• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.295-305
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• 2009

The purpose of this study was to understand of water quality characteristics of lake Paldang, especially at a certain representative site, right in front of Paldang dam ($P_2$ site) and to propose the directions of water quality management of lake Paldang. Water characteristics at $P_2$ site was investigated by principle components analysis and the Pearson correlation coefficient analysis. Also, seasonality was identified by the Kruskal-Wallis test and long term trend of nutrients and chlorophyll-a was analyzed by seasonal decomposition method at lake Paldang statistically. The primary factor affecting on water quality at $P_2$ site was identified as nutrients, while physical parameters, such as rainfall and inflow rate were also important factors. At the result of linear regression analysis particulate organic phosphorus (POP) vs total phosphorus (TP) showed very high correlation of 0.78. TP loading was increased annually from 1995 to 2006. Chlorophyll-a and nutrients show seasonality at $P_2$ site. Long term trend of Chlorophyll-a was increased by increase of TP at lake Paldang.

• Journal of the Korean Geographical Society
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• v.48 no.2
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• pp.184-203
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• 2013

This study analyzes the variability of Korean summer rainfall associated with the tropical low-frequency oscillation using long-term observation data. From the EOF analysis, the first mode showed opposite phase between the South and the North Korea with the regime shift in rainfall variability since the mid-1990s. The summer precipitation over South Korea tends to increase in southern part during strong El Ni$\tilde{n}$o where the warm sea surface temperature extends to far eastern tropical Pacific. In weak La Ni$\tilde{n}$a, the increased precipitation directly influences from the western tropical Pacific to the mid-latitude. In June, the rainfall over South Korea is positively correlated with the Indian Summer Monsoon while in July, it is negatively correlated with the Western North Pacific Summer Monsoon. In August, highly negative correlation between the rainfall over South Korea and the Indian Summer Monsoon is found.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.2
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• pp.67-74
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• 2011

This research focused on the investigation of runoff and nonpoint sources (NPS) pollution characteristics from small soil box plots treated by livestock waste composts. An indoor rainfall simulation was performed over the plots for 60 minutes. Simulated rainfall intensities were 32.4, 43.2, 50.3 and 57.1 mm/hr respectively. Slope of soil box plots was $10^{\circ}$ and $20^{\circ}$, respectively. Rainfall simulation replicated 5 times and the experiment was conducted every four days five times. As the slope of soil box increased, NPS pollution loads increased. And as rainfall intensity was increased from 32.4 to 57.1 mm/hr, NPS pollution loads gradually increased, too. Discharge of NPS pollution loads was the largest in the first simulation and thereafter decreased gradually. Discharged BOD load to the total applied load from $10^{\circ}$ plots, ranged 0.2 to 0.7 %, was 8.4 to 50.0 % lower than slope $20^{\circ}$ plots. When the application rate increased twice, the increase of pollution load was between 1.7~5.7 times. Analysis of Pearson's correlation coefficient showed that organic matter content in pig compost and NPS pollution loads were correlated well. While under liquid compost application, the correlation coefficients between them were not good. It was concluded that application of livestock resources need to consider long-term weather forecast and if necessary, NPS reduction measures must be preceded in order to reduce NPS pollution discharge.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.856-864
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• 2006

For estimating the minimum discharge to maintain a river, low flow analysis is required and long term runoff records are needed for the analysis. However, runoff data should be estimated to run a hydrologic model for ungaged river basin. For the reason, parameter estimation is crucial to simulate rainfall-runoff events for those basins using Tank model. In this study, only runoff data recorded for dry season are used for parameter estimation, which is different to other methods based on runoff data recorded for wet and dry seasons. The Harmony Search algorithm is used to determine the optimum parameters for Tank model. The coefficient of determination ($R^2$) is served as the objective function in the Harmony Search. In cases that recorded data are insufficient, the recording interval is changed and Empirical CDF is adopted to analyze the estimated parameters. The suggested method is applied to Yongdam dam, Soyanggang dam, Chungju dam and Seomjingang dam basins. As results, the higher $R^2s$ are obtained when the shorter recording interval, the better recorded data quality, and the more rainfall events recorded along with certain rainfall amount is. Moreover, when the total rainfall is higher than the certain amount, $R^2$ is high. Considering the facts found from this study for the low flow analysis, it is possible to estimate the parameters for Tank model properly with the desired confidence level.

