National indicator data for river condition in New Zealand - collected by Regional Councils and the National Institute of Water and Atmospheric Research (NIWA), collated and processed by NIWA and protected by copyright owned by the Ministry for the Environment on behalf of the Crown. The dataset consists of physical-chemical water quality and macro-invertebrate data from the regional council State of Environment (SoE) and National River Water Quality Network (NRWQN) programmes. The physical-chemical water quality variables are water clarity (CLAR), Escherichia coli concentration (ECOLI), nitrate-nitrogen concentration (NO3N[1]), ammoniacal nitrogen concentration (NH4N), total nitrogen concentration (TN), dissolved reactive phosphorus concentration (DRP), total phosphorus concentration (TP), temperature (TEMP), dissolved oxygen concentration (DO[2]) and percent saturation (DOSAT), suspended sediment (SS), and turbidity (TURB). The invertebrate variables are taxa lists and counts or coded-abundance classes for each taxon. The raw invertebrate data were post-processed to generate four variables: total number of taxa in a sample (TAXA), the number of taxa from the insect orders Ephemeroptera, Plecoptera and Trichoptera (EPTtaxa), the percentage of individuals in a sample from EPT taxa (%EPTabund), and the Semi-Quantitative Macroinvertebrate Community Index for hard-bottom streams (SQMCI-hb). REC reach numbers where added to site information based on best guesses. In the dataset used for the 2012 study, the start dates for all monitoring site records were 1 January 2006 or earlier, and the end dates ranged from June 2009 to February 2012. The range of end dates poses some potential problems due to temporal variation in water quality. Further, we carried out temporal trend analyses in the current study and recent data were needed to ensure that the analyses corresponded to recent conditions. For these reasons we requested updated physical-chemical water quality data from five regional councils, to fill the most severe gaps in recent data. Each of the five regional councils provided updates, and the ending dates in the current dataset range from January 2011 to December 2012. Note that start and end dates can vary among sites within councils, and among variables within sites. Larned, S.T.; Unwin, M.J. (2012). Representativeness and statistical power of the New Zealand river monitoring network. NIWA Client Report CHC2012-079 prepared for the Ministry for the Environment. 55 p.

The National Institute of Water and Atmospheric Research Ltd (NIWA) has been commissioned by the Ministry for the Environment to estimate 11 components of the national and regional water balance of New Zealand for each of the 20 years from 1 July 1994 to 30 June 2014. This information is for use by Statistics New Zealand in a set of annual national water accounts they are developing, as part of a set of environmental accounts for New Zealand. Specifically, this work is a contribution to the Water Physical Stock Accounts. The data were analysed to summarise the water stock accounts of New Zealand and the 16 regions administered by regional councils or unitary authorities,using a combination of direct measurement and modelled data. The average annual precipitation across the country was 550,000 m3/year (equal to over nine times the volume of Lake Taupo), a reduction from previous years’ calculations. Roughly 20% of this evaporates before reaching the coast, leaving an average of 440,000 million m3/year. There is substantial variation in this water flux from year to year due to a range of climatic factors. Changes in storage – lakes, soil moisture, snow, and ice – represent very small components of the annual water balance. Use of water for hydroelectric power generation represents a significant portion of the nation’s freshwater resource, equating to 36% of the total freshwater flows, but this figure includes multiple use of water within the same catchment. Water fluxes at the regional scale vary depending on the region’s size as well as the spatial variability in the delivery and movement of water. The West Coast receives the largest portion of precipitation – 26% of the national total – and possesses 30% of the nation’s freshwater flow. Nelson City, due to its small size, accounts for the smallest portion in both cases. Canterbury accounts for the greatest portion of hydro-generation water use (mainly for the Waitaki scheme), followed by Waikato. Data are for 11 water balance components: 1. Precipitation 2. Inflows from rivers (regional scale only) 3. Evapotranspiration 4. Abstraction by hydro-generation companies 5. Discharges by hydro-generation companies 6. Outflows to sea from surface water 7. Outflows to other regions (regional scale only) 8. Net change in lakes and reservoirs 9. Net change in soil moisture 10. Net change in snow 11. Net change in ice

