2.7.8.2 Limitations of the receptor impact modelling

Section 2.7.1 and companion submethodology M08 (as listed in Table 1) for receptor impact modelling (Hosack et al., 2018) detail the strengths and limitations of the expert elicitation process used in the BAs for building qualitative ecosystem models and quantitative receptor impact models. There is no need to revisit these here, except to acknowledge that the qualitative models and receptor impact models that were developed to represent the landscape classes in the Namoi zone of potential hydrological change reflect the subjectivity and bias inherent in the knowledge base of the assembled experts (e.g. in defining the scope of the model, its components and connections, ecologically important hydrological variables, representative receptor impact variables, and magnitude and uncertainty of responses to change). Thus, each model represents ‘a view’ of a landscape class or ecosystem; a view that might brook argument about some of the specifics but would generally be accepted as an adequate high-level conceptualisation of the important components of the ecosystem(s) it represents. It is acknowledged in Table 4 that this approach may create the potential to underestimate complex ecosystem function and is something that needs to be considered and evaluated against observations (monitoring) in the future.

Some important knowledge gaps and limitations were identified at the expert elicitation workshops, which limit the assessment of potential impacts from hydrological changes due to additional coal resource development for some landscape classes or components of landscape classes within the zone of potential hydrological change. In other words, they limit this BA and must be flagged as areas requiring further investigation.

While some models include salinity and/or nutrient components, the expert elicitations to define the results space for the receptor impact models are premised on changes in hydrology. Changes in water quality parameters that could occur with a shift in the relative contributions of surface water runoff and groundwater to streamflow or due to enhanced connectivity between aquifers of differing water quality, for example, are not represented. Thus, the potential ecological impacts due to additional coal resource development reported in the impact risk analysis for the Namoi subregion (companion product 3-4, Herr et al., 2018) reflect the risk from hydrological changes only; they could differ if changes in key water quality parameters had been included in the model formulation.

The selection of receptor impact variables was based on their ability to be used to detect changes in the ecohydrology of their respective landscape class. The criteria for selecting the receptor impact variables are discussed in detail in companion submethodology M08 (as listed in Table 1) for receptor impact modelling (Hosack et al., 2018). The receptor impact variables identified reflect those criteria and the ecological experts available at the workshops but may benefit from testing and further consideration of their optimality over time. The receptor impact variables selected may not capture all potential ecological changes brought about by alterations in the surface water and groundwater regimes from the coal resource development pathway. Limitations arising from selecting a receptor based on a particular taxa or functional group or ecosystem component include: the lack of differentiation between species that have differing vulnerability to hydrological change; variation in the different taxa within a receptor across the assessment extent; and assessment of one trophic level as opposed to an assessment of trophic interactions within and across landscape classes and ecosystems. This approach is also confounded by variation in the baseline conditions across a given landscape class that may make detection of changes in a certain variable difficult (i.e. poor condition of existing instream habitat for macroinvertebrates along a ‘Permanent lowland stream’ reach). Moreover, the extent to which the receptor impact variables are suitable indicators of ecosystem response for all terrestrial groundwater-dependent ecosystems (GDEs) and stream ecosystems across the Namoi subregion has not been established.

Based on feedback from the regional experts at the ecological modelling workshops, a decision was made to model the Pilliga region separately. However, the formulation of the landscape classification did not easily facilitate separating landscape classes in the Pilliga from the remaining assessment extent. While this did not create any inherent shortcomings in the ecological models, a separate Pilliga set of classes would have made their formulation and discussion less ambiguous. Efforts have been made to emphasise this within the text and results and future assessments of this kind might consider the Pilliga region separately from the outset.

The group of experts present at the ecological modelling workshops had some knowledge of Pilliga vegetation and geomorphology, however, it can be stated that there was a limited understanding of the nature of groundwater interactions both between riverine and terrestrial ecosystems. This was especially true for the ‘Grassy woodland GDE’ that occupies the largest extent of a terrestrial landscape class in the assessment extent considered to be water dependent. There has been limited assessment of groundwater dependency in the diverse vegetation communities of the Pilliga, despite GDE mapping (NSW Office of Water, Dataset 1) showing considerable patches of potentially dependent vegetation. Thus, a more complete picture of the hydrological connections among the Pilliga riverine, vegetation and wetland elements is considered a key priority for future work.

An inherent shortcoming of the ecological modelling process is that it is assumed that there is sufficient hydrological modelling across the full distribution of a class or group of classes when the quantitative models are elicited. In reality, surface water modelling particularly is limited by the extent to which model simulation and calibration nodes exist and can be used to interpolate model output across the stream network. In the Namoi subregion this limitation focuses much of the available surface water model output into the major lowland riverine reaches such as: Namoi River, Maules Creek, Peel River, Coxs Creek and Pian Creek. There is a paucity of surface water hydrological response information for the majority of the upland riverine reaches, and very limited coverage of the entire stream network in the Pilliga region. In many cases this may not hamper the assessment of potential risks across those parts of the landscape most affected from additional coal resource development, given their location toward the floodplain and lowland parts of the catchment. The extent of different landscape classes that are unquantified by surface water modelling is discussed in companion product 3-4 for the Namoi subregion (Herr et al., 2018).

Climate change is not included directly in the receptor impact modelling, but a mid-range climate projection is used and potential changes to precipitation factored into the process through the surface water modelling of hydrological response variables.

Receptor impact modelling was not conducted in full for several landscape classes that intersect the zone of potential hydrological change. These include the ‘Floodplain grass woodland’ and ‘Floodplain grassy woodland GDE’ landscape classes, the non-floodplain wetland landscape classes, ‘Rainforest’ landscape group and the ‘GAB Springs’ landscape class. While this choice reflects a prioritisation given known causal pathways, workshop logistics and expert availability, it is a gap and something that could be addressed through follow up analysis.

The experts considered the ‘Rainforest’ landscape group in the qualitative modelling workshop and defined its potential linkages. However, considerable uncertainty remains around the degree to which this group would normally access groundwater given its habitat within the Namoi subregion is generally in elevated portions of the landscape. The identification of potentially groundwater-dependent elements of the ‘Rainforest’ landscape group (‘Rainforest GDE’) is based to a large degree on remote-sensing information (Kuginis et al., 2016). It is possible that some of these rainforest elements exhibit spectral properties similar to GDEs (i.e. higher greenness values) while in reality not accessing groundwater during their life cycle. Further research would be needed to ascertain the potential for any reliance on groundwater, as well as a characterisation of the potential flow paths of this water supply within the rainforest landscape.

Specific local knowledge of the springs found within the Namoi subregion zone of potential hydrological change probably reflects the relatively low ecological importance of these elements. The ecological experts had some knowledge of other springs within the assessment extent but considered the aforementioned ‘GAB springs’ as relatively insensitive to hydrological change based on their location and hydrogeological setting (see Section 2.7.7). Thus, this gap in expertise was not considered to be particularly crucial for defining potential ecosystem risks in this case.