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    Navigating Cyclone Threats: A Forecast Approach Using Water Streams’ Physical Characteristics as an Indicator to Predict High Risk Potential Areas in the Sultanate of Oman

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    s41748-024-00392-2.pdf (5.778Mb)
    Date
    2024-04-24
    Author
    Al-Awadhi, Talal
    Abdullah, Meshal
    Al-Ali, Zahraa
    Abulibdeh, Ammar
    Al-Barwani, Mohammed
    Al Nasiri, Noura
    Al-Naabi, Sara
    Mohan, Midhun
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    Abstract
    Tropical cyclone is a natural disaster phenomenon that is considered one of the main challenges for human populations in many countries across the globe. This study investigates the Tropical Cyclone “Shaheen” that hit Oman on October 3, 2021, causing severe damage near Muscat and Al-Batinah governorates. Herein, we focused on developing an integrative method using remote sensing and GIS to understand the streams’ physical characteristics and the main factors that influence flood damage. The results showed that the cyclone had severe impacts on the study area, especially on the urban and agricultural areas. It was illustrated that the disturbance level differed within the study site, as the highest disturbance occurred in zone C where vegetation coverage decreased by 27% and urban areas by 5%. This zone had dam but still showed the highest amount of water flooding, illustrating that the dam couldn’t prevent the flood due to the differences in the physical characteristics of the streams between the different zones. It was also illustrated from the results that variation in the degree of damage was associated with the physical characteristics of the streams, including the length of the stream, the number of stream sub-orders, stream depth, slope degree, and the soil type. Also, locations dominated by loamy and clayey soils with high, steep slopes had a great influence on the water movement, leading to a higher level of disturbance. We concluded that the discovered lines of evidence on the stream's physical characteristics in this study, including the combination of the examined stream's physical factors, could help predict the level of future cyclone risks.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85191241304&origin=inward
    DOI/handle
    http://dx.doi.org/10.1007/s41748-024-00392-2
    http://hdl.handle.net/10576/55713
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    • Humanities [‎155‎ items ]

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