Articles | Volume 28, issue 6
https://doi.org/10.5194/hess-28-1287-2024
https://doi.org/10.5194/hess-28-1287-2024
Research article
 | 
22 Mar 2024
Research article |  | 22 Mar 2024

Effects of high-quality elevation data and explanatory variables on the accuracy of flood inundation mapping via Height Above Nearest Drainage

Fernando Aristizabal, Taher Chegini, Gregory Petrochenkov, Fernando Salas, and Jasmeet Judge

Related authors

Non-dendritic hydrologic networks: foundational patterns, algorithms, and a global empirical demonstration
David Blodgett, Taher Chegini, Ryan Gillespie, and Scott Kehoe
EGUsphere, https://doi.org/10.5194/egusphere-2026-6636,https://doi.org/10.5194/egusphere-2026-6636, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
An algorithm for deriving the topology of belowground urban stormwater networks
Taher Chegini and Hong-Yi Li
Hydrol. Earth Syst. Sci., 26, 4279–4300, https://doi.org/10.5194/hess-26-4279-2022,https://doi.org/10.5194/hess-26-4279-2022, 2022
Short summary
Extrapolating continuous vegetation water content to understand sub-daily backscatter variations
Paul C. Vermunt, Susan C. Steele-Dunne, Saeed Khabbazan, Jasmeet Judge, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022,https://doi.org/10.5194/hess-26-1223-2022, 2022
Short summary

Cited articles

Afshari, S., Tavakoly, A. A., Rajib, M. A., Zheng, X., Follum, M. L., Omranian, E., and Fekete, B. M.: Comparison of new generation low-complexity flood inundation mapping tools with a hydrodynamic model, J. Hydrol., 556, 539–556, 2018. a, b, c, d, e, f
Alajo, S. O., Nakavuma, J., and Erume, J.: Cholera in endemic districts in Uganda during El Niño rains: 2002–2003, Afr. Health Sci., 6, 93–97, 2006. a
Archuleta, C.-A. M., Constance, E. W., Arundel, S. T., Lowe, A. J., Mantey, K. S., and Phillips, L. A.: The National Map seamless digital elevation model specifications, Tech. rep., US Geological Survey, https://doi.org/10.3133/tm11B9, 2017. a, b, c
Aristizabal, F.: Data and Software for Effects of High-Quality Elevation Data and Explanatory Variables on the Accuracy of Flood Inundation Mapping via Height Above Nearest Drainage, Hydroshare [code and data set], https://doi.org/10.4211/hs.3d98a9e5a6d84020b72800fd27c87f9a, 2023. a
Aristizabal, F. and Judge, J.: Mapping Fluvial Inundation Extents with Graph Signal Filtering of River Depths Determined from Unsupervised Clustering of Synthetic Aperture Radar Imagery, in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 11–16 July 2021, Brussels, Belgium, 6124–6127, https://doi.org/10.1109/IGARSS47720.2021.9553575, 2021. a, b
Download
Short summary
Floods are significant natural disasters that affect people and property. This study uses a simplified terrain index and the latest lidar-derived digital elevation maps (DEMs) to investigate flood inundation extent quality. We examined inundation quality influenced by different spatial resolutions and other variables. Results showed that lidar DEMs enhance inundation quality, but their resolution is less impactful in our context. Further studies on reservoirs and urban flooding are recommended.
Share
Altmetrics
Final-revised paper
Preprint