Skip to main content
SpringerLink
Log in

Prediction of the future flood severity in plain river network region based on numerical model: A case study

  • Article
  • Published:
Journal of Hydrodynamics Aims and scope Submit manuscript

Abstract

Suzhou is one of China’s most developed regions, located in the eastern part of the Yangtze Delta. Due to its location and river features, it may at a high risk of flood under the climate change background in the future. In order to investigate the flood response to the extreme scenario in this region, 1-D hydrodynamic model with real-time operations of sluices and pumps is established. The rain-runoff processes of the urban and rural areas are simulated by two lumped hydrologic models, respectively. Indicators for a quantitative assessment of the flood severity in this region are proposed. The results indicate that the existing flood control system could prevent the Suzhou Downtown from inundation in the future. The difficulty of draining the Taihu Lake floods should be given attention to avoid the flood hazard. The modelling approach based on the in-bank model and the evaluation parameters could be effective for the flood severity estimation in the plain river network catchment. The insights from this study of the possible future extreme flood events may assist the policy making and the flood control planning.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Gong Z., Zhang C. K., Wan L. M. et al. Tidal level response to sea-level rise in the Yangtze Estuary [J]. China Ocean Engineering, 2012, 26(1): 109–122.

    Article  Google Scholar 

  2. Pachauri R. K., Meyer L., Plattner G. K. et al. IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[R]. IPCC, 2015.

    Google Scholar 

  3. Han L. F., Xu Y. P., Pan G. B. et al. Changing properties of precipitation extremes in the urban areas, Yangtze River Delta, China, during 1957–2013 [J]. Natural Hazards, 2015, 79(1): 437–454.

    Article  Google Scholar 

  4. Zhang Q., Xu C. Y., Zhang Z. et al. Spatial and temporal variability of precipitation maxima during 1960–2005 in the Yangtze River basin and possible association with large-scale circulation [J]. Journal of Hydrology, 2008, 353(3): 215–227.

    Article  Google Scholar 

  5. Mendizabal M., Sepúlveda J., Torp P. Climate change impacts on flood events and its consequences on human in Deba River [J]. International Journal of Environmental Research, 2014, 8(1): 221–230.

    Google Scholar 

  6. Milly P., Wetherald R., Dunne K. et al. Increasing risk of great floods in a changing climate [J]. Nature, 2002, 415(6871): 514–517.

    Article  Google Scholar 

  7. Hirabayashi Y., Mahendran R., Koirala S. et al. Global flood risk under climate change [J]. Nature Climate Change, 2013, 3(9): 816–821.

    Article  Google Scholar 

  8. Hunt A., Watkiss P. Climate change impacts and adaptation in cities: A review of the literature [J]. Climatic Change, 2011, 104(1): 13–49.

    Article  Google Scholar 

  9. Han S. Q., Xie Y. Y., Li D. M. et al. Risk analysis and management of urban rainstorm water logging in Tianjin [J]. Journal of Hydrodynamics, Ser. B, 2006, 18(5): 552–558.

    Article  Google Scholar 

  10. Liu L., Xu Z. X., Reynard N. S. et al. Hydrological analysis for water level projections in Taihu Lake, China [J]. Journal of Flood Risk Management, 2013, 6(1): 14–22.

    Article  Google Scholar 

  11. Liang Q., Smith L., Xia X. New prospects for com putational hydraulics by leveraging high-performance heterogeneous computing techniques [J]. Journal of Hydrodynamics, 2016, 28(6): 977–985.

    Article  Google Scholar 

  12. Wicks J. M., Hu C., Scott M. et al. A broad scale model for flood simulation in the Taihu Basin, China [J]. Journal of Flood Risk Management, 2013, 6(1): 33–41.

    Article  Google Scholar 

  13. Xu Z. X., Liu L. Detection of climate change and projection of future climate change scenarios in Taihu Lake Basin [J]. Advances in Science and Technology of Water Resources, 2012, 32(1): 1–7.

    Google Scholar 

  14. Yu C., Hall J. W., Cheng X. et al. Broad scale quantified flood risk analysis in the Taihu Basin, China [J]. Journal of Flood Risk Management, 2013, 6(1): 57–68.

