Assessment of the effect of extreme rainfall events on temporal rainfall variability in Kuwait

被引:0
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作者
Habib Al-Qallaf
Amjad Aliewi
Ahmed Abdulhadi
机构
[1] Kuwait Institute for Scientific Research,Water Research Center
[2] Kuwait Institute for Scientific Research,Science & Technology Sector
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关键词
Rainfall temporal variability; Extreme rainfall events; Frequency analysis; CDM;
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摘要
In recent decades, Kuwait is witnessing an increase in the number of flash floods, which puts a serious risk on human lives and properties. During November 2018, the highest extreme rainfall event was recorded in Kuwait. This paper aims at investigating the frequency of occurrence of extreme rainfall events and their effect on the temporal variability of rainfall in Kuwait. Statistical methods were implemented, such as frequency analysis of annual maximum hourly and daily rainfalls, in addition to the cumulative departure from the mean (CDM) to analyze the effect of extreme rainfall events on the temporal pattern of rainfall in Kuwait. The results show that the total annual rainfall is very wide from 31 mm in 1964 to 344 mm in 2018, while the general trend of rainfall in Kuwait is increasing with time. The statistical analysis based on developing suitable cumulative density functions for rainfall events in Kuwait shows that the return periods of the annual maximum hourly (41.5 mm/h) and the annual maximum daily (103.1 mm/day) rainfall events were 50 and 155 years, respectively. The analysis show that without the rainfall data of 2018, 49% of the CDM curve remains above the average limit of 112 mm/year. However, when the extreme rainfall events of 2018 are included in the analysis, only 11% of the CDM curve remains above the mean line of the new average limit of 116 mm. The study concluded that the rainfall pattern of Kuwait is affected considerably by extreme rainfall events and the amount of rainfall increases against reduction in number of days in the recent decades, which accordingly increases the rainfall intensities to produce more flash floods.
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