2023 年 6 月海地鲁约讷河泛滥导致莱奥甘市洪水泛滥的洪水模拟

IF 3 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES Water Pub Date : 2024-09-13 DOI:10.3390/w16182594
Rotchild Louis, Yves Zech, Adermus Joseph, Nyankona Gonomy, Sandra Soares-Frazao
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引用次数: 0

摘要

在缺乏水文和测深数据的地区,通过数值模拟评估洪水风险是一项挑战。然而,这一点至关重要,尤其是在可能造成巨大人员伤亡和广泛破坏的城市地区。本文重点介绍 2023 年 6 月 2-3 日在海地莱奥甘发生的事件,当时鲁永河部分淹没了城市。自 2022 年 4 月以来,该河流的水深一直有记录,并且人工测量了一些排水量,但这些都不足以绘制出可靠的等级曲线。利用均匀流量假设结合贝叶斯等级曲线(BaRatin)方法,可以将现有数据推断为更高的排水量。在此基础上,利用分布式水文模型为该地点建立了降雨-径流关系,从而确定了 2023 年 6 月事件的排水量,估计为测量断面河流最大输送能力的两倍。利用无人机摄影测量获得了水深数据,并进行了二维模拟,以表示洪水淹没区域和相关水深。通过比较 21 个实测高水位线的水深和模拟结果,我们得出克林-古普塔效率(KGE)和纳什-苏特克里夫效率(NSE)值分别为 0.890 和 0.882。由此我们可以得出结论,即使只有稀缺的官方数据,也可以利用低成本方法获得的实地数据建立一个足够准确的模型,供洪水管理者和决策者用来评估海地的洪水风险和脆弱性。
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Flood Modeling of the June 2023 Flooding of Léogâne City by the Overflow of the Rouyonne River in Haiti
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 2–3 June 2023 event at Léogâne in Haiti, where the Rouyonne River partly flooded the city. Water depths in the river have been recorded since April 2022, and a few discharges were measured manually, but these were not sufficient to produce a reliable rating curve. Using a uniform-flow assumption combined with the Bayesian rating curve (BaRatin) method, it was possible to extrapolate the existing data to higher discharges. From there, a rainfall–runoff relation was developed for the site using a distributed hydrological model, which allowed the discharge of the June 2023 event to be determined, 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 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 obtained a Kling–Gupta Efficiency (KGE) and Nash–Sutcliffe Efficiency (NSE) values of 0.890 and 0.882, respectively. This allows us to conclude that even when only scarce official data are available, it is possible to use field data acquired by low-cost methodologies to build a model that is sufficiently accurate and that can be used by flood managers and decision makers to assess flood risk and vulnerability in Haiti.
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来源期刊
Water
Water WATER RESOURCES-
CiteScore
5.80
自引率
14.70%
发文量
3491
审稿时长
19.85 days
期刊介绍: Water (ISSN 2073-4441) is an international and cross-disciplinary scholarly journal covering all aspects of water including water science and technology, and the hydrology, ecology and management of water resources. It publishes regular research papers, critical reviews and short communications, and there is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles. Computed data or files regarding the full details of the experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.
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