• Journal of Environmental Science International
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• v.16 no.7
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• pp.805-811
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• 2007

The purpose of this study was to invesitigate relationship between rainfall water quality and precipitation characteristic during the accumulated rainfall and rainless period. As the results of the analysis, rainfall water quality was improved in the rainfall duration. Correlation coefficients between rainwater quality and accumulated rainfall were $0.88{\sim}0.99$ except $Cl^-$. and that between rainless period and initial rainfall water quality were $0.62{\sim}0.75$. During the Asian dust event, concentration of the turbidity, BOD and electric conductivity were high. Therefore, it shows that the rainfall water quality is effected by atmospheric conditions before the rainfall events.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.601-607
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• 2002

Infiltration of rainfall causes railway embankment to be unstable and may result in failure. Basic relationship between the stability of railway embankment and rainfall introducing the partial saturation concept of ground are defined to analyze the stability of embankment by rainfall. A pressure plate test is also peformed to obtain soil-water characteristic curve of unsaturated soils. Based on this curve, the variables in the shear strength function and permeability function are also defined. These functions are used fur the numerical model for evaluation of railway embankments under rainfall. As comparing the model and case studies, the variation of shear strength, the degree of saturation and pore-water pressure for railway embankment during rainfall can be predicted and the safety factor of railway embankment can be expressed as the function of rainfall amount namely rainfall index. Therefore, the research on safety factor on railway embankment considering train speed and rainfall infiltration with the variation of rainfall intensity and rainfall duration was carried out in this paper.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.65-71
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• 2008

This study collected the latest 30-year (1976~2005) continuous rainfall data hourly recorded at 61 meterological observatories in Korea, and the continuous rainfall data was divided into individual rainfall events. In addition, distribution charts of average rainfall event-depth were created to facilitate the application to the overflow risk-based design of detention storage basin. This study shows that 4 hour is appropriate for SST (storm separation time) to separate individual rainfall events from the continuous rainfall data, and the one-parameter exponential distribution is suitable for the frequency distribution of rainfall event depths for the domestic rainfall data. The analysis of the domestic rainfall data using SST of 4 hour showed that the individual rainfall event was 1380 to 2031 times, the average rainfall event-depth was 19.1 to 32.4mm, and ranged between 0.877 and 0.926. Distribution charts of average rainfall event-depth were created for 4hour and 6 hour of SST, respectively. The inland Gyeongsangbuk-do, Western coastal area and inland of Jeollabuk-do had relatively lower average rainfall event-depth, whereas Southern coastal area, such as Namhae, Yeosu, and Jeju-do had relatively higher average rainfall event-depth.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.1
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• pp.13-19
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• 2014

The management of non point sources was marked by the need for clean water environments. It was proposed the fundamentals to promote the reasonable land management in this study. We monitored rainfall events at two non point sources with different crop cultivations such as a sweet potato and a cherry tree for three years. Because the most important factor was rainfall, the rainfall runoff and pollutant loads were generated 100% in the case of rainfall ranges with 50 < rainfall (mm). However the frequency of rainfall runoff was interacted with the crop cultivation and soil characteristics in the case of rainfall ranges such as 30 < rainfall (mm) ${\leq}50^a$ and 10 < rainfall (mm) ${\leq}30^b$. The frequency of rainfall runoff was a : 60% and b : 5% in the cherry tree cultivation with growing significantly and pollutant loads were lower than that of the sweet potato cultivation. Meanwhile the frequency of rainfall runoff was a : 60% and b : 5% in the sweet potato cultivation.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• 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.

• Journal of Korea Water Resources Association
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• v.37 no.5
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• pp.425-435
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• 2004

Mainly, observed maximum rainfall has been evaluated by point rainfall, but actually it should be considered by means of average areal rainfall. Average areal rainfall is an estimated value computed through DAD(rainfall Depth-Area-Duration) analysis. By using this value, an average and maximum areal rainfall according to area-duration relationship could be computed. In this study, we assume that the whole Korea region is hydrologically homogeneous, and then analyze using the storm-centered DAD(moving-area DAD) method for the past century data. From this analysis, we evaluate the yearly variation of observed maximum areal rainfall through area-duration relationship. And we also construct an IDF(rainfall Intensity-Duration-Frequency) curve by using the annual time series data which is composed of maximum areal rainfall. The characteristics of IDF and observed maximum areal rainfall is also evaluated.

• Environmental Engineering Research
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• v.21 no.3
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• pp.226-232
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• 2016

Rainfall is one of crucial factors that impact on our environment. Rainfall data is important in water resources management, flood forecasting, and designing hydraulic structures. However, it is not available in some rural watersheds without rain gauges. Thus, effective ways of interpolating the available records are needed. Despite many widely used spatial interpolation methods, few studies have investigated rainfall center characteristics. Based on the theory that the spatial distribution of convective rainfall event has a definite center with maximum rainfall, we present a mathematical interpolation method to estimate convective rainfall distribution and indicate the rainfall center location and the center rainfall volume. We apply the method to estimate three convective rainfall events in Santa Catalina Island where reliable hydrological data is available. A cross-validation technique is used to evaluate the method. The result shows that the method will suffer from high relative error in two situations: 1) when estimating the minimum rainfall and 2) when estimating an external site. For all other situations, the method's performance is reasonable and acceptable. Since the method is based on a continuous function, it can provide distributed rainfall data for distributed hydrological model sand indicate statistical characteristics of given areas via mathematical calculation.

• 한국방재학회:학술대회논문집
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• 2010.02a
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• pp.51.2-51.2
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• 2010

A novel approach of Poisson cluster stochastic rainfall generator was validated in its ability to reproduce important rainfall and watershed response characteristics at 104 locations of the United States. The suggested novel approach - The Hybrid Model(THM), as compared to the traditional ones, has an additional function to account for the year-to-year variability of rainfall statistics. The two-sample Kolmogorov-Smirnov test was used to see how well THM and traditional approach of Poisson cluster rainfall model reproduce the distribution of the following hydrologic variables: monthly maximum rainfall depths with 1, 3, 6, 12, and 24 hour duration, monthly maximum flow peaks at the virtual watersheds with Curve Number of 50, 60, 70, 80 and 90; and monthly runoff depths at the same virtual watersheds. In all of the testing variables, THM significantly outperformed the traditional approach. This result indicates that the year-to-year variability of rainfall statistics contains important information about the characteristics of rainfall processes that were not considered by the conventional approach of Poisson cluster rainfall modeling and that further considering it in rainfall simulation will enhance the performance of the rainfall models.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.427-427
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• 2015

The storm water management and drainage relation are the key variable that plays a vital role on hydrological design and risk analysis. These require knowledge about spatial variability over a specified area. Generally, design rainfall values are expressed from the fixed point rainfall, which is depth at a specific location. Concurrently, determine the areal rainfall amount is also very important. Therefore, a spatial rainfall interpolation (point rainfall converting to areal rainfall) can be solved by areal reduction factor (ARF) estimation. In mainland of South Korea, for dam design and its operation, public safety, other surface water projects concerned about ARF for extreme hydrological events. In spite of the long term average rainfall (2,061 mm) and increasing extreme rainfall events, ARF estimation is also essential for Jeju Island's water control structures. To meet up this purpose, five fixed rainfall stations of automatic weather stations (AWS) near the "Hancheon Stream Watershed" area has been considered and more than 50 years of high quality rainfall data have been analyzed for estimating design rainfall. The relationship approach for the 24 hour design storm is assessed based on ARF. Furthermore, this presentation will provide an outline of ARF standards that can be used to assist the decision makers and water resources engineers for other streams of Jeju Island.