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
1999
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.
English
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
Environment Australia
Canberra (A.C.T.)
Supervising Scientist Report; 138
1 volume (various pagings) : illustrations, maps
application/pdf
642243417
Copyright
Environment Australia
https://www.legislation.gov.au/Details/C2019C00042
https://hdl.handle.net/10070/264982
https://hdl.handle.net/10070/462402
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
23 (1999) also examined the correlations between the two stations for monthly rainfall, annual rainfall and daily rainfall characteristics. For example, the correlation for monthly rainfall is shown in figure 3.2.1. The correlation coefficients found for the Wet season months were 0.79 for DecemberFebruary and 0.92 for MarchMay. Overall the correlation is very good and the conclusion drawn by Chiew and Wang (1999) is that the Oenpelli data set should, because of the much longer record, be used for estimating the 1:10,000 AEP annual rainfall and for other hydrological modelling for the Jabiluka project. This conclusion is supported by the Bureau of Meteorology (1999). The long-term (19171998) statistics for annual rainfall at Oenpelli are given in table 3.2.2 (Bureau of Meteorology 1999). The long-term mean annual rainfall, 1397 30 mm, is significantly lower than the value of 1500 mm given in table 3.2.1 for the shorter record between 1971 and 1998. Carter (1990) used a cusum technique to examine long-term cycles or trends in the mean annual rainfall at a number of meteorological stations in the Northern Territory. The cusum method (Cumulative Sum) computes the sum, at any time in a time series, of the difference between the current observed value of a variable and the long-term mean value. This analysis revealed that the period between the mid-1960s until the mid1980s was one of significantly higher average rainfall than the long-term mean. This conclusion was valid for the stations at Darwin, Oenpelli, Pine Creek and Katherine. Hence the short-term record for Oenpelli, which is dominated by this period of higher than average rainfall, has a mean annual rainfall greater than the long-term mean. This conclusion is also likely to be true for Jabiru. Incorporation of this decadal-scale variation in rainfall into the design of the Jabiluka water management system is considered in chapter 4. Table 3.2.2 The annual characteristics of Oenpelli rainfall data Statistic Magnitude Standard Error Mean (mm) 1397 30.3 Standard deviation (mm) 284.5 21.4 Coefficient of skewness -0.018 0.257 3.2.2 Estimation of the 1:10,000 AEP annual rainfall for Jabiluka The Bureau of Meteorology (1999) notes that the coefficient of skewness of the annual rainfall series is small and that, therefore, the normal distribution is appropriate to describe the data. The annual rainfall data for Oenpelli and the fit to the data using a normal distribution are shown in figure 3.2.2. The x-axis in this graph has a normal probability scale and plotting position is determined by the rank of annual rainfall (plotted on the y-axis). Data that are normally distributed plot as a straight line on this type of graph. Chi-squared (2) test results (test statistic 4.39/chi-square value (0.05%) 9.49) and Kolmogorov Smirnov test results (test statistic 0.05881/value 0.145) indicate that the annual rainfall data series for Oenpelli is normally distributed. This conclusion is consistent with that of the Supervising Scientist (Vardavas 1992) who examined the distributions of annual rainfall data for several meteorological stations in the north of the Northern Territory. Vardavas (1992) concluded on the basis of a 2 analysis that the data for Darwin and Oenpelli were better described by a normal distribution than by a log-normal distribution. For these reasons, a normal distribution has been assumed in the estimation of the 1:10,000 AEP rainfall for Oenpelli. For a normal distribution, the probability of exceeding a particular value of the variable x is given by