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High-resolution Urban Flood Modeling using Cellular Automata-based WCA2D in the Oncheon-cheon Catchment in Busan, South Korea

셀룰러 오토마타 기반 WCA2D 모형을 이용한 부산 온천천 유역 고해상도 도시 침수 해석

  • 최현진 (금오공과대학교 대학원 토목공학과) ;
  • 이송희 (금오공과대학교 대학원 토목공학과) ;
  • 우현아 (금오공과대학교 대학원 토목공학과) ;
  • 노성진 (금오공과대학교 토목공학과)
  • Received : 2023.02.13
  • Accepted : 2023.05.10
  • Published : 2023.10.01

Abstract

As climate change increasesthe frequency and risk of flooding in major cities around theworld, the importance ofsimulation technology that can quickly and accurately analyze high-resolution 2D flooding information in large-scale areasis emerging. The physically-based approaches based on the Shallow Water Equations (SWE) often requires huge computer resources hindering high-resolution flood prediction. This study investigated the theoretical background of Weighted Cellular Automata 2D (WCA2D), which simulates spatio-temporal changes offlooding using transition rules and weight-based system, and assessed feasibility to simulate pluvial flooding in the urbancatchment, theOncheon-cheon catchmentinBusan, SouthKorea.Inaddition,the computation performancewas compared by applying versions using OpenComputing Language (OpenCL) andOpenMulti-Processing (OpenMP) parallel computing techniques. Simulationresultsshowed that the maximuminundation depthmap by theWCA2Dmodel cansimilarly reproduce historical inundation maps. Also, it can precisely simulate spatio-temporal changes of flooding extent in the urban catchment with complex topographic characteristics. For computation efficiency, parallel computing schemes, theOpenCLandOpenMP, improved the computation by about 8~14 and 5~6 folds respectively, compared to the sequential computation.

기후변화로 인해 전 세계 주요 도시에서 홍수의 빈도와 위험성이 증가함에 따라, 도시 침수에 대비한 선제적 대응을 위해 넓은 공간 영역에서 고해상도 2차원 침수 정보를 신속하고 정확하게 해석할 수 있는 모의 기술의 중요성이 대두되고 있다. 기존의 천수 방정식(shallow water equations)에 기반한 물리적 해석 방법은 고해상도 침수 예측을 위해 많은 컴퓨터 자원과 계산 시간이 소요되는 한계가 있다. 본 연구는 전환 규칙과 가중치 기반 시스템을 사용하여 침수의 시공간 변화를 모의하는 셀룰러 오토마타(cellular automata) 기반 2차원 침수 해석 모형 Weighted Cellular Automata 2D (WCA2D)의 이론적 배경을 고찰하고, 부산 온천천 유역의 침수 사상 모의를 통해 재현하여 국내 도시 유역에 대한 적용성을 검토하였다. 또한, Open Computing Language (OpenCL)와 Open Multi-Processing (OpenMP)과 같은 병렬계산(parallel computing)기술을 적용한 버전을 순차계산(sequential computing)결과와 비교하여 연산성능을 평가 하였다. 연구결과, WCA2D 모형에 의한 최대 침수심 분포는 과거침수 피해지도와 유사하게 모의되어, 복잡한 지형특성을 가지는 도시유역 침수의 시공간적 변화를 해석하기에 적절함을 확인하였다. 또한,병렬 계산 적용시 순차 계산 버전에 비해 OpenCL과 OpenMP는 약8배~14배, 5배~6배 연산 효율이 향상되어 효율적인 도시 침수 모의가 가능하였다.

Keywords

Acknowledgement

본 연구는 정부(과학기술정보통신부)의 재원으로 한국연구재단 (No.2022R1A4A5028840, RS-2023-00246532)의 지원을 받아 수행되었습니다.

