The key indicators for oxygenation of water bodies are biochemical oxygen demand (BOD), which is the amount of oxygen needed by microorganisms for aerobic decomposition of organic matter; and ammonium (NH4+), which is oxygenated by bacteria into nitrate, an important nutrient also increasing eutrophication. The indicator illustrates spatial variations in current state and temporal trends of BOD and ammonium concentration in rivers.
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.
Automatic quality control procedures are applied both to the disaggregated and aggregated data, excluding data failing the tests from further analysis. In addition, a semi-manual procedure is applied, focusing on suspicious values having a major impact on the country time series and on the most recently reported data. This comprises e.g.:
• consecutive values deviating strongly from the rest of the time series;
• 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 and checked with the country.
For time series analyses, only complete series after inter/extrapolation are used. This is to ensure that the aggregated time series are consistent, i.e. including the same sites throughout. Inter/extrapolation of gaps up to 3 years are allowed, to increase the number of available time series. At the beginning or end of the data series, 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 linearly interpolated. The selected time series are aggregated to country and European level by averaging across all sites for each year.
Trends are analysed by the Mann-Kendall method in the free software R , using the wql package. This is a non-parametric test suggested by Mann (1945) and has been extensively used for environmental time series . 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 size of the change is estimated by calculating the Sen slope . The same time series as for the time series analysis, but without gap filling.
For analysis of the present state, average concentrations are calculated across the last 3 years to remove some inter-annual variability. The sites are assigned to different concentration classes and summarised per country.
Several EU directives aim at improving water quality and reducing the loads and impacts of organic matter. Water Framework Directive (WFD) requires the achievement of good ecological status or good ecological potential of surface waters across the EU by 2015 and repeals step by step several older water-related directives. The following directives are complementary to the WFD: the Urban Waste Water Treatment Directive (91/271/EEC), aimed at reducing pollution from sewage treatment works and certain industries; the Nitrates Directive (91/676/EEC), aimed at reducing nitrate and organic matter pollution from agricultural land; and the Industrial Emissions Directive (2010/75/EU), aimed at reducing emissions from industry to air, water and land.
The methodologies used for aggregating and testing trends in concentrations illustrate the overall European trends. Organic and oxygen conditions vary throughout the year, depending especially on flow conditions, affected by weather events etc. Hence, the annual average concentrations should ideally be based on samples collected as often as possible. Using annual averages representing only part of the year introduces some uncertainty, but it also makes it possible to include more river sites, which reduces the uncertainty in spatial coverage. Moreover, the majority of the annual averages represent the whole year.
Data sets uncertainty
The indicator is meant to give a representative overview of oxygenation availability conditions in European rivers. This means it should reflect the variability in conditions in space and time. Countries are asked to provide data on rivers according to specified criteria.
The datasets for rivers include almost all countries within the EEA, but the time coverage varies from country to country, both through the analysed period and within the year for which the aggregated mean value is provided. 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. As an example, the 2016-2018 assessment of current concentrations of ammonium in rivers is based on as many as 13,266 sites, compared to 7,797 sites in the assessment of 2016-2018 (i.e. the last year assessment). However, some sites available in the previous assessment are not part of this year’s assessment and vice versa.
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 to 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; re-codification 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.
Biochemical Oxygen Demand and ammonium are well suited for indicating organic pollution. However, using annual average values does not reflect the variability during the year and can therefore underestimate the severity of short-term low oxygen conditions.