• 한국산업융합학회 논문집
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• 제2권2호
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• pp.51-59
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• 1999

This study aims at the development of the techniques for the rainfall forecasting in river basins by applying neural network theory and compared with results of Multivariate Model (MVM). This study forecasts rainfall and compares with a observed values in the San Chung gauging stations of Nakdong river basin for the rainfall forecasting of river basin by proposed Neural Network Model(NNM). For it, a multi-layer Neural Network is constructed to forecast rainfall. The neural network learns continuous-valued input and output data. The result of rainfall forecasting by the Neural Network Model is superior to the results of Multivariate Model for rainfall forecasting in the river basin. So I think that the Neural Network Model is able to be much more reliable in the rainfall forecasting.

• 한국지하수토양환경학회지:지하수토양환경
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• 제26권6호
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• pp.118-129
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• 2021

The sediment transportation caused by soil erosion due to rainfall-discharge in the large watershed scale plays critical role in human society. The relationship between rainfall-discharge-sediment transportation is depending on the start time of rainfall and end of rainfall but, the studies related with rainfall characteristics are insufficient. In this study, The Soil and Water Assession Tool (SWAT) model was used to study the relationship between rainfall-discharge-sediment transportation at the Sook river watershed which is monitored by the Ministry of Environment. To do this, first of all, the sensitivity analysis about model attributes was performed using monitored data. The accuracy analysis of SWAT model was conducted using the model's efficiency index (Nash and Sutcliffe model efficiency; NSE) and the coefficient of determination (R²). After that, it was studied what results could be obtained according to changes in rainfall timing and end points. In the result of discharge simulation, the modified rainfall values (sum of total rainfall starting time and end time) showed more high accuracy values (R²:0.90, NSE: 0.8) than original rainfall values (R²:0.76, NSE: 0.72). In the result of sediment transportation simulation, during calibration had more resonable results(R²:0.87, NSE: 0.86) than compared with original rainfall values (R²:0.44, NSE: 0.41). However, validation results of sediment transportation simulation showed low accuracy values compared with calibration results. This results maybe cause monitoring periods of sediment flow compared with discharge monitoring periods. Nevertheless, since rainfall characteristic plays critical rule in model results, continuous research on rainfall characteristic is needed.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.152-152
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• 2022

Only employing historical data limits the estimation of the full distribution of probable Tropical Cyclone (TC) risk due to the insufficiency of samples. Addressing this limitation, this study introduces a semi-physical TC rainfall model that produces spatially and temporally resolved TC rainfall data to improve TC risk assessments. The model combines a statistical-based track model based on the Markov renewal process to produce synthetic TC tracks, with a physics-based model that considers the interaction between TC and the atmospheric environment to estimate TC rainfall. The simulated data from the combined model are then fitted to a probability distribution function to compute the spatially heterogeneous risk brought by landfalling TCs. The methodology is employed in South Korea as a case study to be able to implement a country-scale-based vulnerability inspection from damaging TC impacts. Results show that the proposed model can produce TC tracks that do not only follow the spatial distribution of past TCs but also reveal new paths that could be utilized to consider events outside of what has been historically observed. The model is also found to be suitable for properly estimating the total rainfall induced by landfalling TCs across various points of interest within the study area. The simulated TC rainfall data enable us to reliably estimate extreme rainfall from higher return periods that are often overlooked when only the historical data is employed. In addition, the model can properly describe the distribution of rainfall extremes that show a heterogeneous pattern throughout the study area and that vary per return period. Overall, results show that the proposed approach can be a valuable tool in providing sufficient TC rainfall samples that could be an aid in improving TC risk assessment.

• 한국습지학회지
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• 제12권1호
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• pp.51-61
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• 2010

