The Hurst phenomenon and Monte Carlo simulation to forecast reliability of an Australian reservoir

G Cox; Smythe, C; Koutsoyiannis, D

dc.contributor.author	G Cox	en
dc.contributor.author	Smythe, C	en
dc.contributor.author	Koutsoyiannis, D	en
dc.date.accessioned	2014-03-01T02:54:12Z
dc.date.available	2014-03-01T02:54:12Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36715
dc.title	The Hurst phenomenon and Monte Carlo simulation to forecast reliability of an Australian reservoir	en
heal.type	conferenceItem	en
heal.publicationDate	2006	en
heal.abstract	The issue of water supply reliability from Australian reservoirs has recently been the subject of increased scientific and media debate. 'Drought Persistence' or prolonged sequences of low inflows has driven reservoirs to seriously low levels. Statistical justification for these persistent droughts is often difficult to find if classical statistics and typical stochastic approaches are used. Therefore persistent droughts may be overlooked in reliability of supply calculations. This can result in dramatically underestimated risk of failure. The Hurst phenomenon offers a consistent basis to remedy this and the Hurst coefficient can be a simple measure to quantify the amount of persistence in a time series. For this study, the Hurst coefficient was calculated for the historical flow data of the Boyne River, Queensland. Based on the coefficient and the probability distribution of the historical inflow data, synthetic reservoir inflow sequences were generated preserving the persistence. Using this data and Monte Carlo simulation, a tool was developed to forecast the reliability of supply into the future from the current storage level. This is used for planning risk reduction strategies by providing valuable information such as the lead-time available to implement contingencies.	en