DOI QR코드

DOI QR Code

농촌지역 미래 홍수 위험도 평가를 위한 수문 모델 개발

Developing a hydrological model for evaluating the future flood risks in rural areas

  • Adeyi, Qudus (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Ahmad, Mirza Junaid (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Adelodun, Bashir (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Odey, Golden (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Akinsoji, Adisa Hammed (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Salau, Rahmon Abiodun (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Choi, Kyung Sook (Department of Agricultural Civil Engineering, Kyungpook National University)
  • 투고 : 2023.11.30
  • 심사 : 2023.12.08
  • 발행 : 2023.12.31

초록

미래 기후변화 현상은 농촌지역의 홍수 위험을 중가 시켜 농업의 지속 가능성과 식량 안보를 위협할 것으로 예견된다. 본 연구에서는 미래기후변화를 파악하기 위해 세 개의 GCM을 선정하여 RCP 및 SSP 시나리오 중 중간 및 극한조건을 각각 적용하여 미래 기후변화를 예측하였다. 충북 청주시 신대지구를 대상으로 미래 홍수 위험도를 평가하기 위한 수문 모델을 개발하였으며, 대상지구에서 발생했던 2021~2022년내 강우사상에 대한 시우량, 유출량 측정자료를 사용하여 수문 모델을 검보정 하였다. RCP와 SSP 시나리오에 의한 미래 기상자료를 활용하여 홍수 위험 정도를 비교 분석한 결과. 미래로 갈수록 극한 강우 발생가능성이 높아지는 경향을 보여, 2051~2100년 기간에 극한강우 발생 가능성이 가장 높게 나타났다. 대상지구에서 발생한 침수심이 700 mm를 초과하는 경우는 2015~2030년 기간에는 13~36%, 2031~2050년 기간에는 54~74%, 2051~2100년 기간에는 71~91%를 각각 차지하는 것으로 나타났다. 또한 RCP 시나리오 보다 SSP 시나리오에 적용한 미래 기후변화 조건에서 극한 홍수 발생 가능성이 더 높게 나타나는 것으로 평가되었다.

Climate change is expected to amplify the future flooding risks in rural areas which could have devastating implications for the sustainability of the agricultural sector and food security in South Korea. In this study, spatially disaggregated and statistically bias-corrected outputs from three global circulation models (GCMs) archived in the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and 6) were used to project the future climate by 2100 under medium and extreme scenarios. A hydrological model was developed to simulate the flood phenomena at the Shindae experimental site located in the Chungcheongbuk Province, South Korea. Hourly rainfall, inundation depth, and discharge data collected during the two extreme events that occurred in 2021 and 2022 were used to calibrate and validate the hydrological model. Probability analysis of extreme rainfall data suggested a higher likelihood of intense and unprecedented extreme rainfall events, which would be particularly notable during 2051-2100. Consequently, the flooded area under an inundation depth of >700 mm increased by 13-36%, 54-74%, and 71-90% during 2015-2030, 2031-2050, and 2051-2100, respectively. Severe flooding probability was notably higher under extreme CMIP6 scenarios than under their CMIP5 counterparts.

키워드

과제정보

This work was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through the Agricultural Foundation and Disaster Response Technology Development Program, funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA)(321071-3).

