• 한국토양비료학회지
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• 제44권3호
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• pp.337-343
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• 2011

A particular empirical equation for rainfall kinetic energy is needed to compute rainfall erosivity, calculated by the annual sum of the product of total rainfall energy and maximum 30-min rainfall intensity. If rainfall kinetic energy equation was different, rainfall erosivity will be produced differently. However, the previous studies in Korea had little concern about rainfall kinetic energy equation and it was not clear which rainfall kinetic energy is suitable for Korea. The purpose of this study is to analyze and evaluate the difference of the rainfall erosivity based on different rainfall kinetic energy equations obtained from previous studies. This study introduced new rainfall erosivity factors based on rainfall kinetic energy equation of Noe and Kwon (1984) that is only regression model developed in Korea. Data of annual rainfall erosivity for 21 weather stations in 1980~1999 were used in this study. The result showed that rainfall erosivity factors by the previous equations had been about 10~20% overestimated than rainfall erosivity by Noe and Kwon (1984)'s equation in Korea.

• 한국농공학회논문집
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• 제49권1호
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• pp.3-13
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• 2007

In this study, spatial characteristics of rainfall in Imha basin were investigated by cross-correlation analysis among rainfall gaging stations and rainfall-runoff analysis used in HEC-HMS model for analysis of influence on observed rainfall. The Kriging technique was applied to rain(all analysis in Imha basin to reflect spatial characteristics of regional rainfall. Their results are compared to rainfall-runoff data with spatially distributed rainfall data as well as the classical thiessen method. The results by kriging technique approached by geostatistical method could reflect spatial characteristics of regional rainfall properly in Imha basin.

• 대기
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• 제26권4호
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• pp.495-508
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• 2016

In order to determine the prediction possibility of heavy rainfall, a variety of analyses was conducted by using three-dimensional data obtained from Korea Local Analysis and Prediction System (KLAPS) re-analysis data. Strong moisture convergence occurring around the time of the heavy rainfall is consistent with the results of previous studies on such continuous production. Heavy rainfall occurred in the cloud system with a thick convective clouds. The moisture convergence, temperature and potential temperature advection showed increase into the heavy rainfall occurrence area. The distribution of integrated liquid water content tended to decrease as rainfall increased and was characterized by accelerated convective instability along with increased buoyant energy. In addition, changes were noted in the various characteristics of instability indices such as K-index (KI), Showalter Stability Index (SSI), and lifted index (LI). The meteorological variables used in the analysis showed clear increases or decreases according to the changes in rainfall amount. These rapid changes as well as the meteorological variables changes are attributed to the surrounding and meteorological conditions. Thus, we verified that heavy rainfall can be predicted according to such increase, decrease, or changes. This study focused on quantitative values and change characteristics of diagnostic variables calculated by using numerical models rather than by focusing on synoptic analysis at the time of the heavy rainfall occurrence, thereby utilizing them as prognostic variables in the study of the predictability of heavy rainfall. These results can contribute to the identification of production and development mechanisms of heavy rainfall and can be used in applied research for prediction of such precipitation. In the analysis of various case studies of heavy rainfall in the future, our study result can be utilized to show the development of the prediction of severe weather.

• 대한토목학회논문집
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• 제28권1B호
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• pp.1-9
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• 2008

