Version 1
: Received: 23 July 2024 / Approved: 23 July 2024 / Online: 23 July 2024 (16:43:31 CEST)
How to cite:
Louis, R.; Zech, Y.; Joseph, A.; Gonomy, N.; Soares-Frazao, S. Flood Modelling of June 2023 Flooding of Léogâne City by the Overflow of the Rouyonne River (Haiti). Preprints2024, 2024071812. https://doi.org/10.20944/preprints202407.1812.v1
Louis, R.; Zech, Y.; Joseph, A.; Gonomy, N.; Soares-Frazao, S. Flood Modelling of June 2023 Flooding of Léogâne City by the Overflow of the Rouyonne River (Haiti). Preprints 2024, 2024071812. https://doi.org/10.20944/preprints202407.1812.v1
Louis, R.; Zech, Y.; Joseph, A.; Gonomy, N.; Soares-Frazao, S. Flood Modelling of June 2023 Flooding of Léogâne City by the Overflow of the Rouyonne River (Haiti). Preprints2024, 2024071812. https://doi.org/10.20944/preprints202407.1812.v1
APA Style
Louis, R., Zech, Y., Joseph, A., Gonomy, N., & Soares-Frazao, S. (2024). Flood Modelling of June 2023 Flooding of Léogâne City by the Overflow of the Rouyonne River (Haiti). Preprints. https://doi.org/10.20944/preprints202407.1812.v1
Chicago/Turabian Style
Louis, R., Nyankona Gonomy and Sandra Soares-Frazao. 2024 "Flood Modelling of June 2023 Flooding of Léogâne City by the Overflow of the Rouyonne River (Haiti)" Preprints. https://doi.org/10.20944/preprints202407.1812.v1
Abstract
Evaluating flood risk though numerical simulations in areas where hydrometric and bathymetric data are scarcely available is a challenge. This is however of paramount importance, particularly in urban areas, where huge losses of human life and extensive damage can occur. This paper focuses on the June 2-3, 2023 event at Léogâne in Haiti, where the Rouyonne River partly flooded the city. Water depths in the river were recorded since April 2022 and a few discharges were measured manually but it was not sufficient to produce a reliable rating curve. Using a uniform flow assumption combined with the BaRatin method (Bayesian rating curve), it was possible to extrapolate the existing data to higher discharges. From there, a rainfall-runoff relation was developed for the site using the AtHyS distributed hydrological model, which allowed to determine the discharge of the June 2023 event, which was estimated as twice the maximum conveying capacity of the river in the measurement section. Bathymetric data were obtained using drone-based photogrammetry and two-dimensional simulations were carried out using the WATLAB computational environment to represent the flooded area and the associated water depths. By comparing the water depths of 21 measured high-water marks with the simulation results, we obtain KGE and NSE criteria of, respectively, 0.890 and 0.882. This allows us to conclude that the model is sufficiently accurate and could be used by flood managers and decision-makers to assess flood risk and vulnerability in Haiti.
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.
