The hydrological analysis encompasses the surface water and groundwater modelling reported in companion product 2.6.1 (Aryal et al., 2018) and companion product 2.6.2 (Janardhanan et al., 2018), respectively, for the Namoi subregion. The Namoi surface water and groundwater models quantify potential changes in hydrology from multiple coal resource developments and enable an assessment of the cumulative impacts of coal resource development at a regional scale. For streamflow, nine hydrological response variables, which incorporate changes in groundwater fluxes from the groundwater model, allow an assessment of the effects on low-, average- and high-flow characteristics of the time-series data. For groundwater, a single hydrological response variable quantifies the maximum additional drawdown attributable to the modelled additional coal resource development.
Companion submethodology M06 for surface water modelling (Viney, 2016) and companion submethodology M07 for groundwater modelling (Crosbie et al., 2016) (as listed in Table 1) define thresholds for each hydrological response variable. A modelled change at or above the threshold identifies the level of hydrological change due to additional coal resource development that needs to be considered further. Preliminary zones of potential hydrological change for surface water (companion product 2.6.1 (Aryal et al., 2018)) and for groundwater (companion product 2.6.2 (Janardhanan et al., 2018)) identify the areas beyond which impact is considered very unlikely.
For surface water, a model node is included in the zone of potential hydrological change if it registered a change above the threshold in at least one of the nine hydrological response variables. The Namoi link-node mapping shows where results from surface water model nodes define upstream and downstream links in the stream network (see companion product 2.6.1 (Aryal et al., 2018)), and it identifies which stream reaches are within the surface water zone of potential hydrological change (see Figure 37 in Aryal et al. (2018)).
For groundwater, a maximum drawdown of 0.2 m due to additional coal resource development is used as a threshold. If 5% or more of the model simulations predict a drawdown of greater than 0.2 m, the model node is included in the groundwater zone of potential hydrological change (see Figure 10 in Section 3.3). If less than 5% of the model simulations predict a drawdown of greater than 0.2 m, then hydrological impact is assessed as very unlikely.
The zones of potential hydrological change for surface water and groundwater modelling, identified in companion product 2.6.1 (Aryal et al., 2018) and companion product 2.6.2 (Janardhanan et al., 2018), form the basis for a combined zone of potential hydrological change that is spatially explicit and at a 1 km pixel resolution, and this resolution is aligned with the shape of assessment units. Assessment units are the basis of the subsequent assessment (see Section 3.2.5 for details). This resolution recognises the input data resolutions in the hydrological modelling and allows for an assessment at the bioregional level. Section 3.3 outlines the process of this zone development for the Namoi subregion. The additional processing steps needed to incorporate stream reaches that are not explicit in the AWRA-R link-node network are also available in Section 3.3. This includes those landscape classes that have an inherent surface water dependency and intersect with these stream reaches. This overcomes the spatial limitation of representing streams as line features, which do not include riparian and floodplain areas. The zone of potential hydrological change underpins the ‘rule-out’ overlay analysis of landscape classes and assets (Section 3.2.4).
3.2.3.1 Representing predictive uncertainty
The models used in the assessment produce a large number of predictions of groundwater drawdown and streamflow characteristics rather than a single number. This results in a range or distribution of predictions, which are typically reported as probabilities – the percent chance of something occurring (Figure 7). This approach allows an assessment of the likelihood of exceeding a given magnitude of change, and underpins the assessment of risk.
Groundwater models, for example, require information about physical properties such as the thickness of geological layers, how porous aquifers are, and whether faults are present. As the exact values of these properties are not always known, the modellers used a credible range of values, which are based on various sources of data (commonly point-scale) combined with expert knowledge. Incorporation of this credible range included running the model 3500 times using a different set of plausible values for those physical properties each time. Historical observations, such as groundwater level and changes in water movement and volume from across the subregion, help to constrain and validate the model runs subsequently.
The complete set of model runs produces a range or distribution of predictions (Figure 7) that is consistent with the available regional observations and the understanding of the modelled system. The range conveys the confidence in model results, with a wide range indicating that the expected outcome is less certain, while a narrow range provides a stronger evidence base for decision making. The distributions created from these model runs are expressed as probabilities that drawdown or a change in streamflow will exceed relevant thresholds, as there is no single ‘best’ estimate of change.
In this Assessment, the estimates of drawdown or streamflow change are shown as 5th, 50th or 95th percentile results, corresponding to a 95%, 50% or 5% chance of exceeding thresholds. Figure 8 illustrates this predictive uncertainty spatially.
Throughout this product, the term ‘very likely’ describes where there is a greater than 95% chance of something occurring, and ‘very unlikely’ is used where there is a less than 5% chance.
Figure 7 Illustrative example of probabilistic drawdown results using percentiles and percent chance
The chart on the left shows the distribution of results for drawdown, obtained from an ensemble of thousands of model runs that use many sets of parameters. These generic results are for illustrative purposes only.
Figure 8 Illustrative example of key areas in the landscape defined by probabilistic results
The assessment extent was divided into smaller square assessment units (see Section 3.2.5) and the probability distribution (Figure 7) was calculated for each. In this product results are reported with respect to the following key areas:
A. outside the zone of potential hydrological change, where hydrological changes (and hence impacts) are very unlikely (defined by maps showing the 95th percentile)
B. inside the zone of potential hydrological change, comprising the assessment units with at least a 5% chance of exceeding the threshold (defined by maps showing the 95th percentile). Further work is required to determine whether the hydrological changes in the zone translate into impacts for water-dependent assets and landscapes
C. with at least a 50% chance of exceeding the threshold (i.e. the assessment units where the median is greater than the threshold; defined by maps showing the 50th percentile)
D. with at least a 95% chance of exceeding the threshold (i.e. the assessment units where hydrological changes are very likely; defined by maps showing the 5th percentile).
Percentile estimates of drawdown enable the reader to choose their own drawdown thresholds. For example, an ecologist may be interested in potential hydrological changes in an area of floodplain remnant vegetation where their conceptual ecological model indicates that herbaceous species are affected by 1 to 2 m of drawdown and floodplain trees are affected by 10 to 20 m of drawdown. The ecologist can use the 5th, 50th and 95th percentile estimates of drawdown for the relevant landscape class or asset to assess the likelihood and extent of potential impacts on and risks to that ecosystem due to coal resource development.
In contrast, the percent chance of exceeding important threshold values enables the reader to choose their level of certainty. A regulator may be interested in the likelihood of a groundwater bore exceeding defined regulatory thresholds. The regulator can then determine the number of bores where there is a 20% chance of exceeding 5 m drawdown.
