Creative Commons Attribution 3.0 New Zealand
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was last updated on MfE Data Service on 10 Aug 2017.
Water quality for swimming categories for rivers 4th order and above. This dataset was used to compose the current state for water quality for swimming.
Note this data is under review and will be updated in due course. This information is based on modelled and measured data using the approach outlined at www.mfe.govt.nz/fresh-water/freshwater-management-... . The modelling methods used are outlined in Snelder et al. (2016) Strategic assessment of New Zealand’s freshwaters for recreational use: a human health perspective. LWP Client Report 2016-011 www.mfe.govt.nz/publications/fresh-water/strategic...
Column headings:
NZREACH: NZREACH from the River Environment Classification Version 1
Segment_length(m): reach length in metres
Category: Water quality for swimming category see www.mfe.govt.nz/fresh-water/national-targets-swimm...
Note blank cells are reaches where a prediction was not possible because of missing predictor variables.
Regional_council: Regional council
| Table ID | 53620 |
|---|---|
| Data type | Table |
| Row count | 66838 |
| Services | Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 4.0 International
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was first added to MfE Data Service on 01 Sep 2019.
This dataset shows land parcels within grassland and annual cropping areas which have an average slope of less than 10 degrees. Polygons are attributed into 3 slope classes: less than 5 degrees mean slope; 5 - 7 degrees mean slope; 7 - 10 degrees mean slope.
| Layer ID | 103847 |
|---|---|
| Data type | Vector multipolygon | Feature count | 589664 |
| Services | Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 3.0 New Zealand
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was last updated on MfE Data Service on 10 Aug 2017.
Water quality for swimming categories for lakes with perimeters over 1.5 km. This dataset was used to compose the current state for water quality for swimming.
This data is under review and will be updated in due course. This information is based on modelled and measured data using the approach outlined at www.mfe.govt.nz/fresh-water/national-targets-swimm... .
The modelling methods used are outlined in Snelder et al. (2016) Strategic assessment of New Zealand’s freshwaters for recreational use: a human health perspective. LWP Client Report 2016-011 www.mfe.govt.nz/publications/fresh-water/strategic...
Column headings:
LID: LID from Freshwater Environments of New Zealand (FENZ)
Name: Lake name
Category: Water quality for swimming category see www.mfe.govt.nz/fresh-water/freshwater-management-...
Note blank cells are lakes where a prediction was not possible because of missing predictor variables.
Lake_Permeter(m): lake perimeter in metres
Regional_council: Regional council
| Table ID | 53618 |
|---|---|
| Data type | Table |
| Row count | 861 |
| Services | Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 4.0 International
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was last updated on MfE Data Service on 24 Jul 2019.
This dataset provides boundaries for catchments that drain to the sea (i.e. sea draining catchments).
It is extracted from the Freshwater Ecosystems of New Zealand (FENZ) v1.0 geodatabase. Ministry for the Environment hosts this copy of this layer for convenience and visibility. For all inquiries please contact Department of Conservation directly.
FENZ requires specialist GIS knowledge for its technical operation and biodiversity knowledge for understanding the content. Because of FENZ’s complexity, DOC is providing advice, briefings and training (where possible) to ensure users understand its strengths, limitations and appropriate applications.
If you would like more information about FENZ or access to any FENZ data sets, email fenz@doc.govt.nz.
www.doc.govt.nz/our-work/freshwater-ecosystems-of-...
Variables:
Catch_id - This is a unique identifier that can be used to link to other datasets in the FENZ database, or datasets from other sources that also use a FENZ id.
| Layer ID | 99776 |
|---|---|
| Data type | Vector multipolygon | Feature count | 10131 |
| Services | Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 4.0 International
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was first added to MfE Data Service on 27 Jun 2018.
Summary
Water quality for swimming categories for rivers 4th order and above. This dataset was used to compose the current state for water quality for swimming.
Note this data is under review and will be updated in due course. This information is based on modelled and measured data using the approach outlined at www.mfe.govt.nz/fresh-water/freshwater-management-... .
The modelling methods used are outlined in Snelder et al. (2016) Strategic assessment of New Zealand’s freshwaters for recreational use: a human health perspective. LWP Client Report 2016-011 www.mfe.govt.nz/publications/fresh-water/strategic...
Versions
This dataset is the geometric version of this: data.mfe.govt.nz/table/53620-river-water-quality-f...
