Trend detection in short and long duration storm events : a case study for NSW, Australia

Anthropogenic climate change is one of the key challenges the earth is facing today, which affects many aspects of the environment. Climate change affects hydrological cycle including rainfall, evaporation, soil moisture and catchment runoff. Change in rainfall has significant implications as it influences floods, droughts, vegetation and ecology. There have been numerous studies on trend identification in annual rainfall data; however, a trend in extreme rainfall data has received relatively less attention. Trends in the extreme rainfalls would affect design and operation of many engineering structures in near future. This paper examines the trends in annual maximum rainfall data from 20 pluviograph stations in New South Wales (NSW), Australia by using two non-parametric tests, Mann-Kendall (MK) and Spearman’s Rho (SR) tests. Rainfall events data are analysed for fifteen different durations ranging from 6 minutes to 3 days. The relationship between the observed trends and elevations of pluviograph stations, mean annual rainfall and Southern Oscillation Index (SOI) are examined. It is found that trends are generally influenced by these catchment and climate indices; however, no significant link could be established. The results of the MK and SR test statistics are found to be modestly correlated with the mean annual rainfall and the elevation of the pluviograph stations, with a maximum correlation coefficient of 0.31. It has been found that the correlation coefficient between MK test statistic and mean annual rainfall is higher for the longer durations than the shorter duration rainfall events. In case of correlation between the MK test statistic and elevation, it has been found that the correlation coefficient is higher for the shorter durations than the longer duration events. It has also been found that the SOI index is weakly correlated with monthly maximum rainfall data. Overall, this study shows that there are little trends in the rainfall events data in NSW that could be deemed to be significant