Assessing Flood Risk Dynamics in Southern Laos: A Comparative Analysis of HEC-RAS, Empirical and Physically Based Froude Number Models along the Xekaman River

Ketsana Phommavong, Jianguo Yan, Chikondi Chisenga and Shoukat Ali Shah
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Ketsana Phommavong: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, P. R. China
Jianguo Yan: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, P. R. China†Xinjiang Astronomical Observatory, Chinese Academy of Sciences, Urumqi 830011, P. R. China
Chikondi Chisenga: ��State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Box 129, Luoyu Road, Wuhan 430079, P. R. China§Department of Earth Sciences, Ndata School of Climate and Earth Sciences, Malawi University of Science and Technology, P. O. Box 5196, Limbe, Malawi
Shoukat Ali Shah: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, P. R. China¶Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, P. R. China

Chinese Journal of Urban and Environmental Studies (CJUES), 2025, vol. 13, issue 02, 1-31

Abstract: Flooding, intensified by climate change, urbanization, and unsustainable land use, presents a significant danger to riverine communities, especially in Southeast Asia. This study analyzes flood dynamics along the Xekaman River in Attapeu Province, Laos, employing the empirical Froude number (EFR) and physically based Froude number (PBF) models, in conjunction with Hydrologic Engineering Center’s River Analysis System (HEC-RAS), to evaluate river flow and flood risk over 72h in 2022. The EFR model achieves a peak flow velocity of 15m/s at 12h, whereas the PBF model reaches 10.96m/s. At 72h, peak velocities increase to 75 and 109.97m/s, respectively, demonstrating substantial disparities in flow conditions. The EFR model offers a wider distribution of flood risk, while the PBF model delivers a more accurate representation of extreme flood events. HEC-RAS improves analysis by providing comprehensive floodplain delineation, variations in water depth, and distribution of flow velocity, thereby enhancing the spatial precision of flood risk evaluations. These findings highlight the necessity of incorporating various modeling methods to enhance flood risk assessments and monitoring, and optimize mitigation initiatives in flood-prone areas.

Keywords: Flood risk assessment; HEC-RAS modeling; Froude number; flow velocity; climate change (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S2345748125500137

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