Kyanjo, B.; Calhoun, D.; George, D.L. GeoFlood: Computational Model for Overland Flooding. Preprints2024, 2024031029. https://doi.org/10.20944/preprints202403.1029.v1
APA Style
Kyanjo, B., Calhoun, D., & George, D.L. (2024). GeoFlood: Computational Model for Overland Flooding. Preprints. https://doi.org/10.20944/preprints202403.1029.v1
Chicago/Turabian Style
Kyanjo, B., Donna Calhoun and David L. George. 2024 "GeoFlood: Computational Model for Overland Flooding" Preprints. https://doi.org/10.20944/preprints202403.1029.v1
Abstract
This paper presents GeoFlood, a new open-source software package for solvingshallow water equations (SWE) on a quadtree hierarchy of mapped, logicallyCartesian grids managed by the parallel, adaptive library ForestClaw (Calhounand Burstedde, 2017). The GeoFlood model is validated using standard benchmarktests from Neelz and Pender (2013) and against George (2011) results obtainedfrom the GeoClaw software (Clawpack Development Team, 2020) for the historicalMalpasset dam failure problem. The benchmark test results are compared againstGeoClaw and software package HEC-RAS (Hydraulic Engineering Center - RiverAnalysis System, Army Corp of Engineers) results (Brunner, 2018). Thiscomparison demonstrates the capability of GeoFlood to accurately andefficiently predict flood wave propagation on complex terrain. The results fromcomparisons with the Malpasset dam break show good agreement with the GeoClawresults and are consistent with the historical records of the event.
Computer Science and Mathematics, Computational Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