References

  1. Chen, A. S., Khoury, M., Vamvakeridou-Lyroudia, L., Stewart, D., Wood, M., Savic, D. A. and Djordjevic, S. (2018). "3D visualisation tool for improving the resilience to urban and coastalflooding in Torbay, UK." Procedia Engineering, Elsevier, Vol. 212, pp. 809-815, https://doi.org/10.1016/j.proeng.2018.01.104. 
  2. Cho, D. (2008). "Cellular automata based urban landuse change modeling considering development density." Journal of the Korean Geographical Society, KGS, Vol. 43, No. 1, pp. 117-133 (in Korean). 
  3. Doocy, S., Daniels, A., Murray, S. and Kirsch, T. D. (2013). "The human impact of floods: a historical review of events 1980-2009 and systematic literature review." PLoS Currents, Public Library of Science, Vol. 5, https://doi.org/10.1371/currents.dis.f4deb457904936b07c09daa98ee8171a. 
  4. Dottori, F. and Todini, E. (2010). "A 2D flood inundation model based on cellular automata approach." XVIII International Conference on Water Resources, Carrera, J. eds., CIMNE, Barcelona, Spain. 
  5. Dottori, F. and Todini, E. (2011). "Developments of a flood inundation model based on the cellular automata approach: Testing different methods to improve model performance." Physics and Chemistry of the Earth, Parts A/B/C, Elsevier, Vol. 36, Nos. 7-8, pp. 266-280, https://doi.org/10.1016/j.pce.2011.02.004. 
  6. Ghimire, B., Chen, A. S., Guidolin, M., Keedwell, E. C., Djordjevic, S. and Savic, D. A. (2013). "Formulation of a fast 2D urban pluvial flood model using a cellular automata approach." Journal of Hydroinformatics, IWA, Vol. 15, No. 3, pp. 676-686, https://doi.org/10.2166/hydro.2012.245. 
  7. Guidolin, M., Chen, A. S., Ghimire, B., Keedwell, E. C., Djordjevic, S. and Savic, D. A. (2016). "A weighted cellular automata 2D inundation model for rapid flood analysis." Environmental Modelling & Software, Elsevier, Vol. 84, pp. 378-394, https://doi.org/10.1016/j.envsoft.2016.07.008. 
  8. Guidolin, M., Duncan, A., Ghimire, B., Gibson, M. J., Keedwell, E., Chen, A. S., Djordjevic, S. and Savic, D. (2012). "CADDIES: a new framework for rapid development of parallel cellular automata algorithmsfor flood simulation." Proceedings of the 10th International Conference on Hydroinformatics, IWA, Hamburg, Germany. 
  9. Hino, M. and Nance, E. (2021). "Five ways to ensure flood-risk research helps the most vulnerable." Nature, Springer Nature, Vol. 595, pp. 27-29, https://doi.org/10.1038/d41586-021-01750-0. 
  10. Hunter, N. M., Horritt, M. S., Bates, P. D., Wilson, M. D. and Werner, M. G. F. (2005). "An adaptive time step solution for raster-based storage cell modelling of floodplain inundation." Advances in Water Resources, Elsevier, Vol. 28, No. 9, pp. 975-991, https://doi.org/10.1016/j.advwatres.2005.03.007. 
  11. Issermann, M., Chang, F.-J. and Jia, H. (2020). "Efficient urban inundation model for live flood forecasting with cellular automata and motion cost fields." Water, MDPI, Vol. 12, No. 7, pp. 1997, https://doi.org/10.3390/w12071997. 
  12. Jamali, B., Bach, P. M., Cunningham, L. and Deletic, A. (2019). "A cellular automata fast flood evaluation (CA-ffe) model." Water Resources Research, AGU, Vol. 55, No. 6, pp. 4936-4953, https://doi.org/10.1029/2018WR023679. 
  13. Jeon, H.-S. and Choo, Y.-M. (2022). "A study on the operation of drainage pump station considering the water level of urban river to reduce flooding." Journal of the Korea Academia-Industrial Cooperation Society, KAIS, Vol. 23, No. 2, pp. 14-21, https://doi.org/10.5762/KAIS.2022.23.2.14 (in Korean). 
  14. Joo, J. W., Joo,J. M., Kim, D. M., Lee, D. H. andChoi, S. H. (2020). "A tsunami simulation model based on cellular automata for analyzing coastal inundation: case study of Gwangalli beach." Journal of Korea Multimedia Society, KMMS, Vol. 23, No. 5, pp. 710-720, https://doi.org/10.9717/kmms.2020.23.5.710 (in Korean). 
  15. Kim, J., Baek, J.-S. and Shin, H.-S. (2021). "A study on improvement of hydrologic cycle by selection of LID technology application area -in Oncheon Stream Basin-." Journal of Korea Academia-Industrial Cooperation Society, KAIS, Vol. 22, No. 4, pp. 545-553, https://doi.org/10.5762/KAIS.2021.22.4.545 (in Korean). 
  16. Kim, S. J. and Jung, I. K. (2006). "Land use change prediction using cellular automata and Markov Chain." Korean National Committee on Irrigation and Drainage, KCID, Vol. 13, No. 1, pp. 110-117 (in Korean). 
