Layers

Wetlands support high levels of biodiversity. They provide habitat for native invertebrates, plants, fish, and bird species (eg fernbird, kōkopu, and eels), many of which live only in wetlands. Wetlands act as ‘kidneys’ and giant sponges – they clean the water of excess nutrients and sediment, control flood water and pollutants, and act as carbon sinks (removing carbon dioxide from the atmosphere). Wetlands have strong cultural and spiritual importance for Māori. They are a food source (eg eel, whitebait) and provide material for weaving (eg raupō, harakeke (flax)). Draining wetlands for agricultural and urban development over the past 150 years has led to significant wetland loss and deterioration.

Summary report available at www.mfe.govt.nz/publications/fresh-water/analysis-...

More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

This dataset relates to the March 2018 report National E. coli modelling - Supplementary material to support setting draft regional targets for swimmable rivers.

Scenario 1 represents the level of stock exclusion and riparian planting for the nominal year 2030
when the CWP rules have been implemented assuming that the effects of the measures have been realised and water quality has attained a new attribute state. Scenario 1 also includes the impact of regional committed work (that is, work already committed to by councils in their policy plans, or planned infrastructure investment) in regions that have committed to mitigation beyond the CWP.

The geometries are based off REC1, and the field 'Swimability_band' defines the modelled E. coli attribute state NPS-FM human health for recreation value. The rest of the fields come from the River Environment Classification.

This dataset relates to the March 2018 report National E. coli modelling - Supplementary material to support setting draft regional targets for swimmable rivers.

It represents Scenario 0, baseline (i.e. 2017) including the current level of on-farm fencing and land use - further details available in the above report.

The geometries are based off REC1, and the field 'Swimability_band' defines the modelled E. coli attribute state NPS-FM human health for recreation value. The rest of the fields come from the River Environment Classification.

"Water clarity is a measure of underwater visibility in rivers and streams and can vary due to differences in land use, climate, elevation, and geology. Water clarity can be reduced by the presence of fine particles like silt, mud or organic material in the water. This affects the habitat and feeding of aquatic life like fish and aquatic birds. Water clarity is an important indicator of the health of a waterway, and is also a consideration for recreational activities like swimming and wading.
This dataset relates to the ""Geographic pattern of river water clarity"" measure on the Environmental Indicators, Te taiao Aotearoa website. "

Water clarity is a measure of underwater visibility in rivers and stream. Water clarity can be reduced by the presence of fine particles like silt, mud or organic material in the water. This affects the habitat and feeding of aquatic life like fish and aquatic birds. Water clarity is an important indicator of the health of a waterway, and is also a consideration for recreational activities like swimming and wading.
This dataset relates to the "River water quality trends: clarity" measure on the Environmental Indicators, Te taiao Aotearoa website.

To view the map of vulnerable catchments, click the orange 'plus’ icon above.

The Government has committed $100 million over 10 years through the Freshwater Improvement Fund to support initiatives which improve the management of fresh water within quality and quantity limits.

The fund focuses on projects that will make a significant and measurable improvement to rivers, lakes, streams, groundwater and wetlands, with priority on the most vulnerable catchments.

This dataset shows catchments that have been classified as vulnerable (as defined by the criteria for the Freshwater Improvement Fund).

This dataset includes three “packages” of information, each with multiple variables. The packages include:

1. Load – results on mean annual suspended sediment load reported by REC 2 river reach scale for various model scenario variations.
2. Lakes – results on sediment inflow, outflow, and entrapment in lakes and reservoirs
3. Coastal – results on sediment inflows, trap efficiency, and sedimentation rates in coastal hydrosystems (estuaries)

For further detail on the modelling methods and discussing results, see Hicks, M., Semademi-Davies, A., Haddadchi, A., Shankar, U., Plew, D. (2019) Updated sediment load estimator for New Zealand. NIWA Client Report No. 2018341CH, prepared for Ministry for the Environment. January 2019. Available online: www.mfe.govt.nz/publications/fresh-water/updated-s...

Note that some portions of this dataset refine and update 2011 modelling on suspended sediment loads across New Zealand, whereas other components, especially the coastal package, report new modelling results.

"Sunshine is important for our health and recreation, and for the environment. It is also important for our agriculture-based economy, for example, for plant growth.

This layer shows percentage of normal sunshine hours across New Zealand for 2013 as part of the data series for years 1972 to 2013. Data is for a calendar year (January–December).

The National Institute of Water and Atmospheric Research (NIWA) mapped mean annual sunshine hours from the virtual climate station network data (NIWA) generated from data in its National Climate Database, for the period 1981–2013. It generated the Units: percentage of normal by comparing the annual average to the long-term mean for 1981–2010.

This dataset relates to the "Sunshine hours in New Zealand" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: raster catalogue
Unit: hrs/yr"

Sunshine is important for our health and recreation, and for the environment. It is also important for our agriculture-based economy, for example, for plant growth.

This layer shows percentage of normal sunshine hours across New Zealand for 2012 as part of the data series for years 1972 to 2013. Data is for a calendar year (January–December).

The National Institute of Water and Atmospheric Research (NIWA) mapped mean annual sunshine hours from the virtual climate station network data (NIWA) generated from data in its National Climate Database, for the period 1981–2013. It generated the Units: percentage of normal by comparing the annual average to the long-term mean for 1981–2010.

This dataset relates to the "Sunshine hours in New Zealand" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: raster catalogue
Unit: hrs/yr

"Sunshine is important for our health and recreation, and for the environment. It is also important for our agriculture-based economy, for example, for plant growth.

This layer shows percentage of normal sunshine hours across New Zealand for 2011 as part of the data series for years 1972 to 2013. Data is for a calendar year (January–December).

The National Institute of Water and Atmospheric Research (NIWA) mapped mean annual sunshine hours from the virtual climate station network data (NIWA) generated from data in its National Climate Database, for the period 1981–2013. It generated the Units: percentage of normal by comparing the annual average to the long-term mean for 1981–2010.

This dataset relates to the "Sunshine hours in New Zealand" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: raster catalogue
Unit: hrs/yr"