Impacts of serial correlation on trends in rainfall annual maximum series data in NSW, Australia

Speaker: Evan Hajani

Affiliation: Western Sydney University

Time: Monday 08/02/2016 from 14:00 to 15:00

Venue: Access Grid UWS. Presented from Penrith (Y239), accessible from Parramatta (EB.1.32) and Campbelltown (26.1.50).

Abstract: Design rainfall is used as an important input to hydrological models. Climate change and climate variability are likely to affect design rainfalls at many regions in future. In this paper, the trends of sub-hourly, sub-daily and daily extreme rainfall events from 42 rainfall stations located in New South Wales (NSW), Australia were examined. Two non-parametric tests, Mann-Kendall (MK) test and Spearman Rho (SR) test, were applied to detect trends at 1%, 5% and 10% significance levels. Pre-whitening (PW), Trend-Free Pre-whitening (TFPW) and the Variance Correction (VC) approaches were used to account for the impact of serial correlation on the both the MK and SR test results. In this study, statistically significant positive (upward) trends are more frequently observed compared with statistically significant negative (downward) trends, in particular for the short duration rainfall events. Use of PW, TFPW and VC approaches, which account for the impact of serial correlation on trend results, has resulted in a reduction in the numbers of stations exhibiting significant upward trend.

Biography: 2010 Duhok University, Iraq, Masters of engineering (Water resources)
2005 Duhok University, Iraq, Bachelor of civil engineering (Water resources)
2014 Commenced PhD study at University of Western Sydney, Australia