• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.15-22
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• 2019

In order to preserve water environment, Total Maximum Daily Load(TMDL) is used to manage the total amount of pollutant from various sources, and the annual average load of source is calculated by the unit load method. Determination of the unit load requires reliable data accumulation and analysis based on a reasonable estimation method. In this study, we propose a revised unit load estimation method by analyzing the unit load calculation procedure of National Institute of Environment Research(NIER) method. Both methods were tested using observed runoff ratio and water quality data of rice paddy fields. The estimated values with the respective NIER and revised NIER methods were highly correlated each other. However, the Event Mean Concentration(EMC) and the runoff ratio considered in the NIER method appeared to be influenced by rainfall classes, and the difference in unit load increases as the runoff and EMC increase. The error can be further increased when the EMC and runoff ratio are changed according to changes in rainfall patterns by climate change and change of agricultural activities. Therefore, it is recommended to calculate unit load by applying the revised NIER method reflecting the non point pollution runoff characteristics for different rainfall classes.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.381-393
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• 2021

As part of the National Disaster Management Research Institute's Official Development Assistance (ODA) projects for transferring new technologies in the field of disaster-safety management, a flood forecasting and warning system was established in 2019 targeting the Borikhan in the Namxan River Basin in Bolikhamxai Province, Laos. In the target area, which is an ungauged small and medium river basin, observation stations for real-time monitoring of rainfall and runoff and alarm stations were installed, and a software that performs real-time data management and flood forecasting and warning functions was also developed. In order to establish a flood warning standard and develop a nomograph for flood prediction, hydraulic and hydrological analysis was performed based on the 30-year annual maximum daily rainfall data and river morphology survey results in the target area. This paper introduces the process and methodology used in this study, and presents the results of the system's applicability review based on the data observed and collected in 2020 after system installation.

• Journal of Environmental Science International
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• v.4 no.1
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• pp.19-28
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• 1995

A rainfall runoff model described in this paper which is based on Basin- wide Ecological Model(BAWEM) calculates the fate of afro-chemicals in a watershed located of golf links. The rainfall runoff coefficients of afro-chemicals, which are the dominant parameters to predict the movement of agro-chemicals from soil and turfgrass to downstream water, are estimated. Also, the model is used to estimate the level of health risks the residents around golf links are exposed to. The fidelity of rainfall runoff model of afro-chemicals was validated by the observed data obtained during rainy period. The calculated results from this model were found to be in the same order of that of the observed. The rainfall runoff coefficients of four agro-chemicals used in golf links were 5.4$\times$$10^{-3}$, 1.9$\times$$10^{-3}$, 3.0$\times$$10^{-4}$ and 4.4$\times$$10^{-3}$ for flutolanil, isoprothiolane, chlorpyrifos and simazine, respectively The health risk level to the residents around golf links is evaluated to be rather low:the ratio of estimated dose through drinking water to the 10% of ADI(Acceptable Daily Intake) value or VSD for 10-a life time risk varied in the range of 0.005~0.04 and 0.003~0.11, respectively, for both the annual mean and maximum monthly mean cases.

• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.177-189
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• 2022

The purpose of this study is to apply the d4PDF (Data for Policy Decision Making for Future Change) constructed from a large-scale ensemble climate simulation to estimate the probable rainfall with low frequency and high intensity. In addition, this study analyzes the uncertainty caused by the application of the frequency analysis by comparing the probable rainfall estimated using the d4PDF with that estimated using the observed data and frequency analysis at Geunsam, Imsil, Jeonju, and Jangsu stations. The d4PDF data consists of a total of 50 ensembles, and one ensemble provides climate and weather data for 60 years such as rainfall and temperature. Thus, it was possible to collect 3,000 annual maximum daily rainfall for each station. By using these characteristics, this study does not apply the frequency analysis for estimating the probability rainfall, and we estimated the probability rainfall with a return period of 10 to 1000 years by distributing 3,000 rainfall by the magnitude based on a non-parametric approach. Then, the estimated probability rainfall using d4PDF was compared with those estimated using the Gumbel or GEV distribution and the observed rainfall, and the deviation between two probability rainfall was estimated. As a result, this deviation increased as the difference between the return period and the observation period increased. Meanwhile, the d4PDF reasonably suggested the probability rainfall with a low frequency and high intensity by minimizing the uncertainty occurred by applying the frequency analysis and the observed data with the short data period.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.12-19
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• 1999

CERES-rice, a rice growth simulation model, was used in conjunction with daily weather data to figure out the spatial variation of the phenology and yields of paddy rice at 168 rice cultivation zone units(CZU) of Kyunggi Province in 1997. Two sets of cultivar specific coefficients, which represent early and mid-season maturing varieties, were derived from field experiments conducted at two crop experiment stations. The minimum data set to run the model for each CZU (daily maximum and minimum temperature, solar irradiance, and rainfall) was obtained by spatial averaging of existing 'Digital Map of Korean Climate'(Shin et al., 1999). Soil characteristics and management information at each CZU were available from the Rural Development Administration. According to a preliminary test using 5 to 9 years field data, trends of the phasic development(heading and physiological maturity), which were obtained from the model adjusted for these coefficients, were in good agreement with the observed data. However, the simulated inter-annual variation was somewhat greater than the reported variation. Rough rice yields of the early maturing cultivar calculated by the model were comparable with the reported data in terms of both absolute value and inter -annual variation. But those of the mid season cultivar showed overestimation. After running the simulation model runs with 1997 weather data for 168 CZU's, rough rice yields of the 168 CZU's calculated by the model were aggregated into corresponding 33 counties by acreage-weighting to facilitate direct comparison with the reported statistics from the Ministry of Agriculture and Forestry. The simulation results were good at 22 out of the 26 counties with reportedly increasing yield trend with respect to the past 9 years average.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.419-431
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• 2021

