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.

252
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)

Depth to hydrogeological basement map, 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.

244
8
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

You may use this work for commercial purposes.

You must attribute the creator in your own works.

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)

Ground-level ozone concentrations, Auckland, 2001–16

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

2511
12
Updated
20 Nov 2019

This dataset was last updated on MfE Data Service on 20 Nov 2019.

Ground-level (tropospheric) ozone (O3) exists at a natural background level but is also produced when nitrogen oxides (NOx) and volatile organic compounds from vehicle emissions, petrol fumes, industrial processes solvents, and other human-made sources react in the presence of sunlight. It is the primary component of photochemical smog.
Ozone also occurs naturally in the stratosphere, where it protects us from ultraviolet radiation – this ozone occasionally can mix downwards to ground level.
Because sunlight and warmth are required for the chemical reactions that form ground-level ozone, peak concentrations often occur in summer when daylight hours are longer and temperatures are higher. Since the precursors for ozone can travel downwind from their sources before they react with sunlight, ozone concentrations can be high many kilometres from the precursor emissions’ sources.
Exposure to high concentrations of ozone can cause respiratory health problems and is linked to cardiovascular health problems and mortality. It can also damage vegetation.
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.

Table ID 98423
Data type Table
Row count 535064
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Lake Submerged Plant Index, 1991–2016

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Creative Commons Attribution-NonCommercial 4.0 International

You may not use this work for commercial purposes.

You must attribute the creator in your own works.

3406
21
Added
25 Apr 2017

This dataset was first added to MfE Data Service on 25 Apr 2017.

Submerged plants are good indicators of the ecological quality of lakes. Because they are attached to the bed of lakes, submerged plants are easy to observe and identify, and they are unable to move away from environmental changes. The plant species found within lakes can tell us about their level of habitat degradation and exotic weed invasion.

The file contains Lake submerged plant index scores for each sampling occasion.

Table ID 53606
Data type Table
Row count 248
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

2016 LUCAS Land Use Mapping Report Manaaki Whenua Landcare Research

241
125
Added
21 Oct 2019

This item was first added to MfE Data Service on 21 Oct 2019

48
Document ID22375
File name2016-lucas-land-use-mapping-report-manaaki-whenua-landcare-research.pdf
TypePDF
Size2.79 MB

LUM 1990 2008 2012 2016 v006 Land Use Change Tables

184
82
Added
21 Oct 2019

This item was first added to MfE Data Service on 21 Oct 2019

Document ID22374
File namelum-1990-2008-2012-2016-v006-land-use-change-tables.xlsx
TypeXLSX
Size136 KB

Ocean and coastal extreme waves (8m), 2012

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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.

1088
3
Added
16 Oct 2019

This dataset was first added to MfE Data Service on 16 Oct 2019.

These data estimate the occurence of extreme wave events in coastal and oceanic waters for 2012, particularly for wave events where significant wave height exceeds a threshold of 8 metres and for a period of at least 12 hours. Significant wave height is defined as four times the square root of the variance of sea surface elevation due to wave motion.

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.

Layer ID 104088
Data type Grid
Resolution About 13356.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Ocean and coastal extreme waves (6m), 2012

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

993
1
Added
16 Oct 2019

This dataset was first added to MfE Data Service on 16 Oct 2019.

These data estimate the occurence of extreme wave events in coastal and oceanic waters for 2012, particularly for wave events where significant wave height exceeds a threshold of 6 metres and for a period of at least 12 hours. Significant wave height is defined as four times the square root of the variance of sea surface elevation due to wave motion.

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.

Layer ID 104087
Data type Grid
Resolution About 13356.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Oceanic_and_coastal_extreme_waves_spatial_data_quality_report.pdf

56
6
Updated
16 Oct 2019

This item was last updated on MfE Data Service on 16 Oct 2019

2
Document ID22371
File nameoceanic_and_coastal_extreme_waves_spatial_data_quality_reportpdf.pdf
TypePDF
Size449 KB
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