• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.882-885
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• 2014

최근, 기후변화에 의해 가뭄 및 홍수의 발생빈도 및 지속시간이 길어지고, 하천유량감소 및 연도별 편차가 증대하고 있다. 이러한 추세는 지속될 것으로 예상되며, 수자원의 관리는 수량, 수질 등을 종합적으로 분석하고 관리하는 쪽으로 변화하고 있다. 이러한 수자원의 관리를 위해서는 수자원관련 기초자료의 취득, 저장, 처리, 활용 등이 유기적으로 이루어져야 하는데, 이를 전자적으로 수행하는 것을 홍수경보시스템이라 하고, 이는 수문관측시스템과 경보방송시스템으로 구분할 수 있다. 수문관측시스템은 댐 유역의 수문현황을 관측할 수 있는 수문관측소(수위, 강우량, 수질)에서 계측된 수문관측자료를 인공위성 등 다양한 통신망을 통하여 댐 사무소에 위치한 중앙감시제어시스템에 전송되고, 수집된 수문관측자료는 1분 단위로 K-water본사에 전송된다. 전송된 자료를 활용하여 각종 수문분석 및 표출을 통해 대내 외에 제공되어 댐에 대한 이 치수의 의사결정을 지원한다. 본 논문에서는 수문관측시스템 구축방안에 대해서 알아본다.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2002년도 학술발표회 발표논문집
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• pp.261-264
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• 2002

Yi-dong experimental basin is operated for research on the rural basin characteristics and accumulation of a long term data by hydrological observation equipments. It is basin area 9,440ha, length 14.4km and slope 0.67%. Hydrological observation network is constructed of rainfall meter 4points, reservoir storage level 3points and river water level 2points.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2003년도 학술발표회논문집(2)
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• pp.611-614
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• 2003

Yi-dong experimental basin is operated for research on the rural basin characteristics and accumulation of a long term data by hydrological observation equipments. It is basin area 9,440ha, length 14.4km and slope 0.67%. Hydrological observation network is constructed of rainfall meter 4points, reservoir storage level 3points and river water level 2points.

• 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.

• 한국수자원학회논문집
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• 제54권11호
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• pp.891-901
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• 2021

본 연구에서는 월 단위 수문순환 관측자료를 이용하여 수문순환 건전성 평가 기법을 개발하였다. 경안천 유역을 다섯 개의 소유역으로 나누고 무강우 일수, 무 강우 일수 변동폭, 일 30 mm 이상 강우 횟수, 일 30 mm 이상 강우 횟수 변동폭, 평균하천수위, 평균하천수위 변동폭, 평균지하수위, 평균지하수위 변동폭으로 8가지 수문순환 건전성 평가 기준을 정하였다. 관측값을 표준화를 하고 엔트로피 방법을 이용하여 각 소유역 별 가중치를 산정하였다. 산정된 가중치 값으로 TOPSIS를 이용하여 수문순환 건전성 평가 지수를 산정하였다. 연구결과 경안천 상류는 11 ~ 1월, 경안천 수위표는 2 ~ 4월, 곤지암천은 4 ~ 5월, 경안천 하류는 11 ~ 2월에 수문순환 건전성 불안전한 것으로 나왔다. 본 연구에서 개발 기법은 수문순환 건전성을 관리 방안을 수립하는 정책적 결정에 있어 정량적 근거가 될 수 있을 것으로 기대된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.179-179
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• 2015

Citarum River is one of the important river in West Java, Indonesia. During the rainy season, flood happens almost every year in Upper Citarum Watershed, hence, it is necessary to establish the countermeasure in order to prevent and mitigate flood damages. Since the lack of hydrological data for the modelling is common problem in this area, it is difficult to prepare the countermeasures. Therefore, we used Rainfall-Runoff-Inundation (RRI) Model developed by Sayama et al. (2010) as the hydrological and inundation modelling for evaluating the inundation case happened in Upper Citarum Watershed, West Java, Indonesia and the satellite based information such as rainfall (GSMaP), landuse and so on instead of the limited hydrological data. In addition, 3 arc-second HydroSHEDS Digital Elevation Model (DEM) is used. To verify the model, the observed data of Nanjung water stage gauging station and the daily observation data are used. Simulated inundation areas are compared with the flood extent figure from Upper Citarum Basin Flood Management Project (UCBFM).

• 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.

• 한국농공학회논문집
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• 제48권2호
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• pp.37-43
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• 2006

A hydrological drought index, MSWSI (Modified Surface Water Supply Index) was suggested based on SWSI (Surface Water Supply Index). With the available data of spatially distributed observation station of precipitation, dam storage, stream water level and natural groundwater level, South Korea was divided into 32 regions. This was conducted to represent the calculated index as a spatially distributed information. Monthly MSWSI was evaluated for the period of 1974 and 2001. It is necessary to compare this result with PDSI (Palmer Drought Severity Index) and SPI (Standard Precipitation Index), and check the applicability of the suggested index in our hydrological drought situation.

• 한국관개배수논문집
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• 제14권2호
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• pp.225-235
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• 2007

The shape of streamflow hydrograph during the early period of spring is very much controlled by the area and depth of snow cover especially in mountainous area. When we simulate the streamfolw of a watershed snowmelt, we need some information for snow cover extent and depth distribution as parameters and input data in the hydrological models. The purpose of this study is to suggest an extraction method of snow cover area and snow depth distribution using Terra MODIS image. Snow cover extent for South Korea was extracted for the period of December 2000 and April 2006. For the snow cover area, the snow depth was interpolated using the snow depth data from 69 meteorological observation stations. With these data, it is necessary to run a hydrological model considering the snow-related data and compare the simulated streamflow with the observed data and check the applicability for the snowmelt simulation.

• 한국환경과학회지
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• 제20권12호
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• pp.1635-1646
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• 2011

This April 5th dam and Hwanggang dam, which are located in Imjin river, North Korea, become the main causes of water shortages and damages in Imjin river downstream. April 5th dam is assumed a small or medium-sized dam, its total storage volume reaches about 88 million $m^3$. And Hwanggang dam, multi-purposed dam of total storage volume approximately 0.3 billion $m^3$ to 0.4 billion $m^3$ is used as source of residental or industrial water in Gaeseong Industrial Complex. North Korea, which has April 5th dam and Hwanggang dam in Imjin river, manages water of approximately 0.39 billion $m^3$ to 0.49 billion $m^3$ directly. As water is storaged or discharged through dam, it causes a severe damage to areas in Yeoncheon-gun and Paju city, South Korea. Therefore, this study intends to analyze and estimate runoff through dam construction by using hydrological observation data and artificial data such as service water supply and agricultural water in Imjin river, water shortage and damage correctly.