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Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling

机译:水力模型中粗糙度系数不确定性导致未吞吐河道的洪水淹没概率映射

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Probabilistic flood inundation mapping is performed and analysed at the ungauged Xerias stream reach, Volos, Greece. The study evaluates the uncertainty introduced by the roughness coefficient values on hydraulic models in flood inundation modelling and mapping. The well-established one-dimensional (1-D) hydraulic model, HEC-RAS is selected and linked to Monte-Carlo simulations of hydraulic roughness. Terrestrial Laser Scanner data have been used to produce a high quality DEM for input data uncertainty minimisation and to improve determination accuracy on stream channel topography required by the hydraulic model. Initial Manning's n roughness coefficient values are based on pebble count field surveys and empirical formulas. Various theoretical probability distributions are fitted and evaluated on their accuracy to represent the estimated roughness values. Finally, Latin Hypercube Sampling has been used for generation of different sets of Manning roughness values and flood inundation probability maps have been created with the use of Monte Carlo simulations. Historical flood extent data, from an extreme historical flash flood event, are used for validation of the method. The calibration process is based on a binary wet-dry reasoning with the use of Median Absolute Percentage Error evaluation metric. The results show that the proposed procedure supports probabilistic flood hazard mapping at ungauged rivers and provides water resources managers with valuable information for planning and implementing flood risk mitigation strategies.
机译:在希腊沃洛斯的未塞满的Xerias河段进行了概率洪水淹没制图,并进行了分析。该研究评估了洪水淹没建模和制图中水力模型的粗糙度系数值所引入的不确定性。选择了行之有效的一维(1-D)水力模型HEC-RAS,并将其与水力粗糙度的蒙特卡洛模拟相联系。地面激光扫描仪数据已用于生成高质量的DEM,以最小化输入数据的不确定性,并提高水力模型所需的流道地形确定精度。曼宁的初始n粗糙度系数值基于卵石计数现场调查和经验公式。拟合各种理论概率分布并对其准确性进行评估,以表示估计的粗糙度值。最后,拉丁超立方采样已用于生成不同的曼宁粗糙度值集,并且已使用蒙特卡洛模拟创建了洪水泛滥概率图。来自极端历史暴洪事件的历史洪水范围数据用于该方法的验证。校准过程基于二进制干法推理,并使用中位数绝对百分比误差评估指标。结果表明,所提出的程序支持未引流河流的概率性洪水灾害制图,并为水资源管理者提供了有价值的信息,以计划和实施减轻洪水风险的策略。

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