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Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach

Author

Listed:
  • G. Papaioannou

    (University of Thessaly)

  • A. Loukas

    (University of Thessaly)

  • L. Vasiliades

    (University of Thessaly)

  • G. T. Aronica

    (University of Messina)

Abstract

An innovative approach in the investigation of complex landscapes for hydraulic modelling applications is the use of terrestrial laser scanner (TLS) that can lead to a high-resolution digital elevation model (DEM). Another notable factor in flood modelling is the selection of the hydrodynamic model (1D, 2D and 1D/2D), especially in complex riverine topographies, that can influence the accuracy of flood inundation area and mapping. This paper uses different types of hydraulic–hydrodynamic modelling approaches and several types of river and riparian area spatial resolution for the implementation of a sensitivity analysis for floodplain mapping and flood inundation modelling process at ungauged watersheds. Four data sets have been used for the construction of the river and riparian areas: processed and unprocessed TLS data, topographic land survey data and typical digitized contours from 1:5000-scale topographic maps. Modelling approaches combinations consist of: one-dimensional hydraulic models (HEC-RAS, MIKE 11), two-dimensional hydraulic models (MIKE 21, MIKE 21 FM) and combinations of coupled hydraulic models (MIKE 11/MIKE 21) within the MIKE FLOOD platform. Historical flood records and estimated flooded area derived from an observed extreme flash-flood event have been used in the validation process using 2 × 2 contingency tables. Flood inundation maps have been generated for each modelling approach and landscape configuration at the lower part of Xerias River reach at Volos, Greece, and compared for assessing the sensitivity of input data and model structure uncertainty. Results provided from contingency table analysis indicate the sensitivity of floodplain modelling on the DEM spatial resolution and the hydraulic modelling approach.

Suggested Citation

  • G. Papaioannou & A. Loukas & L. Vasiliades & G. T. Aronica, 2016. "Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 117-132, October.
    • Handle: RePEc:spr:nathaz:v:83:y:2016:i:1:d:10.1007_s11069-016-2382-1
    DOI: 10.1007/s11069-016-2382-1
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    3. Emrah Yalcin, 2020. "Assessing the impact of topography and land cover data resolutions on two-dimensional HEC-RAS hydrodynamic model simulations for urban flood hazard analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 101(3), pages 995-1017, April.
    4. Peyman Yariyan & Saeid Janizadeh & Tran Phong & Huu Duy Nguyen & Romulus Costache & Hiep Le & Binh Thai Pham & Biswajeet Pradhan & John P. Tiefenbacher, 2020. "Improvement of Best First Decision Trees Using Bagging and Dagging Ensembles for Flood Probability Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 3037-3053, July.
    5. Chengwei Lu & Jianzhong Zhou & Zhongzheng He & Shuai Yuan, 2018. "Evaluating typical flood risks in Yangtze River Economic Belt: application of a flood risk mapping framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(3), pages 1187-1210, December.
    6. Nikunj K. Mangukiya & Ashutosh Sharma, 2022. "Flood risk mapping for the lower Narmada basin in India: a machine learning and IoT-based framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(2), pages 1285-1304, September.
    7. Mayara Maria Arruda Gomes & Lívia Fragoso Melo Verçosa & José Almir Cirilo, 2021. "Hydrologic models coupled with 2D hydrodynamic model for high-resolution urban flood simulation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(3), pages 3121-3157, September.
    8. Neslihan Beden & Asli Ulke Keskin, 2021. "Flood map production and evaluation of flood risks in situations of insufficient flow data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(3), pages 2381-2408, February.
    9. Tewodros Assefa Nigussie & Abdusselam Altunkaynak, 2019. "Modeling the effect of urbanization on flood risk in Ayamama Watershed, Istanbul, Turkey, using the MIKE 21 FM model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(2), pages 1031-1047, November.
    10. Yan Chen & Hao Hou & Yao Li & Luoyang Wang & Jinjin Fan & Ben Wang & Tangao Hu, 2022. "Urban Inundation under Different Rainstorm Scenarios in Lin’an City, China," IJERPH, MDPI, vol. 19(12), pages 1-18, June.
    11. H. Zaifoglu & A. M. Yanmaz & B. Akintug, 2019. "Developing flood mitigation measures for the northern part of Nicosia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(2), pages 535-557, September.

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