Estimated groundwater flux, 2019: Flow

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Creative Commons Attribution 4.0 International

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32
7
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 was used to estimate near-surface groundwater flow amplitudes and separated into four classes to encompass the uncertainty of the dataset.

Layer ID 104449
Data type Image/Raster
Resolution 250.000m
Services Catalog Service (CS-W)

Estimated groundwater flux, 2019: Discharge

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Creative Commons Attribution 4.0 International

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389
13
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

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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.

482
9
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)

Depth to hydrogeological basement map, 2019

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Creative Commons Attribution 4.0 International

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352
14
Added
27 Jan 2020

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

This data set provides an update of New Zealand’s depth to hydrogeological basement map. Depth to hydrogeological basement can be loosely defined as the ‘base of aquifers’; or more strictly as ‘the depth to where primary porosity and permeability of geological material is low enough such that flued volumes and flow rates can be considered negligible’. For more detail on the process and methods, see Westerhoff et al. (2019). New Zealand groundwater atlas: depth to hydrogeological basement. Lower Hutt (NZ): GNS Science. 19 p. Consultancy Report 2019/140.

A national model was used to estimate depth to hydrogeological basement. Hydrogeological basement refers to geological material with primary porosity and permeability that is low enough such that fluid volumes and flow rates can be considered negligible.

Layer ID 104446
Data type Grid
Resolution 250.000m
Services Raster Query API, Catalog Service (CS-W)

Nationally consistent Hydrogeological-unit Map, 2019

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Creative Commons Attribution 4.0 International

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48
12
Added
27 Jan 2020

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

This set of data sets provides a classification of geological units in terms of their importance for groundwater flow and storage. For more detail on the process and methods, see White et al. (2019). New Zealand groundwater atlas: hydrogeological-unit map of New Zealand. Lower Hutt (NZ): GNS Science. 88 p. Consultancy Report 2019/144.

New Zealand Hydrogeological unit map (HUM) separated into aquifers, aquitards, aquicludes and basement developed in a nationally-consistent manner. This dataset includes only outcropping hydrogeological units. This dataset was also joined to the hydrogeological system dataset (Moreau et al. 2019), to provide a single polygon for each unique combination of HUM and hydrogeological system. Summary statistics of surficially mapped products are provided for each polygon (groundwater use, flow, recharge, discharge to the surface; depth to hydrogeological basement; and number of drinking water wells serving >100 people).

Attachment: New Zealand Hydrogeological unit map (HUM) separated into aquifers, aquitards, aquicludes and basement developed in a nationally-consistent manner. This dataset includes overlapping stacked polygons that represent different aged hydrogeological units.

Layer ID 104445
Data type Vector multipolygon
Feature count 1290
ElevationZ coordinates
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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687
11
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)

Erosion modelling to support proposed sediment attribute impact testing 2019

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Creative Commons Attribution 4.0 International

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1011
27
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)

Hydrological modelling to support proposed sediment attribute impact testing 2020

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Creative Commons Attribution 4.0 International

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679
20
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)

Updated suspended sediment yield estimator and estuarine trap efficiency model results 2019

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Creative Commons Attribution 4.0 International

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151
25
Added
14 Aug 2019

This dataset was first added to MfE Data Service on 14 Aug 2019.

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.

Layer ID 103686
Data type Vector linestring
Feature count 593466
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W)

Predicted reference and current streambed deposited fine sediment 2017

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Creative Commons Attribution 4.0 International

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309
16
Added
13 Aug 2019

This dataset was first added to MfE Data Service on 13 Aug 2019.

This dataset reports modelled reference and current state of streambed deposited fine sediment at the REC1 stream segment scale. It provides predicted reference state from a boosted regression tree model trained on 1.) reference site data defined by land cover rules, 2.) all available deposited sediment. It also shows predicted current state trained on all available deposited sediment data.

See Clapcott & Goodwin (2017) for further information on the relevant model rules and data inputs.

Table ID 103685
Data type Table
Row count 576273
Services Web Feature Service (WFS), Catalog Service (CS-W)
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