Accounting for local conditions
Default guideline values (DGVs) can provide you with an important starting point for managing water quality but they cannot account for the large spatial or temporal variation in natural water quality. This includes variation in environmental variables that influence the bioavailability and toxicity of contaminants.
Toxicant DGVs are based on data from a specific set of solution parameters, such as pH, hardness, dissolved organic carbon, salinity and temperature. These characteristics vary widely throughout Australian and New Zealand waters.
In addition, DGVs may not protect locally important species because published global data are usually only available for a very limited number of (usually standard) toxicity testing species. Very few of them are Australian or New Zealand species.
This is why you should, wherever possible, tailor DGVs and the types of water chemistry data collected to account for local conditions. The ultimate tailoring of a DGV to local conditions is the derivation of a site-specific guideline value. In addition to the guidance provided in the Water Quality Guidelines, another relevant source of guidance for deriving site-specific guideline values can be found in van Dam et al. (2019), while Huynh & Hobbs (2019) provide specific guidance tailored for the coal resource industry, but which will also have broader applicability.
In some cases, DGVs can be appropriately modified to account for some important local factors. For example:
- corrections for the effects of hardness for metals
- corrections for the effects of pH for ammonia
- dealing with naturally elevated background concentrations (natural toxicant concentrations unrelated to human disturbance).
In addition, or alternatively, direct toxicity assessment (DTA) can be a useful tool to account for local conditions (sections 184.108.40.206 and 8.3.6 of ANZECC & ARMCANZ 2000), and has several applications. We provide some updated guidance on the benefits and uses of DTA.
The process of accounting for local conditions is usually completed in the Water Quality Management Framework at:
- Step 4 — Determine water/sediment quality guideline values
- Step 6 — Assess if draft water/sediment quality objectives are met.
Knowing when to refine default guideline values
Note that your local jurisdiction may have its own guidance for applying and refining guideline values, and you should always consult with it on appropriate methods.
For most indicators and issues, you would only refine DGVs after continuous and extensive monitoring showed that test-site data exceedances posed no risk to the ecosystem. This would require hierarchical measurements of the stressor line of evidence, in this case water chemistry, together with other lines of evidence that also demonstrate no ecosystem detriment.
You could also refine guideline values if longer-term monitoring showed that test-site data were consistently below the DGVs.
Evaluating monitoring data against default guideline values
You need to interpret water quality monitoring data correctly to enable effective comparison with guideline values.
To do this, you should apply a decision scheme that provides step-by-step guidance on how to consider and (if necessary) treat water chemistry data obtained for site-specific environmental conditions. Such a scheme would include consideration of:
- bioavailable fraction
- background concentrations
- analytical detection limits.
It is not mandatory to use hierarchical chemical measurements because, in most instances, the chemistry line of evidence will be assessed in parallel with other lines of evidence.
If you want to make meaningful and appropriate comparisons with DGVs or site-specific guideline values, then hierarchical chemical measurements are important. They can greatly assist with interpretation of the chemistry line of evidence where initial measurements (i.e. steps early in the hierarchy) are near or above the guideline value.
The simple adjustments and corrections that we describe here make this a cost-effective and (in practice) rapid exercise when data on key water quality parameters are available.
You should consider the extent to which local factors will influence your sampling and data collection and manipulation requirements when defining the issue and setting objectives for a monitoring or assessment program.
Refining default guideline values for metals
When evaluating measured chemistry against DGVs for metals, where possible it will be important to account for the influences of important local water quality variables, such as water hardness, pH, salinity and the associated mix of dissolved salts, and dissolved organic carbon (DOC) on metal bioavailability.
DGVs are typically derived for either low hardness, near neutral pH fresh waters with negligible DOC or pristine marine waters of typical oceanic salinity. Currently, there are no DGVs for estuarine waters or inland saline waters.
Refining toxicant guideline values based on other considerations
We describe how guideline values can potentially be refined based on a number of other considerations.
Using multiple lines of evidence
So far our discussion concerns the assessment of the chemistry line of evidence for evaluating compliance with guideline values. But it is important that compliance with guideline values is considered as one of a number of lines of evidence that may be used when assessing water quality (as part of a weight-of-evidence process). These lines of evidence could include monitoring or assessment of other pressures, stressors (e.g. habitat, flow) and ecosystem receptors.
Ultimately, it is biological measurement of relevant ecosystem receptors that will provide confirmation that water quality at a site is not being affected.
If the guideline value is exceeded or there is low confidence in desktop assessments (e.g. difficulty in modelling metal speciation), then you should opt for DTA or biodiversity assessment as an additional line of evidence. Additional evidence can be obtained from measurements of bioaccumulation.
The toxicity line of evidence could specifically deal with cases where chemical mixtures modify toxicity from that based on the additivity of individual toxicant effects. This will also be of use where the protection of locally important species is a concern.
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