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Method for fluvial and pluvial flood risk assessment in rural settlements

Authors :
Maurizio Tiepolo
Elena Belcore
Sarah Braccio
Souradji Issa
Giovanni Massazza
Maurizio Rosso
Vieri Tarchiani
Source :
MethodsX, Vol 8, Iss , Pp 101463- (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

Flood risk assessments in the Global South have increased since the adoption of the United Nations Sendai Framework for Disaster Risk Reduction 2015–2030. However, they often fail to meet disaster risk reduction needs at the local scale, because they typically consider only one hazard (fluvial or pluvial floods). Furthermore, hazard and exposure are considered as stationary conditions, flood-prone assets are rarely identified, risk reduction measures are not identified in detail for specific locations, and the convenience of reducing or accepting risk is not evaluated. This paper describes a flood risk assessment method that is innovative in that it considers three hazard types (backwater, fluvial, and pluvial floods) and multiple risk scenarios; it uses orthophotos generated from images captured by an unmanned aerial vehicle and very high-resolution satellite images, and it involves communities in risk assessment. The method was applied to four rural settlements along the Sirba River, Niger. The assessment identifies the benefit of reducing risk in monetary terms, as well as the intangible benefits that reducing risk could generate, and it detects opportunities that flooding offers for rural development. The method can be replicated in all contexts where decision-making support is needed for flood risk assessment planning. • Risk analysis and evaluation is participatory. • Risk assessment is improved by combining local and technical knowledge. • Assets are identified using very-high-resolution satellite and drone images.

Details

Language :
English
ISSN :
22150161
Volume :
8
Issue :
101463-
Database :
Directory of Open Access Journals
Journal :
MethodsX
Publication Type :
Academic Journal
Accession number :
edsdoj.f8b3f85a08b642aaa3b0e04a8bea7f08
Document Type :
article
Full Text :
https://doi.org/10.1016/j.mex.2021.101463