The Macroinvertebrate Community Index (MCI) is used by Regional Councils and other organisations in New Zealand for a range of purposes including State of Environment and consent monitoring in freshwaters. The index is designed to reflect human impacts on waterways, particularly organic pollution, and is calculated from tolerance values (TVs) assigned to freshwater invertebrate taxa. For streams with hard bed substrate, published TVs exist for 180 freshwater invertebrate taxa, with many other taxa not having TVs assigned. Regional Councils currently treat taxa that do not have assigned TVs in different ways; some councils exclude these taxa from their MCI calculations while others have developed TVs using professional judgement. Developing standard TVs for all freshwater invertebrate taxa is a key step towards ensuring national consistency in calculation and reporting of the MCI. Extensive testing of the revised TVs and resulting MCI site scores was beyond the scope of this study. We compiled a national-scale dataset of macroinvertebrate community data from over 1300 freshwater monitoring sites. There were insufficient data from streams with soft bed substrate to revise the version of the MCI used in soft-bottomed streams (MCI-sb) therefore these 122 sites were excluded. A total of 10548 samples were collected at the remaining 1266 hard-bottomed sites. Data were divided into two datasets; the full dataset with all sampling occasions per site and a reduced dataset, consisting of 50 random sub-samples of the full dataset, each sub-sample consisting of one sampling occasion per site. Data were further grouped into eight classes based on Climate and Source of Flow categories from the River Environment Classification (REC). To revise the MCI TVs we applied an iterative computational process developed by Chessman (2003), which has been previously applied to develop two other indices in New Zealand (MCI-sb and a wetland MCI). The Chessman method was run on all eight environmental classes on both the full and reduced datasets. Tolerance values were compared across the environmental classes and two different approaches to assigning singular TVs to taxa across the environmental classes were compared. This resulted in revised MCI TVs for 234 taxa. There were 12 taxa with insufficient data to generate revised TVs. All of the revised TVs reported here were assigned using an objective computational approach, whereas of the 180 original published scores, 133 were assigned by professional judgement. Further testing is required to determine whether the revised TVs are more or less sensitive to gradients of human impacts than the original TVs. Our preliminary analyses show that the revised TVs and resulting MCI site scores were correlated with existing TVs and MCI site scores, and also with catchment-scale measures of land use. Revised MCI site scores were generally, but not always, higher than original MCI scores. As such, while revised TVs and MCI site scores are likely to provide a sensitive indicator of human impacts on rivers and streams it may be necessary to also revise water quality categories. For example, the original values place 15% of sites in the ‘excellent’ water quality category (MCI > 120) while the revised values place 50% of sites in this category. We provide revised TVs for 234 taxa but note the following caveats: 1) Original and revised TVs must be used separately; they are not interchangeable or directly comparable. Back calculation of MCI site scores would be required for historical comparisons using the revised TVs. We recommend that revised MCIs are reported as MCI-2-hb. 2) How taxa without revised TVs are included or excluded from analyses should be reported to ensure transparency, especially when comparing between sites or over time. 3) A new water quality categorical scale may be required as MCI site scores based on revised MCI TVs are generally higher than those created using the original TVs 4) Further testing is required to validate the sensitivity (in relation to human impacts on waterways) of the MCI scores developed using the revised TVs. The data were collected between 1990 and 2012 from 1388 sites distributed nationally (map provided). Listing of data in tables, figures and appendices follow: Tables Table 2-1: Sites were categorised by combined REC Climate and Source of Flow classes. Table 2 2: Number and percentage of samples with MCI-hb site scores within the four water quality classes for MCI-hb as identified in Stark and Maxted (2007b. Table 2 3: Spearman rank correlations (Rs) between upstream land use type and MCI-hb site scores generated using the original and revised TVs. Table 3 1: Taranaki Regional Councils MCI categories of biological water quality conditions adapted for Taranaki streams. Figures Figure 2-1: Distribution of invertebrate sampling sites showing all sites and those with hard (HB sites) and soft (SB sites) bed substrate. Figure 2 2: Histograms of MCI-hb tolerance values for taxa a) as originally reported by Stark and Maxted (2007b) and b) the revised MCI-hb. Figure 2 3: Original MCI-hb tolerance values (as reported in Stark and Maxted 2007b) and revised MCI-hb tolerance values for 161 taxa for which both values exist. Figure 2 4: MCI-hb for all site visits (n = 10548) calculated from the original and revised MCI-hb taxa tolerance values. Figure 2 5: Frequency histograms for MCI site scores calculated using the original MCI-hb tolerance values in Stark and Maxted (2007b) and the revised values. Figure 2 6: Scatterplots of MCI-hb site scores calculated from revised and original MCI TVs and the proportion of upstream land in pastoral and native land use. Appendices: Appendix A Revised MCI-hb tolerance values for freshwater invertebrate taxa. Appendix B Taxa with existing MCI-hb tolerance values for which revised scores were not generated Appendix C. Original and revised taxa tolerance values across environmental classes. Appendix D. Distributions of tolerance values across eight environmental class for individual taxa from 50 datasets each generated with one random visit per site. Appendix E. Testing the influence of environmental class on generated TVs.

NIWA National Virtual Climate Station Network (VCSN) Points Coordinate reference system is NZGD 1949 (which is consistent with all CliDB products). Attributes: Agent_No Network_No Latitude Longitude