참고문헌

  1. Adelodun, B., Ahmad, M.J., Odey, G., Adeyi, Q., and Choi, K.S. (2023). "Performance-Based evaluation of CMIP5 and CMIP6 global climate models and their multi-model ensembles to simulate and project seasonal and annual climate variables in the Chungcheong region of South Korea." Atmosphere, MDPI, Vol. 14, No. 10, pp. 1569-1595. https://doi.org/10.3390/atmos14101569
  2. Adelodun, B., Odey, G., Cho, H., Lee, S., Adeyemi, K.A., and Choi, K.S. (2022). "Spatial-temporal variability of climate indices in Chungcheong provinces of Korea: Application of graphical innovative methods for trend analysis." Atmospheric Research, Elsevier, Vol. 280, 106420.
  3. Ahmad, M.J., and Choi, K.S. (2023). "Spatial-temporal evolution and projection of climate extremes in South Korea based on multiGCM ensemble data." Atmospheric Research, Elsevier, Vol. 289, 106772.
  4. Al-Awadi, A.T., Al-Saadi, R.J.M., and Mutasher, A.K.A. (2023). "Frequency analysis of rainfall events in Karbala city, Iraq, by creating a proposed formula with eight probability distribution theories." Smart Science, Vol. 11, No. 3, pp. 639-648. https://doi.org/10.1080/23080477.2023.2220916
  5. Al-Ghobari, H., Dewidar, A., and Alataway, A. (2020). "Estimation of surface water runoff for a semi-arid area using RS and GIS-based SCS-CN method." Water, MDPI, Vol. 12, No. 7, 1924.
  6. Althoff, D., and Rodrigues, L.N. (2021). "Goodness-of-fit criteria for hydrological models: Model calibration and performance assessment." Journal of Hydrology, Elsevier Vol. 600, 126674.
  7. Badou, D.F., Adango, A., Hounkpe, J., Bossa, A., Yira, Y., Biao, E.I., Adounkpe, J., Alamou, E., Sintondji, L.O.C., and Afouda, A.A. (2021). "Heavy rainfall frequency analysis in the Benin section of the Niger and Volta Rivers basins: Is the Gumbel's distribution a one-size-fits-all model?." Proceedings of the International Association of Hydrological Sciences, Copernicus, Vol. 384, pp. 187-194.
  8. Calvin, K., Dasgupta, D., Krinner, G., Mukherji, A., Thorne, P.W., Trisos, C., Romero, J., Aldunce, P., Barrett, K., Blanco, G., et al. (2023). "IPCC, 2023: Climate change 2023: Synthesis report." Contribution of working groups I, II and III to the sixth assessment report of the Intergovernmental panel on climate change Edited by Core Writing Team, Lee, H., and Romero, J., Intergovernmental Panel on Climate Change, Geneva, Switzerland.
  9. Chang, D. (2023). Over 8,000 public, private properties reported damaged from torrential rains, Yonhap News Agency, Accessed November 28 2023, <https://en.yna.co.kr/view/AEN20230722002300325>.
  10. de Almeida, I.K., Almeida, A.K., Steffen, J.L., and Alves Sobrinho, T. (2016). "Model for estimating the time of concentration in watersheds." Water Resources Management, Springer, Vol. 30, No. 12, pp. 4083-4096. https://doi.org/10.1007/s11269-016-1383-x
  11. Eccles, R., Zhang, H., Hamilton, D., Trancoso, R., and Syktus, J. (2021). "Impacts of climate change on streamflow and floodplain inundation in a coastal subtropical catchment." Advances in Water Resources, Vol. 147, 103825.
  12. Edamo, M.L., Hatiye, S.D., Minda, T.T., and Ukumo, T.Y. (2023). "Flood inundation and risk mapping under climate change scenarios in the lower Bilate catchment, Ethiopia." Natural Hazards, Springer, Vol. 118, No. 3, pp. 2199-2226. https://doi.org/10.1007/s11069-023-06101-y
  13. Garg, V., Chaubey, I., and Haggard, B.E. (2003). "Impact of calibration watershed on runoff model accuracy." Transactions of the ASAE, ASABE, Vol. 46, No. 5, pp. 1347-1353. https://doi.org/10.13031/2013.15445
