Section summarises the prediction results for nine hydrological response variables and for 65 surface water model nodes. The nine hydrological response variables for streamflow are:

  • AF – the annual flow volume (GL/year)
  • P99 – the daily streamflow rate at the 99th percentile (ML/day)
  • IQR – the interquartile range in daily streamflow (ML/day); that is, the difference between the daily streamflow rate at the 75th percentile and at the 25th percentile
  • FD – the number of high-flow days per year. The threshold for high-flow days is the 90th percentile from the simulated 90-year period (2013 to 2102). In some early products, this was referred to as ‘flood days’
  • P01 – the daily streamflow rate at the 1st percentile (ML/day)
  • ZFD – the number of zero-flow days each year
  • LFD – the number of low-flow days per year. The threshold for low-flow days is the 10th percentile from the simulated 90-year period (2013 to 2102)
  • LFS – the number of low-flow spells per year. A spell is defined as a period of contiguous days of streamflow below the 10th percentile threshold
  • LLFS – the length (days) of the longest low-flow spell each year.

These hydrological response variables were chosen to be able to quantify changes across the entire flow regime (see submethodology M06 surface water modelling (Viney, 2016)). For each of these hydrological response variables a time series of annual values for the period 2013 to 2102 is constructed for each model node.

For each model node, 3000 sets of randomly selected parameter values were used to generate 3000 replicates of development impact. From these, the best 300 replicates for each hydrological response variable – as assessed by their ability to predict that hydrological response variable at the 22 observation sites – were chosen for further analysis. The 22 assessment nodes are chosen for their availability of suitable observational data. Each boxplot was generated from the resulting 300 samples. The boxplots show the distributions over the 300 replicates of the maximum raw change (amax) in each metric between the baseline and coal resource development pathway (CRDP) predictions, the corresponding maximum percent change (pmax) and the year of maximum change (tmax). In general, the most meaningful diagnostic for the flux-based metrics (P01, P99, AF and IQR) will be pmax, while the most meaningful diagnostic for the frequency-based metrics (LFD, LFS, LLFS, ZFD and FD) will be amax.

It is important to recognise that the amax and pmax values give the largest annual departure between the baseline and CRDP predictions for the respective hydrological response variables. As such, amax and pmax represent extreme responses. They do not represent the magnitudes of responses that would be expected to occur every year.

Results are for those additional coal resource developments that were able to be modelled. As discussed in companion product 2.3 (conceptual modelling) for the Hunter subregion (Dawes et al., 2018), there was insufficient data to model West Muswellbrook and Mandalong developments; Wambo and Mount Arthur developments were assessed as not causing any additional impact on catchment runoff and therefore were not modelled; and the Chain Valley extension is under Lake Macquarie and does not affect surface runoff. The potential effects on surface water from developments at West Muswellbrook and Mandalong are considered qualitatively in companion product 3-4 (impact and risk analysis) for the Hunter subregion (as listed in Table 2).

Last updated:
18 January 2019
Thumbnail of the Hunter subregion

Product Finalisation date