Journal of the Korean Association of Geographic Information Studies (한국지리정보학회지)

The Korean Association of Geographic Information Studies (한국지리정보학회)
권호 표지
DOI QR코드

DOI QR Code

Development and Performance Assessment of the Nakdong River Real-Time Runoff Analysis System Using Distributed Model and Cloud Service

분포형 모형과 클라우드 서비스를 이용한 낙동강 실시간 유출해석시스템 개발 및 성능평가

  • KIM, Gil-Ho (Department of Hydro Science and Engineering Research, KICT) ;
  • CHOI, Yun-Seok (Department of Hydro Science and Engineering Research, KICT) ;
  • WON, Young-Jin (Research Institute of HermeSys Co. Ltd.) ;
  • KIM, Kyung-Tak (Department of Hydro Science and Engineering Research, KICT)
  • 김길호 (한국건설기술연구원 수자원연구실) ;
  • 최윤석 (한국건설기술연구원 수자원연구실) ;
  • 원영진 ((주)헤르메시스 기업부설연구소) ;
  • 김경탁 (한국건설기술연구원 수자원연구실)
  • Received : 2017.06.02
  • Accepted : 2017.07.06
  • Published : 2017.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

The objective of this study was to develop a runoff analysis system of the Nakdong River watershed using the GRM (Grid-based Rainfall-runoff Model), a physically-based distributed rainfall-runoff model, and to assess the system run time performance according to Microsoft Azure VM (Virtual Machine) settings. Nakdong River watershed was divided into 20 sub-watersheds, and GRM model was constructed for each subwatershed. Runoff analysis of each watershed was calculated in separated CPU process that maintained the upstream and downstream topology. MoLIT (Ministry of Land, Infrastructure and Transport) real-time radar rainfall and dam discharge data were applied to the analysis. Runoff analysis system was run in Azure environment, and simulation results were displayed through web page. Based on this study, the Nakdong River real-time runoff analysis system, which consisted of a real-time data server, calculation node (Azure), and user PC, could be developed. The system performance was more dependent on the CPU than RAM. Disk I/O and calculation bottlenecks could be resolved by distributing disk I/O and calculation processes, respectively, and simulation runtime could thereby be decreased. The study results could be referenced to construct a large watershed runoff analysis system using a distributed model with high resolution spatial and hydrological data.

본 연구의 목적은 물리적 분포형 강우-유출 모형인 GRM(Grid based Rainfall-runoff Model)과 마이크로소프트 Azure(Microsoft cloud computing service)를 이용하여 낙동강 유역의 유출해석시스템을 개발하고, Azure의 가상머신(VM, Virtual Machine) 설정에 따른 시스템 실행시간을 평가하는 것이다. 이를 위해서 낙동강 유역을 20개의 소유역으로 구분하고, 각 소유역에 대해서 GRM 모형을 구축하였다. 각 유역의 유출해석은 상하류 위상관계를 유지하면서 독립된 프로세스로 실행된다. 실시간 유출해석을 위해 국토교통부의 실시간 강우레이더 자료와 댐방류량 자료를 이용한다. 유출해석시스템은 Azure에서 실행되며, 유출해석 결과는 웹을 통해서 가시화 된다. 연구결과 실시간 수문자료 수신서버와 유출해석 계산서버(Azure) 및 사용자 PC가 연계된 낙동강 실시간 유출해석시스템을 개발할 수 있었다. 유출해석을 위한 전산장비는 하드디스크와 메모리 보다는 CPU의 성능에 크게 의존하는 것으로 평가되었다. 유출해석시의 디스크 입출력(I/O)과 계산 프로세스를 분산함으로써 입출력과 계산 병목을 각각 감소시킬 수 있었고, 실행시간을 단축시킬 수 있었다. 본 연구의 결과는 고해상도의 공간 및 수문 자료를 활용하는 분포형 모형을 이용한 대유역 유출해석시스템을 구축하기 위한 기술로 활용될 수 있을 것이다.

