• 제목/요약/키워드: GLCF

검색결과 4건 처리시간 0.018초

SRTM(Shuttle Radar Topography Mission)의 정확성 평가 (Assessment of Accuracy of SRTM)

  • 유승환;남원호;최진용
    • 한국관개배수논문집
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    • 제14권1호
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    • pp.80-88
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    • 2007
  • The Shuttle Radar Topography Mission (SRTM) obtained elevation data on a near-global scale to generate the most complete high-resolution digital topographic database of Earth. SRTM consisted of a specially modified radar system that flew onboard the Space shuttle SRTM consisted of a specially modified radar system that flew onboard the Space Shuttle Endeavour during an 11-day mission on February 2000. Since 2004, in a GLCF (Global Land Cover Facility, http;//glcf.umiacs.umd.edu/) web-site, products of SRTM including 1Km and 90m resolutions for outside US and a 30m resolution for the US have been provided. This study is to assess the accuracy of SRTM-DEM in comparing with NGIS-DEM generated from NGIS digital topographic map(1:25,000) in Guem river watershed. For the Geum river watershed, SREM-DEM elevation ranged from 0 to 1,605m and NGIS-DEM ranged from 6 to 1,610m, and the average elevation of SRTM-DEM was 226.7m and 218.9m for NGIS-DEM, respectively. NGIS-DEM was subtracted from SRTM in three zones -Zone I (0~100m), Zone II (100~400m), Zone III (over 400m)- to estimate difference between SRTM and NGIS-DEM. As the results, the differences of these DEM were 5.2m (11.6%) in Zone I, 8.8m (3.8%) in Zone II, 12.5m (2.1%) in Zone III. Although there were differences between SRTM-DEM and NGIS-DEM, SREM-DEM would be possible to be utilized as DEM data for the region where DEM is not prepared.

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시군관리 농촌지역 소규모 저수지의 실태 조사 (Investigation of Small Reservoir in Rural Area)

  • 윤성수;김한중;박진선
    • 한국관개배수논문집
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    • 제14권2호
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    • pp.194-206
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    • 2007
  • The number of all agricultural reservoir is 18,000, but the ratio of reservoir is 53% before 1945, 35% from 1946 to 1971 in Korea. Therefore, it may have been required that new management system and maintenance techniques are introduced. In this study, there are many facilitie(50.0%), that have been over 50 years, and reservoirs that have been over 30 years is 98.3% in study. So, this study may suggest that reservoir must be considered as new concept through the change of usage and the unification. On the other hand, reservoir works must be developed as amenity resources, other circumstances and district values.

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메콩강 유출모의를 위한 물리적 및 데이터 기반 모형의 비교·분석 (Comparison of physics-based and data-driven models for streamflow simulation of the Mekong river)

  • 이기하;정성호;이대업
    • 한국수자원학회논문집
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    • 제51권6호
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    • pp.503-514
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    • 2018
  • 최근 기후변화 및 유역개발로 인하여 메콩강 유역의 수문환경이 급격히 변화하고 있으며, 메콩강을 공유하는 국가의 수재해 예방 및 지속가능한 수자원개발을 위해서는 메콩강 주요지점에서의 유량 정보의 분석 및 예측이 요구된다. 본 연구에서는 물리적 기반의 수문모형인 SWAT과 데이터기반 딥러닝 알고리즘인 LSTM을 이용하여 메콩강 하류 Kratie 지점의 유출모의를 수행하고, 유출모의 정확도 및 두 가지 방법론의 장 단점을 비교 분석한다. SWAT 모형의 구축을 위해 범용 입력자료(지형: HydroSHED, 토지이용: GLCF-MODIS, 토양: FAO-Soil map, 강우: APHRODITE 등)을 이용하였으며 warming-up 및 매개변수 보정 후 2003~2007년 일유량 모의를 수행하였다. LSTM을 이용한 유출모의의 경우, 딥러닝 오픈소스 라이브러리인 TensorFlow를 활용하여 Kratie 지점기준 메콩강 상류 10개 수위관측소의 두 기간(2000~2002, 2008~2014) 일수위 정보만을 이용하여 심층신경망을 학습하고, SWAT 모형과 마찬가지로 2003~2007년을 대상으로 Kratie 지점에 대한 일수위 모의 후 수위-유량관계곡선식을 이용하여 유출량으로 환산하였다. 두 모형의 모의성능 비교 검토를 위하여 모의기간에 대해 NSE (Nash-Sutcliffe Efficiency)을 산정한 결과, SWAT은 0.9, LSTM은 보다 높은 0.99의 정확도를 나타내는 것으로 분석되었다. 메콩강과 같은 대유역의 특정 지점에 대한 수문시계열 자료의 모의를 위해서는 다양한 입력자료를 요구하는 물리적 수문모형 대신 선행 시계열자료의 변동성을 기억 학습하여 이를 예측에 반영하는 LSTM 기법 등 데이터기반의 심층신경망 모형의 적용이 가능할 것으로 판단된다.

Analysis of future flood inundation change in the Tonle Sap basin under a climate change scenario

  • Lee, Dae Eop;Jung, Sung Ho;Yeon, Min Ho;Lee, Gi Ha
    • 농업과학연구
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    • 제48권3호
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    • pp.433-446
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    • 2021
  • In this study, the future flood inundation changes under a climate change were simulated in the Tonle Sap basin in Cambodia, one of the countries with high vulnerability to climate change. For the flood inundation simulation using the rainfall-runoff-inundation (RRI) model, globally available geological data (digital elevation model [DEM]; hydrological data and maps based on Shuttle elevation derivatives [HydroSHED]; land cover: Global land cover facility-moderate resolution imaging spectroradiometer [GLCF-MODIS]), rainfall data (Asian precipitation-highly-resolved observational data integration towards evaluation [APHRODITE]), climate change scenario (HadGEM3-RA), and observational water level (Kratie, Koh Khel, Neak Luong st.) were constructed. The future runoff from the Kratie station, the upper boundary condition of the RRI model, was constructed to be predicted using the long short-term memory (LSTM) model. Based on the results predicted by the LSTM model, a total of 4 cases were selected (representative concentration pathway [RCP] 4.5: 2035, 2075; RCP 8.5: 2051, 2072) with the largest annual average runoff by period and scenario. The results of the analysis of the future flood inundation in the Tonle Sap basin were compared with the results of previous studies. Unlike in the past, when the change in the depth of inundation changed to a range of about 1 to 10 meters during the 1997 - 2005 period, it occurred in a range of about 5 to 9 meters during the future period. The results show that in the future RCP 4.5 and 8.5 scenarios, the variability of discharge is reduced compared to the past and that climate change could change the runoff patterns of the Tonle Sap basin.