9 Content for product 2.7 (receptor impact modelling)

Although some examples are interspersed throughout this submethodology, it is recommended that M08 be read in conjunction with its application in product 2.7 (receptor impact modelling) for each bioregion or subregion. The structure in product 2.7 closely follows the methodology outlined in M08. Table 11 shows the recommended content for product 2.7. It identifies those landscape classes (or landscape groups) that may experience some hydrological change and those that are very unlikely to do so. For those that do, product 2.7 provides a summary of the landscape class (or landscape group) and how it works, details the qualitative mathematical modelling expert workshop and sign-directed graph output for that landscape class, describes the choice of hydrological response variables and receptor impact variables selected, summarises the elicitation scenarios presented to experts, and concludes with a description of the receptor impact model that is constructed and any interpretations that may be made around it.

Table 11 Recommended content for product 2.7 (receptor impact modelling)

Section number

Title of section

Main content to include in section





  • construction of qualitative models for landscape classes
  • choice of hydrological impact variables and receptor impact variables
  • construction of receptor impact models
  • expert elicitation process


Prioritising landscape classes for receptor impact modelling



  • highlight landscape classes that are considered (and those that are not) based on the hydrological and conceptual modelling
  • discuss connectivity between landscape classes, if appropriate


Landscape class #1

Summary Description

  • general description of landscape class (typically based on review and collation ahead of qualitative modelling workshop); provides opportunity to include some of that evidence base Qualitative model

  • both results (from the qualitative modelling workshop) and narrative
  • highlight key assets where possible
  • include evidence base
  • include signed digraph and analysis for every landscape class Choice of hydrological response variables and receptor impact variables

On the basis of the advice from both experts and the Assessment team:

  • describe choice of HRVs and RIVs from the qualitative models
  • describe how those variables are represented in the surface water and groundwater models Elicitation scenarios

  • for ecological assets: these are the elicitation scenarios considered and questions asked of experts – to find out relationship between HRVs and RIVs
  • details about the scenarios (e.g. questions) should be compiled as a document (doesn't need to align with BA look and feel); this document then should be registered as a dataset and cited here Receptor impact model

  • outline results from elicitation [data]
  • describe and interpret the statistical model (based on data) that describes ΔRIV given one or more hydrological response variables and the different reporting times
  • note: this is just the model not the application of the model; instead, the results arising from applying this model are presented in product 3-4


Landscape class #2

As per above


Add more landscape classes as appropriate

As per above


Limitations and gaps

This is the final section of this product. The numbered section may vary depending on the number of landscape class sections prior to this section.

HRV = hydrological response variable, RIV = receptor impact variable

The receptor impact modelling methodology (this product) and its implementation was affected by design choices that have been made within BA. Some of these broader choices are described in companion submethodology M10 (as listed in Table 1) for analysing impacts and risks (Henderson et al., 2018). Table 12 summarises some of the assumptions made for the receptor impact modelling, the implications of those assumptions for the results, and how those implications are acknowledged through the BA products.

Table 12 Summary of the receptor impact modelling assumptions, the implications of those assumptions and how the potential implications are acknowledged through bioregional assessment products

Assumptions of receptor impact modelling



Discretisation of continuous landscape surface

Provided a defined spatial scope for experts to address. Connections between landscape classes broken. Changes in one landscape class may have implications for adjacent landscape classes

Identify potential connections between landscape classes where possible in the impact and risk product

Data underpinning landscape classes (omissions / incorrect attribution)

Landscape class definition required data input from pre-existing data sources. Prioritisation for qualitative mathematical models and RIMs may be affected. Minimal effect on model development for RIMs

Acknowledge issues with data in the impact and risk product (also done in the conceptual modelling product); in product 3-4 acknowledge that mapped results reflect the mapped inputs

Areas of landscape classes are constant over modelling period

Provided a defined spatial scope for experts to address. BA is about identifying existing areas that are at risk from coal resource development as opposed to predicting the changes in areal extent or transition to different landscape classes. Some potential exists for changes in the area of the landscape class to affect its sensitivity to hydrological change but this would need to be assessed on an asset by asset basis.

