Premium
Detection of trends in annual extreme rainfall
Author(s) -
Adamowski Kaz,
Bougadis John
Publication year - 2003
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.1353
Subject(s) - autocorrelation , homogeneous , trend analysis , environmental science , storm , spatial dependence , spatial correlation , spatial variability , statistics , climatology , physical geography , meteorology , mathematics , geography , geology , combinatorics
Information on intensity–duration–frequency of rainfall is commonly required for a variety of hydrologic applications. In this study, trends are estimated for different durations of annual extreme rainfall using the regional average Mann–Kendall S trend test. The method of L‐moments was employed to delineate homogeneous regions. The trend test was modified to account for observed autocorrelation, and a bootstrap methodology was used to account for the observed spatial correlation. Numerical analysis was performed on 44 rainfall stations from the province of Ontario, Canada, for a 20 year time frame. This was done using data from homogeneous regions established using the L‐moments procedure for the annual maximum observations for the following durations: 5, 10, 15 and 30 min, and 1, 2, 6 and 12 h. Depending on different rainfall durations, four or five homogeneous regions were delineated. Based on a 5% significance level, approximately 23% of the regions tested had a significant trend, predominantly for short‐duration storms. Serial dependency was observed in 2·3% of data sets and spatial correlation was found in 18% of the regions. The presence of serial and spatial correlation had a significant impact on trend determination. Copyright © 2003 John Wiley & Sons, Ltd.