기후변화로 인하여 국지성 집중호우가 크게 늘어나고 그로인해 막대한 인적 및 물적 피해를 야기하고 있다. 따라서 강우의 시간적 공간적 특성을 파악하는 것이 중요하다고 할 수 있다. 본 연구에서는 레이다 강우를 이용하여 시공간적 변동성을 고려한 격자형 면적강우량을 산정하기 위하여 추계학적 방법인 칼만필터 기법을 이용하여 지상 강우 관측망과 레이다 강우 관측망을 조합하여 면적강우량을 산정하였다. 또한 전통적인 지상 강우량을 면적강우량으로 전환하는 기법인 Thiessen법, 역거리법, 크리깅 기법을 이용하여 면적강우량을 산정한 후 칼만필터 기법에 의해 보정된 면적 레이다 강우와 비교하였다. 그 결과, 칼만필터 기법에 의해 보정된 레이다 강우는 실제 강우 분포와 유사한 공간분포를 가지는 원시 레이다 강우 분포를 잘 재현하면서도 강우 체적은 우량계 자료의 체적과 유사하게 나타났다. 그리고 안성천 유역을 대상유역으로 선정하여 칼만필터 기법에 의해 보정된 레이다 강우를 물리적 기반의 분포형 모형인 $Vflo^{TM}$ 모형과 준분포형 모형인 ModClark 모형에 적용하여 홍수유출을 모의하였다. 그 결과, $Vflo^{TM}$ 모형은 첨두시간과 첨두치가 관측 수문곡선과 유사하게 모의되었으며 ModClark 모형은 총 유출체적에서 좋은 결과를 나타냈다. 그러나 매개변수 검증에서는 $Vflo^{TM}$ 모형이 ModClark 모형보다 관측 수문곡선을 잘 재현하였다. 이를 통해 지상강우와 레이더 강우를 적절하게 조합하여 정확도 높은 면적강우량을 산정하고 분포형 수문모형과 연계하여 홍수유출모의를 실시할 경우 충분한 적용성을 가지고 있음을 확인할 수 있었다.

• 대기
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• 제26권1호
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• pp.141-158
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• 2016

The objective of this study is to examine the impact of urban canopy and the horizontal resolution on simulated meteorological variables such as 10-m wind speed, 2-m temperature and precipitation using WRF model for a local, convective rainfall case. We performed four sensitivity tests by varying the use of urban canopy model (UCM) and the horizontal resolution, then compared the model results with observations of AWS network. The focus of our study is over the Seoul metropolitan area for a convective rainfall that occurred on 16 August 16 2015. The analysis shows that mean diurnal variation of temperature is better simulated by the model runs with UCM before the convective rainfall. However, after rainfall, model shows significant difference in air temperature among sensitivity tests depending on the simulated rainfall amount. The rainfall amount is significantly underestimated in 0.5 km resolution model run compared to 1.5 km resolution, particularly over the urban areas. This is due to earlier occurrence of light rainfall in 0.5 km resolution model. Earlier light rainfall in the afternoon eliminates convective instability significantly, which prevents occurrence of rainfall later in the evening. The use of UCM results in a higher maximum rainfall in the domain, which is due to higher temperature in model runs with urban canopy. Earlier occurrence of rainfall in 0.5 km resolution model is related to rapid growth of PBL. Enhanced mixing and higher temperature result in rapid growth of PBL, which provides more favorable conditions for convection in the 0.5 km resolution run with urban canopy. All sensitivity tests show dry bias, which also contributes to the occurrence of light precipitation throughout the simulation period.

• 한국농공학회논문집
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• 제61권2호
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• pp.63-74
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• 2019

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs). Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for construction of ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall), Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessen network, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that used all station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models that used point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The model performance for the ANNs model 2 in Chungju dam resulted in the $R^2$ value of 0.94, NSE of 0.94 $NSE_{ln}$ of 0.88 and PBIAS of -0.04 respectively. The model-2 predictions of Soyangriver Dam with the $R^2$ and NSE values greater than 0.94 were reasonably well agreed with the observations. The results of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2012년도 학술발표회
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• pp.976-976
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• 2012

The applicability of a distributed rainfall-runoff model for large river basin flood forecasts is analyzed by applying the model to the Nakdong River basin. The spatially explicit hydrologic model was constructed and calibrated by the several storm events. The assimilation of the large scale Nakdong River basin were conducted by calibrating the sub-basin channel outflow, dam discharge in the basin rainfall-runoff model. The applicability of automatic and semi-automatic calibration methods was analyzed for real time calibrations. Further an ensemble distributed rainfall runoff model has been developed to measure the runoff hydrograph generated for any temporally-spatially varied rainfall events, also the runoff of basin can be forecast at any location as well. The results of distributed rainfall-runoff model are very useful for flood managements on the large scale basins. That offer facile, realistic management method for the avoiding the potential flooding impacts and provide a reference for the construct and developing of flood control facilities.

