| dc.description.abstract | Detecting trends in both hydrological and
hydrometeorological data series is important in the
context of climate change. Although multiday rainfall has
caused disastrous consequences for Sri Lanka in the past,
little attention has been paid to analyse multiday extreme
rainfall data for trends. This paper analyses past extreme
rainfall data in the Kelani River basin of a period of 57
years from 1960 to 2016 using both parametric and non-
parametric tests to detect trends in a multiday scale. The
daily rainfall data was assessed for homogeneity using the
RhtestsV4 and extreme rainfall data was extracted using
the Block Maxima method. Modified Mann-Kendall test,
Mann-Kendall test, Sen’s slope estimator, Linear
regression method and the Innovative Trend Analysis
method was used in detecting trends in the extreme
rainfall data. It was found that Norton and Maussakelle
shows significant positive trend for 1-day and
Maussakelle for 2-day, and Wewalthalawa shows a
significant negative trend for 4-day. The study will also
help in assessing the suitability of using the Innovative
Trend Analysis method for detecting rainfall trends in Sri
Lanka. By determining trends in extreme rainfall data
from the Kelani River basin, predictions can be made
about the future direction of rainfall, which can aid in
preparing for future hazards and risks. | en_US |