• Journal of Wetlands Research
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• v.11 no.1
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• pp.49-64
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• 2009

Rainfall-runoff models are used for efficient management, distribution, planning, and design of water resources in accordance with the process of hydrologic cycle. The models simplify the transition of rainfall to runoff as rainfall through different processes including evaporation, transpiration, interception, and infiltration. As the models simplify complex physical processes, gaps between the models and actual rainfall events exist. For more accurate simulation, appropriate models that suit analysis goals are selected and reliable long-term hydrological data are collected. However, uncertainty is inherent in models. It is therefore necessary to evaluate reliability of simulation results from models. A number of studies have evaluated uncertainty ingrained in rainfall-runoff models. In this paper, Meta-Gaussian method proposed by Montanari and Brath(2004) was used to assess uncertainty of simulation outputs from rainfall-runoff models. The model, which estimates upper and lower bounds of the confidence interval from probabilistic distribution of a model's error, can quantify global uncertainty of hydrological models. In this paper, Meta-Gaussian method was applied to analyze uncertainty of simulated runoff outputs from $Vflo^{TM}$, a physically-based distribution model and HEC-HMS model, a conceptual lumped model.

• Journal of Korea Water Resources Association
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• v.39 no.11 s.172
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• pp.905-914
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• 2006

For an accurate rainfall-runoff simulation in the river basin, not evaluation of runoff model but accurate runoff data are very important. In this study, SSARR model was applied to the Geum River basin and these results are compared with runoff data observed at the Gongju gauging station. The model results didn't good fit the discharge data determined from the rating curve at Gongju gauging station during normal and dry season, especially. For the reliability analysis for the existing rating curve, we observed new stream discharge set from 2003 to 2005. We also estimated long term runoff data from the base flow separation method and defined the hydraulic characteristics. The results show that the new observed stream discharge is similar to the rainfall-runoff model results but existing rating curve seems to be overestimated about 10-20% during normal and dry season. We found that the continuous monitoring and update for the existing rating curve at the gaging station are needed for accurate estimation of runoff data.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.333-343
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• 2022

For water resource management, the design flood is calculated using the flood frequency analysis technique and the rainfall runoff model. The method by design flood frequency analysis calculates the stochastic design flood by directly analyzing the actual discharge data and is theoretically evaluated as the most accurate method. Actual discharge data frequency analysis of the measured flow was limited due to data limitations in the existing flood flow analysis. In this study, design flood frequency analysis was performed using the measured flow data stably secured through the water level-discharge relationship curve formula. For the frequency analysis of design flood, the parameters were calculated by applying the bayesian inference, and the uncertainty of flood volume by frequency was quantified. It was confirmed that the result of calculating the design flood was close to that calculated by the rainfall-runoff model by applying long-term rainfall data. It is judged that hydrological analysis can be done from various perspectives by using long-term actual flow data through hydrological survey.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.833-844
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• 1998

The objectives of this study are to adopt a snowmelt model for coupling a rainfall-runoff model and to study snowmelt effects for long-term runoff analysis on the northeast mountaneous area in Korea. The NWS temperature-index snowmelt model was selected and tested on the 1,059+,6 km$^2$ Naerinchen basin. It can be observed that the time variations of the computed areal extents of snow cover from the model are well agreement with those of the observe station snowfall records on the Inje meteorological station. It is also evident that the computed soil water contents and river flows indicate quite different behaviors with or without snowmelt model. It is concluded that the snowmelt model works well and the snowmelt effects for multi-decadal river flow computations are important on the study area.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.123-123
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• 2020

The present study is aimed to correcting radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty analysis of water levels contributed at each stage in the process. For this reason, a long short-term memory (LSTM) network is used to reproduce three-hour mean areal precipitation (MAP) forecasts from the quantitative precipitation forecasts (QPFs) of the McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE). The Gangnam urban catchment located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 24 heavy rainfall events, 22 grid points from the MAPLE system and the observed MAP values estimated from five ground rain gauges of KMA Automatic Weather System. The corrected MAP forecasts were input into the developed coupled 1D/2D model to predict water levels and relevant inundation areas. The results indicate the viability of the proposed framework for generating three-hour MAP forecasts and urban flooding predictions. For the analysis uncertainty contributions of the source related to the process, the Bayesian Markov Chain Monte Carlo (MCMC) using delayed rejection and adaptive metropolis algorithm is applied. For this purpose, the uncertainty contributions of the stages such as QPE input, QPF MAP source LSTM-corrected source, and MAP input and the coupled model is discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.259-266
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• 2023

Global climate change is increasing, and the damage and scale of localized torrential rains are increasing. Pre-flood analysis simulation results should be derived from rainfall data through rainfall forecasts to prevent flood damage. In addition, it is necessary to control the use and management of flood response disaster prevention facilities through immediate decision-making. However, methods using spills and flood models such as XPSWMM and GATE2018 are limited due to professional usability and complex analytical procedures. Prototype (flood disaster prevention facility simulator) of this study is developed by calculating rainfall (short-term and long-term) using CBD software development methods. It is also expected to construct administrator and user-centric interfaces and provide GIS and visible data (graphs, charts, etc.).