소양강댐 유역의 관측유입량과 융설 모의의 포함 유무에 따른 모의 결과를 비교함으로써 적설 및 융설 모형의 필요성을 분석하였다. 사용한 융설 모형은 Sugawara 등의 개념적 융설 모형이고, 강우-유출 모형은 NWS-PC를 사용하였다. 모형의 매개변수는 다단계 자동보정법에 의해 추정하였고, 각 단계별로 SCE-UA 알고리즘에 의해 최적화되었다. 매개변수 추정시와 검증 모의에서 RMSE, PBIAS, NSE, PME 통계량은 융설을 포함한 모의가 그렇지 않은 모의보다 좋은 결과를 나타내었다. 소양강댐의 관측유입량은 약 두 달 이상의 자기상관성을 나타내었고, 융설을 포함하지 않은 경우에 모의된 유량시계열은 20일 정도의 자기상관성을 나타내었다. 융설을 포함한 경우의 모의유량 시계열은 관측 유량시계열과 유사하게 약 두 달 이상의 자기상관성을 나타내었다. 이와 같은 결과로 소양강댐 유역의 강우-유출 모의시 적설 및 융설 모형을 포함하여야 모형의 정확성을 향상시킬 수 있다.

• 한국산학기술학회논문지
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• 제20권12호
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• pp.828-835
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• 2019

인공강우장치는 실내실험 기반의 모형실험 데이터를 생성하는 연구도구로 널리 이용되고 있다. 다양한 연구에 인공강우장치가 이용되고 있음에도 불구하고 대부분의 연구에서 강우분포의 균질성에 대한 논의는 등한시되고 있다. 다양한 강우특성이 반영된 급경사지 붕괴 모의실험을 위해서는 저강도에서 고강도까지 강우를 모사할 수 있는 강우장치가 필수적이며 실험의 신뢰성을 확보하기 위해서라도 강우분포의 균질성은 확보되어야 한다. 본 연구에서는 급경사지 붕괴모의실험의 주요설비인 인공강우장치의 최대 강우강도 130mm/hr 내에서 10mm/hr 단위 제어를 목표로 하며, 균등계수 80% 이상 확보하고자 하였다. 이를 위해 노즐타입, 크기, 위치 및 펌프압력에 따른 다양한 조건하에서 강우실험을 수행하였다. 실험결과 노즐형태는 원형노즐, 크기는 1.9mm와 1.4mm가 적합한 것으로 분석되었고 적정 펌프압력은 3~6kg/㎠으로 분석되었다. 다양한 강우강도를 재현하기 위해 노즐수는 2, 3, 5개, 펌프압력은 3, 4, 5, 6kg/cm2로 조건을 달리하여 실험을 수행하였다. 펌프압력이 증가함에 따라 강우강도는 선형적으로 증가하는 경향을 보였다. 실험결과를 바탕으로 펌프압력, 노즐형태 및 노즐수를 변수로 하는 강우제어 매뉴얼을 작성하였다. 또한 검증실험을 수행하여 목표 강우강도 대비 오차범위 ±3.1%, 균등계수는 평균 86.8%로 균질한 강우분포를 보였다.

• 물과 미래
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• 제19권4호
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• pp.347-354
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• 1986

강우와 유역특성으로부터 홍수유출을 예측하기 위해서 Nash 모델의 매개변수 N, K가 결정될 필요가 있다. 또한 순간단위도의 매개변수 N,K가 적율법에 의해서 유도되어야 한다. 강우특성으로부터 유도되는 Nash 모델의 매개변수는 낙동강에 위치한 위천유역에 적용하였다. 선형이론에 의한 순간단위도의 유도에 있어서 강우특성으로서 저장상수 K는 매우 높은 상관계수 0.97을 가진 K=1.327 $·$·$·$·$·$을 채택하였다. 이와 같은 강우특성으로서 Gamma 함수 N는 매우 높은 상관계수인 0.97로서 N=0.032$·$·$·$·$·$으로 나타났다. 검정결과 Nash 모델의 순간단위도와 이로 인한 홍수유출은 강우특성으로부터 예측될 수 있음이 입증되었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.183-183
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• 2021

