Nutrients in freshwater in Europe

Indicator Specification
Indicator codes: CSI 020 , WAT 003
Created 07 Oct 2004 Published 11 May 2005 Last modified 07 Oct 2019
17 min read
This indicator shows concentrations of phosphate and nitrate in rivers, total phosphorus in lakes and nitrate in groundwater bodies. The indicator can be used to illustrate geographical variations in current nutrient concentrations and temporal trends.

Update of indicator specification to take into account minor changes in data analysis

Assessment versions

Published (reviewed and quality assured)

Rationale

Justification for indicator selection

Large inputs of nitrogen and phosphorus to water bodies from urban areas, industry and agricultural areas can lead to eutrophication. This causes ecological changes that can result in a loss of plant and animal species (reduction in ecological status), and can have negative impacts on the use of water for human consumption and other purposes.

The environmental quality of surface waters with respect to eutrophication and nutrient concentrations, is an objective of several directives: the Water Framework Directive, the Nitrate Directive, the Urban Waste Water Treatment Directive, the Surface Water Directive and the Freshwater Fish Directive.

Scientific references

  • No rationale references available

Indicator definition

This indicator shows concentrations of phosphate and nitrate in rivers, total phosphorus in lakes and nitrate in groundwater bodies. The indicator can be used to illustrate geographical variations in current nutrient concentrations and temporal trends.

Units

The concentration of nitrate is expressed as milligrams of nitrate per litre (mg NO3/l) for groundwater and milligrams of nitrate-nitrogen per litre (mg NO3-N/l) for rivers.

The concentration of phosphate and total phosphorus are expressed as milligrams of phosphorous per litre (mg P/l).

Policy context and targets

Context description

The environmental quality of freshwater with respect to eutrophication and nutrient concentrations is an objective of several directives. These include: the Nitrates Directive (91/676/EEC), aimed at reducing nitrate pollution from agricultural land, the Urban Waste Water Treatment Directive (91/271/EEC), aimed at reducing pollution from sewage treatment works and certain industries, the Industrial Emissions Directive (2010/75/EU), aimed at reducing emissions from industry to air, water and land, , the Convention on Long-range Transboundary Air Pollution and the National Emission Ceilings Directive, aimed at reducing air pollution to a.o. avoid eutrophication of surface waters from air pollution, and the Water Framework Directive, which requires the achievement of good ecological status or good ecological potential of surface waters by 2015, unless exemptions are applied. The Water Framework Directive also requires the achievement of good chemical and good quantitative groundwater status by 2015 as well as the reversal of any significant and sustained upward trend in the concentration of any pollutant. In addition, the Drinking Water Directive (98/83/EC) sets the maximum allowable concentration for nitrate of 50 mg NO3/l. It has been shown that drinking water in excess of the nitrate limit can result in adverse health effects, especially in infants less than two months of age. Groundwater is a very important source of drinking water in many countries and is often used untreated, particularly from private wells.


Among the key principles of The Seventh Environment Action Programme of the European Community 2014-2020 are the “full integration of environmental requirements and considerations into other policies”, “better implementation of legislation” and “more and wiser investment for environment and climate policy”. This could result in a more intense application of agri-environmental measures to reduce nutrient pollution of the aquatic environment, e.g. in the Common Agricultural Policy, which after the reform in 2013 has an even stronger focus on sustainable farming and innovation.

Targets

This indicator is not directly related to a specific policy target. The environmental quality of surface waters with respect to eutrophication and nutrient concentrations is, however, an objective of several directives:

-         Drinking Water Directive (98/ 83/EC) — maximum allowable concentration for nitrate of 50 mg/l.

-         Surface Water for Drinking Directive (75/440/EEC) — guideline concentration for nitrate of 25 mg/l.

-         Nitrates Directive (91/676/EEC) — requires the identification of groundwater sites/bodies where annual average nitrate concentrations exceed or could exceed 50 mg NO3/l.

-         Urban Waste Water Treatment Directive (91/71/EEC) — aims to decrease organic pollution.

Related policy documents

Key policy question

Are nutrient concentrations in Europe's freshwaters decreasing?

Specific policy question

Are nitrate concentrations in Europe's groundwater decreasing?

Specific policy question

Are nutrient concentrations in Europe's surface waters decreasing?

