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Indicator Specification

Nutrients in freshwater in Europe

Indicator Specification
  Indicator codes: CSI 020 , WAT 003
Published 11 May 2005 Last modified 31 Aug 2020
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.

Updated with 2018 data and text revised accordingly

 

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 Nitrates Directive, the Urban Waste Water Treatment Directive, the Surface Water for Drinking Directive and the Drinking Water 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, inter alia, 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 old. 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. Reducing nutrient pollution from agriculture is also an important aspect of the European Green Deal and the ‘Farm to Fork’ Strategy. Other action points in the European Green Deal are also related to reducing nutrient pollution, e.g. ‘Zero pollution action plan for water, air and soil’ and ‘Measures to address the main drivers of biodiversity loss’.

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.
  • The UN Sustainable Development Goals also include qualitative targets related to freshwater nutrient pollution. The most relevant targets are 6.3 on improving water quality and 6.6 on protecting and restoring water-related ecosystems, but also 6.1 on safe drinking water and several other targets with a more indirect coupling to nutrient pollution.



Related policy documents

  • COM (2001) 31 final. Environment 2010.
    Environment 2010: Our future, our choice, 6th Environmental Action Programme, Communication from the Commission to the Council, the European Parliament, the Economic and Social Committee and the Committee of the Regions. COM (2001) 31 final.
  • Council Directive (91/271/EEC) of 21 May 1991
    Council Directive of 21 May 1991 concerning urban waste water treatment (91/271/EEC)
  • Council Directive (91/676/EEC) 12 December 1991
    Council Directive of 12 December 1991 concerning the protection of waters against pollution caused by nitrates from agricultural sources (91/676/EEC).
  • Council Directive 75/440/EEC
    Council Directive 75/440/EEC of 16 June 1975 concerning the quality required of surface water intended for the abstraction of drinking water in the Member States
  • Council Directive 96/61/EC (IPPC)
    Council Directive 96/61/EC of 24 September 1996 concerning Integrated Pollution Prevention and Control (IPPC). Official Journal L 257.
  • Council Directive 98/83/EC
    Council Directive 98/83/EC of 3 November 1998 on the quality of water intended for human consumption
  • Environmental Health Action Plan for Europe (EHAPE)
    WHO/Europe programme on environmental health policy.
  • The Future We Want –Declaration of the UN Conference on Sustainable Development, Rio (2012)
    The Future We Want is the declaration on sustainable development and a green economy adopted at the UN Conference on Sustainable Development in Rio on June 19, 2012. The Declaration includes broad sustainability objectives within themes of Poverty Eradication, Food Security and Sustainable Agriculture, Energy, Sustainable Transport, Sustainable Cities, Health and Population and Promoting Full and Productive Employment. It calls for the negotiation and adoption of internationally agreed Sustainable Development Goals by end 2014. It also calls for a UN resolution strengthening and consolidating UNEP both financially and institutionally so that it can better disseminate environmental information and provide capacity building for countries.
  • Water Framework Directive (WFD) 2000/60/EC
    Water Framework Directive (WFD) 2000/60/EC: Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy.

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-6) data collection process. It includes data on nutrients, organic matter, hazardous substances and general physico-chemical parameters as well as for biological data for rivers and lakes. The WISE-6 data flow was new as of 2019, and has from 2020 replaced WISE-4. 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-6)supersedes Eurowaternet reporting.

The data in Waterbase is a sub-sample of national data assembled for the purpose of providing comparable indicators of the 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 QC process (see the QC section below). The time series analysis is 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.

Determinands
The determinands 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 QC procedure is applied when data are reported, including checking that the values are within a certain range defined for each determinand. 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 that 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 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 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. However, the statistical approach chosen can handle gaps in the data series, so inter/extrapolation is not applied here. 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 groundwater time series in the analyses.

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 sites were 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 7 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 to inter/extrapolate all gaps of missing values of 1-2 years 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 2 years and by the average of the 2 neighboring values for gaps of 1 year.

In 2010, this approach was modified, allowing for gaps of up to 3 years, both at the ends and in the middle of the data series. At the beginning or end of the data series, up to 3 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 1 year and for the middle year in gaps of 3 years, where missing values were replaced by the average of the 2 neighboring 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. Even if the gap filling is not applied in the trend analyses, the same time series are used, for easier comparison of the time series and trend analysis results. The 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, making the data more representative. Still, the number of sites in the time series/trend analysis is markedly lower compared with 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 et al., 2020) in the free software R (R Core Team 2020), using the wql 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 a 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, while data series with p-value >= 0.05 and <0.10 are reported as marginally increasing or decreasing. 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. For the relative Sen slope (Sen slope %), the slope joining each pair of observations is divided by the first of the pair before the overall median is taken and multiplied by 100. 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 over the last 3 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 that have complete time series after inter/extrapolation. The 3-year average is used to remove some inter-annual variability. Also, since data are not available for all sites each year, selecting data from 3 years will give more sites. The average value thus represents 1, 2 or 3 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, for example, 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

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

Each annual update of the indicator is based on the updated set of monitoring sites. This also means that due to changes in the database, including changes in the QC procedure that excludes or re-includes individual sites or samples and retroactive reporting of data for the past periods, which may re-introduce lost time series that were not used in the recent indicator assessments, the derived results of the assessment vary in comparison to previous assessments.

Waterbase contains a large amount of data collected throughout many years. Ensuring the quality of the data has always been a high priority. A revision of Waterbase reporting and the database-composition process took place in the period 2015–2017. This included restructuring of the data model and corresponding reporting templates; transformation of the legacy data (i.e. data reported in the past, for the period up until and including 2012); re-definition of specific data fields, such as aggregation period defining the length of aggregation in a year; update of the datasets according to correspondence with national reporters; recodification of monitoring site codes across EIONET dataflows; and connection of the legacy data time series with the newly-reported data in restructured reporting templates. Still, suspicious values or time series are sometimes detected and the automatic 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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