Meso-scale hazard zoning of potentially flood prone areas

Raffaele De Risi*, Fatemeh Jalayer, Francesco De Paola

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

25 Citations (Scopus)


Identification of flood-prone areas is a fundamental step for flood risk management. This work focuses on a fast procedure for hazard zoning within the flood-prone areas at a meso-scale in the absence of detailed hydrologic and hydraulic calculations for large areal extents. To this end, a probabilistic methodology for hazard zoning of the potentially flood-prone areas is presented. The main output consists of prompt GIS-compatible maps for the hazard zoning (by flood height) of the potentially flood-prone areas. A flood height-dependent extension of the Topographic Wetness Index (TWI) threshold is proposed as the lower-limit TWI for zones with flood height greater than a given value. This procedure, that starts from a consolidated geomorphic algorithm, relies on calibrating the flood height-dependent TWI threshold through maximum likelihood estimation and inundation maps carried out at micro-scale level for a given spatial window. This calibration is performed for different values of flood depth in order to investigate the correlation between the flood height-dependent TWI threshold and the flood depth conditioned on return period, through simple linear regression. The resulting regression model is used in order to up-scale the results from the micro-scale to the meso-scale level. The procedure is applied for the City of Addis Ababa, Ethiopia and the resulting map of flood hazard zoning is validated for a spatial window not used for calibration purposes.

Original languageEnglish
Pages (from-to)316-325
Number of pages10
JournalJournal of Hydrology
Publication statusPublished - 1 Aug 2015


  • Basin geomorphology
  • Bayesian inference
  • Flood delineation
  • Maximum likelihood parameter estimation
  • Territorial hazard zonation
  • Topographic wetness index


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