• Journal of the Korean Geographical Society
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• v.41 no.6 s.117
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• pp.670-681
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• 2006

The purpose of this study is to clarify the behavior of subsurface water flow during rainfall on the hillslope in the Dongguneung experimental basin. As a result of the study, the following conclusions were obtained. Under the total rainfall of 20mm, there were no groundwater level changes. However, it was found that total rainfall amount and rainfall intensity were important factors to change groundwater level in hilly slope. Also the rainfall duration and preexisted rainfall amount were important factors to change it on the head hollow. To analyze the modification of 'U-shaped Gol' landform, the pattern of return flow and through flow have to check during storm events. The microgeomorphic change of head hollow is based on the pattern of subsurface water flow.

• Journal of the Korean GEO-environmental Society
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• v.16 no.3
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• pp.49-55
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• 2015

The rainfall pattern, rainfall intensity as well as topographical conditions used for the analysis of debris flow affect, in general, the magnitude of debris flow and flow velocity, when debris flow occurs. The consideration of topographical conditions implies that the topography is equally divided into grids and the slope of inside the grid is computed as an average, leading to, in turn, obtain the closer results to the reality as the grid is smaller in the case of the severely bended topography. Although the size of grid should be as small as possible so as for more accurate analysis of debris flow, the analysis of debris flow has been so far conducted by using sparsely divided grids due to the limitation of analysis algorithm, computational ability and running time. So, it is necessary to suggest an appropriate grid size for the practical approaches. Therefore, this study presents the evaluation of the effect of the size of a grid on the debris flow besides the factors which referred to the previous studies such as accumulated rainfall, rainfall intensity and rainfall duration time. From this, it enables to suggest a rational and practical grid size for topography to be divided.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.237-247
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• 2020

The purpose of this study is to analyze whether design rainfall and hyetograph, which are the main elements of design rainfall, can properly reflect the those of observed rainfalls through inundated rainfall events. The target areas were selected at seven large cities with high damages regarding to the flooding. Comparative analysis between probability and observed rainfall shows that 57% of the cases, in which rainfall amount through the IDF curve is estimated lower than the observed rainfall, do not properly reflect the observed rainfalls. In particular, this trend is exacerbated by the cases in low return period and the rain type of typhoon or frontal rain. The comparative results of rainfall intensity formula showed that the Talbot and Japanese formula were stable in the short- and long-term return periods, respectively. The comparison of hyetograph results also showed that the Mononobe method properly reflects the maximum rainfall intensity and the Huff method properly reflects the shape of rainfall pattern.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.4
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• pp.246-254
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• 2015

This study explored the effect of rainfall pattern and soil characteristics on water management in rice paddy fields, using a soil water balance model, BUDGET. In two sites with different soil textural group, coarse loamy soil (Gangseo series) and fine soil (Hwadong series), respectively, we have monitored daily decrease of water depth, percolation rate, and groundwater table. The observed evapotranspiration (ET) was obtained from differences between water depth decrease and percolation rate. The root mean square difference values between observed and BUDGET-estimated ET ranged between 10% and 20% of the average observed ET. This is comparable to the measurement uncertainty, suggesting that the BUDGET model can provide reliable ET estimation for rice fields. In BUDGET model of this study, irrigation requirement was determined as minimum water need for maintaining water-saturated soil surface, assuming 100 mm of bund height and no lateral loss of water. The model results showed different water balance and irrigation requirement with the different soil profile and indicated that minimum percolation rate by plow pan could determine the irrigation requirement of rice paddy field. For the condition of different rainfall distribution, the results presented different irrigation period and amounts, representing the importance of securing water for irrigation against different rainfall pattern.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.152-152
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• 2022

Only employing historical data limits the estimation of the full distribution of probable Tropical Cyclone (TC) risk due to the insufficiency of samples. Addressing this limitation, this study introduces a semi-physical TC rainfall model that produces spatially and temporally resolved TC rainfall data to improve TC risk assessments. The model combines a statistical-based track model based on the Markov renewal process to produce synthetic TC tracks, with a physics-based model that considers the interaction between TC and the atmospheric environment to estimate TC rainfall. The simulated data from the combined model are then fitted to a probability distribution function to compute the spatially heterogeneous risk brought by landfalling TCs. The methodology is employed in South Korea as a case study to be able to implement a country-scale-based vulnerability inspection from damaging TC impacts. Results show that the proposed model can produce TC tracks that do not only follow the spatial distribution of past TCs but also reveal new paths that could be utilized to consider events outside of what has been historically observed. The model is also found to be suitable for properly estimating the total rainfall induced by landfalling TCs across various points of interest within the study area. The simulated TC rainfall data enable us to reliably estimate extreme rainfall from higher return periods that are often overlooked when only the historical data is employed. In addition, the model can properly describe the distribution of rainfall extremes that show a heterogeneous pattern throughout the study area and that vary per return period. Overall, results show that the proposed approach can be a valuable tool in providing sufficient TC rainfall samples that could be an aid in improving TC risk assessment.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.188-188
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• 2017

