Flood risk assessment through large-scale modeling under uncertainty
<p>The complexity of flood risk models is intrinsically linked to a variety of sources of uncertainty (hydrology, hydraulics, exposed assets, vulnerability, coping capacity, etc.) that affect the accuracy and reliability of the analyses. Estimating the uncertainties associated with the differe...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2024-12-01
|
| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://nhess.copernicus.org/articles/24/4507/2024/nhess-24-4507-2024.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846128966412271616 |
|---|---|
| author | L. Pavesi E. Volpi A. Fiori |
| author_facet | L. Pavesi E. Volpi A. Fiori |
| author_sort | L. Pavesi |
| collection | DOAJ |
| description | <p>The complexity of flood risk models is intrinsically linked to a variety of sources of uncertainty (hydrology, hydraulics, exposed assets, vulnerability, coping capacity, etc.) that affect the accuracy and reliability of the analyses. Estimating the uncertainties associated with the different components allows us to be more confident in the risk values on the ground, thus providing a more reliable assessment for investment, insurance and flood risk management purposes. In this study, we investigate the flood risk of the entire Central Apennines District (CAD) in Central Italy using the laRgE SCale inUndation modEl – Flood Risk (RESCUE-FR), focusing on the interaction between the uncertainty in the hydraulic Manning parameter and the risk variability. We assess the coherence between the quantile flood risk maps generated by our model and the official risk maps provided by the Central Apennines District Authority (CAD Authority) and focusing on three specific zones within the CAD region. Thus, RESCUE-FR is used to estimate the expected annual damage (EAD) and the expected annual population affected (EAPA) across the CAD region and to conduct a comprehensive uncertainty analysis. The latter provides a range of confidence of risk estimation that is essential for identifying vulnerable areas and guiding effective mitigation strategies.</p> |
| format | Article |
| id | doaj-art-53ad9341ea254e96893e9124935a0855 |
| institution | Kabale University |
| issn | 1561-8633 1684-9981 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Natural Hazards and Earth System Sciences |
| spelling | doaj-art-53ad9341ea254e96893e9124935a08552024-12-10T11:04:11ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812024-12-01244507452210.5194/nhess-24-4507-2024Flood risk assessment through large-scale modeling under uncertaintyL. Pavesi0E. Volpi1A. Fiori2DICITA, Roma Tre University, Rome, ItalyDICITA, Roma Tre University, Rome, ItalyDICITA, Roma Tre University, Rome, Italy<p>The complexity of flood risk models is intrinsically linked to a variety of sources of uncertainty (hydrology, hydraulics, exposed assets, vulnerability, coping capacity, etc.) that affect the accuracy and reliability of the analyses. Estimating the uncertainties associated with the different components allows us to be more confident in the risk values on the ground, thus providing a more reliable assessment for investment, insurance and flood risk management purposes. In this study, we investigate the flood risk of the entire Central Apennines District (CAD) in Central Italy using the laRgE SCale inUndation modEl – Flood Risk (RESCUE-FR), focusing on the interaction between the uncertainty in the hydraulic Manning parameter and the risk variability. We assess the coherence between the quantile flood risk maps generated by our model and the official risk maps provided by the Central Apennines District Authority (CAD Authority) and focusing on three specific zones within the CAD region. Thus, RESCUE-FR is used to estimate the expected annual damage (EAD) and the expected annual population affected (EAPA) across the CAD region and to conduct a comprehensive uncertainty analysis. The latter provides a range of confidence of risk estimation that is essential for identifying vulnerable areas and guiding effective mitigation strategies.</p>https://nhess.copernicus.org/articles/24/4507/2024/nhess-24-4507-2024.pdf |
| spellingShingle | L. Pavesi E. Volpi A. Fiori Flood risk assessment through large-scale modeling under uncertainty Natural Hazards and Earth System Sciences |
| title | Flood risk assessment through large-scale modeling under uncertainty |
| title_full | Flood risk assessment through large-scale modeling under uncertainty |
| title_fullStr | Flood risk assessment through large-scale modeling under uncertainty |
| title_full_unstemmed | Flood risk assessment through large-scale modeling under uncertainty |
| title_short | Flood risk assessment through large-scale modeling under uncertainty |
| title_sort | flood risk assessment through large scale modeling under uncertainty |
| url | https://nhess.copernicus.org/articles/24/4507/2024/nhess-24-4507-2024.pdf |
| work_keys_str_mv | AT lpavesi floodriskassessmentthroughlargescalemodelingunderuncertainty AT evolpi floodriskassessmentthroughlargescalemodelingunderuncertainty AT afiori floodriskassessmentthroughlargescalemodelingunderuncertainty |