Assessment of the Jabiluka Project : report of the Supervising Scientist to the World Heritage Committee
Johnston, A.; Prendergast, J. B.; Bridgewater, Peter
E-Publications; E-Books; PublicationNT; Supervising Scientist Report; 138
Alligator Rivers Region
Main report--Appendix 2 of the Main Report. Submission to the Mission of the World Heritage Committee by some Australian Scientists ... --Attachment A. Johnston A. and Needham S. 1999. Protection of the environment near the Ranger uranium mine--Attachment B. Bureau of Meteorology 1999. Hydrometeorological analysis relevant to Jabiluka--Attachment C. Jones, R.N., Hennessy, K.J. and Abbs, D.J. 1999. Climate change analysis relevant to Jabiluka--Attachment D. Chiew, F and Wang, Q.J. 1999. Hydrological anaysis relevant to surface water storage at Jabiluka--Attachment E. Kalf, F. and Dudgeon, C. 1999. Analysis of long term groundwater dispersal of contaminants from proposed Jabiluka mine tailings repositories--Appendix 2 of Attachment E. Simulation of leaching on non-reactive and radionuclide contaminants from proposed Jabiluka silo banks.
Uranium mill tailings - Environmental aspects - Northern Territory - Alligator Rivers Region; Environmental impact analysis - Northern Territory - Jabiluka; Uranium mines and mining - Environmental aspects - Northern Territory - Jabiluka; Jabiluka - Environmental aspects
Supervising Scientist Report; 138
1 volume (various pagings) : illustrations, maps
https://hdl.handle.net/10070/462403; https://hdl.handle.net/10070/462400; https://hdl.handle.net/10070/462405; https://hdl.handle.net/10070/462406; https://hdl.handle.net/10070/462408; https://hdl.handle.net/10070/462409; https://hdl.handle.net/10070/462411
24 )(1)( 00 xFxxP = where F(x) is the cumulative distribution function for a normal distribution. From Institution of Engineers, Australia, (1987), F(x0) = 0.0001 when 719.30 =x where and are the mean and standard deviation of the distribution. Hence, using the data in table 3.2.2, the Bureau of Meteorology conclude that the 1:10,000 AEP annual rainfall estimate for Oenpelli is 2455 mm with a standard error of 85 mm. The 95 % confidence limit for this estimate, rounded to the nearest 10 mm is 2460 170 mm. Figure 3.2.2 Distribution of annual rainfall for Oenpelli The Bureau of Meteorology (1999) notes that an alternative method of calculating annual exceedance probability (AEP) from a relatively short record is to calculate the expected probability (Institution of Engineers, Australia, 1987, Beard 1960). Here, expected is used in the statistical sense and the name would be more precisely expressed as Expected Annual Exceedance Probability. This approach takes the view that one record, such as the Oenpelli record, is just one sample from a normally distributed population, and it can be shown that, on average, over a large number of samples, the expected probability of estimates of the 1 in Y AEP event is always greater than 1 in Y. This implies a higher annual rainfall because it is the rainfall for the expected probability rather than that for the sample probability. The concept is a complex one and the subject is still debated in the literature. However, if the procedures recommended by Beard (1960) are followed, the estimate of the 1 in 10,000 year annual rainfall for Oenpelli is 2,510 mm. This estimate is not significantly different from the 2,460 mm recommended. The recommended value of the 1:10,000 AEP annual rainfall is in very good agreement with the value adopted by ERA in the Draft EIS, namely 2450 mm. The rationale adopted by ERA in deriving this estimate is described in the Supplement to the Draft EIS (page 522). ERA 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0 A v e ra g e R e c u rre n c e In te rv a l ( y e a rs ) A c tua l F it ted d is t r ibu t ion .1 .0 5 .0 1 A n n u a l E xc e e d a n c e P r o b a b i l ity .184.108.40.206 .0 0 1 2 5 1 0 2 0 1 0 0 1 0 0 01 .2 5
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