• The Journal of Engineering Geology
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• v.31 no.4
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• pp.631-646
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• 2021

Increasing incidences of landslides in Korea are endangering life and damaging property. To ascertain the cause of the rapid increase in landslides in 2020, this study analyzed the correlation between frequency of their occurrence and persistence of rainfall. The study area comprised seven areas in Gangwon-do, Gyeonggi-do, Gyeongsangnam-do, Gyeongsangbuk-do, Jeollanam-do, Jeollabuk-do, and Chungcheongnam-do. The used rainfall factors were monthly rainfall in June, July, and August, rainfall during the summer (June-August), rainfall during the monsoon season, and number of precipitation days during the summer and during the monsoon season. The effect of these factors on landslides was identified by comparing them with the occurrence of landslides in the year of increased landslide occurrence in each area. The results confirmed that not only rainfall but also the number of precipitation days during the monsoon season affect the occurrence of landslides. The rapid increase in landslide occurrence in 2020 was attributed to increases in both the number of precipitation days during the monsoon season and rainfall during the monsoon season in 2020. These results are expected to be used as basic data for future landslide warning standards that consider the effect of the persistence of rainfall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.389-398
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• 2006

The present study compositely applied the self-organizing map (SOM), which is a kind of artificial neural networks (ANNs), and the back propagation algorithm (BPA) for the rainfall-runoff prediction model taking account of the irregular variation of the spatiotemporal distribution of rainfall. To solve the problems from the previous studies on ANNs, such as the overestimation of low flow during the dry season, the underestimation of runoff during the flood season and the persistence phenomenon, in which the predicted values continuously represent the preceding runoffs, we introduced SOM theory for the preprocessing in the prediction model. The theory is known that it has the pattern classification ability. The method proposed in the present research initially includes the classification of the rainfall-runoff relationship using SOM and the construction of the respective models according to the classification by SOM. The individually constructed models used the data corresponding to the respectively classified patterns for the runoff prediction. Consequently, the method proposed in the present study resulted in the better prediction ability of runoff than that of the past research using the usual application of ANNs and, in addition, there were no such problems of the under/over-estimation of runoff and the persistence.

• Journal of the Korean Geographical Society
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• v.45 no.6
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• pp.748-765
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• 2010

This study aims to investigate the difference of synoptic characteristics over East Asia according to the persistence of rainfall in Korea during the Changma season (June and July). In the cases of consecutive rainfall which lasts four or more days, there are developed ridges in 850hPa level east of the Korean peninsula which introduce stagnation of the synoptic cyclone over Korea. An cold area in 850hPa level moves southward from the Northern China in one day before the beginning the rainfall day in Korea and it aids the development of the stationary front in East Asia. When rainfall lasts a day or two, cyclones pass over Korea in rainy day and the stationary front in East Asia is not intensified. In both cases the synoptic cyclones near the Korean peninsula shows a deep-baroclinic structure, while in the former cases over the southwestern part of Japan a subtropical frontal zone which has a shallow structure appears near Japan. In latter cases the frontal structures are same near Korea and Japan. So, this means that the Changma is not necessarily similar to the Baiu of Japan in all cases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.1-9
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• 2008

The impact of snow accumulation and snowmelt in rainfall-runoff modelling was analyzed for the Soyanggang dam basin by comparing the measured and simulated discharges simulated by the NWS-PC model. Sugawara's conceptual model was used to simulate the snow accumulation and snowmelt phenomena and NWS-PC model was employed to simulate rainfall-runoff. Parameters in model calibration were estimated by the Multi-step Automated Calibration Scheme and optimized using SCE-UA algorithm in each step. The results of the model calibration and verification show that the model considering snowmelt process is better than the one without consideration of snowmelt under the performance criteria such as RMSE, PBIAS, NSE, and PME. The measured discharge time series has over 60 days of persistence. Correlograms for each simulation showed that the simulated discharge with snowmelt model reproduce the persistence closely to the measured discharge's while the one without snow accumulation and snowmelt model reproduce only 20 days of persistence. The study result indicates that the inclusion of snow accumulation and snowmelt model is important for the accurate simulation of rainfall-runoff phenomena in the Soyanggang dam basin.

