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Current state vs freshwater objectives: Sediment

Description

Comparison of visual clarity and sediment loads to National Bottom Lines in New Zealand’s river receiving environments.

The dataset contains the following attributes for rivers and watersheds.

Attributes for Watersheds:

  • The unique DN2.4 segment identifier
  • The best estimate of the excess Sediment load (as a yield) for the critical catchment that this watershed belongs to (t/km2/year)
  • The best estimate of the excess Sediment load (as a proportion of current yield) for the critical catchment that this watershed belongs to (%)

Attributes for Riverlines:

  • The unique DN2.4 segment identifier
  • Current estimated median visual clarity (m) for this segment
  • Current estimated Sediment yield (t/km2/year) for this segment
  • The best estimate of the excess Sediment load for this segment (t/km2/year)
  • The probability that the current state as defined by the estimated median visual clarity complies with the criteria for the NOF C-band for this segment

 

Date: 19 August 2023 Version: v2

Contact: Ton Snelder, LWP Ltd

 

Link to report / paper

Snelder TH, Whitehead AL, Fraser C, Larned, S, Schallenberg, M. (2020) Nitrogen loads to New Zealand aquatic receiving environments: comparison with regulatory criteria. New Zealand Journal of Marine and Freshwater Research 54:527–550

Snelder T, Smith H, Plew D, Fraser C (2023) Nitrogen, phosphorus, sediment and Escherichia coli in New Zealand’s aquatic receiving environments: Comparison of current state to national bottom lines. LWP Ltd Report 2023-09, Christchurch, New Zealand

 

Preview Image

 

Dataset attributes

Spatial extent All NZ
Spatial resolution Based on the digital river network used by the River Environment Classification (REC). This river network is generally consistent with 1:50,000 scale maps.
Temporal extent Nominally 2016 to 2020. This 5-year period was used to esimate current nutrient related attribute states.
Temporal resolution Loads are average annual.
Evaluation method (Validation) Individual models were evaluated using bootstrapping or leave-one-out cross validation.
Evaluation result (Numeric) Several measures were used to describe the performance of the models used to predict the current state of the nutrient attributes (i.e., the four nutrient concentrations) and to predict nutrient yields. See report for details.
Evaluation result (Categorical)
Uncertainty method Monte Carlo analysis was used to estimate the overall uncertainties for all segments of the river network. (i.e., delete “lakes and estuaries”.)
Uncertainty data format (Numeric) Confidence interval of 90% confidence interval.
Uncertainty data format (Categorical)

 

Methodology

Based on spatial statistical models and a comparison of predicted concentration to criteria defined by the NPSFM for various nutrient related attribute target states for rivers and lakes and equivalent thereof for estuaries.

See Snelder T, Smith H, Plew D, et al (2021) Nitrogen, phosphorus, sediment and Escherichia coli in New Zealand’s aquatic receiving environments. Comparison to national bottom lines. LWP Ltd, Christchurch, New Zealand.

 

Fitness for purpose / limitations

This table indicates whether the dataset is suitable for different types of questions at different scales.

Note: Users should carefully consider their purpose as this dataset may not be suitable.

Operational Absolute Relative Screening/scoping
Block/farm No No No No
Multi-farms(5+) No No No No
Catchment Maybe Maybe Maybe Maybe
National/regional Yes Yes Yes Yes
Caveat(s) The study has used all the available data. Therefore, it would be difficult in most catchments to improve on the analysis. However, because the models were all national in extent, there may be a degree of model bias when the results are applied at fine scales.

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