Clause 1.6: Best available information and the NOF

Clause 1.6 of the NPS-FM provides direction on how local authorities should proceed in the absence of complete and scientifically robust data. This requirement to use the best information applies to local authorities when implementing all parts of the NPS-FM (including when identifying take limits and managing attributes affected by nutrients), rather than just to specific parts.

This requirement in the preliminary provisions of the NPS-FM (Part 1) applies to local authorities when implementing all parts of the NPS-FM (including when identifying take limits and managing attributes affected by nutrients), rather than just to specific parts. It makes it clear that local authorities can use a range of information sources and must not delay making decisions solely because of uncertainty about the quality or quantity of the information available. For instance, where that information is incomplete, uncertainty about its quality or quantity must not be a reason to delay decisions giving effect to the NPS-FM.

Councils should reduce any uncertainty as much as practicable by improving monitoring or analysing data. Doing nothing because of a lack of information is not an acceptable option.

This clause speaks to aspects of the precautionary principle and requires action even where there may be uncertainty about data or the outcomes that will be achieved.

Councils must interpret uncertain information in the way that will “best give effect to this National Policy Statement”. The fundamental concept, objective and policy direction of the NPS-FM is to give effect to Te Mana o te Wai. This means that information must be interpreted in a way that provides first for the health and well-being of the water body.

Situations that can cause uncertainty include:

• no information
• imperfect information (eg, about cause–effect pathways)
• uncertainty from measurement errors or inherent randomness
• ambiguity or varied interpretations.

There may not be enough information if, for example, the monitoring record is short or incomplete. This may make it difficult to determine the current or baseline state of water quality. This will be common for relatively new or newly applied attributes (for example, Fish Index of Biotic Integrity (IBI)) or novel mātauranga Māori attributes that have not been routinely observed before.

This direction emphasises a theme throughout the NPS-FM: knowledge systems other than complete Western scientific data have value and should inform decisions about freshwater. This importantly includes mātauranga Māori, and can also include other local knowledge that has been robustly gathered and validated.

Uncertainty about data or expected outcomes warrants a precautionary approach, rather than using it as a reason to not act or to gather more information before acting. This can mean you take action before there is certainty about outcomes, or that you build a more conservative buffer into a TAS to ensure the health and well-being of the water body.

For limit setting, this may be particularly relevant when linking the achievement of the instream TASs to a restriction on land use or land use practice. For example, it may not be possible to predict with complete scientific certainty that a rule with a limit on stocking rates will achieve x milligrams of chlorophyll-a in a particular lake. However, where the best information available shows a link between the stocking rate and the drivers of chlorophyll-a, and national data shows that reductions in those drivers can be expected as a result of a particular practice, this could be enough to justify limit setting via land use rules.

Councils may set up expert panels to advise on interpreting or applying available information, interpreting national data sets in the local context, or the likely effects of management approaches. The panels should incorporate experts in both Western science and mātauranga Māori, to integrate knowledge across a range of values.

To reduce uncertainty over time, councils can increase monitoring and improve understanding about interactions and the models that estimate them. When new or improved information arises, councils should review their freshwater plans and adjust their actions to reflect that new information.

Best information available and use of models

Where possible, use real data, rather than modelled. However, models will be required to identify and understand relationships between values and attributes, and to calculate catchment-scale interactions. Only use modelled data where other types are not available.

Councils will have to use modelled information in many circumstances. For example, if there is no flow recorder on a river, modelled information from another catchment can provide an understanding of important flow attributes and their timing. Some information will have to be modelled or estimated for future states, for example, projections about how future climate will affect flow levels.

Applying mātauranga Māori can also involve models. These can range from conceptual models of relationships within a catchment, to quantitative models developed by tangata whenua.

Although no models are prescribed for use, it is best practice to ensure they meet certain standards so they will provide quality outputs. For the purpose of the NPS-FM, this includes:

• integrating a range of different values, including Māori values, and relationships in a system
• inputting both quantitative and qualitative data
• using data that is representative of the catchment or water body type where possible. National data sets can also be useful, and may be necessary, where local data is absent or poor
• using evidence-based climate projections
• identifying sources of uncertainty (such as through global sensitivity analysis) and taking action to reduce these
• ensuring all parts of the model, including all assumptions and uncertainties, are clearly set out and transparently reported.
• ensuring the information, including modelled data, is representative of the environment and receiving environment. This may include episodic events or total cumulative load to the receiving environment, rather than relying on base flow calculations.

Weather data: averaging events

Weather data should capture storminess and dry periods rather than averaging these across the year. Averaging weather events can have significant effects on the modelled contribution of contaminants in a catchment.

For example, high Escherichia coli (E. coli) Ioads are carried from pasture and stormwater in storm events. Storms may cause contaminants to bypass riparian barriers and concentrate in overland flow paths. Not modelling the transport of E. coli in storms could indicate that riparian and stock exclusion measures are more effective than they are.

Other measures, such as critical source area management, may have a bigger impact on E. coli levels in those circumstances. Where models do not account adequately for localised variability, the outputs may not account for localised issues. This is especially important for larger freshwater management units or catchments with varied rainfall and land types. For example, if nutrient management tools average nitrogen outputs across different land types, the results may not account for localised increases in contaminants.