Delineación probabilística de áreas inundables basada en modelos digitales de elevaciones e inundaciones históricas: El caso de Ouagadougou

Translated title of the contribution: Probabilistic delineation of flood-prone areas based on a digital elevation model and the extent of historical flooding: The case of ouagadougou

R. De Risi*, F. Jalayer, F. De Paola, M. Giugni

*Corresponding author for this work

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

27 Citations (Scopus)

Abstract

The delineation of food-prone areas is one of the most important steps for food risk assessment and mitigation. This study uses a probabilistic and DEM-based framework for the delineation of food-prone areas based on information about the extent of historical flooding in the area of interest. This is particularly useful for the delineation of food-prone areas in cases where more accurate hydraulic profile calculations are not available. The delineation of food-prone areas is carried out by using the Topographic Wetness Index (TWI) which allows for the delineation of a portion of a hydrographic basin potentially exposed to flooding by identifying all the areas characterized by a topographic index that exceeds a given threshold. A Bayesian updating framework is used for estimating the TWI threshold for identifying the food-prone areas based on available information on the spatial extent of historical flooding. An application of the proposed method is demonstrated for the delineation of potentially food-prone areas in the city of Ouagadougou, based on the observed spatial extent of the 2009 flooding event in the city.

Translated title of the contributionProbabilistic delineation of flood-prone areas based on a digital elevation model and the extent of historical flooding: The case of ouagadougou
Original languageSpanish
Pages (from-to)329-340
Number of pages12
JournalBoletin Geologico y Minero
Volume125
Issue number3
Publication statusPublished - 1 Jan 2014

Keywords

  • Africa
  • Bayesian parameter estimation
  • Food-prone areas
  • GIS
  • Topographic wetness index

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