شاخص سیل ناگهانی شهری
ترجمه نشده

شاخص سیل ناگهانی شهری

عنوان فارسی مقاله: شاخص سیل ناگهانی شهری بر اساس تاریخچه بارش های باران
عنوان انگلیسی مقاله: Urban flash flood index based on historical rainfall events
مجله/کنفرانس: جامعه و شهرهای پایدار – Sustainable Cities and Society
رشته های تحصیلی مرتبط: جغرافیا
گرایش های تحصیلی مرتبط: آب و هواشناسی، مخاطرات آب و هوایی، مخاطرات محیطی
کلمات کلیدی فارسی: سیل ناگهانی شهری، آسیب پذیری سیل، احتمال وقوع سیل، شاخص یکپارچه، مدلسازی هیدرولوزیکی
کلمات کلیدی انگلیسی: urban flash flood; flood vulnerability; flood susceptibility; integrated index; hydrological modelling
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.scs.2020.102088
دانشگاه: Universiti Kebangsaan Malaysia, Selangor, Malaysia
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 5.248 در سال 2019
شاخص H_index: 34 در سال 2020
شاخص SJR: 1.100 در سال 2019
شناسه ISSN: 2210-6707
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 33
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E14600
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract


1- Introduction


2- Methodology


3- Results and discussion


4- Conclusions


Acknowledgements


References

بخشی از مقاله (انگلیسی)

Abstract


Urban flash flood poses significant hazards on urbanised area, in particular to buildings and infrastructure due to its fast occurrence and high magnitude in financial loss. Risk assessment of the flash flood identify the critically flood-prone areas and provide assistance in improving the resiliency of mitigation plans. In this study, we developed an assessment of flood susceptibility, vulnerability, the impact of socio-economic, and integrated flash flood index based on the historical data of flood events recorded in Kuala Lumpur. Data of rainfall characteristics, inundated location, and areas are extracted from the reports of flood events from the year 2005-2015. Each event is then segregated according to the place of incidence, providing point-based recurrence of flood at each identified location. Indicators of assessment include frequency and month of occurrence, rainfall characteristics (of intensity, duration, and depth), and land use categories. A total of 137 (point) locations have been identified, where each location is colour-coded based on a 5-point rating scale. The point-based flood-prone locations are validated with the watershed based of 50-ARI rainfall modelling, providing comprehensive hotspot maps. Developed interactive colour-coded flood prone maps facilitate relevant agencies for improved coordination in flash flood mitigation, response and early warning.


Introduction


Urban flooding occurs when the capacity of both natural and drainage systems could not cater to the volume of precipitation and runoff discharge within an urbanised area. High surface runoff discharge from heavy rainfall due to impervious surfaces and high building densities escalate the urban flooding (Gaitan et al., 2016; Yao et al., 2016). Although urban flooding is commonly associated with the short duration-high intensity precipitation, such flooding also has been recorded due to prolonged moderate rainfall (Coulthard et al., 2007; Abdullah and Julien, 2014a; Abdullah et al., 2018).


Flash flood is defined as the flood events resulted from high precipitation in short duration, usually less than 6 hours (Suparta et al., 2014). Localised convective storms in a small catchment within short time results in fast-rising of water level, usually with no advance or little time of warning. As such, the flood occurrence in the urbanised area due to insufficient drainage capacity from short duration-high intensity rainfall-induced the urban flash flooding (UFF). Considering the short duration of rainfall, the limb of the hydrograph rose fast to the peak flow whereby the UFF can even be visible just only after 30 minutes of rainfall. The non-alerted and unpredicted flood events caused devastating impacts to the road infrastructures, particularly at the low-lying areas (Doocy et al., 2013). Risk assessment of UFF on the intra-urban transportation network by evaluating the impact of flood depth (obtained through the 2D hydrodynamic modelling) and traffic or probability analysis provide a quantitative impact of UFF (Yin et al., 2016; Li et al., 2018).

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