Developing an Ensemble Machine Learning Approach for Enhancing Flood Damage Assessment

IF 2.6 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Mohammad Roohi, Hamid Reza Ghafouri, Seyed Mohammad Ashrafi
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引用次数: 0

Abstract

Climate change has caused fundamental changes in the pattern of rainfall worldwide. Climate change can alter precipitation patterns, consequently intensifying the frequency and severity of flash floods in specific regions, including Iran. It is important for communities to be prepared for these events and to take steps to mitigate their impact. Full control or damage management of the resulted floods through structural measures is not always feasible due to economic, technological, environmental and social limitations. Therefore, often non-structural measures play an important role in reducing probable damages and casualties. The significance of advanced systems for both short- and long-term flood forecasting cannot be overstated. In this article, short-term flood prediction model is discussed using Ensemble Prediction Systems (EPSs) Machine Learning algorithms (ML) and HEC-HMS hydrological model. Also, in order to achieve high accuracy in the assessment of flood-damaged areas, remote sensing techniques have been used. The results show that the use of EPS improves the speed and accuracy of the daily prediction model (R2 = 0.8). Also, with the use of Sentinel-1 radar satellite images and the simultaneous use of supervised learning algorithms, a suitable estimate of the evaded area has been made for seven selected floods in the Kan basin, which is a mountainous region in the north of Tehran, in 2015–2022 period.

Abstract Image

开发增强洪水损害评估的集合机器学习方法
气候变化已导致全球降雨模式发生根本性变化。气候变化会改变降水模式,从而加剧包括伊朗在内的特定地区山洪暴发的频率和严重程度。社区必须做好应对这些事件的准备,并采取措施减轻其影响。由于经济、技术、环境和社会方面的限制,通过结构性措施完全控制或管理所造成的洪灾并不总是可行的。因此,非结构性措施往往在减少可能造成的损失和人员伤亡方面发挥着重要作用。先进的系统对短期和长期洪水预报的重要性怎么强调都不为过。本文讨论了使用集合预测系统(EPS)机器学习算法(ML)和 HEC-HMS 水文模型的短期洪水预测模型。此外,为了实现洪水灾区评估的高精度,还使用了遥感技术。结果表明,EPS 的使用提高了每日预测模型的速度和准确性(R2 = 0.8)。此外,利用哨兵-1 雷达卫星图像并同时使用监督学习算法,对德黑兰北部山区坎盆地 2015-2022 年期间的七次选定洪水进行了适当的回避面积估算。
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来源期刊
CiteScore
5.40
自引率
0.00%
发文量
104
审稿时长
1.7 months
期刊介绍: International Journal of Environmental Research is a multidisciplinary journal concerned with all aspects of environment. In pursuit of these, environmentalist disciplines are invited to contribute their knowledge and experience. International Journal of Environmental Research publishes original research papers, research notes and reviews across the broad field of environment. These include but are not limited to environmental science, environmental engineering, environmental management and planning and environmental design, urban and regional landscape design and natural disaster management. Thus high quality research papers or reviews dealing with any aspect of environment are welcomed. Papers may be theoretical, interpretative or experimental.
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