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Water Resources Management

, Volume 29, Issue 8, pp 2619–2636 | Cite as

Rapid Inundation Modelling in Large Floodplains Using LiDAR DEM

  • J. Teng
  • J. Vaze
  • D. DuttaEmail author
  • S. Marvanek
Article

Abstract

Rapid and accurate inundation modelling in large floodplains is critical for emergency response and environmental management. This paper describes the development and implementation of a floodplain inundation model that can be used for rapid assessment of inundation in very large floodplains. The model uses high resolution DEM (such as LiDAR DEM) to derive floodplain storages and connectivity between them at different river stages. We tested the performance of the model across several large floodplains in southeast Australia for estimating floodplain inundation extent, volume, and water depth for a few recent flood events. The results are in good agreement with those obtained from high resolution satellite imageries and MIKE 21 two-dimensional hydrodynamic model. The model performed particularly well in the reaches that have confined channels with above 85 % agreement with the flood maps derived from Landsat TM imagery in cell-to-cell comparison. While the model did not performance as well in the flat and complex floodplains, the overall level of agreement of the modelled inundation maps with the satellite flood maps was still satisfactory (60–75 %). The key advantage of this model is demonstrated by its capability to simulate inundation in large floodplains (over 2000 km2) at a very high resolution of 5-m with more than 81 million cells at a reasonably low computational cost. The model is suitable for practical floodplain inundation simulation and scenario modelling under current and future climate conditions.

Keywords

Rapid inundation modelling LiDAR DEM Floodplain TVD model Hydrodynamic modelling Flood emergency response 

Notes

Compliance with Ethical Standards

Funding

This study was undertaken as part of the Australian Water resource Assessment (AWRA) project and was funded by the Land and Water Flagship, CSIRO and the Australian Bureau of Meteorology (BoM) under the WIRADA alliance between CSIRO and BoM.

