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Remote Sensing with UAVs for Flood Modeling: A Validation with Actual Flood Records
Abstract
The use of unmanned aerial vehicles (UAVs) is steadily increasing due to their capacity to capture terrain elevation data with remarkable precision and cost-effectiveness. Nonetheless, their application for estimating water surface elevations and submerged terrain, such as channel bathymetry, remains constrained. Consequently, the development of a digital terrain model that relies on UAV data during low-water periods assumes a more extensive dry channel surface area, thus alleviating the information gap regarding submerged terrain. The objective of this brief report is to validate a hydraulic model for flood calculation. To this end, a 1D steady-state hydrological model of the Ñuble River based on a UAV survey in the low-water period of 2016 was constructed in HEC-RAS v.5.0.3 and compared to water surface elevation observations of the flood on 24 June 2023. The model tends to overestimate the flood, but the errors are considered tolerable for flood calculation (on average, a 10.6% depth error was obtained for a 30-year return period flood); therefore, the hydraulic model derived from remote sensing seems to be an effective alternative for the construction of hydraulic models for flood studies.
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“Water surface area was consistently minimal (60 m 2 ), suggesting negligible hydrological influence on these phenological shifts 26 .”
From AI-driven digital twinning quantifies the trade-off between flood conveyance and riparian stability under climate extremes (2026) · cites this paper as [26]
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Cited by
Shin, J. H., Go, S. H., & Park, J. H. (2026) · Scientific Reports · doi:10.1038/s41598-026-63704-8
Metadata
- Authors
- Clasing, R., Muñoz, E., Arumí, J. L., & Parra, V.
- Affiliations
- Department of Civil Engineering, Universidad Católica de la Santísima Concepción, Concepción 4090541, Chile
- Department of Water Resources, Universidad de Concepción, Chillán 3812120, Chile
- Department of Envioromental Engineering, Universidad de Concepción, Concepción 4070386, Chile
- Venue
- Water
- Publisher
- MDPI AG
- Published
- 2023-10-31
- Volume
- 15
- Issue
- 21
- Pages
- 3813
- ISSN
- 2073-4441
- Cited by
- 16
- References
- 60
- Language
- en
- Funders
- CIBAS 2019-01 (DI-FME 03/2021, ANID/FONDAP/15130015)
- CRHIAM Center (DI-FME 03/2021, ANID/FONDAP/15130015)
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