• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.259-267
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• 2009

Generalized Extreme Value (GEV) distribution is recommended for flood frequency and extreme rainfall distribution in many country. L-moment method is the most common estimation procedure for the GEV distribution. In this study, the relationships between the cross-site correlations between extreme events and the cross-correlation of estimators of L-moment ratios (L-moment Coefficient of Variation (L-CV) and L-moment Coefficient of Skewness (L-CS)) for data generated from GEV distribution were derived by Monte Carlo simulation. Those relationships were fit to the simple power function. In this Monte Carlo simulation, GEV+ distribution were employed wherein unrealistic negative values were excluded. The simple power models provide accurate description of the relationships between cross-correlation of data and cross-correlation of L-moment ratios. Estimated parameters and accuracies of the power functions were reported for different GEV distribution parameters combinations. Moreover, this study provided a description about regional regression approach using Generalized Least Square (GLS) regression method which require the cross-site correlation among L-moment estimators. The relationships derived in this study allow regional GLS regression analyses of both L-CV and L-CS estimators that correctly incorporate the cross-correlation among GEV L-moment estimators.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.125-125
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• 2022

저수지 운영자료는 다목적 댐 경우와 마찬가지로, 유입량, 저수량, 방류량 자료로 구성된다. 여기에 강우량을 포함하여, 실시간으로 관리돼야 한다. 그러나 우리나라 저수지는 저수율 자료만 관리하고 있다. 유입량, 방류량이 없는 것이 아니고 관리를 하지 않는다. 강우량은 전혀 없다. 큰 문제인데, 아직도 그 심각성을 모르고, 대충하면 되는 줄 알고 있다. 가장 기초가 되는 일을 무시하고 물관리를 하고 있는 상황이고, 누구도 그 신뢰성을 믿지 않고 있다. 여기서는 이를 해결하는 방안으로 준 실시간 물수지 모형을 구축하여, 10분 단위, 30분 단위, 1시간 단위로 저수위, 저수량, 유입량, 방류량, 강우량을 연속하여 생산하고 검증하는 체제를 제시한다. 준 실시간의 뜻은 계산에 의하지 않고 유입량을 모의에 의해 적용하고 검증하는 과정이 필요하여, 실시간 보다 하루 이틀 늦게 자료를 생산한다는 의미다. 대상 저수지는 유역 내 강우량 수집이 가능한 유역면적 218.80km², 유효저수량 3,494만m³, 수혜면적 5,117 ha인 탑정지를 선정했다. 탑정지 방류량은 탑정1(폭 7.5m×높이 1.5m), 탑정2(4m×1.6m), 양수장(3m×1.6m) 수로로 관개용수 공급량과, 9연의 수문(9m×7.5m)으로 홍수기 방류량으로 구성된다. 분석기간은 1월1일부터 1시간 단위로 연속하여 기간은 자유롭게 설정하여 검정하는 체제를 갖추고 검증된 결과를 제시토록 했다. 2021년 9월의 1시간 단위의 탑정지 저수지 물수지 모의 결과를 요약하면 다음과 같다. 첫째, 탑정지 유역의 환경부 관리 장선, 양촌, 연산 관측소의 면적우량은 최대 15.3mm, 총 160.4mm(3,510만m³)였고, ONE 모형에 의해 연속유량을 모의한 결과, 유입량은 최대 35.6m³/s, 총 1,464만m³로 유출률 41.7%였다. 둘째, 탑정1, 탑정2, 양수장 수로의 수위자료에 수위-유량 관계식을 적용해 수로유량을 산정한 결과 합하여 최대 16.8m³/s였고, 총 548만m³였으며, 수문 방류량은 최대 20.0m³/s였고, 총 108만m³였다. 셋째, 저수지 수위는 관측수위는 EL.28.21~29.38m, 평균 EL.28.87m, 모의수위는 EL.28.08~29.62m, 평균 EL.28.80m로 나타났고, R²는 0.910로 만족한 결과를 얻었다. 정리하면 저수지 운영자료가 없는데도, 10분, 1시간 단위로 연속으로 유입량, 저수량을 모의하여 관측저수량과 비교한 결과가 괄목할 신뢰도를 나타냈다. 이를 바탕으로 저수량, 유입량, 방류량, 강우량 등 준 실시간 저수지 운영자료 생산체제를 마련한 것으로 결론을 내렸다.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1143-1154
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• 2021

The selection of activation function has a great influence on the groundwater level prediction performance of artificial neural network (ANN) model. In this study, five activation functions were applied to ANN model for two groundwater level observation wells in the middle mountainous area of the Pyoseon watershed in Jeju Island. The results of the prediction of the groundwater level were compared and analyzed, and the optimal activation function was derived. In addition, the results of LSTM model, which is a widely used recurrent neural network model, were compared and analyzed with the results of the ANN models with each activation function. As a result, ELU and Leaky ReLU functions were derived as the optimal activation functions for the prediction of the groundwater level for observation well with relatively large fluctuations in groundwater level and for observation well with relatively small fluctuations, respectively. On the other hand, sigmoid function had the lowest predictive performance among the five activation functions for training period, and produced inappropriate results in peak and lowest groundwater level prediction. The ANN-ELU and ANN-Leaky ReLU models showed groundwater level prediction performance comparable to that of the LSTM model, and thus had sufficient potential for application. The methods and results of this study can be usefully used in other studies.