Rainfall is an important input to hydrological models. The accuracy of hydrological studies for water resources and floods management depend primarily on the estimation of rainfall. Thailand is among the countries that have regularly affected by floods. Flood forecasting and warning are necessary to prevent or mitigate loss and damage. Merging near real time satellite-based precipitation estimation with relatively high spatial and temporal resolutions to ground gauged precipitation data could contribute to reducing uncertainty and increasing efficiency for flood forecasting application. This study tested the applicability of satellite-based rainfall for water resources management and flood forecasting. The objectives of the study are to assess uncertainty associated with satellite-based rainfall estimation, to perform bias correction for satellite-based rainfall products, and to evaluate the performance of the bias-corrected rainfall data for the prediction of flood events. This study was conducted using a case study of Thai catchments including the Chao Phraya, northeastern (Chi and Mun catchments), and the eastern catchments for the period of 2006-2015. Data used in the study included daily rainfall from ground gauges, telegauges, and near real time satellite-based rainfall products from TRMM, GSMaP and PERSIANN CCS. Uncertainty in satellite-based precipitation estimation was assessed using a set of indicators describing the capability to detect rainfall event and efficiency to capture rainfall pattern and amount. The results suggested that TRMM, GSMaP and PERSIANN CCS are potentially able to improve flood forecast especially after the process of bias correction. Recommendations for further study include extending the scope of the study from regional to national level, testing the model at finer spatial and temporal resolutions and assessing other bias correction methods.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.5
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• pp.116-126
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• 2002

Discharge pattern and water quality were investigated in the drainage water from about 10 ha of groundwater-irrigated paddy field in the growing season of 2001. Total discharge quantity was about 1,117.2 mm in which about 75% was caused by management drainage due to cultural practice of paddy rice farming and the rest by rainfall runoff where total rainfall was about 515 mm. Dry-day sampling data showed wide variations in constituent concentrations with average of 26.14 mg/L, 0.37 mg/L, 3.54 mg/L at the inlet, and 43.60 mg/L, 0.34 mg/L, 3.58 mg/L at the outlet for CO $D_{cr}$ , T-P, and T-N, respectively. Wet-day sampling data demonstrated that generally CO $D_{cr}$ followed the discharge pattern and T-P was in opposite to the discharge pattern, but T-N did not show apparent pattern to the discharge. Discharge and load are in strong relationship. And based on regression equation, pollutant loads from groundwater irrigation area are estimated to be 288.34, 1.17, and 5.45 kg/ha for CO $D_{cr}$ , T-P, and T-N, respectively, which was relatively lower than the literature value from surface water irrigation area which implies that groundwater irrigation area might use less irrigation water and result in less drainage water, Therefore, total pollutant load from paddies irrigation with groundwater could be significantly lower than that with surface water. This study shows that agricultural drainage water management needs a good care of drainage outlet as well as rainfall runoff. This study was based on limited monitoring data of one year, and further monitoring and successive analysis are recommended for more generalized conclusion.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.29-35
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• 2011

This research proposes the suitable method for estimating the future probable rainfall based in 2100 on the observed rainfall data from main climate observation stations in Korea and the rainfall data from the A1B climate change scenario in the Korea Meteorological Administration. For all those, the frequency probable rainfall in 2100 was estimated by the relationship between average values of 24-hours annual maximum rainfalls and related parameters. Three methods to estimate it were introduced; First one is the regressive analysis method by parameters of probable distribution estimated by observed rainfall data. In the second method, parameters of probable distribution were estimated with the observed rainfall data. Also the rainfall data till 2100 were estimated by the A1B scenario of the Korea Meteorological Administration. Last method was that parameters of probable distribution and probable rainfall were estimated by the A1B scenario of the Korea Meteorological Administration. The estimated probable rainfall by the A1B scenario was smaller than the observed rainfall data, so it is required that the estimated probable rainfall was calibrated by the quantile mapping method. After that calibration, estimated probable rainfall data was averagely became approximate 2.3 to 3.0 times. When future probable rainfall was the estimated by only observed rainfall, estimated probable rainfall was overestimated. When future probable rainfall was estimated by the A1B scenario, although it was estimated by similar pattern with observed rainfall data, it frequently does not consider the regional characteristics. Comparing with average increased rate of 24-hours annual maximum rainfall and increased rate of probable rainfall estimated by three methods, optimal method of estimated future probable rainfall would be selected for considering climate change.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.252-252
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• 2011

Rainfall-runoff models are calibrated and validated by using a same data set such as observations. The past climate change effects the present rainfall pattern and also will effect on the future. To predict rainfall-runoff more preciously we have to consider the climate change pattern in the past, present and the future time. Thus, in this study, the climate change represents changes in mean precipitation and standard deviation in different patterns. In some river basins, there is no enough length of data for the analysis. Therefore, we have to generate the synthetic data using proper distribution for calculation of precipitation based on the observed data. In this study, Kajiyama model is used to analyze the runoff in the dry and the wet period, separately. Mean and standard deviation are used for generating precipitation from the gamma distribution. Twenty hypothetical scenarios are considered to show the climate change conditions. The mean precipitation are changed by -20%, -10%, 0%, +10% and +20% for the data generation with keeping the standard deviation constant in the wet and the dry period respectively. Similarly, the standard deviations of precipitation are changed by -20%, -10%, 0%, +10% and +20% keeping the mean value of precipitation constant for the wet and the dry period sequentially. In the wet period, when the standard deviation value varies then the mean NSE ratio is more fluctuate rather than the dry period. On the other hand, the mean NSE ratio in some extent is more fluctuate in the wet period and sometimes in the dry period, if the mean value of precipitation varies while keeping the standard deviation constant.