Back to Search
Start Over
Probabilistic assessment of failure of infiltration structures under model and parametric uncertainty.
- Source :
-
Journal of environmental management [J Environ Manage] 2023 Oct 15; Vol. 344, pp. 118466. Date of Electronic Publication: 2023 Jul 06. - Publication Year :
- 2023
-
Abstract
- We focus on the quantification of the probability of failure (PF) of an infiltration structure, of the kind that is typically employed for the implementation of low impact development strategies in urban settings. Our approach embeds various sources of uncertainty. These include (a) the mathematical models rendering key hydrological traits of the system and the ensuing model parametrization as well as (b) design variables related to the drainage structure. As such, we leverage on a rigorous multi-model Global Sensitivity Analysis framework. We consider a collection of commonly used alternative models to represent our knowledge about the conceptualization of the system functioning. Each model is characterized by a set of uncertain parameters. As an original aspect, the sensitivity metrics we consider are related to a single- and a multi-model context. The former provides information about the relative importance that model parameters conditional to the choice of a given model can have on PF. The latter yields the importance that the selection of a given model has on PF and enables one to consider at the same time all of the alternative models analyzed. We demonstrate our approach through an exemplary application focused on the preliminary design phase of infiltration structures serving a region in the northern part of Italy. Results stemming from a multi-model context suggest that the contribution arising from the adoption of a given model is key to the quantification of the degree of importance associated with each uncertain parameter.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2023 Elsevier Ltd. All rights reserved.)
- Subjects :
- Uncertainty
Probability
Italy
Models, Theoretical
Subjects
Details
- Language :
- English
- ISSN :
- 1095-8630
- Volume :
- 344
- Database :
- MEDLINE
- Journal :
- Journal of environmental management
- Publication Type :
- Academic Journal
- Accession number :
- 37421819
- Full Text :
- https://doi.org/10.1016/j.jenvman.2023.118466