Abstract
The Yangtze River Economic Belt is one of the three national strategies of China, while flood risk is one of the most important concerns in the development of Yangtze River Economic Belt. In order to decrease the risks caused by floods, complete flood management system and adequate pre-arranged planning are desiderated to be researched in advance. This study considers two typical situations of flood risk, in which one is sluice-control situation in flood detention area and another is dike-break situation in flood-protected area, and proposes a framework for flood risk mapping. The results show that the losses caused by flood hazards are massive both in the two typical cases when extreme floods happen. The economic losses of different indicators are of great difference in flood detention area and flood-protected area, respectively. The framework effectively handles the complex boundaries in the Yangtze River Economic Belt and provides more accurate flood routing information. The evacuation plan module which has been incorporated in the framework also provides informative assistance for emergent action of evacuation under urgent condition.
Similar content being viewed by others
References
Ahmadisharaf E, Kalyanapu AJ, Chung ES (2017) Sustainability-based flood hazard mapping of the swannanoa river watershed. Sustainability 9:1–15. https://doi.org/10.3390/su9101735
Alho P, Aaltonen J (2008) Comparing a 1D hydraulic model with a 2D hydraulic model for the simulation of extreme glacial outburst floods. Hydrol Process 22:1537–1547. https://doi.org/10.1002/hyp.6692
Alkema D (2003) Flood risk assessment for EIA: an example of a motorway near Trento, Italy. Med Phys 34:2593–2594
Andrei A, Robert B, Erika B (2017) Numerical limitations of 1D hydraulic models using MIKE11 or HEC-RAS software—case study of Baraolt River, Romania. In: World multidisciplinary civil engineering-architecture-urban planning symposium-Wmcaus. https://doi.org/10.1088/1757-899x/245/7/072010
Apel H, Merz B, Thieken AH (2009) Influence of dike breaches on flood frequency estimation. Comput Geosci 35:907–923. https://doi.org/10.1016/j.cageo.2007.11.003
Chow VT (1959) In: Chow VT, Harmer ED (eds) Open-channel hydraulics, vol 54, Civil engineering, vol 6, International student edition. McGraw-Hill Book Company, New York, pp 182–192. https://doi.org/ISBN 07-010776-9
DHI (2014a) MIKE 11: a modelling system for rivers and channels user guide. DHI Water and Environment, Hørsholm
DHI (2014b) MIKE FLOOD: 1D–2D modelling user manual. DHI Water and Environment, Hørsholm
Glas H, Jonckheere M, Mandal A, James-Williamson S, De Maeyer P, Deruyter G (2017) A GIS-based tool for flood damage assessment and delineation of a methodology for future risk assessment: case study for Annotto Bay, Jamaica. Nat Hazards 88:1867–1891. https://doi.org/10.1007/s11069-017-2920-5
Islam MDM, Sado K (2000) Development of flood hazard maps of Bangladesh using NOAA-AVHRR images with GIS. Hydrol Sci J 45:337–355. https://doi.org/10.1080/02626660009492334
Jancikova A, Unucka J (2015) DTM impact on the results of dam break simulation in 1D hydraulic models. In: GIS Ostrava compilation surface models for geosciences. Tech Univ Ostrava, Ostrava, Czech Republic, pp 125–136. https://doi.org/10.1007/978-3-319-18407-4_11
Jing R, Nedovic-Budic Z (2016) Integrating spatial planning and flood risk management: a new conceptual framework for the spatially integrated policy infrastructure. Comput Environ Urban Syst 57:68–79. https://doi.org/10.1016/j.compenvurbsys.2016.01.008
Jongman B, Ward PJ, Aerts JCJH (2012) Global exposure to river and coastal flooding: long term trends and changes. Glob Environ Change Hum Policy Dimens 22:823–835. https://doi.org/10.1016/j.gloenvcha.2012.07.004
Jongman B et al (2014) Increasing stress on disaster-risk finance due to large floods. Nat Clim Change 4:264–268. https://doi.org/10.1038/NCLIMATE2124
Kabenge M, Elaru J, Wang HT, Li FT (2017) Characterizing flood hazard risk in data-scarce areas, using a remote sensing and GIS-based flood hazard index. Nat Hazards 89:1369–1387. https://doi.org/10.1007/s11069-017-3024-y
Kalyanapu AJ, Judi DR, McPherson TN, Burian SJ (2012) Monte Carlo-based flood modelling framework for estimating probability weighted flood risk. J Flood Risk Manag 5:37–48. https://doi.org/10.1111/j.1753-318X.2011.01123.x
Kourgialas NN, Karatzas GP (2017) A national scale flood hazard mapping methodology: the case of Greece—protection and adaptation policy approaches. Sci Total Environ 601:441–452. https://doi.org/10.1016/j.scitotenv.2017.05.197
Kundzewicz ZW et al (2014) Flood risk and climate change: global and regional perspectives. Hydrol Sci J 59:1–28. https://doi.org/10.1080/02626667.2013.857411
Leopardi A, Oliveri E, Greco M (2002) Two-dimensional modeling of floods to map risk-prone areas. J Water Resour Plan Manag ASCE 128:168–178. https://doi.org/10.1061/(ASCE)0733-9496(2002)128:3(168)