Methodology

Methodology for indicator calculation

Source of data:

The data on water quality of rivers, lakes and groundwater in Waterbase are collected annually through the WISE SoE - Water Quality (WISE-4) data collection process. It includes data on nutrients, organic matter, hazardous substances and general physico-chemical parameters; for rivers and lakes also biological data. This reporting obligation is an EIONET core data flow. A request is sent to National Focal Points and National Reference Centres every year with reference to templates to use and guidelines. As of 2015, WISE SoE Water Quality (WISE-4) supersedes Eurowaternet reporting.

The data in Waterbase is a sub-sample of national data assembled for the purpose of providing comparable indicators of pressures, state and impact of waters on a European-wide scale. The data sets are not intended for assessing compliance with any European directive or any other legal instrument. Information on the sub-national scales should be sought from other sources.

Site selection: Data from all reported monitoring sites are extracted for the indicator assessment. Some data are excluded following the QA/QC process (see QA/QC below). The time series and trend analysis are based on complete time series only (see Inter/extrapolation and consistent time series below). For groundwater, the time series are based on data for groundwater bodies, not individual monitoring sites. 

Determinants: The determinants selected for the indicator and extracted from Waterbase are:

  • for groundwater: nitrate,
  • for rivers: nitrate, total oxidised nitrogen and orthophosphate,
  • for lakes: total phosphorus.

For rivers, total oxidised nitrogen is used instead of nitrate when nitrate data are missing. If both are monitored at the same site and at the same time, nitrate values are given precedence. All values are labelled as nitrate in the graphs, but it is indicated in the graph notes for which countries total oxidised nitrogen data are used.

Mean: Annual mean concentrations are used as a basis in the indicator analyses. Unless the country reports aggregated data, the aggregation to annual mean concentrations is done by the EEA. Countries are asked to substitute any sample results below the limit of quantification (LOQ) by a value equivalent to half of the LOQ before calculating the site annual mean values. The same principle is applied by the EEA.
The annual data in most cases represent the whole year, but data are used also if they represent shorter periods. Up until 2012, data could be reported at different temporal aggregation levels. Here, annual data have been selected, but if this was not available, seasonal data were selected according to a specific order of preference.

Quality control (QC): An automatic QA/QC procedure is applied when data are reported. Automatic outlier tests based on z scores are also applied, both to the disaggregated and aggregated data, excluding data failing the tests from further analysis. In addition, a semi-manual procedure is applied, to identify issues which are not identified in the automatic outlier tests. The focus is particularly on suspicious values having a major impact on the country time series, and on the most recently reported data. This comprises e.g.
• values deviating strongly from the whole time series
• values not so different from values in other parts of the time series, but deviating strongly from the values closer in time
• consecutive values deviating strongly from the rest of the time series (including step changes)
• whole time series deviating strongly in level compared to other time series for that country and determinand
• where values for a specific year are consistently far higher or lower than the remaining values for that country and determinand.
Such values are removed from the analysis (both time series/trend and present state analysis) and checked with the countries. Depending on the response from the countries, the values are corrected, flagged as outliers or flagged as confirmed valid. Any response affecting the indicator analysis is corrected in the next update of the indicator.

Inter/extrapolation and consistent time series 

For time series and trend analyses, only series that are complete after inter/extrapolation (i.e. no missing values in the site data series) are used. This is to ensure that the aggregated time series are consistent, i.e. including the same sites throughout the time series. In this way, assessments are based on actual changes in concentration, and not changes in the number of sites. For the trend analysis, it is essential that the same time period is used for the different sites, so that the results are comparable. For rivers and lakes, “sites” in this context means individual monitoring sites. For groundwater it means groundwater bodies, i.e. the basis for inter/extrapolation and selection of complete data series is groundwater body data series. Each groundwater body may have several monitoring sites, and in some cases the number of monitoring sites has changed over the years. This means that some of the complete data series for groundwater (after inter/extrapolation) are not truly consistent, and must hence be regarded as more uncertain than the complete series for lakes and rivers. The purpose of choosing this approach is to increase the number of consistent groundwater time series.

Changes in methodology: Site selection and inter/extrapolation.
Until 2006, only complete time series (values for all years from 1992 to 2004) were included in the assessment. However, a large proportion of the sites was excluded by this criterion. To allow the use of a considerably larger share of the available data, it was decided in 2007 (i.e. when analysing data up until 2005) to include all time series with at least seven years of data. This was a trade-off between the need for statistical rigidity and the need to include as much data as possible in the assessment. However, the shorter series included might represent different parts of the whole time interval, and the overall picture may therefore not be reliable.

