Accelerating Tsunami Modeling for Evacuation Studies through Modification of the Manning Roughness Values

IF 6.5 3区工程技术 Q1 ENGINEERING, GEOLOGICAL

Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards Pub Date : 2022-10-26 DOI:10.3390/geohazards3040025

Giovanni Cárdenas, P. Catalán

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引用次数: 2

Abstract

The role of the Manning roughness coefficient in modifying a tsunami time series of flow depth inundation was studied in Iquique, Chile, using a single synthetic earthquake scenario. A high-resolution digital surface model was used as a reference configuration, and several bare land models using constant roughness were tested with different grid resolutions. As previously reported, increasing the Manning n value beyond the standard values is essential to reproduce mean statistics such as the inundated area extent and maximum flow depth. The arrival time showed to be less sensitive to changes in the Manning n value, at least in terms of the magnitude of the error. However, increasing the Manning n value too much leads to a critical change in the characteristics of the flow, which departs from its bore-like structure to a more gradual and persistent inundation. It was found that it is possible to find a Manning n value that resembles most features of the reference flow using less resolution in the numerical grids. This allows us to speed up inundation tsunami modeling, which could be useful when multiple inundation simulations are required.

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通过修正曼宁粗糙度值加速海啸模拟疏散研究

在智利伊基克，使用单一的合成地震情景，研究了曼宁粗糙度系数在改变海啸流深淹没时间序列中的作用。采用高分辨率数字地表模型作为参考配置，并在不同网格分辨率下对几种恒定粗糙度裸地模型进行了测试。如前所述，将曼宁n值增加到标准值之外对于再现淹没面积范围和最大水流深度等平均统计数据至关重要。到达时间对曼宁n值的变化不太敏感，至少在误差的大小方面是这样。然而，过多地增加曼宁n值会导致水流特征发生关键变化，从钻孔状结构转向更缓慢和持续的淹没。结果发现，在数值网格中使用较少的分辨率可以找到与参考流的大多数特征相似的曼宁n值。这使我们能够加快洪水海啸建模，这在需要多次洪水模拟时可能很有用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards Multiple-

CiteScore

8.70

自引率

10.40%

发文量

期刊介绍： Georisk covers many diversified but interlinked areas of active research and practice, such as geohazards (earthquakes, landslides, avalanches, rockfalls, tsunamis, etc.), safety of engineered systems (dams, buildings, offshore structures, lifelines, etc.), environmental risk, seismic risk, reliability-based design and code calibration, geostatistics, decision analyses, structural reliability, maintenance and life cycle performance, risk and vulnerability, hazard mapping, loss assessment (economic, social, environmental, etc.), GIS databases, remote sensing, and many other related disciplines. The underlying theme is that uncertainties associated with geomaterials (soils, rocks), geologic processes, and possible subsequent treatments, are usually large and complex and these uncertainties play an indispensable role in the risk assessment and management of engineered and natural systems. Significant theoretical and practical challenges remain on quantifying these uncertainties and developing defensible risk management methodologies that are acceptable to decision makers and stakeholders. Many opportunities to leverage on the rapid advancement in Bayesian analysis, machine learning, artificial intelligence, and other data-driven methods also exist, which can greatly enhance our decision-making abilities. The basic goal of this international peer-reviewed journal is to provide a multi-disciplinary scientific forum for cross fertilization of ideas between interested parties working on various aspects of georisk to advance the state-of-the-art and the state-of-the-practice.