What do we mean by ‘trend’?
A trend is a long-term, overall change in data in a consistent direction. Trends help us understand how water quality indicators behave over time, and whether conditions are improving or degrading. In river and lake water quality, a trend shows if measured values have generally risen or fallen over a period.
LAWA calculates trends for the past 5, 10, 15, and 20 years for river and lake water quality data.
What do water quality trends show us?
Water quality is always changing. It can vary with rainfall, floods, droughts, land use or management changes, and climate patterns.
Trends calculated over different periods tell us different information. Shorter-term trends can detect changes arising from specific land use activities (e.g., reduced point-source discharges from upgrades to sewage treatment plants). Longer-term trends may be more reliable, and less sensitive to short-term influences of seasonal and climatic weather patterns.
Trends can indicate regional scale changes in land use or management practices. They help show where improvements are working - and where further effort is needed.
Because water quality changes can take years, and restoration actions can take decades to show results, long-term trend analysis is essential for tracking progress.
What water quality indicators does LAWA show trends for?
LAWA shows 5, 10, 15, and 20-year trends for 10 indicators of river water quality (physical, chemical and biological):
- E. coli
- clarity (black disc)
- turbidity
- total nitrogen (TN)
- total oxidised nitrogen (TON)
- dissolved inorganic nitrogen (DIN)
- ammoniacal nitrogen
- nitrate nitrogen
- dissolved reactive phosphorus (DRP)
- total phosphorus (TP)
LAWA shows 10, 15 and 20-year trends for three indicators of river ecological health:
- Macroinvertebrate Community Index (MCI)
- Quantitative Macroinvertebrate Community Index (QMCI)
- Macroinvertebrate Average Score Per Metric (ASPM)
LAWA shows 5, 10, 15, and 20-year trends for seven indicators of lake aquatic life and water quality:
- E. coli
- clarity (Secchi disc)
- total phosphorus (TP)
- total nitrogen (TN)
- ammoniacal nitrogen
- chlorophyll a
- cyanobacteria
LAWA trend categories for rivers and lakes
Trends are grouped into five categories, adapted from the IPCC framework*
These trend categories reflect how confident we are that change is happening, not the rate of change. Even when we are highly confident in a trend direction, the actual change might still be small.
*These likelihood definitions are based on the framework laid out by the Intergovernmental Panel on Climate Change (IPCC), (Stocker et al., 2013).
Improving Trends
The improving trend symbols are used for sites that show an improving trend in water quality and are either classified as 'very likely improving' or 'likely improving'. An improvement is a decrease in most water quality indicators, such as phosphorus and nitrogen concentrations. However, for visual clarity indicators (black disc and Secchi disc depth) and the Macroinvertebrate Community Index (MCI), an improvement is an increase in value.
The trend evaluation method reports the confidence in the trend result:
- Between 90 and 100% confidence = 'very likely improving'
- Between 67 and 90% = 'likely improving'
The lower likelihood reflects that while there is an indication of an improving trend, there is less statistical certainty associated with this result.
Indeterminate Trend
An 'indeterminate' trend result is given to sites where there is not enough evidence to say whether water quality is improving or degrading.
An indeterminate trend means that the data do not show an upward or downward trend direction with sufficient statistical likelihood. When the trend evaluation method reports confidence in either trend direction below 67%, we assign an 'indeterminate' trend category.
Degrading Trends
The degrading trend symbols are used for sites that show a degrading trend in water quality and are either classified as 'very likely degrading' or 'likely degrading'. A degrading trend is an increase in most water quality indicators, such as phosphorus and nitrogen concentrations. However, for visual clarity indicators (black disc and Secchi disc depth) and the Macroinvertebrate Community Index (MCI), a degradation is a decrease in value.
The trend evaluation method reports the confidence in the trend result:
- Between 90 and 100% confidence = 'very likely degrading'
- Between 67 and 90% = 'likely degrading'
The lower likelihood reflects that while there is an indication of an improving trend, there is less statistical certainty associated with this result.
Trend not assessed
Sites are not assessed when the data do not meet the criteria to be included in the trend analysis. This includes:
- not enough data/samples over the period
- not enough variability in the data to assess a trend - either too many below detection-limit samples in the dataset, or long runs of the same value.
How do we calculate water quality trends?
Trends are calculated for a range of time periods, using hydrological years:
- 5 years (July 2019-June 2024)
- 10 years (July 2014-June 2024)
- 15 years (July 2009-June 2024)
- 20 years (July 2004-June 2024)
Data requirements
Quality coding framework
LAWA calculates trends for river and lake sites after removing data of a lessor quality based on Quality Code (QC) information provided by councils. This removes data that may have been compromised or undergone significant modification and therefore may not be representative of the intended measurement. All measurements with a NEMS QC 100 (missing data) and 400 (measured value may have been compromised and/or undergone significant modification) are removed from the dataset before calculation. This also includes internal QC 400 child codes (e.g. 403, 404, 450) and 'poor quality' codes from council's internal QC code schemas (e.g., for Auckland: 41, 61, 100, 42 and 151). This is part of an ongoing data improvement process that councils are actively working on to implement.
