Article
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GeoFlood: Computational Model for Overland Flooding
Version 1
: Received: 15 March 2024 / Approved: 18 March 2024 / Online: 19 March 2024 (06:45:45 CET)
How to cite: Kyanjo, B.; Calhoun, D.; George, D. L. GeoFlood: Computational Model for Overland Flooding. Preprints 2024, 2024031029. https://doi.org/10.20944/preprints202403.1029.v1 Kyanjo, B.; Calhoun, D.; George, D. L. GeoFlood: Computational Model for Overland Flooding. Preprints 2024, 2024031029. https://doi.org/10.20944/preprints202403.1029.v1
Abstract
This paper presents GeoFlood, a new open-source software package for solving shallow water equations (SWE) on a quadtree hierarchy of mapped, logically Cartesian grids managed by the parallel, adaptive library ForestClaw (Calhoun and Burstedde, 2017). The GeoFlood model is validated using standard benchmark tests from Neelz and Pender (2013) and against George (2011) results obtained from the GeoClaw software (Clawpack Development Team, 2020) for the historical Malpasset dam failure problem. The benchmark test results are compared against GeoClaw and software package HEC-RAS (Hydraulic Engineering Center - River Analysis System, Army Corp of Engineers) results (Brunner, 2018). This comparison demonstrates the capability of GeoFlood to accurately and efficiently predict flood wave propagation on complex terrain. The results from comparisons with the Malpasset dam break show good agreement with the GeoClaw results and are consistent with the historical records of the event.
Keywords
Adaptive Mesh Refinement; GeoFlood; p4est; Flood modeling
Subject
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.
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