Acknowledge in Methods

Other developments and users of water (e.g. agriculture) are constant over time

Provided a defined context for experts to consider. BA is about identifying existing areas that are at risk from coal resource development as opposed to predicting the changes due to other developments or the relative attribution

Acknowledge in Methods

Landscape characteristics other than hydrological variables are not represented in quantitative RIMs

Refined scope for experts to how RIMs were associated with hydrological variables that could be provided by hydrological models developed by BA. Loss of within-landscape class predictive performance from the RIMs

Identify as knowledge gap where model does not represent some dependencies that are not captured by statistical dependencies with the chosen hydrological response variables. Acknowledge importance of local (versus regional) analyses where the concern is over particular parts of a landscape class

Selection of experts, limited expert availability, and impact on represented domain knowledge and expertise

Experts provided domain expertise and experience that informed both model structure and provided quantifiable predictions of RIV response to novel hydrological scenarios. Expert availability affected the quality/utility of the qualitative mathematical model; identification of RIVs that reflect expertise of those in the room

Acknowledge that the receptor impact variable is an ‘indicator’ of the potential ecosystem response. Identify as knowledge gap where part of the landscape class is not represented

Simplification of complex systems

Provided formal approach to model identification and selection of candidate RIVs. Not all components and relationships are represented by receptor impact models

Acknowledge that one or two RIVs can under estimate complex ecosystem function; make assumptions clear; high-level interpretation of results; emphasise importance of interpreting the hydrological change

The common set of modelled hydrological response variables are used across each landscape class

Refined scope for experts to how RIMs were associated with hydrological variables that could be provided by hydrological models developed by BA. Enables some simplification of complex systems. Loss of local specificity in predictions of receptor impact variables

The need for local-scale information is identified (in multiple places)

RIV selection (assumption that RIV is good indicator of ecosystem response)

The qualitative models informed the selection of RIVs within the additional constraints imposed by expert availability given project timelines. Focus of the quantified relationships within the landscape class

The need for local-scale information is identified (in multiple places)

Extrapolation of predictions beyond elicitation scenarios

The ranges of hydrological scenarios to be considered at the expert elicitation sessions were informed by preliminary hydrological modelling output and hydrological expert advice within BA. However, final model results sometimes extended beyond this preliminary range due to necessary changes in underlying hydrological modelling assumptions and assimilation of data. Extrapolation beyond the range of hydrological response variables considered by the expert elicitation increases uncertainty in receptor impact variable predictions

Identify as a limitation for the appropriate landscape class in the impact and risk product where this occurs

For qualitative models, focus on impacts of long-term sustained hydrological changes (press perturbations) to ecosystems. Note that quantitative RIMs can and do account for pulse perturbations and associated RIV responses

Qualitative models may under-represent impacts of shorter-term hydrological changes (pulse perturbations) on ecosystems and landscape classes

Describe rationale for the focus on press perturbations in the receptor impact modelling submethodology (this product). Note that many potential pulse perturbations are caused by accidents and managed by site-based processes. Identify as a limitation / knowledge gap. Note that quantitative RIMs do account for pulse perturbations

BA = bioregional assessment, HRV = hydrological response variable, RIM = receptor impact model, RIV = receptor impact variable

Product 2.7 (receptor impact modelling) does not cover results for the prediction of receptor impact variables. These results are addressed as part of product 3-4 (impact and risk analysis). Companion submethodology M10 (as listed in Table 1) for analysing impacts and risks (Henderson et al., 2018) describes some of the additional underlying methodology for these results, and in particular the choice of summary and aggregation of predictions to landscape classes and water-dependent assets. These results for landscape classes and assets are derived by applying the methodology described in Section 8.1 and Section 8.2.

Last updated:
18 December 2018