Sample abundance requirements vary by indicator type and time period
The data used to calculate water quality trends for rivers and lakes is collected monthly or quarterly. Macroinvertebrate data are generally collected annually, but sometimes twice per year. Generally, the more data points we have available for a site, the more statistical power we have for detecting a trend.
River and lake water quality indicators
Ten, 15, and 20-year trends:
Require monthly data preferably, and quarterly data if trends cannot be calculated with monthly data (e.g. too many months are missing). Datasets are evaluated for a trend if they meet either of two sets of sample abundance criteria:
- Samples for 90% of the number of months in the period, and 90% of the years sampled.
- 90% of the quarters sampled, and 90% of the years sampled.
If the monthly abundance criteria were met, the trend is deemed to be more reliable than if only the quarterly abundance criteria were met.
Five-year trends:
Require monthly data (quarterly data are not used).
- Data are excluded from the analysis if they have less than 90% of the monthly data expected (fewer than 54 samples).
River ecology indicators
Macroinvertebrate indicators are excluded from analysis if a site has less than 80% of the data expected.
- 10-year trends: requires at least eight years of data
- 15-year trends: requires at least 12 years of data
- 20-year trends: requires at least 16 years of data
LAWA does not calculate five-year trends for macroinvertebrates.
Further data requirements for trend analyses
If too many data points in the datasets are censored (i.e., reported as less than or greater than the detection limit of the laboratory method), the trend evaluation can become unreliable. Thus, LAWA does not calculate trends for sites where there are fewer than five total and three unique, non-censored observations. Trends are also not calculated if a single value occurs consecutively in more than half of the dataset. Sites which do not meet these data requirements for trend analysis are reported as 'not assessed'. 'Not assessed' is also used when sites do not meet the data abundance requirements.
The trend methodology
LAWA implements trend analyses following the methods provided by LandWaterPeople (v2502) implemented in the programming language R (R Core Team). The statistical interpretation of results is done following advice of McBride (2019).
Trends are calculated on data for one site/measurement combination at a time. The method consists in testing each site/measurement combination for seasonal effects. Then, data are analysed with either a seasonal or non-seasonal version of the non-parametric Mann-Kendall Slope Test. This statistical test evaluates all pairwise combinations of the data, calculating whether the later observation is higher or lower than the earlier observation, for each pair. The magnitude of the difference has no importance, only the sign. The seasonal version of this test compares the water quality data of each season separately (January with Januaries, February with Februaries, etc) which means any changes present are not hidden by seasonal patterns.
Censored values (data that are less than or greater than laboratory detection limits) can be used for the Mann-Kendall tests. A recent update to the LandWaterPeople software (v2505), removes the need to substitute censored values with very low or very high values, as was previously required. However, if too many of the data are censored below the detection limit of the laboratory method, the trend evaluation would become unreliable, and we opt not to calculate it (see Data requirements section above).
After the Mann-Kendall test is performed, the LWP trend evaluation method reports the percentage confidence that the analysed dataset features a decreasing trend. If the trend must be either decreasing or increasing, the percentage confidence of an increasing trend is simply one hundred minus the confidence of a decreasing trend. Further details can be found in guidance for the approach to calculating trends (Larned et al. 2021). Finally, we interpret the percentage confidence obtained from the Mann-Kendall test to assign each site/measurement combination into one of the five trend categories.
Flow adjustment
Some scientists recommend data be flow adjusted before trend analysis to remove any variation in water quality measurements caused by variation in stream flow. As many water quality sampling sites do not have concurrent flow records, LAWA does not apply flow-adjustment for trend analysis.
Where do I find more information?
Fraser C and Snelder T, 2025. The LWP-Trends Library; v2502 March 2025. LWP Ltd Report, 55 pp.
Gadd J, Snelder T, Fraser C, and Whitehead A, 2020. Urban river and stream water quality state and trends 2008-2017. Prepared for the Ministry for the Environment. NIWA Client Report 2018328AK
LandWaterPeople (LWP). https://landwaterpeople.co.nz/
Larned S, et al. 2021. Guidance for the analysis of temporal trends in environmental data. Prepared for Horizons Regional Council and MBIE Envirolink. 99 pp.
McBride G, 2019. Has water quality improved or been maintained? A quantitative assessment procedure. Journal of Environmental Quality 48:412-420.
R Core Team, 2024. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.https://www.R-project.org/
Snelder T and Fraser C, 2018. Aggregating trend data for environmental reporting. LWP Client Report 2018-01.
Stocker T, Qin D and Plattner G (Editors), 2014. Climate Change 2013: The physical science basis: working group | Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.