  14. Goldenson, N., Leung, L.R., Mearns, L.O., Pierce, D.W., Reed, K.A., Simpson, I.R., Ullrich, P., Krantz, W., Hall, A., Jones, A., and Rahimi, S. (2023). "Use-inspired, process-oriented GCM Selection: Prioritizing models for regional dynamical downscaling." Bulletin of the American Meteorological Society, AMS, Vol. 104, No. 9, pp. E1619-E1629. https://doi.org/10.1175/BAMS-D-23-0100.1
  15. Han, H., Kim, D., and Kim, H.S. (2022). "Inundation analysis of coastal urban area under climate change scenarios." Water, MDPI, Vol. 14, No. 7, pp. 1159-1178. https://doi.org/10.3390/w14071159
  16. Hawkins, R.H., Theurer, F.D., and Rezaeianzadeh, M. (2019). "Understanding the basis of the curve number method for watershed models and TMDLs." Journal of Hydrologic Engineering, ASCE, Vol. 24, No. 7, 06019003.
  17. Hosseinzadehtalaei, P., Ishadi, N.K., Tabari, H., and Willems, P. (2021). "Climate change impact assessment on pluvial flooding using a distribution-based bias correction of regional climate model simulations." Journal of Hydrology, Vol. 598, 126239.
  18. Hwang, J., Ahn, J., Jeong, C., and Heo, J.-H. (2018). "A study on the variation of design flood due to climate change in the ungauged urban catchment." Journal of Korea Water Resources Association, Vol. 51, No. 5, pp. 395-404.
  19. Im, S.-J., and Park, S.-U. (1997). "Estimating runoff curve numbers for paddy fields." Journal of Korea Water Resources Association, KWRA, Vol. 30, No. 4, pp. 379-387.
  20. Karmalkar, A.V., Thibeault, J.M., Bryan, A.M., and Seth, A. (2019). "Identifying credible and diverse GCMs for regional climate change studies - case study: Northeastern United States." Climatic Change, Springer, Vol. 154, No. 3-4, pp. 367-386. https://doi.org/10.1007/s10584-019-02411-y
  21. Katz, R.W., and Brown, B.G. (1992). "Extreme events in a changing climate: Variability is more important than averages." Climatic Change, Vol. 21, No. 3, pp. 289-302. https://doi.org/10.1007/BF00139728
  22. Kim, S., Kwon, J.H., Om, J.S., Lee, T., Kim, G., Kim, H., and Heo, J.H. (2023). "Increasing extreme flood risk under future climate change scenarios in South Korea." Weather and Climate Extremes, Elsevier, Vol. 39, 100552.
  23. Kim, S.-M., Kang, M.-S., and Jang, M.-W. (2018). "Assessment of agricultural drought vulnerability to climate change at a municipal level in South Korea." Paddy and Water Environment, Springer, Vol. 16, No. 4, pp. 699-714. https://doi.org/10.1007/s10333-018-0661-z
  24. Kim, Y., Yu, J., Lee, K., Sung, H.C., and Jeon, S.W. (2020). "Application of the HEC-HMS model for prediction of future rainfall runoff in the Daecheong Dam basin of the Geum River." Journal of Climate Change Research, KSCC, Vol. 11, No. 6-1, pp. 609-619. https://doi.org/10.15531/KSCCR.2020.11.6.609
  25. Kousari, M.R., Malekinezhad, H., Ahani, H., and Asadi Zarch, M.A. (2010). "Sensitivity analysis and impact quantification of the main factors affecting peak discharge in the SCS curve number method: An analysis of Iranian watersheds." Quaternary International, Pergamon, Vol. 226, No. 1-2, pp. 66-74. https://doi.org/10.1016/j.quaint.2010.05.011
  26. Kwak, J., Kim, J., Jun, S.M., Hwang, S., Lee, S., Lee, J.N., and Kang, M.S. (2020). "Assessment of future flood according to climate change, rainfall distribution and CN." Journal of the Korean Society of Agricultural Engineers, Vol. 62, No. 6, pp. 85-95.
  27. Lee, J., and Shin, H. (2021). "Assessment of future climate change impact on an agricultural reservoir in South Korea." Water, MDPI AG, Vol. 13, No. 15, 2125.
  28. Li, H.-C., Hsiao, Y.-H., Chang, C.-W., Chen, Y.-M., Lin, L.-Y., Chang, C.-W., Chen, Y.-M., Lin, L.-Y., and Michailidis, A. (2021). "Agriculture adaptation options for flood impacts under climate change - A simulation analysis in the Dajia River Basin." Sustainability, MDPI, Vol. 13, No. 13, 7311.
