Regional frequency analysis of annual daily rainfall maxima in Skåne, Sweden

Extreme daily rainfall events are critical for the urban drainage system, human life, agriculture and small catchments. The information about extreme rainfall magnitudes and frequencies is immensely important for civil engineers, city planners, scientists related to water management, rescue operatio...

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Bibliographic Details
Published in:International journal of climatology 2021-06, Vol.41 (8), p.4307-4320
Main Authors: Ul Hassan, Mahmood, Noreen, Zahra, Ahmed, Rashid
Format: Article
Language:English
Subjects:
Agricultural watersheds
Agriculture
Annual rainfall
Catchment area
Catchments
Civil engineering
Civil engineers
Daily
Distribution
Drainage systems
Emergency preparedness
Engineers
Extreme weather
Flood control
Flood management
Frequency analysis
Heterogeneity
K-fold cross validation
L-moments
Maxima
Maximum daily rainfall
Mean annual precipitation
Monte Carlo simulation
quantile estimates
Quantiles
Rain
Regional analysis
regional frequency analysis
Rescue operations
spatial map
Support vector machines
Urban drainage
Water management
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Summary:Extreme daily rainfall events are critical for the urban drainage system, human life, agriculture and small catchments. The information about extreme rainfall magnitudes and frequencies is immensely important for civil engineers, city planners, scientists related to water management, rescue operations and flood control works. This study illustrates the results of regional frequency analysis (RFA) of annual maximum daily rainfall (AMDR) of Skåne County, Sweden. L‐moments based heterogeneity measure (H) reveals that the Skåne County is a homogeneous region. Based on the L‐moment ratio diagram and ZDist statistic results, the generalized normal (GNO) distribution is selected as the most suitable regional distribution. The accuracy measures used in K‐fold cross validation indicate that support vector machine (SVM) model is an appropriate model to find the index rainfall at ungauged sites in the region. The sites characteristics, elevation and latitude are identified as the most important variables to explain the variation in mean annual maximum daily rainfall (MAMDR). Finally, spatial maps of predicted MAMDR for different return periods are constructed by using index rainfall combined with regional quantiles. Spatial maps offer an overall view of the expected MAMDR in the region that is helpful for multiple decision makers including infrastructure planners, city planners, emergency managers, engineers and many others. Flowchart summarized the main steps of the methodology
ISSN:0899-8418
1097-0088
1097-0088
DOI:10.1002/joc.7074