Abstract
The spatial and temporal structures of extreme rainfall trends in South Korea are investigated in the current study. The trends in the annual maximum rainfall series are detected and their spatial distribution is analyzed. The scaling exponent is employed as an index representing the temporal structure. The temporal structure of the annual maximum series is calculated and spatially analyzed. Subsequently, the block bootstrap based Mann-Kendall test is employed detect the trend in the scaling exponent series subsampled by the annual maximum rainfalls using a moving window. Significant trends are detected in a small number of stations and there are no significant trends in many stations for the annual maximum rainfall series. There is a large variability in the temporal structures of the extreme rainfall events. Additionally, the variations of the scaling exponent estimates for each month within a rainy season are larger than the variation of the scaling exponent estimates on an annual basis. Significant trends in the temporal structures are observed at many stations unlike the trend test results of annual maximum rainfall series. Decreasing trends are observed at many stations located in the coastal area, while increasing trends are observed in the inland area.
Highlights
IntroductionUnderstanding the spatial and temporal variability of the extreme rainfalls plays an important role in water resource management, especially in mitigation and prevention of floods
Extreme rainfall events are a main source of floods worldwide
The current study aims to investigate the temporal structure of the extreme rainfall in South Korea using the scaling property, and the changes in the spatial and temporal structure of the extreme rainfalls are examined
Summary
Understanding the spatial and temporal variability of the extreme rainfalls plays an important role in water resource management, especially in mitigation and prevention of floods. It is reported by many studies that the extreme rainfall simulated by global climate models under climate change scenarios change in the future [10,11,12,13,14,15,16]. Since the changes in the extreme rainfalls can alter strategy and policy in water resources as well as design criteria of water-related infrastructures, understanding the change in spatial and temporal variability of rainfall extremes is essential to efficiently managing water resources and preventing the damages from water-related disasters such as floods and landslides.
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