  29. Ministry of Environmen (ME) (2019). Standard guidelines for estimating flood. Publication No. 11-148000- 001604-14 (in Korean).
  30. Ministry of Land, Transport and Maritime Affairs (MLTM) (2012). Design flood estimation methods. (in Korean).
  31. Moazzam, M.F.U., Rahman, G., Munawar, S., Farid, N., and Lee, B.G. (2022). "Spatiotemporal rainfall variability and drought assessment during past five decades in South Korea using SPI and SPEI." Atmosphere, MDPI, Vol. 13, No. 2, 292..
  32. Mohammad, A.G. (1978). "Flood routing by the Muskingum method." Journal of Hydrology, Vol. 36, pp. 353-363. https://doi.org/10.1016/0022-1694(78)90153-1
  33. Park, S., Sur, C., Kim, J., Choi, S., Lee, J., and Kim, T. (2021). "Projected drought risk assessment from water balance perspectives in a changing climate." International Journal of Climatology, Wiley, Vol. 41, No. 4, pp. 2765-2777. https://doi.org/10.1002/joc.6988
  34. Perdikaris, J., Gharabaghi, B., and Rudra, R. (2018). "Reference time of concentration estimation for ungauged catchments." Earth Science Research, CSCE, Vol. 7, No. 2, 58.
  35. Qin, X.S., and Lu, Y. (2014). "Study of climate change impact on flood frequencies: A combined weather generator and hydrological modeling approach." Journal of Hydrometeorology, Vol. 15, No. 3, pp. 1205-1219. https://doi.org/10.1175/JHM-D-13-0126.1
  36. Rentschler, J., and Salhab, M. (2020). People in Harm's Way: Flood exposure and poverty in 189 countries, The World Bank, Washington, DC.
  37. Son, K.-H., Lee, B.-J., and Bae, D.-H. (2010). "Assessment on flood characteristics changes using Multi-GCMs climate scenario." Journal of Korea Water Resources Association, KWRA, Vol. 43, No. 9, pp. 789-799. https://doi.org/10.3741/JKWRA.2010.43.9.789
  38. Song, Y.H., Chung, E., and Shahid, S. (2021). "Spatiotemporal differences and uncertainties in projections of precipitation and temperature in South Korea from CMIP6 and CMIP5 general circulation model." International Journal of Climatology, Wiley, Vol. 41, No. 13, pp. 5899-5919. https://doi.org/10.1002/joc.7159
  39. Tegegne, G., Melesse, A.M., and Worqlul, A.W. (2020). "Development of multi-model ensemble approach for enhanced assessment of impacts of climate change on climate extremes." Science of the Total Environment, Elsevier B.V., Vol. 704, 135357.
  40. Tramblay, Y., Bouvier, C., Martin, C., Didon-Lescot, J.-F., Todorovik, D., and Domergue, J.-M. (2010). "Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling." Journal of Hydrology, Elsevier, Vol. 387, No. 3-4, pp. 176-187. https://doi.org/10.1016/j.jhydrol.2010.04.006
  41. World Meteorological Organization (WMO) (2023). Atlas of mortality and economic losses from weather, climate and water-related hazards, accessed November 26 2023, <https://public-old.wmo.int/en/resources/atlas-of-mortality>.
  42. Xu, C.-Y., Widenwid widen, E., and Halldin, S. (2005). "Modelling hydrological consequences of climate change-progress and challenges." Advances in Atmospheric Sciences, Vol. 22, No. 6, pp. 789-797. https://doi.org/10.1007/BF02918679
  43. Xu, K., Zhuang, Y., Bin, L., Wang, C., and Tian, F. (2023). "Impact assessment of climate change on compound flooding in a coastal city." Journal of Hydrology, Elsevier, Vol. 617, 129166.
  44. Zhang, Y., Wang, Y., Chen, Y., Liang, F., and Liu, H. (2019). "Assessment of future flash flood inundations in coastal regions under climate change scenarios - A case study of Hadahe River basin in northeastern China." Science of The Total Environment, Elsevier, Vol. 693, 133550.