Journal of Geographical Sciences ›› 2020, Vol. 30 ›› Issue (10): 1649-1663.doi: 10.1007/s11442-020-1805-9

• Research Articles • Previous Articles     Next Articles

Using LiDAR-DEM based rapid flood inundation modelling framework to map floodplain inundation extent and depth

ZHANG Yongqiang()   

  1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2020-03-10 Accepted:2020-07-10 Online:2020-10-25 Published:2020-10-27
  • About author:Zhang Yongqiang, PhD, E-mail:
  • Supported by:
    CAS Talents Program and IGSNRR Supporting Fund, No(YJRCPT2019-101)


Mapping floods is important for policy makers to make timely decisions in regards to emergency responses and future planning. It is therefore crucial to develop a rapid inundation modelling framework to map flood inundation. This study develops an airborne scanning laser altimetry (LiDAR) digital elevation model (DEM) based Rapid flood Inundation Modelling framework (LiDAR-RIM) for assessment of inundation extent, depth, volume and duration for flood events. The modelling framework has been applied to the mid-Murrumbidgee region in the southeast Murray-Darling Basin, Australia for two flood events occurred in December 2010 and March 2012. The inundation extents estimated using this methodology compared well to those obtained from two Landsat ETM+ images, demonstrating suitability and applicability of this method. For testing possibility of larger area application, the framework also uses 30-m resolution shuttle radar topography mission (SRTM)-DEM to replace LiDAR-DEM for the same modelling. The inundation extents obtained by using the SRTM-DEM are smaller than those obtained using the LiDAR-DEM, especially for large flood events. A possible reason is that the river cross sections obtained from the SRTM-DEM are not accurate enough for inundation modelling. The LiDAR-RIM has an advantage for process modelling and scenario modelling under future climatic conditions.

Key words: inundation modelling, DEM, LiDAR, floodplain, hydraulic, remote sensing