In 2009, it was decided rather to inter/extrapolate all gaps of missing values of 1-2 year for each site. At the beginning or end of the data series one missing value was replaced by the first or last value of the original data series, respectively. In the middle of the data series, missing values were replaced by the values next to them for gaps of two years and by the average of the two neighbouring values for gaps of one year.

In 2010, this approach was modified, allowing for gaps of up to three years, both at the ends and in the middle of the data series. At the beginning or end of the data series up to three years of missing values are replaced by the first or last value of the original data series, respectively. In the middle of the data series, missing values are replaced by the values next to them, except for gaps of one year and for the middle year in gaps of three years, where missing values are replaced by the average of the two neighbouring values.

In 2018, this approach was slightly modified, using linear interpolation for gap filling in the middle of the time series. Moreover, if data were available from 1989-1991 these were applied in the gap filling procedure, making it possible to interpolate instead of extrapolating at the beginning of the time series.

Only time series with no missing years for the whole period from 1992 or 2000 after such inter/extrapolation are included in the assessment. This gap filling procedure increases the number of sites that can be included in the time series/trend analysis. Using also the shorter time period from 2000 allows the inclusion of more sites, and hence increases the representativeness. Still, the number of sites in the time series/trend analysis is markedly lower compared to the analysis of the present state, where all available data can be used.

Aggregation of time series 

The selected time series (see above) are aggregated to country and European level by averaging across all sites for each year.

Trend analyses

Trends are analysed by the Mann-Kendall method (Jassby and Cloern 2013) in the free software R (R Core Team 2019), using the wq package. This is a non-parametric test suggested by Mann (1945) and has been extensively used for environmental time series (Hipel and McLeod, 2005). Mann-Kendall is a test for monotonic trend in a time series y(x), which in this analysis is nutrient concentration (y) as a function of year (x). The test is based on Kendall's rank correlation, which measures the strength of monotonic association between the vectors x and y. In the case of no ties in the x and y variables, Kendall's rank correlation coefficient, tau, may be expressed as tau=S/D where S = sum_{i<j} (sign(x[j]-x[i])*sign(y[j]-y[i])) and D = n(n-1)/2. S is called the score and D, the denominator, is the maximum possible value of S. The p-value of tau is computed by an algorithm given by Best and Gipps (1974). The tests reported here are two-sided (testing for both increasing and decreasing trends). Data series with p-value < 0.05 are reported as significantly increasing or decreasing (very positive/negative), while data series with p-value >= 0.05 and <0.10 are reported as marginally significant (marginally positive/negative). The results are summarised by calculating the percentage of sites (groundwater body/river site/lake site) within each category relative to all sites within the specific aggregation (Europe or country). The test analyses only the direction and significance of the change, not the size of the change.


The size of the change is estimated by calculating the Sen slope (or the Theil or Theil-Sen slope) (Theil 1950; Sen 1968) using the R software. The Sen slope is a non-parametric method where the slope m is determined as the median of all slopes (yj − yi)/(xj − xi) when joining all pairs of observations(xi,yi). Here the slope is calculated as the change per year for each site. This is summarised by calculating the average slope (regardless of the significance of the trend) for all sites in Europe or a country. The relative change per year (Sens slope %) is calculated as the Sen slope relative to the time series average. Again, this is summarised for Europe or individual countries by averaging across sites. The Sen slope was introduced for this indicator in 2013.

The Mann-Kendall method or the Sen slope will only reveal monotonic trends and will not identify changes in the direction of the time series over time. Hence a combination of approaches is used to describe the time series: A visual inspection of the time series, describing whether the general impression is a monotonic trend, no apparent trend, clear shifts in direction of the trend or high variability with no clear direction; an evaluation of significant versus non-significant and decreasing versus increasing monotonic trends using the Mann-Kendall results; an evaluation of the average size of the monotonic trends using the Sen slope results.

Current concentration distributions:

For analysis of the present state, average concentrations are calculated across the last three years. Outliers and suspicious values are removed before averaging. In this case all groundwater bodies and lake and river sites can be used, which is a far higher number than those which have complete time series after inter/extrapolation. The three-year average is used to remove some inter-annual variability. Also, since data is not available for all sites each year, selecting data from three years will give more sites. The average value thus represents one, two or three years. The sites are assigned to different concentration classes and summarised per country (count of sites per concentration class).
• The classes defining values for nitrate are based on typical background concentrations in the different water categories and the legislative standard (11.3 mg N/l) and guide value (5.6 mg N/l).
• The classes defining values for phosphate (rivers) and total phosphorus (lakes) concentrations are based on typical background concentrations in the different water categories and on the range of concentrations found in Waterbase and only give an indication of the relative distribution of concentrations of phosphorus in each country.