• Journal of Environmental Science International
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• v.11 no.7
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• pp.721-727
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• 2002

The characteristics of drinking groundwater quality at Chung Cheong Nam Do was analyzed by investigating the 3,086 groundwater data which were carried out the water quality inspection from Jan. 1998 to Dec. 1998. It was found that all the mean concentration of items was not over the drinking water quality standard except Zn at Yeongee area. The highest mean concentration of nitrate was $8.2 mg/{\ell}$ at Hongsung area. And the mean concentrations of nitrate and ammonium at Sucheon, Yesan, Yeongee were relatively higher. It was considered that the groundwater of that area was contaminated by breeding livestock as farm pollutants. The mean concentrations of chloride, hardness and evaporation residual at coastal regions were higher than inland regions. Especially the mean concentration of chloride was 2.5 times higher. It was considered that the groundwater at coastal regions was affected by seawater. It was found that the correlation between Fe and Mn was relatively high(r=0.776) and the correlation between hardness and evaporation residual was very high(r=0.983). The rainfall series and detection rate of E-coli had the hydrologic persistence. The correlation between the detection rate and rainfall series over 150 mm was very high (r=0.9146). Therefore it is surely required to control the groundwater sanitation in the rainy season.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.301-306
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• 2006

본 연구에서는 강우의 시 공간적 분포의 불규칙한 변동성을 고려한 강우-유출예측을 위해 인공신경망(Artificial Neural Networks: ANNs)의 기법의 일종인 자기조직화(Self Organizing Map: SOM) 이론과 역전파 학습 알고리즘(Back Propagation Algorithm: BPA) 이론을 복합적으로 이용하였다. 기존의 인공신경망 연구에서 야기된 저..갈수기의 유출량에 대한 과대평가, 홍수기의 유출량에 대한 과소평가, 예측값이 선행 유출량의 지속성을 갖는 Persistence 현상을 해결하기 위하여 패턴분류 성능을 지닌 SOM 이론을 도입하여 예측모형의 전처리 과정으로 이용하였다. 이는 기존의 인공신경망 모형이 하나의 모형을 구성하여 유출량의 전 범위에 해당하는 자료를 예측하는 방법을 개선한 것으로 SOM에 의해 패턴이 분류된 강우-유출관계의 각 패턴별 예측모형을 통해 분류된 자료들의 예측을 수행하는 방법이다. 이와 같이 SOM을 강우-유출예측모형의 전처리과정으로 이용함으로서 기존의 인공신경망 연구에서 야기된 현상들을 해결할 수 있었고, 예측력 또한 기존의 인공신경망 모형의 결과에 비해 우수하였다.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.5
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• pp.766-771
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• 1999

The first paper of this series compared the effects of rates and frequencies of application of dairy slurry on herbage yields and stand persistence of orchardgrass (Dactylis glomerata L.), reed canarygrass (Phalaris arundinacea L.), and alfalfa (Medicago sativa L.)-grass mixtures managed as a 4-cutting system. This paper compares the effects of rates and frequencies of application of dairy slurry on herbage yield and stand persistence of alfalfa, orchardgrass, tall fescue (Festuca arundinacea Schreb.), and alfalfa-orchardgrass mixture managed as a 5-cutting system. The results presented here are part of a larger study having a primary objective of comparing alfalfa, various grasses, and alfalfa-grass mixtures for utilizing nutrients from dairy slurry applied to established stands. A randomized complete block design with treatments in a split plot arrangement with four replicates was used. The main plots consisted of 9 fertility treatments: 7 slurry rate and frequency of application treatments, one inorganic fertilizer treatment, and an unfertilized control. The sub-plots were the forage species. Manure used for the study was composed from stored solids scraped from the alleyways of a free-stall dairy barn. Water was added to from a slurry having about 8 % solids. Slurry was pumped from the liquid spreader tank into 10.4 L garden watering cans for manual application to the plots. Herbage yields of alfalfa, tall fescue, and alfalfa-orchardgrass were generally not affected by slurry application rates and were not significantly different from the inorganic fertilizer treatment. Tall fescue significantly outyielded all other forage species at all manure and the inorganic fertilizer treatments in the second year when rainfall during the growing season was unusually high. Grasses generally had a greater response to manure applications than alfalfa and alfalfa-orchardgrass. Increasing rates of manure did not increase herbage yields of alfalfa and alfalfa-orchardgrass. Herbage yields within each species were not affected by frequency of application of the same total rate. Stand ratings of alfalfa, orcahrdgrass and alfalfa-orchardgrass were significantly lower for the very high manure application rate compared to the control treatment. Based upon the results of this study, multiple annual applications of slurry manure can be made onto these species at rates up to $1,700kg\;total\;N\;ha^{-1}\;yr^{-1}$ without detrimental effects on herbage yield and stand persistence.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.276-276
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• 2021