This dataset has now been superseded due to consultation with local authorities, and this is the latest version: data.mfe.govt.nz/layer/95555-river-water-quality-f...
Column headings:
NZREACH: NZREACH from the River Environment Classification Version 1
ORDER: Strahler stream order
Category: Water quality for swimming category see www.mfe.govt.nz/fresh-water/national-targets-swimm...
PrGT540: percentage of samples that exceeded 540 E.coli per 100mL
PrGT260: percentage of samples that exceeded 260 E.coli per 100mL
Median: median E.coli per 100mL
Q95: 95th percentile E.coli per 100mL
Note: blank cells are reaches where a prediction was not possible because of missing predictor variables.
| Layer ID | 95562 |
|---|---|
| Data type | Vector linestring | Feature count | 570577 |
| Services | Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 4.0 International
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was first added to MfE Data Service on 24 Jun 2018.
This dataset is a result of Random Forest modelling to predict cyanobacterial biovolume in lakes nationally, which included spatial modelling of chlorophyll a, TN, TP, Secchi depth, Trophic Level Index, and Cyanobacterial biovolume.
More information about the methods used to create this dataset can be found here: www.mfe.govt.nz/publications/fresh-water/strategic...
LID - FENZ Lake ID
Name - Name of lake (where available)
RegionalCo - Regional council name
CHLA - Chlorophyll a (mg/L)
TN - Total nitrogen (mg/m3)
TP - Total phosphorus (mg/m3)
SECCHI - Secchi disc depth (m)
TLI3 - Trophic Level Index (unitless)
CyanoBioVo - Cyanobacterial biovolume (mm3/L)
| Layer ID | 95541 |
|---|---|
| Data type | Vector multipolygon | Feature count | 3819 |
| Services | Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 4.0 International
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was first added to MfE Data Service on 05 Sep 2019.
This dataset reports erosion modelling results regarding annual mean sediment load reductions required to meet proposed suspended sediment attribute bottom lines. For more detail on the modelling process and methods, see Neverman et al. (2019). Impact testing of a proposed suspended sediment attribute: identifying erosion and sediment control mitigations to meet proposed sediment attribute bottom lines and the costs and benefits of those mitigations. Maanaki Whenua Landcare Research Client Report. Prepared for the Ministry for the Environment.
Results of modelled mitigations are reported at catchment scale and at the REC2 river reach scale. The modelled on-farm mitigations (per economic optimisation as reported in Neverman et al. (2019) are also mapped.
| Layer ID | 103850 |
|---|---|
| Data type | Vector multipolygon | Feature count | 585 |
| Services | Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 4.0 International
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was first added to MfE Data Service on 27 Jun 2018.
Summary
Water quality for swimming categories for rivers 4th order and above. This dataset was used to compose the current state for water quality for swimming.
This information is based on modelled and measured data using the approach outlined at www.mfe.govt.nz/fresh-water/freshwater-management-... .
The modelling methods used are outlined in Snelder et al. (2016) Strategic assessment of New Zealand’s freshwaters for recreational use: a human health perspective. LWP Client Report 2016-011 www.mfe.govt.nz/publications/fresh-water/strategic...
Versions
This dataset is the geometric version of this: data.mfe.govt.nz/table/53620-river-water-quality-f...
This dataset is the latest version of the Water Quality for Swimming Categories set.
Column headings:
NZREACH: NZREACH from the River Environment Classification Version 1
ORDER: Strahler stream order
Category: Water quality for swimming category see www.mfe.govt.nz/fresh-water/national-targets-swimm...
Note: blank cells are reaches where a prediction was not possible because of missing predictor variables.
| Layer ID | 95555 |
|---|---|
| Data type | Vector linestring | Feature count | 66837 |
| Services | Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 4.0 International
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was first added to MfE Data Service on 10 Oct 2018.
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.
| Layer ID | 98359 |
|---|---|
| Data type | Vector multilinestring | Feature count | 73336 |
| Services | Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W) |
Creative Commons Attribution 4.0 International
You may use this work for commercial purposes.
You must attribute the creator in your own works.
This dataset was first added to MfE Data Service on 10 Oct 2018.
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.
| Layer ID | 98358 |
|---|---|
| Data type | Vector multilinestring | Feature count | 73336 |
| Services | Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W) |