Although high-resolution digital surface model (DSM) data derived from lidar surveys can describe land surface macrostructures like trees and buildings, digital terrain model (DTM) data obtained by filtering out these macrostructures are commonly used in flood inundation models. In the present study, it is shown for the first time that DSM data can be used directly in flood inundation models by employing automatically-extracted ridges as breaklines for the generation of geomorphologically-informed meshes (GIMs). Even under the simplifying assumption of impermeable macrostructures, especially when GIM refinement is applied, the use of DSM data in preference to DTM data leads to significant improvement in flood predictions. By comparing simulations and observations for a real flood inundation, it is found that the direct use of 1-m DSM data in place of the related DTM data leads to a 42% improvement in predicted flood area, a 36% improvement in predicted flood areal position, and a 25% improvement in predicted times of travel.

Flood plain inundation modeling with explicit description of land surface macrostructures / Pizzileo, Simone; Moretti, Giovanni; Orlandini, Stefano. - In: ADVANCES IN WATER RESOURCES. - ISSN 0309-1708. - 188:6(2024), pp. 1-16. [10.1016/j.advwatres.2024.104713]

Flood plain inundation modeling with explicit description of land surface macrostructures

Pizzileo, Simone;Moretti, Giovanni;Orlandini, Stefano
2024

Abstract

Although high-resolution digital surface model (DSM) data derived from lidar surveys can describe land surface macrostructures like trees and buildings, digital terrain model (DTM) data obtained by filtering out these macrostructures are commonly used in flood inundation models. In the present study, it is shown for the first time that DSM data can be used directly in flood inundation models by employing automatically-extracted ridges as breaklines for the generation of geomorphologically-informed meshes (GIMs). Even under the simplifying assumption of impermeable macrostructures, especially when GIM refinement is applied, the use of DSM data in preference to DTM data leads to significant improvement in flood predictions. By comparing simulations and observations for a real flood inundation, it is found that the direct use of 1-m DSM data in place of the related DTM data leads to a 42% improvement in predicted flood area, a 36% improvement in predicted flood areal position, and a 25% improvement in predicted times of travel.
2024
188
6
1
16
Flood plain inundation modeling with explicit description of land surface macrostructures / Pizzileo, Simone; Moretti, Giovanni; Orlandini, Stefano. - In: ADVANCES IN WATER RESOURCES. - ISSN 0309-1708. - 188:6(2024), pp. 1-16. [10.1016/j.advwatres.2024.104713]
Pizzileo, Simone; Moretti, Giovanni; Orlandini, Stefano
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0309170824001003-main.pdf

Open access

Descrizione: manuscript
Tipologia: Versione pubblicata dall'editore
Dimensione 10.7 MB
Formato Adobe PDF
10.7 MB Adobe PDF Visualizza/Apri
1-s2.0-S0309170824001003-mmc1.pdf

Open access

Descrizione: supporting information
Tipologia: Versione pubblicata dall'editore
Dimensione 11.7 MB
Formato Adobe PDF
11.7 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1338886
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact