## Abstract In order to investigate the behaviour of climatic and hydrological variables, several statistical and stochastic techniques are currently applied to time series. In the present study a statistical analysis of annual and seasonal precipitation has been performed over 109 cumulated rainfa
Detection of trends in annual extreme rainfall
✍ Scribed by Kaz Adamowski; John Bougadis
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 251 KB
- Volume
- 17
- Category
- Article
- ISSN
- 0885-6087
- DOI
- 10.1002/hyp.1353
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
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.
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