Global and low-cost topographic data to support flood studies

Kun Yan, Jeffrey C. Neal, Dimitri P. Solomatine, Giuliano Di Baldassarre

Research output: Chapter in Book/Conference proceedings/Edited volumeChapterScientificpeer-review

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This chapter provides an overview of global and low-cost topographic data to support flood studies, with a focus on usefulness of shuttle radar topography mission (SRTM) topography in supporting two-dimensional hydraulic modeling of floods. In particular, flood propagation and inundation modeling of a 10-km reach of the River Dee (United Kingdom) was performed by using LISFLOOD-FP to simulate the December 2006 flood event. Flood extent maps from satellite imagery (ERS-2 Synthetic Aperture Radar SAR) and hydrometric information (downstream water levels) were used as evaluation data. Uncertainty analysis was carried out within the generalized likelihood uncertainty estimation framework using the roughness coefficients and downstream water surface slope as free parameters. The results of this study showed: (1) the potentials and limitations of SRTM topographic data in flood inundation modeling; (2) the value of downstream water levels in constraining uncertainty in hydraulic model of floods; and (3) the impact of setting a water surface slope as downstream boundary on the results of the hydraulic model (e.g., predictions of water stages and flood extent).

Original languageEnglish
Title of host publicationHydro-Meteorological Hazards, Risks, and Disasters
EditorsJohn F. Shroder, Giuliano Di Baldassarre, Paolo Paron
Number of pages18
ISBN (Electronic)9780128191019
Publication statusPublished - 2023

Publication series

NameHazards and Disasters Series

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Flood inundation
  • GLUE
  • SAR
  • SRTM
  • Uncertianty estimation


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