Keywords

References

  1. Ajami, N.K., H. Gupta, T. Wagener, and S. Sorooshian. 2004. Calibration of a semidistributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4):112-135. https://doi.org/10.1016/j.jhydrol.2004.03.033
  2. Andersen, J., J.C. Refsgaard, and H.J. Jensen. 2001. Distributed hydrological modeling of the Senegal river basin-model construction and validation. Journal of Hydrology 247(3-4):200-214. https://doi.org/10.1016/S0022-1694(01)00384-5
  3. Bloschl, G and M. Sivapalan. 1995. Scale issues in hydrological modeling: a review. Hydrological Processes 9(3-4):251-290. https://doi.org/10.1002/hyp.3360090305
  4. Brettschneider, M., B. Pfutzner, and F. Fuchs-Kittowski. 2015. Cloud computing applied to calibration of flood simulation models. Simulation Notes Europe: Technical Note 25(3-4):171-177.
  5. Chen, Y., J. Li, H. Wang, J. Qin, and L. Dong. 2017. Large-watershed flood forecasting with high-resolution distributed hydrological model. Hydrology and Earth System Sciences 21:735-749. https://doi.org/10.5194/hess-21-735-2017
  6. Choi, Y.S., C.K. Choi, and K.T. Kim. 2012. Development of a multi-site calibration module of distributed model-the case of GRM. Journal of the Korean Association of Geographic Information Studies 15(3):103-118 (최윤석, 최천규, 김경탁.2012. 분포형 모형의 다지점 보정 모듈 개발-GRM 모형을 중심으로. 한국지리정보학회지 15(3):103-118). https://doi.org/10.11108/kagis.2012.15.3.103
  7. Choi, Y.S., C.K. Choi, H.S. Kim, K.T. Kim, and S.J. Kim. 2015. Multi-site calibration using a grid-based event rainfall-runoff model: a case study of the upstream areas of the Nakdong River basin in Korea. Hydrological Processes 29(9):2089-2099. https://doi.org/10.1002/hyp.10355
  8. Choi, Y.S. and K.T. Kim. 2017. Grid based rainfall-runoff model user's manual for MapWindow GIS. Korea Institute of Civil Engineering and Building Technology. pp.70-71 (최윤석, 김경탁. 2017. Grid based rainfall-runoff model user's manual for MapWindow GIS. 한국건설기술연구원. 70-71쪽).
  9. Choi, Y.S., K.T. Kim, and J.H. Kim. 2012. Development and evaluation of a real time runoff modelling system using weather radar and distributed model. Journal of Korean Wetlands Society 14 (3):385-397 (최윤석, 김경탁, 김주훈. 2012.기상레이더와 분포형 모형을 이용한 실시간유출해석 시스템 개발 및 평가. 한국습지학회지 14(3):385-397).
  10. Chung, S.Y., J.H. Park, Y.T. Hur, and K.S. Jung. 2010. Application of MPI technique for distributed rainfall-runoff model. Journal of Korea Water Resources Association 43(8):747-755 (정성영, 박진혁,허영택, 정관수. 2010. 분포형 강우유출모형병렬화 처리기법 적용. 한국수자원학회논문집43(8):747-755). https://doi.org/10.3741/JKWRA.2010.43.8.747
  11. Demir, I., S. Small, R. Goska, K. Keahey, P. Armstrong, P. Riteau, B. Seo, and R. Mantilla. 2014. Hydroinformatics on the cloud: data integration, modeling and information communication for flood risk management. Proceedings of 11th International Conference on Hydroinformatics, New York City, USA. Available at: http://academicworks.cuny.edu/cc_conf_hic/330(Accessed May 16, 2017).
  12. Hong, W.Y., G.A. Park, I.K. Jung, and S.J. Kim. 2010. Development of a grid-based daily watershed runoff model and the evaluation of its applicability. Journal of Korean Society of Civil Engineers 30(5B) :459-469 (홍우용, 박근애, 정인균, 김성준.2010. 분포형 유역 일유출 모형의 개발 및적용성 검토. 대한토목학회논문집 30(5B):459-469).
  13. Glenis, V., A.S. McGough, V. Kutija, C. Kilsby, and S. Woodman. 2013. Flood modelling for cities using cloud computing. Journal of Cloud Computing: Advances, Systems and Applications 2013 2:7. https://doi.org/10.1186/2192-113X-2-7
  14. Jeon, B.K., C.K. Lee, and Y.S. Kim. 2012. Evaluation of rainfall measurement capability of dual polarization radar. Journal of Korean Society of Hazard Mitigation 12(2):215-224 (전병국, 이충기, 김양수. 2012. 이중편파 레이더의 강우관측 능력 평가.한국방재학회논문집 12(2):215-224). https://doi.org/10.9798/KOSHAM.2012.12.2.215
  15. Jung, D.H., J.H. Choi, and J.H. Kim. 2016. Application of parallel computation to water resources engineering. Water for Future, Korea Water Resources Association 49(3):75-83 (정동휘, 최지호, 김중훈.2016. 병렬계산의 수자원공학에 적용. 한국수자원학회지: 물과미래 49(3):75-83).
