A trend in water quality data indicates that measured values have been overall rising or falling over a time period. LAWA displays trends for the last 5, 10 and 15 years for the river and lake water quality data. A trend may be classified as indeterminate if there is insufficient evidence to determine if the values are changing in either direction. Sites that are 'not assessed' may be monitored, but the data do not meet eligibility criteria for trend analysis.
What do water quality trends show us?
LAWA calculates trends to show how the quality of water in rivers and lakes has changed at each site over time. Changes in water quality often take years to be seen, and it may be decades for any restoration actions to show effect in water quality trend results.
Trends calculated over different periods tell us different information. Natural systems are variable, and trends can be influenced by climate and weather patterns, as well as being affected by land use and land management changes at sites (e.g. changes in point-source discharges such as sewage treatment plant upgrades). Longer-term trends may be more reliable, and less sensitive to short-term influences of seasonal and climatic weather patterns.
What water quality indicators does LAWA show trends for?
LAWA shows 5, 10 and 15-year trends for ten river water quality indicators:, ( ), , , , , , , and . LAWA also shows 10 and 15-year trends for the ( ), Quantitative Macroinvertebrate Community Index ( ), and Macroinvertebrate Average Score Per Metric ( ) which are indicators of the ecological health of a river.
LAWA shows trends for seven lake water quality indicators:, , , a, , ( ) and .
LAWA trend categories for rivers and lakes
LAWA categorises trends into five classes. These are: very likely degrading, likely degrading, indeterminate, likely improving, and very likely improving. These likelihood definitions simplify the framework laid out by the Intergovernmental Panel on Climate Change (IPCC), (Stocker et al., 2013).
Note that the trend confidence categories do not reflect the rate of change, this is how quickly values might be rising or falling, only how confident we can be that the values are changing. The actual changes might be very small, even for sites with high confidence that they're changing in a certain direction.
Very likely improving trend
Likely improving trend
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.
When the trend evaluation method reports a confidence in an improving trend of between 90 and 100%, we assign a 'very likely improving' category. When the reported confidence is between 67 and 90% we assign a 'likely improving' category. The lower likelihood reflects that while these is an indication of an improving trend, these is less statistical support for it.
When the trend evaluation method reports confidence in either trend below 67% we assign an 'indeterminate' trend category. This classification is given to sites where there is insufficient evidence to confidently determine if water quality is showing an improving or degrading trend. An indeterminate trend means that the data do not show an upward or downward trend direction with sufficient statistical likelihood.
Very likely degrading trend
Likely degrading trend
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.
When the trend evaluation method reports confidence in a degrading trend of between 90 and 100%, we assign a 'very likely degrading' trend. When the method reports confidence between 67 and 90% we assign a 'likely degrading' trend. The lower likelihood reflects the fact that while these is an indication of a degrading trend, there is less statistical support for it.
Trend Not Assessed
Sites are not assessed for trends when they do not meet the criteria to be included in the trend analysis (e.g. there were not enough data/samples over the period, not enough variability in the data to assess a trend, too many belowsamples in the data, or long runs of the same value).
How do we calculate water quality trends?
Trends are calculated for the last 5, 10 and 15 years. Data are evaluated to determine whether water quality is showing improving, degrading, or indeterminate trends.
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. LAWA calculates and displays 10- and 15-year trends for river and lake water quality sites using monthly data preferably, and quarterly data if trends can not be calculated with monthly data (e.g. too many months are missing). LAWA calculates and displays 5-year trends using monthly data only, it does not use quarterly data for 5-year trends.
River and lake water quality datasets are evaluated for a trend if they meet either of two sets of sample abundance criteria. The require:
- samples for 90% of the number of months in the period, and 90% of the years sampled, OR
- 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 are only evaluated if a dataset meets the monthly-abundance criteria. Sets of quarterly sampled data will only ever meet the quarterly-abundance criteria.
For five-year river and lake trends, water quality sites were excluded from the analysis if they have less than 90% of the monthly data expected (fewer than 54 samples).
For 10- and 15-year trends, macroinvertebrate indicators are excluded from analysis if a site has less than 80% of the data expected, or if there is data from fewer than eight years (or thirteen) out of the last ten (or fifteen) years. LAWA does not calculate five-year trends for macroinvertebrates.
The trend methodology
To determine whether water quality at a river or lake site is showing improving, degrading or indeterminate trends, LAWA follows the methodology of McBride (2018), as implemented in R functions (R Core Team) provided by LandWaterPeople (v2102). LAWA uses the trend analysis methods provided by LandWaterPeople (Snelder and Fraser (2019)), which assume that data will always show an increase or decrease over time. The LWP trend evaluation method reports the percentage confidence that the analysed data set 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 water quality trends (Larned et al, 2021).
Trends are calculated on data for one site/measurement combination at a time.
The data for each combination are tested for seasonal effects, and then analysed with either a seasonal or non-seasonal version of the non-parametric Mann-Kendall Slope Test. This test evaluates all pairwise combinations of the data, evaluating 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) are substituted in the trend analysis, by very low or very high values. 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. We choose not to calculate trends where there are fewer than five total and three unique, non-censored observations. Sites which do not meet these requirements for trend analysis are reported as 'not assessed'. This label is also used when sites do not have enough measurements available, such as only six years of measurements available for ten-year trends.
Some investigators recommend data be flow adjusted before trend analysis to remove any variation in water quality measurements caused by variation in stream flow. However, many councils do not measure river flow at all of their water quality sampling sites so data used for trend analysis on LAWA are not flow-adjusted.
Where do I find more information?
Gadd, J., Snelder, T., Fraser, C. & 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 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. 2018. Has water quality improved or been maintained? A quantitative assessment procedure. Paper submitted to Journal of Environmental Quality.
Snelder T & Fraser C. 2018. Aggregating trend data for environmental reporting. LWP Client Report 2018-01.
Snelder T & Fraser C. 2019. "The LWP-Trends Library: v2101 April 2021", LWP Ltd Report, p35.
Stocker T, Qin D & 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.