최근 댐과 같은 수공구조물의 건설로 대규모 홍수피해는 급격히 줄어들었지만, 돌발홍수(flash flood)로 인한 저지대 침수 등의 도시홍수 발생빈도가 급증하고 있다. 2020년에는 최장의 장마가 관측되었으며, 전국적으로 홍수로 인한 침수피해가 발생하였다. 홍수에 선제적으로 대응하기 위해서 신뢰성 있는 홍수예·경보가 필요하며, 이를 위해서는 신속하고 정확성있는 강우예측이 선행되어야 한다. 이에 본 연구에서는 초단기 강우예측을 목적으로 둔 레이더 기반의 강우앙상블 예측모형을 개발하였다. 라그랑지안 지속성(Lagrangian persistence)을 기반으로 개발하였으며, 강우장의 이동 패턴은 이류특성을 활용해 추정하였다. 즉, 강우장의 예측정확도를 향상시키기 위해 공간적 규모별 캐스캐이드(cascade) 방법으로 분리해 이동 경로를 추정하였다. 예측시간에 따른 강우량은 각 캐스캐이드에 자기회귀모형을 적용하였다. 레이더 강우량은 2016-2020년 사이에 발생한 강우사상에 대한 환경부 홍수통제소에서 제공한 레이더 합성장을 이용하였다. 예측강우량에 대한 평가는 RMSE, Pearson's Correlation, FSS 등 통계치를 통해 수행하였다. 본 연구에서 소개된 강우예측 모형은 초단기 홍수예측에 정확도 높은 강우 정보를 제공할 수 있으며, 이에 따라 홍수피해를 저감하는데 도움이 될 것으로 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.603-611
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• 2020

Potholes on the road directly affect drivers' safety, satisfaction, and vehicle damage. Thus, real-time detection and response are required. Increasing frequency of patrols allows for potholes to be detected and responded to quickly, but this takes much manpower, money, and time. In addition, potholes have different occurrence characteristics depending on the rain conditions, so it is necessary to consider the optimal frequency from an economic and road-service perspective. Therefore, a quantitative analysis was done on the effects of rainfall on the occurrence characteristics of potholes. Information on the persistence, impact of rainfall intensity, and weather information was collected over a long period. Based on the results, a risk-based, optimized, and changeable road-patrol strategy is presented. The analysis results show that the probability of pothole occurrence increases by 2.4 times in rainy weather. Furthermore, the impact continues for 3 days even after the rain stops. The probability of pothole occurrence increases by 0.46% per 1 mm of rainfall, and the occurrence characteristics react sensitively to even a small amount of rain of around 1 mm. It was concluded that road patrol is required at least once every three days for an effect-free period, while twice a day is needed for the "sphere of influence" period to achieve a 95% reliability level.ys for effect-free period, while twice a day for sphere of influence period to satisfy 95% reliability level.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.145-159
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• 2019

A good number of drought indices have been introduced and applied in different regions for monitoring drought conditions, but some of those are region-specific and have limitations for use under other climatic conditions because of the inherently complex characteristics of drought phenomenon. Standardized Precipitation Index (SPI) indices are widely used all over the world, including Bangladesh. Although newly developed, studies have demonstrated The Effective Drought Index (EDI) to perform better compared to SPIs in some areas. This research examined the performance of EDI to the SPI for detecting drought events throughout 35 years (1981 to 2015) in Bangladesh. Rainfall data from 27 meteorological stations across Bangladesh were used to calculate the EDI and SPI values. Results suggest that the EDI can detect historical records of actual events better than SPIs. Moreover, EDI is more efficient in assessing both short and long-term droughts than SPIs. Results also indicate that SPI3 and the EDI indices have a better capability of detecting drought events in Bangladesh compared to other SPIs; however, SPI1 produced erroneous estimates. Therefore, EDI is found to be more responsive to drought conditions and can capture the real essence of the drought situation in Bangladesh. Outcomes from this study bear policy implications on mitigation measures to minimize the loss of agricultural production in drought-prone areas. Information on severity level and persistence of drought conditions will be instrumental for resource managers to allocate scarce resources optimally.