Methodology for gap filling

Methodology for gap filling is described above (under inter/extrapolation and consistent time series).

Methodology references

Data specifications

EEA data references

Data sources in latest figures

Uncertainties

Methodology uncertainty

Nutrient conditions vary throughout the year, depending on e.g. season and flow conditions. Hence, the annual average concentrations should ideally be based on samples collected throughout the year. Using annual averages representing only part of the year introduces some uncertainty, but it also makes it possible to include more sites, which reduces the uncertainty in spatial coverage. Moreover, the majority of the annual averages represent the whole year.
Nitrate concentrations in groundwater originate mainly from anthropogenic influence caused by agricultural land-use. Concentrations in water are the effect of a multidimensional and time-related process, which varies from groundwater body to groundwater body and is, as yet, less quantified. To properly evaluate the nitrate concentration in groundwater and its development, closely-related parameters such as ammonium and dissolved oxygen should be taken into account.

Data sets uncertainty

The indicator is meant to give a representative overview of nutrient conditions in European rivers, lakes and groundwater. This means it should reflect the variability in nutrient conditions in space and time. Countries are asked to provide data on rivers and lakes and on important groundwater bodies according to specified criteria. 

The datasets for groundwater and rivers include almost all countries within the EEA, but the time coverage varies from country to country. The coverage of lakes is less good. It is assumed that the data from each country represents the variability in space in their country. Likewise, it is assumed that the sampling frequency is sufficiently high to reflect variability in time. In practice, the representativeness will vary between countries. 

Waterbase contains a large amount of data collected throughout many years. Ensuring the quality of the data has always been a high priority. During 2015–2017 there was a major revision of Waterbase, when checking previously reported data was part of the process. Still, suspicious values or time series are sometimes detected, and the automatic QA/QC routines exclude some of the data. Through the communication with the reporting countries the quality of the database can be further improved.

Rationale uncertainty

Using annual average values provides an overview of general trends and geographical patterns, in line with the aim of the indicator. However, the severity of shorter term high nutrient periods will not be reflected.

Further work

Short term work

Work specified here requires to be completed within 1 year from now.

Work description

This indicator will be improved as more countries implement Eurowaternet. There are gaps in river, lake and groundwater characteristic information from some countries. This does not enable the stratification of all stations by river and lake size, and thus limits to some extent the current dataset for size-stratification. Also many countries did not report all the requested summary statistics such as the median. A bigger gap in the information is in terms of catchment pressures. Some countries have used Corine land cover data to provide proxy indicators of pressures. It is expected that this aspect will improve significantly during the next year as new updated Corine data will be available, and as work is undertaken by the ETC/WTR and ETC/TE to fill in the gaps in the pressure indicators. More times series data would improve the dataset particular from Southern countries.

Resource needs

Improve dataset in terms of time series (esp. from southern countries)

Status

In progress

Deadline

2006/01/01 00:00:00 GMT+1

Work description

All countries should have completed their delineation of groundwater bodies according to WFD in March 2005. As a consequence it should be easier to get more information on groundwater bodies. Especially information on GIS data should be available. Existing data on groundwater bodies will have to be evaluated and updated as the delineation of GW-bodies is likely to be changed due to WFD requirements. Countries will also be designing and/or modifying their monitoring programmes for rivers, lakes and groundwater bodies over the coming years as a requirement of the WFD. This should increase the extent of information potentially available to the EEA through the EWN process.

Resource needs

No resource needs have been specified

Status

Not started

Deadline

2008/01/01 00:00:00 GMT+1

Long term work

Work specified here will require more than 1 year (from now) to be completed.

General metadata

Responsibility and ownership

EEA Contact Info

Peter Kristensen

Ownership

European Environment Agency (EEA)

Identification

Indicator code
CSI 020
WAT 003
Specification
Version id: 1

Frequency of updates

Updates are scheduled once per year

Classification

DPSIR: State
Typology: Descriptive indicator (Type A - What is happening to the environment and to humans?)

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Data used

Latest figures and vizualizations

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