Hazards
; Landslides
; Rain
; Soil mechanics
; Storms
; Thunderstorms
; Distribution parameters
; Minor axis lengths
; Primary objective
; Principal directions
; Rainfall intensity
; Spatial correlations
; Spatial variations
; Topographic effects
; Spatial distribution
; correlation
; future prospect
; hazard assessment
; landslide
; parameterization
; precipitation intensity
; rainstorm
; spatial distribution
; spatial variation
; topographic effect
; trend analysis
; trigger mechanism
; China
; Hong Kong
英文摘要:
Rainfall is the primary trigger of landslides in Hong Kong; hence, rainstorm spatial distribution is an important piece of information in landslide hazard analysis. The primary objective of this paper is to quantify spatial correlation characteristics of three landslide-Triggering large storms in Hong Kong. The spatial maximum rolling rainfall is represented by a rotated ellipsoid trend surface and a random field of residuals. The maximum rolling 4, 12, 24, and 36 h rainfall amounts of these storms are assessed via surface trend fitting, and the spatial correlation of the detrended residuals is determined through studying the scales of fluctuation along eight directions. The principal directions of the surface trend are between 19 and 43-, and the major and minor axis lengths are 83-386 and 55-79 km, respectively. The scales of fluctuation of the residuals are found between 5 and 30 km. The spatial distribution parameters for the three large rainstorms are found to be similar to those for four ordinary rainfall events. The proposed rainfall spatial distribution model and parameters help define the impact area, rainfall intensity and local topographic effects for landslide hazard evaluation in the future.
Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, Hong Kong
Recommended Citation:
Gao L,, Zhang L,, Lu M. Characterizing the spatial variations and correlations of large rainstorms for landslide study[J]. Hydrology and Earth System Sciences,2017-01-01,21(9)