In Seoul, it has been confirmed that the duration of rainfall is shortened and the frequency and intensity of heavy rains are increasing with a changing climate. In addition, due to high population density and urbanization in most areas, floods frequently occur in flood-prone areas for the increase in impermeable areas. Furthermore, the Seoul City is pursuing various projects such as structural and non-structural measures to resolve flood-prone areas. A disaster prevention performance target was set in consideration of the climate change impact of future precipitation, and this study conducted to reduce the overall flood damage in Seoul for the long-term. In this study, 29 GCMs with RCP4.5 and RCP8.5 scenarios were used for spatial and temporal disaggregation, and we also considered for 3 research periods, which is short-term (2006-2040, P1), mid-term (2041-2070, P2), and long-term (2071-2100, P3), respectively. For spatial downscaling, daily data of GCM was processed through Quantile Mapping based on the rainfall of the Seoul station managed by the Korea Meteorological Administration and for temporal downscaling, daily data were downscaled to hourly data through k-nearest neighbor resampling and nonparametric temporal detailing techniques using genetic algorithms. Through temporal downscaling, 100 detailed scenarios were calculated for each GCM scenario, and the IDF curve was calculated based on a total of 2,900 detailed scenarios, and by averaging this, the change in the future extreme rainfall was calculated. As a result, it was confirmed that the probability of rainfall for a duration of 100 years and a duration of 1 hour increased by 8 to 16% in the RCP4.5 scenario, and increased by 7 to 26% in the RCP8.5 scenario. Based on the results of this study, the amount of rainfall designed to prepare for future climate change in Seoul was estimated and if can be used to establish purpose-wise water related disaster prevention policies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4B
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• pp.413-427
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• 2010

Urbanization means the sudden increment of a population and the industrialization. The hydrologic water cycle causes many changes due to urbanization. Therefore, the affects that urbanization influences on the precipitation events were analyzed. But the precipitation events are very much influenced many meteorological and climatologically indices besides the effect of an urbanization. So, an analysis was performed by using precipitation data observed in many spots of the Korean peninsula. The analysis data are annual precipitation, the duration 1 daily maximum amount of precipitation, the rainy days, and 10 mm over the rainy days, and 80 mm. seasonal precipitation and seasonal rainy days. The analytical method classified 4 clusters in which the precipitation characteristic is similar through the cluster analysis. It compared and analyzed precipitation events of the urban and rural stations. Moreover, the representative rainfall stations were selected and the urban stations and rural stations were compared. In the analyzed result, the increment of the rainy days was conspicuous over 80mm in which it can cause the heavy rainfall. By using time precipitation data, the design precipitation was calculated. Rainfall events over probability precipitation on duration and return period were analyzed. The times in which it exceeds the probability precipitation in which the urban area is used for the hydrologic structure design in comparison with the rural area more was very much exposed to increase.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.627-635
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• 2019

In Korea, snow damage has been happened in the region with no snowfalls in history. Also, casual damage was caused by heavy snow. Therefore, policy about the Natural Disaster Reduction Comprehensive Plan has been changed to include the mitigation measures of snow damage. However, since heavy snow damage was not frequent, studies on snowfall have not been conducted in different points. The characteristics of snow data commonly are not same to the rainfall data. For example, some parts of the southern coastal areas are snowless during the year, so there is often no values or zero values among the annual maximum daily snow accumulation. The characteristics of this type of data is similar to the censored data. Indeed, Busan observation sites have more than 36% of no data or zero data. Despite of the different characteristics, the frequency analysis for snow data has been implemented according to the procedures for rainfall data. The frequency analysis could be implemented in both way to include the zero data or exclude the zero data. The fitness of both results would not be high enough to represent the real data shape. Therefore, in this study, a methodology for selecting a probability density function was suggested considering the characteristics of snow data in Korea. A method to select probability density function using conditional joint probability distribution was proposed. As a result, fitness from the proposed method was higher than the conventional methods. This shows that the conventional methods (includes 0 or excludes 0) overestimated snow depth. The results of this study can affect the design standards of buildings and also contribute to the establishment of measures to reduce snow damage.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.1-19
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• 2014

This study aims to assess the slope stability variation of Jeonbuk drainage areas by RCM model outputs based on A1B climate change scenario and infinite slope stability model based on the previous research by Choi et al.(2013). For a large-scale slope stability analysis, we developed a GIS-based database regarding topographic, geologic and forestry parameters and also calculated daily maximum rainfall for the study period(1971~2100). Then, we assess slope stability variation of the 20 sub-catchments of Jeonbuk under the climate change scenario. The results show that the areal-average value of safety factor was estimated at 1.36(moderately stable) in spite of annual rainfall increase in the future. In addition, 7 sub-catchments became worse and 5 sub-catchments became better than the present period(1971~2000) in terms of safety factor in the future.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.815-826
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• 2012

The underestimating trend using existing ordinary regression (OR) based trend analysis has been a well-known problem. The existing OR method based on least squares approximate the conditional mean of the response variable given certain values of the time t, and the usual assumption of the OR method is normality, that is the distribution of data are not dissimilar form a normal distribution. In this regard, this study proposed a quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. This study assess trend in annual daily maximum rainfall series over 64 weather stations through both in OR and QR approach. The QR method indicates that 47 stations out of 67 weather stations are a strong upward trend at 5% significance level while OR method identifies a significant trend only at 13 stations. This is mainly because the OR method is estimating the condition mean of the response variable. Unlike the OR method, the QR method allows us flexibly to detect the trends since the OR is designed to estimate conditional quantiles of the response variable. The proposed QR method can be effectively applied to estimate hydrologic trend for either non-normal data or skewed data.