• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.373-373
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• 2021

Rainfall forecasting is an important issue that is applied in many areas, such as agriculture, flood warning, and water resources management. In this context, this study proposed a statistical and machine learning-based forecasting model for monthly rainfall. The Bayesian Gaussian process was chosen to optimize the hyperparameters of the Stacked Long Short-term memory (SLSTM) model. The proposed SLSTM model was applied for predicting monthly precipitation of Seoul station, South Korea. Data were retrieved from the Korea Meteorological Administration (KMA) in the period between 1960 and 2019. Four schemes were examined in this study: (i) prediction with only rainfall; (ii) with deseasonalized rainfall; (iii) with rainfall and minimum temperature; (iv) with deseasonalized rainfall and minimum temperature. The error of predicted rainfall based on the root mean squared error (RMSE), 16-17 mm, is relatively small compared with the average monthly rainfall at Seoul station is 117mm. The results showed scheme (iv) gives the best prediction result. Therefore, this approach is more straightforward than the hydrological and hydraulic models, which request much more input data. The result indicated that a deep learning network could be applied successfully in the hydrology field. Overall, the proposed method is promising, given a good solution for rainfall prediction.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.95-95
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• 2020

Urban flooding occurs in the form of internal-water inundation on roads and lowlands due to heavy rainfall. Unlike in the case of rivers, inundation in urban areas there is lacking in research on predicting and warning through measurement data. In order to analyze urban flood patterns and prevent damage, it is necessary to analyze flooding measurement data for various rainfalls. In this study, the pattern of urban flooding caused by rainfall was analyzed by utilizing the urban flooding measuring sensor, which is being test-run in the flood prone zone for urban flooding management. For analysis, 2019 rainfall data, surface water depth data, and water level data of a street inlet (storm water pipeline) were used. The analysis showed that the amount of rainfall that causes flooding in the target area was identified, and the timing of inundation varies depending on the rainfall pattern. The results of the analysis can be used as verification data for the urban inundation limit rainfall under development. In addition, by using rainfall intensity and rainfall patterns that affect the flooding, it can be used as data for establishing rainfall criteria of urban flooding and predicting that may occur in the future.

• 한국방재학회 논문집
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• 제4권1호
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• pp.25-31
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• 2004

강우침투는 철도성토사면의 불안정성을 유발하는 요인으로 작용하여 때때로 파괴의 결과로 나타나게 된다. 강우량과 철도성토사면 안정성과의 기본적인 상관성이 강우에 의한 성토사면의 불안정성을 분석하여 제안되었다. 사면내부로의 강우침투속도를 규명하기 위하여 실내시험을 수행하였으며, 강우침투실험결과에서 강우침투량은 강우침투속도가 사면경사에 의해 지배되기 때문에 저수지 등의 경우에 있어서의 침투와는 상당히 다르다는 것을 알 수 있었다. 이와 같은 견과에 근거하여 강우의 경계조건을 변화시켜 적용한 후, 다양한 수치해석을 수행하였다. 이를 통해 강우시 철도 성토사면의 전단강도, 포화도 그리고 간극수압의 변화를 예측할 수 있었으며, 철도사면의 안전율이 강우량-강우지수의 함수로서 표현될 수 있었다. 따라서 이 강우지수가 강우시 열차운전규제기준을 설정하기 위해 유용함을 밝혔다.

• 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.

• 물과 미래
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• 제29권3호
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• pp.187-195
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• 1996

남한강 상류 평창강 유역을 대상으로 기상레이더 자료와 지상강우량 자료를 이용한 시우량 곡면 예측 방법을 연구하였다. 레이더 자료의 이용시에 필요한 비정상 에코와 지형에코의 제거, 강우에 의한 감쇄 효과의 보정 방법, 레이더 반사도 Z와 강우강도 R의 관계, 등을 검토분석하였다. 보정된 레이더 반사도 자료를 레이더 우량곡면으로 변환하고, 그 결과와 지상강우량 자료를 이용하여 시우량곡면을 합성하였다. 시우량곡면 예측을 위하여 상호상관 계수법을 이용한 강우장의 이동성과 유역 평균 레이더 강우강도의 시변성을 고려하였다. 이 예측방법을 합성된 시우량곡면 자료에 적용하여 3시간까지의 시우량곡면을 예측하고, 예측된 결과를 지상우량 및 합성우량 곡면과 비교하였다. 본 연구의 단시간 강우예측 방법은 보다 많은 자료를 이용한 검증과 강우장의 물리적 특성 및 지형을 고려한 방법으로의 보완이 필요한 것으로 사료되었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.16-16
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• 2011