  16. Kang, M.G. and S.J. Park. 2012. Methodologies for incorporating smart water grid into water resources management considering the outlook for future water resources. Proceedings of 2012 Conference for Korea Water Resources Association. pp.785-789 (강민구, 박성제. 2012. 미래 수자원 전망을 고려한 스마트 워터 그리드 도입 방안. 2012 한국수자원학회 학술발표회 논문집 785-789쪽).
  17. KICT(Korea Institute of Civil Engineering and Building Technology). 2015. Development of flood/snowstorm disaster forecasting and warning platform based on hydrological radars. 3rd year research report. pp.205-220 (한국건설기술연구원. 20 15. 수문레이더 기반 고해상도 홍수해석 기술개발. 3차년도 연구보고서. 205-220쪽.
  18. KICT(Korea Institute of Civil Engineering and Building Technology). 2016. Development of flood/snowstorm disaster forecasting and warning platform based on hydrological radars. 4th year research report. pp.11-19 (한국건설기술연구원. 2016. 수문레이더 기반 고해상도 홍수해석 기술개발. 4차년도 연구보고서. 11-19쪽.
  19. Kim, Y.S., K.H. Chang, B.S. Kim, and H.S. Kim. 2011. Decision of GIS optimum grid on applying distributed rainfall-runoff model with radar resolution. Journal of Korean Wetlands Society 13(1):105-116(김연수, 장권희, 김병식, 김형수. 2011. 레이더 자료의 해상도를 고려한 분포형 강우-유출 모형의 GIS 자료 최적 격자의 결정. 한국습지학회지 13(1):105-116).
  20. Kim, D.Y., J.J. Lee, H.S. Chae, and E.H. Hwang. 2015. A study on the application of standard technology for integrated management of water hazard information platform. Journal of the Korean Association of Geographic Information Studies 18(4):119-130 (김동영, 이정주, 채효석, 황의호. 2015. 수재해 정보 플랫폼 통합관리를위한 표준기술 적용방안. 한국지리정보학회지18(4):119-130). https://doi.org/10.11108/kagis.2015.18.4.119
  21. Kosukhin, S.S., S.V. Kovalchuk, and A.V. Boukhanovsky. 2015. Cloud technology for forecasting accuracy evaluation of extreme metocean Events. Procedia Computer Science 51:2933-2937. https://doi.org/10.1016/j.procs.2015.05.483
  22. Muleta, M.K., J.W. Nicklow, and E.G. Bekele. 2007. Sensitivity of a distributed watershed simulation model to spatial scale. Journal of Hydrologic Engineering 12(2): 163-172. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:2(163)
  23. Noh, S.J., S.W. Choi, Y.S. Choi, and K.T. Kim. 2014. Impact assessment of spatial resolution of radar rainfall and a distributed hydrologic model on parameter estimation. Journal of the Korean Society of Civil Engineers 34(5):1443-1454 (노성진, 최신우, 최윤석, 김경탁. 2014. 레이더강우 및 분포형 수문모형의 공간해상도가 매개변수 추정에 미치는 영향 평가. 대한토목학회 논문집 34(5):1443-1454). https://doi.org/10.12652/Ksce.2014.34.5.1443
  24. Park, J.H. 2014. Parallel flood inundation analysis using MPI technique. Journal of Korea Water Resources Association 47(11):1051-1060 (박재홍. 2014. MPI기법을 이용한 병렬 홍수침수해석. 한국수자원학회논문집 47(11):1051-1060). https://doi.org/10.3741/JKWRA.2014.47.11.1051
  25. Quiroga, V.M., I. Popescu, D.P. Solomatine, and L. Bociort. 2013. Cloud and cluster computing in uncertainty analysis of integrated flood models. Journal of Hydroinformatics 15(1):55-70. https://doi.org/10.2166/hydro.2012.017
  26. Siuta, D., G. West, H. Modzelewski, R. Schigas, and R. Stull. 2016. Viability of cloud computing for real-time numerical weather prediction. American Meteorological Society 31:1985-1996.
  27. Vivoni, E.R., D. Entekhabi, R.L. Bras, and V.Y. Ivanov. 2007. Controls on runoff generation and scale-dependence in a distributed hydrologic model. Hydrology and Earth System Sciences 11:1683-1701. https://doi.org/10.5194/hess-11-1683-2007
  28. Yoon, G.S. and K.W. Lee. 2016. Application of OGC WPS 2.0 to Geo-Spatial Web Services. Journal of the Korean Association of Geographic Information Studies 19(3):16-28 (윤구선, 이기원. 2016. 공간정보 웹 서비스에서 OGC WPS 2.0 적용. 한국지리정보학회지 19(3):16-28). https://doi.org/10.11108/kagis.2016.19.3.016
  29. Young, A. 2006. Stream flow simulation within UK ungauged catchments using a daily rainfall-runoff model. Journal of Hydrology 320(1-2):155-172. https://doi.org/10.1016/j.jhydrol.2005.07.017
  30. Zhang X., R. Srinivasan, and M. Van Liew. 2008. Multi-site calibration of the SWAT model for hydrologic modeling. Transactions of the ASABE 51(6):2039-2049. https://doi.org/10.13031/2013.25407