• 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.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2004년도 춘계학술대회 논문집
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• pp.241-246
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• 2004

본 연구는 강우에 기인한 연안역의 토사 및 영양염류 유출에 관한 현지관측과 대안[( 沖蠅石垣島 ) 오끼나와 이시가키섬]이며, 이를 통한 유출지형분석, 강우강도ㆍ조석과의 영향, 유출입자의 특성(탁도, 임도, 영양염류) 등을 확인하였다. 연안부의 토사 유출과 영양염류의 농도는 강우강도와 조수간만의 시간적 변화에 따라 지역적 차이를 보였으며, 하천유역 주변 토지 이용형태와 주변 식생의 분포비율에 따라 변화되어지고 있음을 확인할 수 있었다.

• 한국항해항만학회지
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• 제29권1호
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• pp.113-118
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• 2005

본 연구는 강우에 기인한 연안역의 토사 및 영양염류 유출에 관한 현지관측과 대안[오끼나와 이시가키섬]이며, 이론 통한 유출지형분석 강우강도$\cdot$조석과의 영향, 유출입자의 특성(탁도, 입도, 영양염류) 등을 확인하였다. 연안부의 토사 유출과 영양 염류의 농도는 강우강도와 조수간만의 시간적 변화에 따라 지역적 차이를 보였으며, 하천유역 주변 토지 이용형태와 주변 식생의 분포비율에 따라 변화되어지고 있음을 확인할 수 있었다.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2003년도 학술발표논문집
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• pp.427-430
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• 2003

Yi-dong experimental site is operated for research on the rural basin characteristics and accumulation of a long term data by hydrological observation equipments. This basin area is 9,300ha, length 14.4km and slope 0.67%. Hydrological observation network has 3 rainfall meter3, 3 reservoir storage levels and 2 river water levels.

• 통합자연과학논문집
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• 제4권3호
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• pp.229-237
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• 2011

Today they use a weather radar with spatially high resolution in predicting rainfall intensity and utilizing the information for super short-range forecast in order to make predictions of such severe meteorological phenomena as heavy rainfall and snow. For a weather radar, they use the Z-R relation between the reflectivity factor(Z) and rainfall intensity(R) by rainfall particles in the atmosphere in order to estimate intensity. Most used among the various Z-R relation is $Z=200R^{1.6}$ applied to stratiform rain. It's also used to estimate basic rainfall intensity of a weather radar run by the weather center. This study set out to compare rainfall intensity between the reflectivity of a weather radar and the ground rainfall of ASOS(Automatic Surface Observation System) by analyzing many different cases of heavy rain, analyze the errors of different weather radars and identify their problems, and investigate their applicability to nowcasting in case of severe weather.

• 한국농공학회논문집
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• 제59권3호
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• 한국농공학회논문집
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• 제63권6호
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• pp.49-60
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• 2021

BCSA (Bias-Correction and Stochastic Analog) is a statistical downscaling technique designed to effectively correct the systematic errors of GCM (General Circulation Model) output and reproduce basic statistics and spatial variability of the observed precipitation filed. In this study, the applicability of BCSA was evaluated using the ASOS observation data over South Korea, which belongs to the monsoon climatic zone with large spatial variability of rainfall and different rainfall characteristics. The results presented the reproducibility of temporal and spatial variability of daily precipitation in various manners. As a result of comparing the spatial correlation with the observation data, it was found that the reproducibility of various climate indices including the average spatial correlation (variability) of rainfall events in South Korea was superior to the raw GCM output. In addition, the needs of future related studies to improve BCSA, such as supplementing algorithms to reduce calculation time, enhancing reproducibility of temporal rainfall patterns, and evaluating applicability to other meteorological factors, were pointed out. The results of this study can be used as the logical background for applying BCSA for reproducing spatial details of the rainfall characteristic over the Korean Peninsula.