• 상하수도학회지
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• 제36권4호
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• pp.229-237
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• 2022

The sewer capacity design have been based on the Huff model or the rational equation in South Korea and often failed to determine optimal capacity, resulting in frequent urban flooding or over-sizing. A time distribution of rainfall (i.e., Huff or ABM method) could be used instead of a rainfall hyetograph obtained from statistical analysis of previous rainfalls. In this study, the Huff method and the ABM method, which predict the time distribution of rain intensity, which are widely used to calculate sewage pipe drainage capacity using the SWMM, were compared with the standard rainfall intensity hyetograph of Seoul. If the rainfall duration was 30 minutes to 180 minutes, the rainfall intensity value calculated by the Huff model tended to be less than the rainfall intensity value of the standard rainfall intensity in the initial 5-10 minutes. As a result, more than 10% to 30% of under-design would be made. In addition, the rainfall intensity value calculated by the Huff model from the section excluding the initial 5-10 minutes of rainfall to the rainfall duration was calculated larger than the value using the standard rainfall intensity equation, which would result in an over-design of 10% to 30%. In the case of a relatively long rainfall duration of 360 minutes (6 hours) to 1,440 minutes (24 hours), it showed an lower rainfall intensity of 60 to 90% in the early stages of rainfall, but the problem of under-design had been solved as the rainfall duration time had elapsed. On the other hand, in the alternating block method (ABM) method, it was found that the rainfall intensity at the entire period at each assumed rainfall duration accurately matched the standard rainfall intensity hyetograph of Seoul.

• 한국농공학회지
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• 제24권1호
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• pp.63-72
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• 1982

To maintain an optimum condition for the plant growth on upland soil, the irrigation planning after the natural rainfall should be given enormous considerations on the rainfall effectiveness. This study has been intended to develop the computer model for estimating the effec- tiveness of the rainfall. The computer model should also estimated the infiltration due to the rainfall and the soil moisture deficiency at the root zone of the plant. For this purpose, the experiments of infiltration using rainfall simulator and the observations of the change of soil moisture content before and after rainfall were carried out. Needed input data for the developed model include final infiltration capacity and field capacity of the soil, porosity of the top soil, root depth of the plant, rainfall intensity and duration, and the Horton's decay coefficient. Among the needed input data for the developed model, final infiltration capacity and Horton's decay coefficient were determined by the experiments of infiltration. And from the result of the experiments, it is found that there is a great correlation between initial infiltration capacity and initial moisture content. And it is also found that the infiltration due to rainfall can be estimated with the Horton's equation. The developed model was tested by the experimental data with two rainfall intensities. Tests were conducted on the different root depths at each rainfall. Observed and estimated effective rainfalls were found to have great correlation. The result of the experiments showed that the effectiveness of the rainfall were 100%, so the comparisons were conducted by the comsumption rates of infiltration at each depth. The developed model can be also used for estimating the deficiency of rainfall, if the rainfall is not sufficient to the needed soil moisture. But, test was not carried out.

• 한국수자원학회논문집
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• 제43권6호
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• pp.533-541
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• 2010

강우-유출모형에 의해서 유역내 강우로부터 직접 유출량을 산출하는 것은 홍수량 예측에 기초가 된다. 직접 유출량은 강우-유출모형에 의해서 초과우량 또는 유효우량으로부터 산출된다. 시간별 초과우량은 시간별 총 강우에서 강우의 손실량을 제하여 산출한다. 이 손실량은 강우-유출모형 내 여러 손실 중에 비중이 큰 침투 손실량과 같도록 취급할 수 있다. 여기서 초과우량 또는 유효우량 산출을 위해서 실용적으로 간편한 $\Phi$지수법, W지수법 또는 이의 수정법이 적용되어 왔다. 본 연구에서는 한 유역 내 강우 손실의 시간적 변화는 잘 알려진 Horton 침투 과정으로 간주하여 Horton 침투모형의 매개변수 값이 주어진 경우에 시간 단위별 침투손실 및 초과우량을 산출하는 절차와 적용 원칙을 제시하고 적용결과를 $\Phi$지수 방법의 적용결과에 비교하였다. 본 연구에서 산출한 강우사상에서 시간 단위의 Horton 침투량 값은 시간에 따라 지수적으로 감쇠되는 Horton 모형의 침투 과정을 잘 보여 준다.