15 years and its five surrounding stations. By use of this certified method the ungauged precipitation values at the Cheolweon station is estimated and the areal average of annual precipitation for 32 years at the Han River basin is calculated.

• Water for future
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• v.29 no.6
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• pp.131-139
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• 1996

The main goal of this study is a rainfall-runoff analysis using atopographically-based distributed model. It consists of two parts: one is a direct runoff submodel and the other is a baseflow submodel. The direct runoff submodel is a distributed model which routed through the drainage networks with a kinematic wave model. The baseflow submodel is considered as a lumped system. This model makes it possible to take the effect of areal and temporal distribution of storm into accout.

• Water for future
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• v.11 no.2
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• pp.62-69
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• 1978

Interstational and interseasonal analyses of the correlation and variability in the seasonal and annual precipitation for 10 basic synoptic stations in South Korea, on the basis of rainfall record of over 40 years, are carried out. It is found that the climatic regions of precipitation could be classified by means of the interstational analysis for the correlations. Corrleation coefficients in interstational relationship of precipitation are lowest in autumn which characterizeds a strong locality while the highest value shows a relatively weak locality in winter. Interseasonal relationship between summer and winter precipitation shows mostly 10 percent significant level with all positive values. The magnitude of the variation coefficients are appeared to be in the order of winter, autumn, spring and summer. It is shown that the highest which is winter ranges between 0.33 0.58, and for the lowest summer, 0.26-0.44, respectively in the areal distribution of the coefficient. The secular changes of the variation coefficient in the recent trend show increases in spring at two station; Seoul and Incheon, in summer at Busan and in autumn at two stations; Busan and Incheon while in winter show devreases at the whole stations. An annual variation seems to show generally a constant trend as whole for all the stations.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1041-1052
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• 2013

In this study, we estimate parameters of a distributed hydrologic model, GRM (grid based rainfall-runoff model), using a model-independent parameter estimation tool, PEST. We implement auto calibration of model parameters such as initial soil moisture, multipliers of overland roughness and soil hydraulic conductivity in the Geumho River Catchment and the Gamcheon Catchment using radar rainfall estimates and ground-observed rainfall represented by Thiessen interpolation. Automatic calibration is performed by GRM-MP (multiple projects), a modified version of GRM without GUI (graphic user interface) implementation, and "Parallel PEST" to improve estimation efficiency. Although ground rainfall shows similar or higher cumulative amount compared to radar rainfall in the areal average, high spatial variation is found only in radar rainfall. In terms of accuracy of hydrologic simulations, radar rainfall is equivalent or superior to ground rainfall. In the case of radar rainfall, the estimated multiplier of soil hydraulic conductivity is lower than 1, which may be affected by high rainfall intensity of radar rainfall. Other parameters such as initial soil moisture and the multiplier of overland roughness do not show consistent trends in the calibration results. Overall, calibrated parameters show different patterns in radar and ground rainfall, which should be carefully considered in the rainfall-runoff modelling applications using radar rainfall.

• Journal of Korea Water Resources Association
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• v.49 no.11
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• pp.913-922
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• 2016

A long-term precipitation record is typically required for establishing the reliable water resources plan in the watershed. However, the observations in the hourly precipitation data are not always consistent and there are missing values within the time series. This study aims to develop a hourly rainfall simulator for extending rainfall data, based on the well-known Neyman-Scott Rectangular Pulse Model (NSRPM). Moreover, this study further suggests a multisite hourly rainfall simulator to better reproduce areal rainfalls for the watershed. The proposed model was validated with a network of five weather stations in the Uee-stream watershed in Seoul. The proposed model appeared a reasonable result in terms of reproducing most of the statistics (i.e. mean, variance and lag-1 autocovariance) of the rainfall time series at various aggregation levels and the spatial coherence over the weather stations.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.134-134
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• 2022

Streamflow forecasting plays a crucial role in water resource control, especially in highly urbanized areas that are very vulnerable to flooding during heavy rainfall event. In addition to providing the accurate prediction, the evaluation of effects and importance of the input predictors can contribute to water manager. Recently, machine learning techniques have applied their advantages for modeling complex and nonlinear hydrological processes. However, the techniques have not considered properly the importance and uncertainty of the predictor variables. To address these concerns, we applied the GA-BART, that integrates a genetic algorithm (GA) with the Bayesian additive regression tree (BART) model for hourly streamflow forecasting and analyzing input predictors. The Jungrang urban basin was selected as a case study and a database was established based on 39 heavy rainfall events during 2003 and 2020 from the rain gauges and monitoring stations. For the goal of this study, we used a combination of inputs that included the areal rainfall of the subbasins at current time step and previous time steps and water level and streamflow of the stations at time step for multistep-ahead streamflow predictions. An analysis of multiple datasets including different input predictors was performed to define the optimal set for streamflow forecasting. In addition, the GA-BART model could reasonably determine the relative importance of the input variables. The assessment might help water resource managers improve the accuracy of forecasts and early flood warnings in the basin.