    Article  Google Scholar 

  15. Cheng X. T., Evans E. P., Wu H. Y. et al. A framework for long-term scenario analysis in the Taihu Basin, China [J]. Journal of Flood Risk Management, 2013, 6(1): 3–13.

    Article  Google Scholar 

  16. Ou Y., Wu H. The Taihu Basin flood in 1999 [M]. Beijing, China: China Water and Power Press, 2001 (in Chinese).

    Google Scholar 

  17. Li J. Sea level variation and its effect on storm surge in the East China Sea [D]. Master Thesis, Qingdao, China: Ocean University of China, 2011(in Chinese).

    Google Scholar 

  18. Li S. L., Han L., Bian J. Projecting heavy rainfall events in the middle and lower reach of the Yangtze River valley in the 21st century based on IPCC AR4 simulations [J]. Torrential Rain and Disasters, 2012, 31(3): 193–200(in Chinese).

    Google Scholar 

  19. Mishra V., Ganguly A. R., Nijssen B. et al. Changes in observed climate extremes in global urban areas [J]. Environmental Research Letters, 2015, 10(2): 024005.

    Article  Google Scholar 

  20. Alfieri L., Thielen J. A European precipitation index for extreme rain-storm and flash flood early warning [J]. Meteorological Applications, 2015, 22(1): 3–13.

    Article  Google Scholar 

  21. Kriebel D. L., Geiman J. D., Henderson G. R. Future flood frequency under sea-level rise scenarios [J]. Journal of Coastal Research, 2005, 31(5): 1078–1083.

    Google Scholar 

  22. Lin B. X., Su X. G. Optimal dispatching of flood control system for sluice groups in plain dike areas [J]. Journal of Zhejiang University (Natural Science), 1996, 30(6): 652–663(in Chinese).

    Google Scholar 

  23. Sabzi H. Z., Humberson D., Abudu S. et al. Optimization of adaptive fuzzy logic controller using novel combined evolutionary algorithms, and its application in Diez Lagos flood controlling system, Southern New Mexico [J]. Expert Systems with Applications, 2016, 43(C): 154–164.

    Article  Google Scholar 

  24. Haddad O. B., Ashofteh P. S., Mariño M. A. Levee layouts and design optimization in protection of flood areas [J]. Journal of Irrigation and Drainage Engineering, 2015, 141(8): 04015004

    Article  Google Scholar 

  25. Gu Z. H., Cao X. M., Liu G. L. et al. Optimizing operation rules of sluices in river networks based on knowledge-driven and data-driven mechanism [J]. Water Resources Management, 2014, 28(11): 3455–3469.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing, 210098, China

    Zi-jun Hu  (胡孜军), Ling-ling Wang  (王玲玲) & Hong-wu Tang  (唐洪武)

  2. College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, 210098, China

    Zi-jun Hu  (胡孜军), Ling-ling Wang  (王玲玲) & Hong-wu Tang  (唐洪武)

  3. Power China Huadong Engineering Corporation Limited, Hangzhou, 311122, China

    Zi-jun Hu  (胡孜军)

  4. Computer Science and Technology Department of Bengbu College, Bengbu, 233000, China

    Xiao-ming Qi  (戚晓明)

Authors
  1. Zi-jun Hu  (胡孜军)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ling-ling Wang  (王玲玲)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hong-wu Tang  (唐洪武)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiao-ming Qi  (戚晓明)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ling-ling Wang  (王玲玲).

Additional information

Project supported by the National Key Research and Development Program of China (Grant No. 2017Yfc0405600, 2016Yfc0401503), the Special Fund for Public Welfare of Water Resources Ministry (Grant No. 201501007, 201201017) and the State Key Program of National Natural Science of China (Grant No. 51239003).

Biography: Zi-jun Hu (1988-), Male, Ph. D. Corresponding author: Ling-ling Wang

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, Zj., Wang, Ll., Tang, Hw. et al. Prediction of the future flood severity in plain river network region based on numerical model: A case study. J Hydrodyn 29, 586–595 (2017). https://doi.org/10.1016/S1001-6058(16)60771-0

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1016/S1001-6058(16)60771-0

Keywords

Search

Navigation