• Clinical and Experimental Pediatrics
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• v.45 no.9
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• pp.1134-1140
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• 2002

Purpose : Childhood accidents have been increasing recently. Accidents rank as the leading cause of childhood mortality and morbidity. We performed this study to evaluate the causes of childhood accidents. Methods : The authors analysed retrospectively the medical records of 6,410 cases of childhood accidental injuries who visited the emergency room of Asan Medical Center from January 1990 to December 1999. Results : The most common type of accidents was trauma which accounted for 5,038 cases of the total accidents, followed by falls, burns, foreign body aspiration, and poisoning. The most common age of foreign body aspiration was under two years old and the male to female ratio was 2 to 1. The most common site of foreign body aspiration was the esophagus and the stomach, followed by the respiratory tract. In airways, the right and left main bronchus were the most common site for foreign body aspiration and were accompanied by the highest mortality. The most common foreign body in the gastrointestinal tract and respiratory tract were coins and peanuts, respectively. Conclusion : The most common cause of accidents was trauma, followed by falls, burns, foreign body aspiration, and poisoning. The incidence of foreign body aspiration and poisoning is increasing in infants. In cases of foreign bodies in airways, proper management is needed because of the high mortality rate.

• Journal of Korean Society of Forest Science
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• v.79 no.2
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• pp.187-195
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• 1990

The following conclusions have been obtained with special reference to the walnut marketing system in Cheonwongun districts 1. The marketing channel of walnut in the producing areas was mainly depended on the individual selling by 89.58%. and sale through farmer's coops and forest owner's association by 10.42%, and share of walnut through fatmer's coops was 84.58%. 2. The market structure in assembling stage of walnut can be represented as oligopoly considering the market share of 86.26% derived by CR3 method. 3. Direct selling from producers to consumers would be recommendable to reduce marketing margin considering the 77.20% of sale's dependency on assembler-commisioner. 4. Two major reasons to follow the marketing channel of assembler-commissioner were the convieniency (45.00%) and dealing with small quantity of walnut (20.00%). Let the walnut producers follow the institutional marketing channels such as farmer's coops and forest owner s association, special actions including better conveniency, smaller quantity and the procedures should be improved. 5. Farmer's share of walnut was estimated as 54.93% and total marketing margin was 45.0% of which 36.70% destined to the retail stage. 6. The price index in November was the lowest(83.63) due to the flood and hunger sale and the index in April was the highest(115.74). To cope with the severe price fluctuation and to stabilize seasonal walnut price, sale's in advance, credit supply and provision of storage facilities must be considered in policy-making decision for forest farmers.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.535-544
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• 2021

Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

• Journal of Korean Society of Disaster and Security
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• v.12 no.2
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• pp.73-82
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• 2019

Recently, as the occurrence frequency of sudden floods due to climate change increased, the flood damage on riverside social infrastructures was extended so that there has been a threat of overflow. Therefore, a rapid prediction of potential flooding in riverside social infrastructure is necessary for administrators. However, most current flood forecasting models including hydraulic model have limitations which are the high accuracy of numerical results but longer simulation time. To alleviate such limitation, data driven models using artificial neural network have been widely used. However, there is a limitation that the existing models can not consider the time-series parameters. In this study the water surface elevation of the Hangang River bridge was predicted using the NARX model considering the time-series parameter. And the results of the ANN and RNN models are compared with the NARX model to determine the suitability of NARX model. Using the 10-year hydrological data from 2009 to 2018, 70% of the hydrological data were used for learning and 15% was used for testing and evaluation respectively. As a result of predicting the water surface elevation after 3 hours from the Hangang River bridge in 2018, the ANN, RNN and NARX models for RMSE were 0.20 m, 0.11 m, and 0.09 m, respectively, and 0.12 m, 0.06 m, and 0.05 m for MAE, and 1.56 m, 0.55 m and 0.10 m for peak errors respectively. By analyzing the error of the prediction results considering the time-series parameters, the NARX model is most suitable for predicting water surface elevation. This is because the NARX model can learn the trend of the time series data and also can derive the accurate prediction value even in the high water surface elevation prediction by using the hyperbolic tangent and Rectified Linear Unit function as an activation function. However, the NARX model has a limit to generate a vanishing gradient as the sequence length becomes longer. In the future, the accuracy of the water surface elevation prediction will be examined by using the LSTM model.