Statistics of extreme rainfall play a vital role in engineering practice from the perspective of mitigation and protection of infrastructure and human life from flooding. While flood frequency assessments, based on river flood flow data are preferred, the analysis of rainfall data is often more convenient due to the finer spatial nature of rainfall recording networks, often with longer records, and potentially more easily transferable from site to site. The rainfall frequency analysis as a design tool has developed over the years in New Zealand from Seelye's daily rainfall frequency maps in 1947 to Thompson's web based tool in 2010. This paper will present a history of the development of New Zealand rainfall frequency analysis methods, and the details of the latest method, so that comparisons may in future be made with the development of Korean methods. One of the main findings in the development of methods was new knowledge on the distribution of New Zealand rainfall extremes. The High Intensity Rainfall Design System (HIRDS.V3) method (Thompson, 2011) is based upon a regional rainfall frequency analysis with the following assumptions: $\bullet$ An "index flood" rainfall regional frequency method, using the median annual maximum rainfall as the indexing variable. $\bullet$ A regional dimensionless growth curve based on the Generalised Extreme Value (GEV), and using goodness of fit test for the GEV, Gumbel (EV1), and Generalised Logistic (GLO) distributions. $\bullet$ Mapping of median annual maximum rainfall and parameters of the regional growth curves, using thin-plate smoothing splines, a $2km\times2km$ grid, L moments statistics, 10 durations from 10 minutes to 72 hours, and a maximum Average Recurrence Interval of 100 years.

• 한국수자원학회논문집
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• 제52권2호
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• pp.125-132
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• 2019

본 연구에서는 기존의 정량적인 강수량 정보를 제공하는 방식에서 벗어나 호우발생에 따른 생활환경의 변화에 끼치는 영향을 고려한 호우영향예보서비스의 필요성을 기반으로 호우위험영향도 평가가 가능한 호우재해 위험영향 매트릭스를 개발하고, 이를 통해 호우위험영향을 평가하는 방법을 제시하였다. 사당동 일대를 대상으로 실제 발생 호우사상(2011년 7월 27일)을 적용하였으며, 호우에 의한 침수로 영향을 받는 대상별(사람, 교통, 시설) 호우위험영향평가를 수행하였다. 이를 위해 1 km 격자기반으로 호우위험정도(Impact Level)를 산정하고, 침수심 결과를 조합하여 격자기반의 잠재호우위험영향(Potential Risk Impact)을 산정하였다. 여기에 강우발생가능성 Likelihood와의 조합을 통해 호우영향예보가 가능한 호우위험영향(Heavy Rainfall Risk Impact) 값을 산정하여 사당동 지역의 호우영향정도를 격자기반으로 4개의 등급으로 분석, 제시하였다.

• 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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.260-260
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• 2016

Soil erosion is a very serious problem from agricultural as well as environmental point of view. Various computer models have been used to estimate soil erosion and assess erosion control practice. Universal Soil loss equation (USLE) is a popular model which has been used in many countries around the world. Erosivity (USLE R-factor) is one of the USLE input parameters to reflect impacts of rainfall in computing soil loss. Value of R factor depends upon Energy (E) and maximum rainfall intensity of specific period ($I30_{max}$) of that rainfall event and thus can be calculated using higher temporal resolution rainfall data such as 10 minute interval. But 10 minute interval rainfall data may not be available in every part of the world. In that case we can use hourly rainfall data to compute this R factor. Maximum 60 minute rainfall ($I60_{max}$) can be used instead of maximum 30 minute rainfall ($I30_{max}$) as suggested by USLE manual. But the value of Average annual R factor computed using hourly rainfall data needs some correction factor so that it can be used in USLE model. The objective of our study are to derive relation between averages annual R factor values using 10 minute interval and hourly rainfall data and to determine correction coefficient for R factor using hourly Rainfall data.75 weather stations of Korea were selected for our study. Ten minute interval rainfall data for these stations were obtained from Korea Meteorological Administration (KMA) and these data were changed to hourly rainfall data. R factor and $I60_{max}$ obtained from hourly rainfall data were compared with R factor and $I30_{max}$ obtained from 10 minute interval data. Linear relation between Average annual R factor obtained from 10 minute interval rainfall and from hourly data was derived with $R^2=0.69$. Correction coefficient was developed for the R factor calculated using hourly rainfall data.. Similarly, the relation was obtained between event wise $I30_{max}$ and $I60_{max}$ with higher $R^2$ value of 0.91. Thus $I30_{max}$ can be estimated from I60max with higher accuracy and thus the hourly rainfall data can be used to determine R factor more precisely by multiplying Energy of each rainfall event with this corrected $I60_{max}$.