• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.811-812
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• 2005

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.164-169
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• 2000

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.124-129
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• 2000

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.203-208
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• 2000

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.55-69
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• 2016

RUSLE (Revised Universal Soil Loss Equation) is the empirical formular widely used to estimate rates of soil erosion caused by rainfall and associated overland flow. Among the factors considered in RUSLE, rainfall erosivity factor (R factor) is the major one derived by rainfall intensity and characteristics of rainfall event. There has been developed various methods to estimate R factor, such as energy based methods considering physical schemes of soil erosion and simple methods using the empirical relationship between soil erosion and annual total rainfall. This study is aimed to quantitatively evaluate the variation among the R factors estimated using different methods for South Korea. Station based observation (minutely rainfall data) were collected for 72 stations to investigate the characteristics of rainfall events over the country and similarity and differentness of R factors calculated by each method were compared in various ways. As results use of simple methods generally provided greater R factors comparing to those for energy based methods by 76 % on average and also overestimated the range of factors using different equations. The variation coefficient of annual R factors was calculated as 0.27 on average and the results significantly varied by the stations. Additionally the study demonstrated the rank of methods that would provide exclusive results comparing to others for each station. As it is difficult to find universal way to estimate R factors for specific regions, the efforts to validate and integrate various methods are required to improve the applicability and accuracy of soil erosion estimation.

• Journal of the Korean association of regional geographers
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• v.17 no.5
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• pp.505-520
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• 2011

This study is aimed to examine the change on extreme precipitation events in South Korea. The country is divided into six basins, and seven extreme precipitation indices-related to heavy rainfall are analyzed at sixty weather stations. The increasing trend in amount of heavy rainfall is more stable than that in days of heavy rainfall. The increasing trend is the most stable when days of rainfall are more than 50 mm, or rainfall is over the 95th percentile. The precipitation indices-related to heavy rainfall was mostly increasing during analysis period. Especially, basins of the Han river, the upper Nakdong river, and the Eastern coast show significantly increasing trends compared to the other basins. However, the increasing trends of the Geum river and the Seomjin river are not statistically significant. Heavy rainfall events had stably increased in the Han and the Nakdong rivers since the mid-1970s. However, the number of stably increasing regions has decreased since the mid-2000s. It means that the frequency and intensity of the recent heavy rainfall become more irregular.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.361-372
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• 2011

This study analyzed the characteristics of stormwater runoff by rainfall type in orchard areas for two years. Effluents were monitored to calculate the EMCs and runoff loads of each pollutant. The runoff characteristics for nonpoint sources from vineyards were also inspected based on independent variables that affect runoff such as rainfall and rainfall intensity. The average runoff loads of each pollutant from vineyard_A and vineyard_B were found as follows: BOD 39.13 mg/$m^2$, COD 112.13 mg/$m^2$, TOC 54.98 mg/$m^2$, SS 1,681.8 mg/$m^2$, TN 18.29 mg/$m^2$, and TP 4.06 mg/$m^2$, which indicates that the COD's runoff load was especially high. The average EMCs from vineyard_A and vineyard_B, which represents the quality of rainfall effluent, were also analyzed: BOD 3.5 mg/L, COD 11.5 mg/L, TOC 5.2 mg/L, SS 211.7 mg/L, TN 1.774 mg/L, and TP 0.324 mg/L. This suggested that the COD, as an indicator of organic pollutants, is high in terms of EMCs as well. As rainfall increased, the EMCs of BOD, COD, TOC and SS kept turning upward. At a point, however, the high rainfall brought about dilution effects and began to push down the EMCs. Higher rainfall intensities led to the increase in the EMCs that displays the convergence of rainfall. Low rainfall intensities also raised pollutant concentrations, although the concentrations themselves were slightly different among pollutants.

• Journal of Korea Water Resources Association
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• v.33 no.2
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• pp.195-205
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• 2000

Many types of factors were devised to calculate time of concentration. Singh(976) derived time of concentration of overland flow using kinematic wave theory for plane, converging, and diverging geometric configurations. The present paper investigated the time of concentration for particularly plane geometric configuration. A theoretical equation of time of concentration is derived based on the assumption of impervious overland flow as in the open channel flow. The study characterized the overland flow by many types of characteristic flow such as rough turbulent flow, smooth turbulent flow, laminar flow, and then suggested a theoretical equation on each flow condition. The present paper further considered the rainfall intensity as a main factor and devised an approximate composite equation reflecting the effect of rainfall intensity given at various return periods.

• Journal of Environmental Science International
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• v.24 no.1
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• pp.133-150
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• 2015

Wind profiler provides vertical profiles of three-dimensional wind vectors with high spatiotemporal resolution. The wind vectors is useful to analyze severe weather phenomena and to validate the various products from numerical weather prediction model. However, the wind measurements are not immune to ground clutter, bird, insect, and aircraft. Therefore, quality of wind vectors from wind profiler must be quantitatively evaluated prior to its application. In this study, wind vectors from UHF wind profiler at Ganwon Regional Meteorological Administration was quantitatively evaluated using 27 radiosonde measurements that were launched every two or three hours according to rainfall intensity during Intensive Observation Period (IOP) from June to July 2013. In comparison between two measurements, wind vectors from wind profiler was relatively underestimated. In addition, the accuracy and quality of wind vectors from wind profiler decrease with increasing beam height. The accuracy and quality of the wind vectors for rainy periods during IOP were higher than for the clear-air measurements. The moderate rainfall intensity lead to multi-peaks in Doppler spectrum. It results in overestimation of vertical air motion, whereas wind vectors from wind profilers shows good agreement with those from radiosonde measurements for light rainfall intensity.

• Journal of Environmental Science International
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• v.19 no.7
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• pp.907-915
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• 2010

Agriculture nonpoint pollution source is a significant contributor to water quality degradation. To establish effective water quality control policy, environpolitics establishment person must be able to estimate nonpoint source loads to lakes and streams. To meet this need for orchard area, we investigated a real rainfall runoff phenomena about it. We developed nonpoint source runoff estimation models for vineyard area that has lots of fertilizer, compost specially between agricultural areas. Data used in nonpoint source estimation model gained from real measuring runoff loads and it surveyed for two years(2008-2009 year) about vineyard. Nonpoint source runoff loads estimation models were composed of using independent variables(rainfall, storm duration time(SDT), antecedent dry weather period(ADWP), total runoff depth(TRD), average storm intensity(ASI), average runoff intensity(ARI)). Rainfall, total runoff depth and average runoff intensity among six independent variables were specially high related to nonpoint source runoff loads such as BOD, COD, TN, TP, TOC and SS. The best regression model to predict nonpoint source runoff load was Model 6 and regression factor of all water quality items except for was $R^2=0.85$.