• Korean Journal of Environmental Biology
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• v.37 no.4
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• pp.640-651
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• 2019

The study analyzed the relationship between harmful cyanobacteria and physicochemical factors in Lake Juam from 2005 to 2018. The research locations were designated St. 1 (Juam-Dam) and St. 2 (Sinpyong). Harmful cyanobacteria was found in four genera (Microcystis sp., Anabaena sp., Aphanizomenon sp., Oscillatoria sp.). The average standing crops of harmful cyanobacteria in both locations were 2,575 cells mL^-1 and 2,557 cells mL^-1 from 2005 to 2011. Since 2012, there has been a significant decrease that the measurements were 42 cells mL^-1 and 82 cells mL^-1 from 2012 to 2018. To analyze the reason for the decrease in harmful cyanobacteria, Pearson's correlation and t-tests were performed on data collected during the summer period (June-September). Pearson's correlation showed a significantly positive correlation with total nitrogen(TN), outflow, and storage and a negative correlation with electrical conductivity. T-tests were conducted in two different periods and showed decreases in total nitrogen, electrical conductivity, and residence time. The average rainfall was decreased from 263.3 mm (2005-2011) to 219.9 mm (2012-2018) and total nitrogen was decreased from 0.912 mg L^-1 (2005-2011) to 0.811 mg L^-1 (2012-2018) and the same variability was seen in TP (total phosphorus). Therefore, it seems that the low-rainfall decreased the nutrients (TN) and variability in the TP, resulting in a decrease in harmful cyanobacteria in Lake Juam.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.363-363
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• 2011

무분별한 개발사업으로 인하여 발생되는 토양 침식 피해를 최소화시키기 위해서는 정확한 토양 침식량을 추정해야 한다. 현재 토양 침식량을 추정하기 위한 공식으로 Wischmeier와 Smith(1997)가 발표한 범양 토양손실공식(RUSLE, Revised Universal Soil Loss Equation)을 주로 사용하고 있다. RUSLE 공식의 매개변수 중 하나인 강우침식능 인자 R은 실무에서는 단일강우 확률강우량의 시간분포 강우량에 대하여 강우침식능을 산정하는 방법을 널리 사용하고 있으나, 연평균 강우침식능을 사용하는 경우도 많다. 국립방재연구소(2009)는 전국 53개소의 1960년대~2008년까지의 1시간 강우자료를 이용하여 연평균 강우침식능을 산정한 바 있고, 본 연구에서는 국립방재연구소의 자료(2009)에 23개소를 추가 하고 2009년~2010년 강우자료를 추가하여 강우침식능을 산정하였다. 강우침식능 산정 시 사용되는 강우 운동에너지 공식은 국내외에서 여러 가지 공식이 제안되고 있으나, 본 연구에서는 RUSLE와 USLE에서 추천하고 있는 식과 노재경 등(1984)의 식, van Dijk(2002) 식을 이용하여 각각의 연평균 강우침식능을 산정하고 전국 연평균 강우침식도를 재산정하였다. 연평균 R값의 76개 지점평균은 RUSLE 식 4890, USLE 식 5538, 노재경 식 4608, van Dijk 식 5444 MJ/ha mm/hr로 산정되었다. 에너지식에 따라 값은 최대 930 MJ/ha mm/hr 차이를 보였으나, 분포 양상은 경북 지역을 제외한 모든 유역에서 비슷함을 알 수 있었다. 노재경 식은 서울과 수원의 관측자료를 이용하여 제안된 식으로 타 식에 비하여 우리나라의 강우특성을 비교적 잘 고려한다고 판단되지만, 시간 및 공간적으로 제한된 데이터를 이용하여 제안된 식이므로 실무 적용을 위해서는 추가적인 검정이 필요할 것으로 사료된다.

• Journal of Korea Water Resources Association
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• v.48 no.11
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• pp.937-944
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• 2015

This study proposed a novel technique, namely the Radar Polygon Method (RPM), for areal rainfall estimation based on radar precipitation data. The RPM algorithm has the following steps: 1. Determine a map of the similar rainfall occurrence of which each grid cell contains the binary information on whether the grid cell rainfall is similar to that of the observation gage; 2. Determine the similar rainfall probability map for each gage of which each grid cell contains the probability of having the rainfall similar to that of the observation gage; 3. Determine the governing territory of each gage by comparing the probability maps of the gages. RPM method was applied to the Anseong stream basin. Radar Polygons and Thiessen Polygons of the study area were similar to each other with the difference between the two being greater for the rain gage highly influenced by the orography. However, the weight factor between the two were similar with each other. The significance of this study is to pioneer a new application field of radar rainfall data that has been limited due to short observation period and low accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.363-374
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• 2008

Intensity-Duration-Frequency (IDF) curve that is essential to calculate rainfall quantiles for designing hydraulic structures in Korea is generally formulated by regression analysis. In this study, IDF curve derived by the cumulative distribution function ("IDF by CDF") of the proper probability distribution function (PDF) of each site is suggested, and the corresponding parameters of IDF curve are computed using genetic algorithm (GA). For this purpose, IDF by CDF and the conventional IDF derived by regression analysis ("IDF by REG") were computed for 22 Korea Meteorological Administration (KMA) rainfall recording sites. Comparisons of RMSE (root mean squared error) and RRMSE (Relative RMSE) of rainfall intensities computed from IDF by CDF and IDF by REG show that IDF by CDF is more accurate than IDF by REG. In order to accommodate the effect of the recent intensive rainfall of Korea, the rainfall intensities computed by the two IDF curves are compared with that by at-site frequency analysis using the rainfall data recorded by 2006, and the result from IDF by CDF show the better performance than that from IDF by REG. As a result, it can be said that the suggested IDF by CDF curve would be the more efficient IDF curve than that computed by regression analysis and could be applied for Korean rainfall data.

• Journal of Korea Water Resources Association
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• v.45 no.10
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• pp.1035-1041
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• 2012

This paper is on the decision of design magnitude for flood control of urban basin, based on flooding characteristic values. In Korea, a design magnitude for flood control is established based on peak discharge of the outlet of basin. However, this method is inappropriate in an urban basin because sewerage only can flow out as much as it could and other discharge overflow to basin. In order to calculate a design magnitude for flood control of an urban basin, flooding characteristic values (peak discharge of pipe, average flooded depth, maximum flooded depths of an important point, flooded area, flooded volume, flooded time) were used as a tool. Using the Gwanghwamun Square as an example, a methodology was proposed that used XP-SWMM 2010 model as a platform to predict urban flood disaster. It can help other local government and residents to better understand, prepare for and manage a flood in urban environments.