• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.959-967
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• 2008

Disaggregation techniques are widely used to transform observed daily rainfall values into hourly ones, which serve as important inputs for flood forecasting purposes. However, an important limitation with most of the existing disaggregation techniques is that they treat the rainfall process as a realization of a stochastic process, thus raising questions on the lack of connection between the structure of the models on one hand and the underlying physics of the rainfall process on the other. The present study introduces a nonlinear deterministic (and specifically chaotic) framework to study the dynamic characteristics of rainfall distributions across different temporal scales (i.e. weights between scales), and thus the possibility of rainfall disaggregation. Rainfall data from the Seoul station (recorded by the Korea Meteorological Administration) are considered for the present investigation, and weights between only successively doubled resolutions (i.e., 24-hr to 12-hr, 12-hr to 6-hr, 6-hr to 3-hr) are analyzed. The correlation dimension method is employed to investigate the presence of chaotic behavior in the time series of weights, and a local approximation technique is employed for rainfall disaggregation. The results indicate the presence of chaotic behavior in the dynamics of weights between the successively doubled scales studied. The modeled (disaggregated) rainfall values are found to be in good agreement with the observed ones in their overall matching (e.g. correlation coefficient and low mean square error). While the general trend (rainfall amount and time of occurrence) is clearly captured, an underestimation of the maximum values are found.

• Journal of Environmental Science International
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• v.23 no.2
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• pp.193-205
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• 2014

The direct-runoff of South Korea's representative dams (Soyanggang, Chungju, Andong, Daecheong, and Seomjingang) and precipitation were analyzed mainly with the evenly distributed spring rainfall events across the country for the last five years. For precipitation, an increasing was presented during the period 2008-2011, but did not continue to increasing 2012. The average precipitation of the five dams displayed a similar trend. Except for Chungju and Andong Dams, the trend of runoff was similar to the one shown in the precipitation. Despite the precipitation of 2009 increased, the runoff volume decreased for Andong and Chungju Dams. In addition, Chungju Dam remarkably showed a bigger runoff volume compared to other dams. As for the Sumjingang Dam, the runoff volume was the smallest, and the difference is as great as over 15-fold when compared to other runoff values. After the result of analyzing the relation between a single runoff event and synoptic weather patterns, pattern 4 contributed to the greatest impact on this event and weather patterns. The total runoff volume of the five dams for spring rain event for the last five years that exhibited this characteristic was estimated at 5.68 billion tons($10^6m^3$). Lastly, the value of this estimation was assessed as approximately 273.1 billion KRW.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.795-807
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• 2009

In this study, homogeneity analysis was performed between rainfall observation data set of Chukwooki (CWK) and rainfall observation data set of modern rain gage (MRG) using Bootstrap method. Since traditional statistical homogeneity test method are validated only when distribution of their population is known, meteorological data which their statistical distributions of population are complicated were difficult to verify the homogeneity and there were plenty of room for doubt for their statistical significance using historical method. In this reason, in this study homogeneity test was evaluated between two data sets using bootstrap method which is not necessary to infer distribution of population. The test results show that there was an statistical homogeneity between CWK and MRG except for slight impact of climatical trend.

• Journal of Korea Water Resources Association
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• v.33 no.4
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• pp.437-446
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• 2000

THe drought analysis is performed by applications of truncation level method and conditional probability concept for hydrologic time series in Han river basin. The distributed trend of conditional probability is determined using kriging method for the time series. This study uses daily flowrate, monthly rainfall, and daily high temperature data sets. The daily flowrate data of 12 years(1986~1997) is used for the analysis. Also, the 14 years' data sets(1986~1999) for monthly rainfall and daily high temperature obtained from the National Weather Service of Korea are used in this study. In the cases of flowrate and rainfall data sets, the estimated value corresponding to the truncation level is decreased as the truncation level is increased but in the high temperature data, the value is increased as the truncation level is increased. The conditional probability varies according to the observations and sites. However, the distributed trend of drought is similar over the basin. As a result, the possibility of the drought is high in the middle and lower parts of Han river basin and thus it is recommended the distributed trend of drought be considered when the plan or measures for drought are established.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

• Water for future
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• v.5 no.1
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• pp.27-36
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• 1972

This thesis is the study of the rainfall probability depth in the major areas of Korea, such as Seoul, Pusan and Taegu. The purpose of the paper is to analyze the rainfall in connection with the safe planning of the hydraulic structures and with the project life. The methodology used in this paper is the statistical treatment of the rainfall data in the above three areas. The scheme of the paper is the following. 1. The complementation of the rainfall data We tried to select the maximm values among the values gained by the three methods: Fourier Series Method, Trend Diagram Method and Mean Value Method. By the selection of the maximum values we tried to complement the rainfall data lacking in order to prevent calamities. 2. The statistical treatment of the data The data are ordered by the small numbers, transformed into log, $\sqrt{}, \sqrt[3]{}, \sqrt[4], and$\sqrt[5], and calculated their statistical values through the electronic computer. 3. The examination of the distribution types and the determination of the optimum distibution types By the $x^2-Test$ the distribution types of rainfall data are examined, and rejected some part of the data in order to seek the normal rainfall distribution types. In this way, the optimum distribution types are determined. 4. The computation of rainfall probability depth in the safety project life We tried to study the interrelation between the return period and the safety project life, and to present the rainfall probability depth of the safety project life. In conclusion we set up the optimum distribution types of the rainfall depths, formulated the optimum distributions, and presented the chart of the rainfall probability depth about the factor of safety and the project life.ct life.

• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.187-199
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• 2010

This study evaluated applicability and confidence of probability rainfalls estimated by the non-stationary rainfall frequency analysis which was recently developed. Using rainfall data at 4 sites which have an obvious increasing trend in observations, we estimated 3 type probability rainfalls; probability rainfalls from stationary rainfall frequency analysis using data from 1973-1997, probability rainfalls from stationary rainfall frequency analysis using data from 1973-2006, probability rainfalls from non-stationary rainfall frequency analysis assuming that the current year is 1997 and the target year is 2006. Based on the comparison of residuals from 3 probability rainfalls, the non-stationary rainfall frequency analysis provided more effective and well-directed estimates of probability rainfalls in the target year. Using Bootstrap resampling, this study also evaluated the parameter estimation methods for the non-stationary rainfall frequency analysis based on confidence intervals. The confidence interval length estimated by the maximum likelihood estimation (MLE) is narrower than the probability weighted moments (PWM). The results indicated that MLE provides more proper confidence than PWM for non-stationary probability rainfalls.

• Journal of the Korean Geographical Society
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• v.33 no.3
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• pp.395-409
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• 1998

The purpose of this paper is to determine the atmospheric conditions in whih urban areas affect the precipitation processes and to evaluate whether certain weather types show more apparent urban effect on precipitation modification over five cities in the southem United States. Each heavy rainstorm is classified into one of three synoptic weather types (frontal storm, airmass storm or tropical disturbance storm). Heavy rainstorm day is defined as day producing rainfall totals that equal o exceed 2 inches (50.08 mm). Houston, Dallass and San Antonio show possible urban effects on rainfall totals and frequencies of heavy rainstorms by airmass storm type while New Orleans and Memphis do not reveal any distinct precipitation enhancements through the synoptic analysis. The results of TSA (Trend Surface Analysis) show that frontal and tropical disturbance storm types have stronger climatic gradients than airmass types and the patterns of rainfall totals have stronger trends than those of rainfall frequencies for the five cities. The results suggest that airmass type events may well reveal possible precipitation enhancements due to urban effects since they are less influenced by a strong climate gradient and they provide favorable conditions for development of urban heat islands. Residual analysis confirms that rainfall totals and frequencies of heavy rainstorms by airmass storm type have positive residuals over the city or the major effect area.

• Environmental Engineering Research
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• v.13 no.4
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• pp.184-191
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• 2008

Long term monitoring was conducted to investigate a surface runoff of pollution from urban highway. The monitoring data was collected for 18 rainfall events and was used to correlate pollution load to various parameters, such as rainfall intensity, antecedent dry days and total discharge flow. Runoff coefficient and seasonal variation were also evaluated. The mean runoff coefficient of the highway was 0.823(range; $0.4687{\sim}0.9884$), and wash-off ratio for $COD_{Mn}$ and SS loads was 72.6% and 64.3%, respectively. For the initial rainfall event, the runoff EMC of $COD_{Mn}$ was high in summer and the EMC of SS was high in autumn season. However the seasonal variation of T-N and T-P was not significant. The discharged $COD_{Mn}$-EMC was $147.6\;mg/L{\sim}9.0\;mg/L$ on the generated $COD_{Mn}$-EMC of $98.8\;mg/L{\sim}8.9\;mg/L$. While the generated EMC of SS was in $285.7\;mg/L{\sim}20.0\;mg/L$ and its discharged EMC was in $190.4\;mg/L{\sim}8.0\;mg/L$. EMC of pollutants was not directly related to the first flush rainfall intensity and the antecedent dry days. But the correlation was relatively high between EMC and cumulative runoff flow volume. The trend of EMC was reduced with the cumulative runoff flow volume.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.212-219
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• 2014

In this study, a land pollutant load calculation method in TMDLs was improved to consider climate change scenarios. In order to evaluate the new method, future change in rainfall patterns was predicted by using SRES A1B climate change scenarios and then post-processing methods such as change factor (CF) and quantile mapping (QM) were applied to correct the bias between the predicted and the observed rainfall patterns. Also, future land pollutant loads were estimated by using both the bias corrected rainfall patterns and the enhanced method. For the results of bias correction, both methods (CF and QM) predicted the temporal trend of the past rainfall patterns and QM method showed future daily average precipitation in the range of 1.1~7.5 mm and CF showed it in the range of 1.3~6.8 mm from 2014 to 2100. Also, in the result of the estimation of future land pollutant loads using the enhanced method (2020, 2040, 2100), TN loads were in the range of 4316.6~6138.6 kg/day and TP loads were in the range of 457.0~716.5 kg/day. However, each result of TN and TP loads in 2020, 2040, 2100 was the same with the original method. The enhanced method in this study will be useful to predict land pollutant loads under the influence of climate change because it can reflect future change in rainfall patterns. Also, it is expected that the results of this study are used as a base data of TMDLs in case of applying for climate change scenarios.