4.6 Article

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

Journal

INTERNATIONAL JOURNAL OF CLIMATOLOGY
Volume 41, Issue 8, Pages 4307-4320

Publisher

WILEY
DOI: 10.1002/joc.7074

Keywords

K‐ fold cross validation; L‐ moments; Monte Carlo simulation; quantile estimates; regional frequency analysis; spatial map

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This study conducted regional frequency analysis of annual maximum daily rainfall in Skane County, Sweden, indicating it is a homogeneous region. The support vector machine model was found to be appropriate for finding index rainfall at ungauged sites. Site characteristics, elevation, and latitude were identified as key variables for explaining the variation in mean annual maximum daily rainfall.
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 Skane County, Sweden. L-moments based heterogeneity measure (H) reveals that the Skane County is a homogeneous region. Based on the L-moment ratio diagram and Z(Dist) 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.

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