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Spatial models for flood risk assessment
Author(s) -
Bee Marco,
Benedetti Roberto,
Espa Giuseppe
Publication year - 2008
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.932
Subject(s) - univariate , flood myth , spatial analysis , computer science , estimation , joint probability distribution , econometrics , conditional probability , data mining , statistics , multivariate statistics , mathematics , geography , machine learning , engineering , systems engineering , archaeology
The problem of computing risk measures associated to flood events is extremely important not only from the point of view of civil protection systems but also because of the necessity for the municipalities of insuring against the damages. In this work we propose, in the framework of an integrated strategy, an operating solution which merges in a conditional approach the information usually available in this setup. First, we use a logistic auto‐logistic model (LAM) for the estimation of the univariate conditional probabilities of flood events. This approach has two fundamental advantages: it allows to incorporate auxiliary information and does not require the target variables to be independent. Then we simulate the joint distribution of floodings by means of the Gibbs sampler. Finally, we propose an algorithm to increase ex post the spatial autocorrelation of the simulated events. The methodology is shown to be effective by means of an application to the estimation of the flood probability for two partitions of the Italian territory with different spatial resolution. Copyright © 2008 John Wiley & Sons, Ltd.