Territory Stories

Assessment of the Jabiluka Project : report of the Supervising Scientist to the World Heritage Committee

Details:

Title

Assessment of the Jabiluka Project : report of the Supervising Scientist to the World Heritage Committee

Creator

Johnston, A.; Prendergast, J. B.; Bridgewater, Peter

Collection

E-Publications; E-Books; PublicationNT; Supervising Scientist Report; 138

Date

1999

Location

Alligator Rivers Region

Table of contents

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.

Language

English

Subject

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

Publisher name

Environment Australia

Place of publication

Canberra (A.C.T.)

Series

Supervising Scientist Report; 138

Format

1 volume (various pagings) : illustrations, maps

File type

application/pdf

ISBN

642243417

Use

Copyright

Copyright owner

Environment Australia

License

https://www.legislation.gov.au/Details/C2019C00042

Parent handle

https://hdl.handle.net/10070/264982

Citation address

https://hdl.handle.net/10070/462402

Related items

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

Page content

50 three years replaced with the wettest three-year sequence, up to the first ten years replaced with the wettest ten-year sequence. The simulations were carried out on a monthly time step, with the annual rainfall data distributed over the 12 months using the same monthly factors for all years of simulations (see table B1.1 in the Jabiluka PER Appendices). Mean monthly storage evaporation rates were used for the simulations (calculated using Hattons (1997) pan coefficients times the mean monthly pan evaporation see discussion in section 3.3). The other water use considerations were similar to those used here except for evaporative losses in the ventilation system (see section 5.2.2). The use of a 15-year water balance simulation by ERA instead of a 30-year simulation is, to a large extent, reasonable because the full evaporative capacity of the ventilation system is not available until the tenth year of operation and, therefore, the storage capacity is most likely to be exceeded in the first few years. (This issue will be further addressed in section 5.2.5.) This is probably also the reason why ERA replaced the first years of the base data with the wettest sequence to mimic the extreme wet conditions. The significance of the other differences between the approach adopted by ERA and that used in this review is assessed below using a sensitivity analysis. 5.2.4 Sensitivity analysis It is difficult to carry out a direct comparison between the ERA approach to hydrological modelling and that used for this review. However, Chiew and Wang (1999) investigated the sensitivity of the required storage capacity to each of the variables for which different assumptions were made by ERA and Chiew and Wang (1999). For the purpose of the sensitivity analysis, the full simulation procedure described in section 5.2.3 was not adopted since it would have been extremely demanding on computer time. Rather, the model was run a number of times using the actual rainfall and evaporation data recorded during the period September 1972 and August 1998. Six water balance calculations were carried out using a monthly time step and three calculations were carried out using a daily time step. Within these subsets, the procedure adopted to determine rainfall, pond evaporation, evaporation losses in the ventilation system and runoff were varied as indicated in table 5.2.3. Values of the largest storage capacity required in each of the nine model runs are tabulated in table 5.2.3; the results are discussed below in terms of the significance of the assumptions made. While this procedure is not as thorough as running the full simulation in each case, the results should be adequate to assess the relative significance of each assumption. Interannual variability in evaporation and the correlation between evaporation and rainfall Runs 1 and 2 are the same except for the use of pan evaporation data. Run 1 uses the actual monthly pan evaporation data while in Run 2 the mean monthly pan evaporation rates, averaged over the 26 years, are used. Run 1 therefore takes into account the interannual variability in evaporation and the correlation between evaporation and rainfall while Run 2 does not. The results in table 5.2.3 indicate that ignoring the interannual variability in evaporation and the correlation between evaporation and rainfall results in a 3% underestimate of the required storage capacity. Actual rainfall versus monthly distribution of annual rainfall Runs 1 and 3 differ only in the use of rainfall data. Run 1 uses the actual monthly rainfall data, while in Run 3 the annual rainfall is distributed over the 12 months using the monthly factors in table B1.1 in the Jabiluka PER Appendices. The use of the actual monthly rainfall


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