Liu Y, Zhou J, Song L, Zou Q, Guo J, Wang Y (2014) Efficient GIS-based model-driven method for flood risk management and its application in central China. Nat Hazards Earth Syst Sci 14:331–346. https://doi.org/10.5194/nhess-14-331-2014
Lu C, Zhou J, Jiang Y, Weng Z, Liu Y, Yuan S (2017) Flood routing numerical simulation in jingjiang diversion area based on MIKE FLOOD model. J Basic Sci Eng 25:905–916. https://doi.org/10.16058/j.issn.1005-0930.2017.05.004
Meyer V, Scheuer S, Haase D (2009) A multicriteria approach for flood risk mapping exemplified at the Mulde river, Germany. Nat Hazards 48:17–39. https://doi.org/10.1007/s11069-008-9244-4
Morgan A, Olivier D, Nathalie B, Claire-Marie D, Philippe G (2016) High-resolution modelling with bi-dimensional shallow water equations based codes-high-resolution topographic data use for flood hazard assessment over urban and industrial environments. In: 12th international conference on hydroinformatics (Hic 2016)-smart water for the future, vol 154, pp 853–860. https://doi.org/10.1016/j.proeng.2016.07.453
Osti R (2016) Framework, approach and process for investment road mapping: a tool to bridge the theory and practices of flood risk management. Water Policy 18:419–444. https://doi.org/10.2166/wp.2015.121
Papaioannou G, Loukas A, Vasiliades L, Aronica GT (2016) Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach. Nat Hazards 83:S117–S132. https://doi.org/10.1007/s11069-016-2382-1
Party CCotCC (2016) Outline of Yangtze River economic belt development plan. Party CCotCC, Beijing
Pelletier JD, Mayer L, Pearthree PA, House PK, Demsey KA, Klawon JE, Vincent KR (2005) An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing. Geol Soc Am Bull 117:1167–1180. https://doi.org/10.1130/B255440.1
Rahmati O, Zeinivand H, Besharat M (2016) Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis. Geomat Nat Hazards Risk 7:1000–1017. https://doi.org/10.1080/19475705.2015.1045043
Resources CWRCotMoW (2012) The comprehensive planning of Yangtze River Basin (2012–2030). Changjiang Water Resources Commission of the Ministry of Water Resources, Wuhan
Sande CJVD, Jong SMD, Roo APJD (2003) A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment. Int J Appl Earth Obs Geoinf 4:217–229. https://doi.org/10.1016/S0303-2434(03)00003-5
Smith L, Liang Q, James P, Lin W (2017) Assessing the utility of social media as a data source for flood risk management using a real-time modelling framework. J Flood Risk Manag 10:370–380. https://doi.org/10.1111/jfr3.12154
Stefanidis S, Stathis D (2013) Assessment of flood hazard based on natural and anthropogenic factors using analytic hierarchy process (AHP). Nat Hazards 68:569–585. https://doi.org/10.1007/s11069-013-0639-5
Timbadiya PV, Patel PL, Porey PD (2014) A 1D–2D coupled hydrodynamic model for river flood prediction in a coastal urban floodplain. J Hydrol Eng 20:05014017. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001029
Wang W (1998) Urban transportation planning theory and its application. Publishing House of Southeast University, Nanjing
Wang T, Zhou J, Jiang Y, Weng Z, Liu Y, Zhang C (2016) Flood refuge and migration model based on network flow. J Nat Disasters 25:56–64. https://doi.org/10.13577/j.jnd.2016.0107
Winsemius HC et al (2016) Global drivers of future river flood risk. Nat Clim Change 6:381–385. https://doi.org/10.1038/NCLIMATE2893
Zavattero E, Du MX, Ma Q, Delestre O, Gourbesville P (2016) 2d sediment transport modelling in high energy river—application to Var River, France. In: 12th international conference on hydroinformatics (Hic 2016)-smart water for the future, pp 536–543. https://doi.org/10.1016/j.proeng.2016.07.549
Zhang W, Zhou JZ, Liu Y, Chen X, Wang C (2016) Emergency evacuation planning against dike-break flood: a GIS-based DSS for flood detention basin of Jingjiang in central China. Nat Hazards 81:1283–1301. https://doi.org/10.1007/s11069-015-2134-7
Zheng N, Lu F, Duan Y (2010) Dynamic dual graph model for turn delays on road networks. J Image Graph 15:915–920
Zhongmin L, Jun W, Ye S, Zhongbo Y (2008) Study on GIS-based flood risk map for flood detention area. In: Geoinformatics 2008 and joint conference on GIS and built environment: monitoring and assessment of natural resources and environments, Guangzhou, China. SPIE, p 71450F. https://doi.org/10.1117/12.812991
Acknowledgements
This work is supported by the National Natural Science Foundation of China (Nos. 91547208, 51509095 and 51579108).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lu, C., Zhou, J., He, Z. et al. Evaluating typical flood risks in Yangtze River Economic Belt: application of a flood risk mapping framework. Nat Hazards 94, 1187–1210 (2018). https://doi.org/10.1007/s11069-018-3466-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11069-018-3466-x