@article{(Open Science Index):https://publications.waset.org/pdf/9999886,
	  title     = {Trend Analysis for Extreme Rainfall Events in New South Wales, Australia},
	  author    = {Evan Hajani and  Ataur Rahman and  Khaled Haddad},
	  country	= {},
	  institution	= {},
	  abstract     = {Climate change will affect the hydrological cycle in
many different ways such as increase in evaporation and rainfalls.
There have been growing interests among researchers to identify the
nature of trends in historical rainfall data in many different parts of
the world. This paper examines the trends in annual maximum
rainfall data from 30 stations in New South Wales, Australia by using
two non-parametric tests, Mann-Kendall (MK) and Spearman’s Rho
(SR). Rainfall data were analyzed for fifteen different durations
ranging from 6 min to 3 days. It is found that the sub-hourly
durations (6, 12, 18, 24, 30 and 48 minutes) show statistically
significant positive (upward) trends whereas longer duration (subdaily
and daily) events generally show a statistically significant
negative (downward) trend. It is also found that the MK test and SR
test provide notably different results for some rainfall event durations
considered in this study. Since shorter duration sub-hourly rainfall
events show positive trends at many stations, the design rainfall data
based on stationary frequency analysis for these durations need to be
adjusted to account for the impact of climate change. These shorter
durations are more relevant to many urban development projects
based on smaller catchments having a much shorter response time.
},
	    journal   = {International Journal of Environmental and Ecological Engineering},
	  volume    = {8},
	  number    = {12},
	  year      = {2014},
	  pages     = {834 - 839},
	  ee        = {https://publications.waset.org/pdf/9999886},
	  url   	= {https://publications.waset.org/vol/96},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 96, 2014},
	}