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
42 Jones et al (1999) analysed a 1000 year sequence of annual rainfall data stochastically generated by Chiew and Wang (1999) using the procedures described in section 5.2.2 and compared the statistics of decadal scale variation observed in the generated data with those observed in the rainfall record for Oenpelli. The 1000 year period of generated data is shown in figure 4.4.3; also plotted is the ten year running mean. It is clear that the simulated data do contain extensive periods of both higher-than-average and lower-than-average rainfall. A shorter sample of that artificial record with the same length as the historical series was analysed. It shows decadal-scale variability of a similar magnitude to that of the historical series but without the same regularity. The coefficient of variability of the 10-year moving average for the shorter record from the 1000-year sample is 6.04.2% while for the historical series it is 6.54.1%. It can be concluded, therefore, that decadal scale variability has been fully accounted for in the hydrological modelling of the Jabiluka water management system presented in section 5.2.3 and there is no justification for adding such a component into a climate change scenario. The long-term average of the sample also exhibited a trend upwards of 1 mm pa, similar to the historical series at 1.7 mm pa, but the record contains three simulated rainfall totals that exceed the historical maximum of 2012 mm in the 19751976 Wet season. This may be due to the positively skewed distribution of annual rainfall in the sample of the artificial series generated and analysed by Chiew and Wang (1999). Therefore, a 3% increase in average rainfall over the next 30 years is likely to be contained within the trends already sampled and applied in the hydrological modelling of Chiew and Wang (1999). Jones et al (1999) concluded that further hydrological modelling incorporating an additional 3% increase in the mean annual rainfall would only be justified if evidence from new climate simulations showed that greater rainfall increases were likely. Effect of climate change on storm intensity The effect of climate change on extreme daily rainfall intensity and on PMPs was also investigated by Jones et al (1999). As in previous studies, it was found that the intensity of extreme events is likely to increase despite the fact that there is an overall decrease in the annual rainfall. In the Wet season, average rainfall was found to decrease by 4.5% but the intensity and frequency of extreme rainfall increases. For example, the intensity of the 1-in10 year event increases by 4%, or the present 10-year event becomes a 9-year event by 2030. The decrease in average rainfall requires a reduction in the frequency or intensity of moderate events. There is a hint of this in the tendency for smaller increases in the strength of events with smaller return periods (and probable decreases in the strength of events with return periods of less than 1 year). Hence the largest summer storms become larger, and moderate downpours become weaker. An assessment of the significance of these findings on the intensity of storms for the design of water containment ponds at Jabiluka is required. This will be considered in Chapter 5. The modelling of Jones et al 1999 also suggests that there could be a significant increase in the magnitude of PMP events, with increases of up to 30% being suggested. Possible increases of this magnitude should be taken into account in the final design of the Jabiluka water management system by increasing the height of exclusion bunds.