  17. Kim, I.-K. and Kwon, H.-S. (2018). "Simulation of land use changes in Hanam city using an object-based cellular automata model." Journal of the Korean Association of Geographic Information Studies, KAGIS, Vol. 21, No. 4, pp. 202-217, https://doi.org/10.11108/kagis.2018.21.4.202 (in Korean). 
  18. Kim, B., Noh, S. J. and Lee, S. (2022). "Retrospective analysis of the urban inundation and the impact assessment of the flood barrier using H12 model." Journal of Korea Water Resources Association, KWRA, Vol. 55, No. 5, pp. 345-356, https://doi.org/10.3741/JKWRA.2022.55.5.345 (in Korean). 
  19. Korea Research Institute for Human Settlements(KRIHS) (2018). Development of the Urban Flooding Risk Prevention System (III), Available at: https://www.krihs.re.kr/ publica/reportView.es?mid=a10102000000&num=000003620284 (Accessed: January 2, 2023) (in Korean). 
  20. Lamb, R., Crossley, M. and Waller, S. (2009). "A fast two-dimensional floodplain inundation model." Proceedings of the Institution of Civil Engineers - Water Management, ICE, Vol. 162, No. 6, pp. 363-370, https://doi.org/10.1680/wama.2009.162.6.363. 
  21. Lee, S., Kim, B., Choi, H. and Noh, S. J. (2022). "A review on urban inundation modeling research in South Korea: 2001-2022." Journal of Korea Water Resources Association, KWRA, Vol. 55, No. 10, pp. 707-721, https://doi.org/10.3741/JKWRA.2022.55.10.707 (in Korean). 
  22. Liu, L., Liu, Y., Wang, X., Yu, D., Liu, K., Huang, H. and Hu, G. (2015). "Developing an effective 2-D urban flood inundation model for city emergency management based on cellular automata." Natural Hazards and Earth System Sciences, EGU, Vol. 15, No. 3, pp. 381-391, https://doi.org/10.5194/nhess15-381-2015. 
  23. Muhajir, I., Lawi, A. and Ribal, A. (2016). "Surface water flow simulation using cellular automata based flow direction D-infinity algorithm." Proceedings of 2016 International Conference on Computational Intelligence and Cybernetics, IEEE, Makassar, Indonesia, pp. 23-27, https://doi.org/10.1109/CyberneticsCom.2016.7892561. 
  24. Noh, S. J., Lee, J.-H., Lee, S., Kawaike, K. and Seo, D.-J. (2018). "Hyper-resolution 1D-2D urban flood modelling using LiDAR data and hybrid parallelization." Environmental Modelling & Software, Elsevier, Vol. 103, pp. 131-145, https://doi.org/10.1016/j.envsoft.2018.02.008. 
  25. Seo, H. and Jun, B. W. (2017). "Modeling the spatial dynamics of urban green spaces in Daegu with a CA-Markov model." Journal of theKorean Geographical Society, KGS, Vol. 52, No. 1, pp. 123-141 (in Korean). 
  26. Shao, Q., Weatherley, D., Huang, L. and Baumgartl, T. (2015). "RunCA: A cellular automata model for simulating surface runoff at different scales." Journal of Hydrology, Elsevier, Vol. 529, No. 3, pp. 816-829, https://doi.org/10.1016/j.jhydrol.2015.09.003. 
  27. Wan Mohtar, W. H. M., Abdullah, J., Abdul Maulud, K. N. and Muhammad, N. S. (2020). "Urban flash flood index based on historical rainfall events." SustainableCities and Society, Elsevier, Vol. 56, 102088, https://doi.org/10.1016/j.scs.2020.102088. 
  28. Wang, Y., Liu, H., Zhang, C., Li, M. and Peng, Y. (2018). "Urban flood simulation and risk analysis based on cellular automaton." Journal of Water Resources Research, Hans, Vol. 7, No. 4, pp. 360-369, https://doi.org/10.12677/JWRR.2018.74040 (inChinese). 
  29. Wijaya, O. T. and Yang, T.-H. (2021). "A novel hybrid approach based on cellular automata and a digital elevation model for rapid flood assessment." Water, MDPI, Vol. 13, No. 9, 1311, https://doi.org/10.3390/w13091311. 
  30. Wolfram, S. (1984). "Cellular automata as models of complexity." Nature, Springer Nature, Vol. 311, pp. 419-424, https://doi.org/10.1038/311419a0. 
  31. Yao, S., Chen, N., Du, W., Wang, C. and Chen, C. (2021). "A cellular automata based rainfall-runoff model for urban inundation analysis under different land uses." Water Resources Management, Springer, Vol. 35, No. 6, pp. 1991-2006, https://doi.org/10.1007/s11269-021-02826-2. 
  32. Yoon, D.-H. and Koh, J.-H. (2012). "A study on analysis of landslide disaster area using cellular automata: An application to Umyeonsan, Seocho-Gu, Seoul, Korea." Journal of Korea Spatial Information Society, KSIS, Vol. 20, No. 1, pp. 9-18, https://doi.org/10.12672/ksis.2012.20.1.009 (in Korean).