Sea-draining catchments

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

1008
190
Updated
24 Jul 2019

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.

Catchment names:

Currently a definitive catchment names dataset does not exist. However for your convenience, an unofficial list has been provided in the attachments ("fenz_catnames.csv") which can be joined to the catchment boundaries to provide names. Feedback on the accuracy or completeness of these names is welcomed.

Layer ID 99776
Data type Vector multipolygon
Feature count 10131
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W)

River Water Quality for Swimming Categories [Raw Model Output]

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

1127
37
Added
27 Jun 2018

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)

Predicted lake water quality, 2009-13

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Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1096
30
Added
24 Jun 2018

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)

Erosion modelling to support proposed sediment attribute impact testing 2019

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Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

868
26
Added
05 Sep 2019

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)

Water quality for swimming: Scenario 1

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Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

738
16
Added
10 Oct 2018

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)

Water quality for swimming: Scenario 0

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

685
20
Added
10 Oct 2018

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)

Hydrological modelling to support proposed sediment attribute impact testing 2020

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

583
18
Updated
03 Jun 2020

This dataset was last updated on MfE Data Service on 03 Jun 2020.

This dataset reports modelled mean annual suspended sediment load reduction required to meet suspended sediment attribute bottom lines in the NPS-FM 2020. Results are reported for the REC 2 river reach scale as well as at the “catchment pourpoint average” scale. The dataset includes masks for the DoC estate as well as glacial mountain source of flow.

During policy development, the Ministry for the Environment tested suspended sediment load reductions required to meet various potential attribute bottom lines. The information from February 2020 reflects the bottom lines in the NPS-FM 2020. For further information on this specific dataset, see “Hicks and Shankar 2020. Contract 23184 Task: Sediment load reductions to meet visual clarity bottom lines”. This report is available on the Ministry for the Environment’s publications website where it is listed as Technical Report 6.

For further information on the modelling, see Hicks et al. (2019) Sediment load reductions to meet suspended and deposited sediment thresholds. NIWA Client Report No. 2019100CH. Prepared for the Ministry for the Environment. This report is available here: www.mfe.govt.nz/publications/fresh-water/sediment-....

Note that the river segment and pour point catchment results provided in the 2019 dataset form the basis for the erosion and economic modelling assessment of proposed sediment attributes as reported in 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.

Layer ID 103687
Data type Vector multipolygon
Feature count 633
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W)

Option 1 for reducing nitrogen loss

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

541
10
Added
20 Sep 2019

This dataset was first added to MfE Data Service on 20 Sep 2019.

This dataset shows land that would be covered by the option 1 of section 8.4 Immediate action to reduce nitrogen loss.

This web map has been developed by the Ministry for the Environment to support policy proposals in the Action for Healthy Waterways discussion document. The proposals are currently being consulted on.

It provides extra detail on Option 1 in section 8.4 of the discussion document (Immediate action to reduce nitrogen loss). The map indicates the pastoral catchments and sub-catchments specified as high-nitrate in Option 1, where regional rules are not already in place or proposed, and shows the land considered to be low-slope.

Low-slope is defined in this option as land parcels with an average slope of less than 5, 7 or 10 degrees. We are seeking feedback on the appropriate slope threshold to use.

The catchments are those with the highest 10% of nitrate levels in the MfE Environmental Reporting River Water Quality dataset found here. Catchments where the predominant sources of nitrate are non-pastoral in origin are excluded.

Under Option 1, a per-hectare cap, or threshold, for nitrogen losses will be set for each sub-catchment with similar soil type and rainfall. This threshold will be based on a ranking of nitrogen losses from farms within each sub-catchment, and could be set at the 90th percentile, or the 70th, or a point between. Feedback is sought on where this threshold should be set.

This is only one of the options being consulted on, The areas indicated are provisional and may not equate to areas included in regulation.

Layer ID 103881
Data type Vector polygon
Feature count 13564
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W)

Estimated groundwater flux, 2019: Discharge

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Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

313
8
Added
27 Jan 2020

This dataset was first added to MfE Data Service on 27 Jan 2020.

This set of data sets provides an estimation of groundwater flux. There are three components: Groundwater recharge: development of nationwide mean (daily and seasonal) groundwater recharge data sets through the combination of three pre-existing groundwater recharge models; Groundwater–surface water exchange: development of a national indicative groundwater discharge data set using an existing national groundwater flow model, as well as comparison with a pre-existing gaining/losing stream prediction data set; Groundwater flow: development of a national groundwater flow data set using an existing national groundwater flow model. For more detail on the process and methods, see Westerhoff et al. (2019). New Zealand groundwater atlas: Groundwater Fluxes. Lower Hutt (NZ): GNS Science. 60 p. Consultancy Report 2019/126.

A national groundwater model (NWT) was used to estimate the probability of groundwater discharging to the surface and separated into classes to encompass the uncertainty of the dataset.

Layer ID 104448
Data type Image/Raster
Resolution 250.000m
Services Catalog Service (CS-W)

Estimated groundwater flux, 2019: Recharge

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

344
6
Added
27 Jan 2020

This dataset was first added to MfE Data Service on 27 Jan 2020.

This set of data sets provides an estimation of groundwater flux. There are three components: Groundwater recharge: development of nationwide mean (daily and seasonal) groundwater recharge data sets through the combination of three pre-existing groundwater recharge models; Groundwater–surface water exchange: development of a national indicative groundwater discharge data set using an existing national groundwater flow model, as well as comparison with a pre-existing gaining/losing stream prediction data set; Groundwater flow: development of a national groundwater flow data set using an existing national groundwater flow model. For more detail on the process and methods, see Westerhoff et al. (2019). New Zealand groundwater atlas: Groundwater Fluxes. Lower Hutt (NZ): GNS Science. 60 p. Consultancy Report 2019/126.

Three national models of groundwater recharge in New Zealand were used (NGRM, TopNet, IrriCalc) to create a mean model of groundwater recharge. This dataset summarises the gridded groundwater recharge from this model mean for the period 2000-2015 in mm/day.

_Attachment 1: _A complementary dataset describing the standard deviation of the NZGroundwaterRecharge_mean_20002015 dataset.

Attachment 2: This dataset summarises the gridded autumn groundwater recharge from this model mean for the period 2000-2015 in mm/day. Also complementary dataset of standard deviation.

Attachment 3: This dataset summarises the gridded spring groundwater recharge from this model mean for the period 2000-2015 in mm/day. Also complementary dataset of standard deviation.

Attachment 4: This dataset summarises the gridded summer groundwater recharge from this model mean for the period 2000-2015 in mm/day. Also complementary dataset of standard deviation.

Attachment 5: This dataset summarises the gridded winter groundwater recharge from this model mean for the period 2000-2015 in mm/day. Also complementary dataset of standard deviation.

Layer ID 104447
Data type Grid
Resolution 1010.000m
Services Raster Query API, Catalog Service (CS-W)
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