• 대한토목학회논문집
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• 제38권2호
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• pp.227-235
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• 2018

본 연구에서는 차량용 레인센서를 이용하여 고해상도의 강우관측을 위한 관계식을 개발하였다. 차량용 레인센서는 8개의 채널로 이루어져 있으며, 각 채널은 강우발생시 차량의 전면유리창에 내리는 우적량을 감지하여 센서시그널을 생성하는데, 강우량이 높을수록 센서시그널은 낮은 값으로 형성된다. 레인센서에서 생성되는 센서시그널의 이러한 특징을 이용하여 관계식을 개발하였다. 특정강우를 발생시키기 위하여 인공강우 발생장치를 제작하였으며, 인공강우발생장치에서 분사되는 강우량의 변화에 따른 센서시그널의 변화 값을 분석하였다. 이 중 민감도 분석을 통해 다양한 강우량을 잘 반영하는 최적의 센서 채널을 선정하였다. 선정된 채널을 이용하여 5분 단위 센서시그널를 생성하였고 생성된 5분 단위 센서시그널의 대표 값을 평균, 25분위, 50분위, 75분위로 설정하여 관계식을 구축하였다. 구축된 관계식을 이용하여 실강우 데이터에 적용하여 강우량 값을 환산하였고, 환산된 강우량은 지상강우관측소에서 관측된 강우량 값과의 비교를 통해 관계식의 신뢰도를 검증하였다. 검증결과 데이터의 이상치가 발견되어 관계식의 신뢰도는 다소 떨어졌지만, 해당 잔차 범위의 실험 데이터가 부족한 것으로 판단되었다. 개발된 관계식을 실강우에 적용시켜 강우량 값을 환산한 하였고, 신뢰도 검증을 위해 동시간에 관측된 지상강우 관측 장비에서 생성된 강우량 값과 비교를 하였고 관측 결과 레인센서는 0.5mm 이하의 미세한 강우량까지 측정하였고 평균 관측 오차는 0.36mm로 나타났다.

• 한국안전학회지
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• 제37권6호
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• pp.148-157
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• 2022

Every year, particularly during the monsoon rainy season, landslides at the Chuncheon province of South Korea cause tremendous damage to lives, properties, and infrastructures. More so, the high rainfall intensity and long rainfall days that occurred in 2020 have increased the water content in the soil, thereby increasing the chances of landslide occurrences. Besides this, the rainfall thresholds and characteristics responsible for the initiation of landslides in this region have not been properly identified. Therefore, this paper addresses the rainfall thresholds responsible for the initiation of landslides at Chuncheon from a regional perspective. Using data obtained from rainfall measurements taken from 2002 to 2011, we identify a threshold relationship between rainfall intensity and rainfall duration for the initiation of landslides. In addition, we identify the relationship between the rainfall intensity using a 3-day, 7-day, and 10-day antecedent rainfall observation. Specifically, we estimate the rainfall data at 8 sites where debris flow occurred in 2011 by kriging. Following this, the estimated data are used to construct the relationship between the intensity (I), duration (D), and frequency (F) of rainfall. The results of the intensity-duration-frequency (IDF) analysis show that landslides will occur under a rainfall frequency below a 2-year return period at two areas in Chuncheon. These results will be effectively used to design structures that can prevent the occurrence of landslides in the future.

• 대한토목학회논문집
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• 제34권3호
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• pp.773-784
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• 2014

본 연구는 우리나라의 극한강우와 극한홍수를 모의하기 위한 MBLRP 포아송 클러스터 강우생성모형의 적용성을 평가하였다. 국내 61개의 기상청 지상기상관측시스템의 강우량 관측지점에 대하여 고립입자 군집화 최적화(ISPSO) 기법을 적용하여 모형의 매개변수를 추정하고, 추정된 매개변수를 바탕으로 각 강우관측지점에서 100년치의 가상 강우시계열을 생성하였다. 생성된 강우시계열을 이용하여 확률강우량 및 확률홍수량을 산정하고 이 값들을 관측치에 근거하여 산정된 값들과 비교하였다. 비교 결과, 모형에 의한 확률강우량은 관측치보다 평균적으로 20~42% 작았으며, 강우의 재현기간이 증가할수록 과소산정되는 정도가 증가하였다. 확률홍수량의 경우, 모형에 의한 값이 관측치에 근거한 값보다 31%에서 50% 작았으며, 이 과소산정량은 홍수의 재현기간의 증가 및 유역의 불투수도의 증가와 함께 증가하였다.