一种评估冰堵塞洪水灾害的随机建模方法的扩展和改进

IF 2.7 4区环境科学与生态学 Q2 Environmental Science

Hydrology Research Pub Date : 2023-01-21 DOI:10.2166/nh.2023.042

K. Lindenschmidt

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引用次数: 1

摘要

2020年春天，位于阿萨巴斯卡河岸边的麦克默里堡镇经历了大约60年来最严重的冰堵塞洪水事件。为了捕捉事件的严重性，作者先前为冰塞洪水预报开发的随机建模方法已被改进，用于冰塞洪水危害和风险评估以及缓解冰塞的可行性研究，这是本文的主题。人工破坏的场景证明了修订后的建模框架的适用性。

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Extension and refinement of a stochastic modelling approach to assess ice-jam flood hazard

In the spring of 2020, the town of Fort McMurray, which lies on the banks of the Athabasca River, experienced an ice-jam flood event that was the most severe in approximately 60 years. In order to capture the severity of the event, a stochastic modelling approach, previously developed by the author for ice-jam flood forecasting, has been refined for ice-jam flood hazard and risk assessments and ice-jam mitigation feasibility studies, which is the subject of this paper. Scenarios of artificial breakage demonstrate the applicability of the revised modelling framework.

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来源期刊

Hydrology Research Environmental Science-Water Science and Technology

CiteScore

5.30

自引率

7.40%

发文量

审稿时长

17 weeks

期刊介绍： Hydrology Research provides international coverage on all aspects of hydrology in its widest sense, and welcomes the submission of papers from across the subject. While emphasis is placed on studies of the hydrological cycle, the Journal also covers the physics and chemistry of water. Hydrology Research is intended to be a link between basic hydrological research and the practical application of scientific results within the broad field of water management.