Deep learning methods and their application have become an essential part of prediction and modeling in water-related research areas, including hydrological processes, climate change, etc. It is known that application of deep learning leads to high availability of data sources in hydrology, which shows its usefulness in analysis of precipitation, runoff, groundwater level, evapotranspiration, and so on. However, there is still a limitation on microclimate analysis and prediction with deep learning methods because of deficiency of gauge-based data and shortcomings of existing technologies. In this study, a real-time rainfall prediction model was developed from a sky image data set with convolutional neural networks (CNNs). These daily image data were collected at Chung-Ang University and Korea University. For high accuracy of the proposed model, it considers data classification, image processing, ratio adjustment of no-rain data. Rainfall prediction data were compared with minutely rainfall data at rain gauge stations close to image sensors. It indicates that the proposed model could offer an interpolation of current rainfall observation system and have large potential to fill an observation gap. Information from small-scaled areas leads to advance in accurate weather forecasting and hydrological modeling at a micro scale.

• 물과 미래
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• 제14권4호
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• pp.27-34
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• 1981

The design flow of the urban strom drainage systems has been assessed largely on a basis of empirical relations between rainfall and runoff, and the rational formula has been widely used for the cities in our country. In order to estimate it more accurately, the urban runoff simulation model based on the RRl method has been developed and applied to the sample basin in this study. The rainfall hyetograph of the design stromfor the design flow has been obtained by the determination of the total rainfall and the temporal distributions of that rainfall. The total rainfall has been assessed from the empirical formula of rainfall intensity and the temporal distribution of that rainfall determined on the basis of Huff's method from the historical rainfall data of the basin. The virtual inflow hydrograph to each inlet of the basin has been constructed by computing the series of discharges in each time increment, using design strom hyetograph and time-area diagram. The actual runoff hydrograph at the basin outlet has been computed from the virtual inflow hydrographs by developing a relations between discharge and storage for the watershed. The discharge data for verification of the simulated runoff hydrograph are not available in the sample basin and so the sensitivity analysis of the simulation model has not been possible. The peak discharge for the design of drainage systems has been estimated from the computed runoff hydrograph at the basin outlet and compared to thatl obtained form the rational formula.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.1147-1151
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• 2009

In this study, we address the problem of producing probability forecasts of summer seasonal rainfall, on the basis of Hindcast experiments from a ensemble of GCMs(cwb, gcps, gdaps, metri, msc_gem, msc_gm2, msc_gm3, msc_sef and ncep). An advanced Hierarchical Bayesian weighting scheme is developed and used to combine nine GCMs seasonal hindcast ensembles. Hindcast period is 23 years from 1981 to 2003. The simplest approach for combining GCM forecasts is to weight each model equally, and this approach is referred to as pooled ensemble. This study proposes a more complex approach which weights the models spatially and seasonally based on past model performance for rainfall. The Bayesian approach to multi-model combination of GCMs determines the relative weights of each GCM with climatology as the prior. The weights are chosen to maximize the likelihood score of the posterior probabilities. The individual GCM ensembles, simple poolings of three and six models, and the optimally combined multimodel ensemble are compared.

• 한국수자원학회논문집
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• 제44권3호
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• pp.221-230
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• 2011

최근 우리나라뿐만 아니라 전 세계적으로 기후변화에 따른 국지성 호우의 증가로 피해가 증가하고 있고 그에 따른 대책으로 단기예보의 중요성이 높아지고 있다. 우리나라의 기상청에서는 전구 모형인 GDAPS와 지역 모델인 RDAPS를 이용하여 정량적 예보인 수치 예보를 하고 있다. RDAPS 모델을 이용하여 생성된 자료는 3시간의 누적 강수량으로 48시간에 대한 예측 자료를 12시간 간격으로 00UTC와 12UTC를 생성한다. 본 연구에서는 2005년의 RDAPS의 결과를 9가지의 경우에 대하여 일강수량으로 변환하였으며, 금강유역을 대상으로 면적평균강수량 (MAP)을 산정하였다. 또한, 기상청 강우관측소의 관측강우량과 절대상대오차평균 (AARE)을 산정하여 가장 정확한 변환의 방법을 제시하고 적용성을 검토하였다.