Geomorphic floodplain mapping in small Mediterranean catchments using LiDAR data

Deiana C.;Deidda R.;Viola F.
2023-01-01

Abstract

Recent advances in remote sensing technologies along with the increased availability of topographic data have lately encouraged the development of automatic DEM (Digital Elevation Model)-based procedures for floodplain delineation. Geomorphic methods, establishing relationships between flood descriptors and morphologic catchment characteristics, appear particularly suitable to be implemented within a GIS algorithm. In the present work, four simplified geomorphic approaches based on “flow-depth scaling laws” (FD) or “flow-cross-sectional area scaling laws” (FA) with contributing area and two methods employing two different flood descriptors (Hydro-Geomorphic Method, HGM and Geomorphic Flood Index method, GFIM) have been applied for the preliminary evaluation of floodplain extent using high resolution DEMs (i.e. LiDAR at 1 and 2 m resolution) as the main input. Taking as a case study six of the largest basins located in southern Italy, the performances of these methods were evaluated and critically compared using government agency derived flood hazard maps as benchmarks. Results show that the adoption of FD especially when combined with morphology to formulate the GFIM, allows to efficiently predict the flood-prone areas with low computational costs. At the same time, performances of the flood mapping procedures based on “flow-area scaling laws”, although in principle more appealing, seem to be slightly lower. Overall, the proposed approaches can be applied for rough mapping of floodplains in ungauged basins or in data-scarce regions where standard flood hazard maps are unavailable.
2023
Inglese
178
104493
1
12
12
Esperti anonimi
internazionale
scientifica
Digital elevation model; Flood descriptors; Floodplain mapping; Scaling laws
no
Deiana, C.; Deidda, R.; Viola, F.
1.1 Articolo in rivista
info:eu-repo/semantics/article
1 Contributo su Rivista::1.1 Articolo in rivista
262
3
open
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