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    Flood Seasonality Analysis in Iran: A Circular Statistics Approach

    Source: Journal of Hydrologic Engineering:;2023:;Volume ( 028 ):;issue: 002::page 04022039-1
    Author:
    Mehdi Bagheri-Gavkosh
    ,
    Seiyed Mossa Hosseini
    DOI: 10.1061/JHYEFF.HEENG-5786
    Publisher: American Society of Civil Engineers
    Abstract: Flood seasonality (FS) analysis is a key to delineating hydrologically homogenous regions and better understanding flood risk, especially for arid regions. Although Iran has undergone heavy floods in current decades, a quantitative spatially distributed overview of the flood seasonality and the its affected mechanisms is currently unavailable. This study aimed in seasonality analysis of annual maximum flood with average recurrence of 2 to 500 years in 291 continuous hydrometric stations across Iran having sufficient recorded flood data (>20  years, total of 9,565 events) using a circular statistics approach. Moreover, the relationships of recurrence season of floods with eight natural and human-induced factors including catchment area, catchment perimeter, mean catchment slope, normalized difference vegetation index (NDVI), elevation of station, mean slope of river, and latitude were examined. Findings showed that flooding in Iran presents strong seasonality, with 32% and 41% of the total events occurring during winter and spring, and mostly during April (24%). Although summer floods (∼11%) are more frequent in the northern parts, winter floods present higher percentages in the south. A significant difference in flood seasonality (2 to 500 years) was identified between the northern and southeastern regions. This study suggests that the geographical location (especially latitude) of the hydrometric station in Iran seems to be more significant than other considered factors in shaping flood seasonality. Results can serve as a foundation for enhancing the scientific understanding of the flood seasonality across Iran, which can provide useful insights for flood prevention planning and future changes projected by models. Flooding is one of most damaging phenomena around the globe that affect humans’ life and economy. So, in order to decrease the dire consequences of flooding, especially in arid zones like Iran, we should increase our knowledge about flood risk by using advanced techniques like flood seasonality analysis. This research is a specific survey at a nationwide scale for enhancing the scientific understanding of the flood timing across Iran, which can provide useful insights for future planning and practical engineering designs. The purpose of this research is the study of seasonality analysis of annual maximum flood in 291 continuous hydrometric stations across Iran with a total of 9,565 events using a circular statistics approach. Owing to the prominent role of humanity and nature on flooding, eight natural and human-induced factors have been surveyed. The results of this study illustrated that 32% and 41% of the total events occurred during winter and spring, mostly during April (24%). What is further noticeable is that a significant difference in flood seasonality was identified between the northern and southeastern regions. Among considered factors in shaping seasonality of flooding, the geographical location (especially latitude) of the hydrometric station in Iran seems to be more significant than other factors.
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      Flood Seasonality Analysis in Iran: A Circular Statistics Approach

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4292795
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    contributor authorMehdi Bagheri-Gavkosh
    contributor authorSeiyed Mossa Hosseini
    date accessioned2023-08-16T19:07:32Z
    date available2023-08-16T19:07:32Z
    date issued2023/02/01
    identifier otherJHYEFF.HEENG-5786.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292795
    description abstractFlood seasonality (FS) analysis is a key to delineating hydrologically homogenous regions and better understanding flood risk, especially for arid regions. Although Iran has undergone heavy floods in current decades, a quantitative spatially distributed overview of the flood seasonality and the its affected mechanisms is currently unavailable. This study aimed in seasonality analysis of annual maximum flood with average recurrence of 2 to 500 years in 291 continuous hydrometric stations across Iran having sufficient recorded flood data (>20  years, total of 9,565 events) using a circular statistics approach. Moreover, the relationships of recurrence season of floods with eight natural and human-induced factors including catchment area, catchment perimeter, mean catchment slope, normalized difference vegetation index (NDVI), elevation of station, mean slope of river, and latitude were examined. Findings showed that flooding in Iran presents strong seasonality, with 32% and 41% of the total events occurring during winter and spring, and mostly during April (24%). Although summer floods (∼11%) are more frequent in the northern parts, winter floods present higher percentages in the south. A significant difference in flood seasonality (2 to 500 years) was identified between the northern and southeastern regions. This study suggests that the geographical location (especially latitude) of the hydrometric station in Iran seems to be more significant than other considered factors in shaping flood seasonality. Results can serve as a foundation for enhancing the scientific understanding of the flood seasonality across Iran, which can provide useful insights for flood prevention planning and future changes projected by models. Flooding is one of most damaging phenomena around the globe that affect humans’ life and economy. So, in order to decrease the dire consequences of flooding, especially in arid zones like Iran, we should increase our knowledge about flood risk by using advanced techniques like flood seasonality analysis. This research is a specific survey at a nationwide scale for enhancing the scientific understanding of the flood timing across Iran, which can provide useful insights for future planning and practical engineering designs. The purpose of this research is the study of seasonality analysis of annual maximum flood in 291 continuous hydrometric stations across Iran with a total of 9,565 events using a circular statistics approach. Owing to the prominent role of humanity and nature on flooding, eight natural and human-induced factors have been surveyed. The results of this study illustrated that 32% and 41% of the total events occurred during winter and spring, mostly during April (24%). What is further noticeable is that a significant difference in flood seasonality was identified between the northern and southeastern regions. Among considered factors in shaping seasonality of flooding, the geographical location (especially latitude) of the hydrometric station in Iran seems to be more significant than other factors.
    publisherAmerican Society of Civil Engineers
    titleFlood Seasonality Analysis in Iran: A Circular Statistics Approach
    typeJournal Article
    journal volume28
    journal issue2
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/JHYEFF.HEENG-5786
    journal fristpage04022039-1
    journal lastpage04022039-15
    page15
    treeJournal of Hydrologic Engineering:;2023:;Volume ( 028 ):;issue: 002
    contenttypeFulltext
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