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. Abbott MM (1973) Cubic equations of state. AICHE J 19(3):596–601CrossRefGoogle Scholar
  2. Bates PD, De Roo APJ (2000) A simple raster-based model for flood inundation simulation. J Hydrol 236(1–2):54–77Google Scholar
  3. Bates PD, Horritt MS, Smith CN, Mason D (1997) Integrating remote sensing observations of flood hydrology and hydraulic modelling. Hydrol Process 11(14):1777–1795CrossRefGoogle Scholar
  4. Bates PD, Horritt MS, Fewtrell TJ (2010) A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. J Hydrol 387(1–2):33–45CrossRefGoogle Scholar
  5. Bhuiyan M, Dutta D (2012) Analysis of flood vulnerability and assessment of the impacts in coastal zones of Bangladesh due to potential sea-level rise. Nat Hazards 61(2):729–743CrossRefGoogle Scholar
  6. DHI (2012) MIKE 21 - 2D modelling of coast and sea, DHI Water & Environment Pty Ltd., http://www.dhisoftware.com/Products/CoastAndSea/MIKE21.aspx, accessed on 25 August 2012
  7. Di Baldassarre G, Montanari A, Lins H, Koutsoyiannis D, Brandimarte L, Blöschl G (2010) Flood fatalities in Africa: from diagnosis to mitigation. Geophys Res Lett 37(22):L22402CrossRefGoogle Scholar
  8. Dottori F, Di Baldassarre G, Todini E (2013) Detailed data is welcome, but with a pinch of salt: accuracy, precision, and uncertainty in flood inundation modeling. Water Resour Res 49(9):6079–6085CrossRefGoogle Scholar
  9. Dutta D, Nakayama K (2009) Effects of spatial grid resolution oil river flow and surface inundation simulation by physically based distributed modelling approach. Hydrol Process 23(4):534–545CrossRefGoogle Scholar
  10. Dutta D, Herath S, Musiake K (2006) An application of a flood risk analysis system for impact analysis of a flood control plan in a river basin. Hydrol Process 20(6):1365–1384CrossRefGoogle Scholar
  11. Dutta D, Alam J, Umeda K, Hayashi M, Hironaka S (2007) A two-dimensional hydrodynamic model for flood inundation simulation: a case study in the lower Mekong river basin. Hydrol Process 21(9):1223–1237CrossRefGoogle Scholar
  12. Dutta D, Welsh W, Vaze J, Kim S, Nicholls D (2012) A comparative evaluation of short-term streamflow forecasting using time series analysis and rainfall-runoff models in eWater Source. Water Resour Manag 26(15):4397–4415CrossRefGoogle Scholar
  13. Dutta D, Teng J, Vaze J, Lerat J, Hughes J, Marvanek S (2013a) Storage-based approaches to build floodplain inundation modelling capability in river system models for water resources planning and accounting. J Hydrol 504:12–28CrossRefGoogle Scholar
  14. Dutta D, Teng J, Vaze J, Hughes J, Lerat J, Marvanek S (2013b) Building flood inundation modelling capability in river system models for water resources planning and accounting, in climate and land surface changes in hydrology, IAHS Red Book. By Boegh E, Blyth E, Hannah DM, Hisdal H, Kunstmann H, Su B, Yilmaz KK (eds) pp. 205–212, IAHS PublicationGoogle Scholar
  15. Gallant JC (2003) A multiresolution index of valley bottom flatness for mapping depositional areas multiresolution valley bottom flatness. Water Resour Res 39(12):1347Google Scholar
  16. Gao BC (1996) NDWI—a normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens Environ 58(3):257–266CrossRefGoogle Scholar
  17. Horritt MS (1999) A statistical active contour model for SAR image segmentation. Image Vis Comput 17(3–4):213–224CrossRefGoogle Scholar
  18. Hughes J, Dutta D, Kim S, Vaze J, Podger G (2014) An automated multi-step calibration procedure for a river system model. Environ Model Software 51:173–183CrossRefGoogle Scholar
  19. Karim F, Dutta D, Mavanek S, Petheram C, Ticehurst C, Lerat J, Kim S, Yang A (2015) Assessing impacts of climate change and water resources development on floodplains and wetlands in the Flinders and Gilbert Catchments, Australia. J Hydrol 522:80–94CrossRefGoogle Scholar
  20. Lhomme J, Sayers P, Gouldby B, Samuels P, Wills M, Mulet-Marti J (2008) Recent development and application of a rapid flood spreading method, in Proceedings of FLOODrisk 2008, Keble College, Oxford, UK, 30 September to 2 October 2008Google Scholar
  21. Nardi F, Vivoni ER, Grimaldi S (2006) Investigating a floodplain scaling relation using a hydrogeomorphic delineation method. Water Resour Res 42(9):W09409Google Scholar
  22. NASA (2012) The thematic mapper, national aeronautics and space administration, http://landsat.gsfc.nasa.gov/about/tm.html, accessed on 03 September 2013
  23. Néelz S (2009) Desktop review of 2D hydraulic modelling packages. Environment Agency, BristolGoogle Scholar
  24. Powell SJ, Letcher RA, Croke BFW (2008) Modelling floodplain inundation for environmental flows: Gwydir wetlands, Australia. Ecol Model 211(3–4):350–362CrossRefGoogle Scholar
  25. Priestnall G, Jaafar J, Duncan A (2000) Extracting urban features from LiDAR digital surface models. Comput Environ Urban Syst 24(2):65–78CrossRefGoogle Scholar
  26. Pulvirenti L, Chini M, Pierdicca N, Guerriero L, Ferrazzoli P (2011) Flood monitoring using multi-temporal COSMO-SkyMed data: image segmentation and signature interpretation. Remote Sens Environ 115(4):990–1002CrossRefGoogle Scholar
  27. Smith LC (1997) Satellite remote sensing of river inundation area, stage, and discharge: a review. Hydrol Process 11(10):1427–1439CrossRefGoogle Scholar
  28. Teng J, Vaze J, Tuteja NK, Gallant JC (2008) A GIS-based tool for spatial and distributed hydrological modelling: CLASS spatial analyst. Trans GIS 12(2):209–225CrossRefGoogle Scholar
  29. Teng J, Vaze J, Dutta D (2013) Simplified methodology for floodplain inundation modelling using LiDAR DEM, in Climate and land surface changes in hydrology, IAHS Red Book, by Boegh E, Blyth E, Hannah DM, Hisdal H, Kunstmann H, Su B, Yilmaz KK (eds) pp. 198–204, IAHS PublicationGoogle Scholar
  30. Thompson JR, Sorenson HR, Gavin H, Refsgaard A (2004) Application of the coupled MIKE SHE/MIKE 11 modelling system to a lowland wet grassland in southeast England. J Hydrol 293(1–4):151–179CrossRefGoogle Scholar
  31. Tsakiris G, Bellos V (2014) A numerical model for two-dimensional flood routing in complex terrains. Water Resour Manag 28(5):1277–1291CrossRefGoogle Scholar
  32. Vaze J, Teng J, Spencer G (2010) Impact of DEM accuracy and resolution on topographic indices. Environ Model Software 25(10):1086–1098CrossRefGoogle Scholar
  33. Vaze J, Davidson A, Teng J, Podger G (2011) Impact of climate change on water availability in the Macquarie-Castlereagh River Basin in Australia. Hydrol Process 25(16):2597–2612CrossRefGoogle Scholar
  34. Vaze J et al (2013) The Australian Water Resource Assessment System (AWRA). In Proceedings of the 20th International Congress on Modelling and Simulation (MODSIM2013), edited, Adelaide, AustraliaGoogle Scholar
  35. Welsh WD et al (2013) An integrated modelling framework for regulated river systems. Environ Model Software 39:81–102CrossRefGoogle Scholar
  36. Williams WA (2000) An automated technique for delineating and characterizing valley-bottom settings. Environ Monit Assess 64(1):105–114CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.CSIRO Land and Water FlagshipCanberraAustralia
  2. 2.CSIRO Land and Water FlagshipUrrbraeAustralia

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