Open AccessEstimation of probabilistic flood inundation maps for an extreme event: P ánuco River, M éxico
Author(s) -
PedrozoAcuña A.,
RodríguezRincón J.P.,
ArganisJuárez M.,
DomínguezMora R.,
González Villareal F.J.
Publication year - 2015
Publication title -
journal of flood risk management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.049
H-Index - 36
ISSN - 1753-318X
DOI - 10.1111/jfr3.12067
Subject(s) - flood myth , hydrograph , storm , environmental science , precipitation , probabilistic logic , drainage basin , hydrology (agriculture) , hydrological modelling , tropical cyclone , estimation , flood forecasting , meteorology , event (particle physics) , climatology , geography , geology , statistics , mathematics , cartography , physics , archaeology , geotechnical engineering , management , quantum mechanics , economics
This investigation evaluates the effects of hydrological uncertainty in the results of flood extent estimates during the incidence of a tropical storm. For this, the methodology is comprised of field measurements, elevation data, a distributed hydrological model and a standard two‐dimensional numerical model. Uncertainty is considered in the distributed hydrological model through the estimation of possible hydrographs from precipitation data registered during the incidence of an extreme event. The characterisation of the run‐off by multiple possibilities opens the door to a probabilistic estimation of flood maps, enabling the consideration of hydrological uncertainties and their propagation to an estimated flood extension. It is shown that during the incidence of the tropical storm A rlene, the estimated flooded area is similar to what was registered by satellite imagery. Although the methodology does not consider all the uncertainties that may be involved in the determination of a flooded area, it is reflected that it favours the preventive action in the generation of flood management strategies. The selected approach is a first iteration in the production of a fully quantified approach to the analysis of flood risk, especially where there are doubts about how the catchment responds to a given extreme precipitation event.