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Indicator Specification
Monitoring the efficiency of water use is important for the protection, conservation and enhancement of the EU’s natural capital. It also contributes to improving resource efficiency, which is included as an objective of the EU's 7th EAP to 2020.
The WEI+ is a water scarcity indicator that provides information on the level of pressure that human activity exerts on the natural water resources of a territory. This helps to identify those areas prone to problems related to water stress (Faergemann, 2012). The purpose of implementing the WEI+ at spatial (e.g. sub-basin or river basin) and temporal (monthly or seasonal) scales, which are finer than annual averages at the country scale, is to better capture the balance between renewable water resources and water use (see Conceptual model of WEI+ computation).
The WEI+ provides a measure of the total water use as a percentage of the renewable freshwater resources for a given territory and time scale.
The WEI+ is an advanced and geo-referenced implementation of the WEI. It quantifies how much water is monthly or seasonally abstracted and how much water is returned after use to the environment via basins. The difference between water abstraction and return is regarded as water use.
WEI+ values are given as percentages, i.e. water use as a percentage of renewable water resources. Absolute water volumes are presented as millions of cubic meters (million m3 or hm3).
The objective of the EU's 7th EAP to 2020 is to ensure the protection, conservation and enhancement of the EU’s natural capital and to improve resource efficiency. Monitoring the efficiency of water use in different economic sectors at national, regional and local levels is necessary to achieve this. The WEI is part of the set of water indicators published by several international organisations, such as the United Nations Environment Programme (UNEP), the Organisation for Economic Co-operation and Development (OECD), Eurostat and the Mediterranean Blue Plan. There is an international consensus about the use of this indicator for assessing the pressure of the economy on water resources, i.e. water scarcity.
The WEI+ is an advanced version of the WEI, which better addresses regional and seasonal aspects of water scarcity. In addition, it also takes water use (water abstraction minus water returned) into account. The indicator describes how total water use exerts pressure on water resources. It identifies areas (e.g. sub-basins or river basins) that have high abstraction levels on a seasonal scale in relation to the resources available and that are therefore prone to water stress. Changes in WEI+ values allow analyses of how changes in water use affect freshwater resources, i.e. by putting them under pressure or by making them more sustainable.
There are no specific targets directly related to this indicator. However, the Water Framework Directive (2000/60/EC) requires Member States to promote the sustainable use of water resources, based on the long-term protection of available water resources, and to ensure a balance between abstraction and the recharge of groundwater, with the aim of achieving good groundwater status by 2015.
The EU's Seventh Environment Action Programme (7th EAP) aims to ensure that stress on renewable water resources is prevented or significantly reduced by 2020 (EU, 2013). The EU’s Roadmap to a Resource Efficient Europe (EC, 2011) also includes a milestone for 2020, namely that ‘water abstraction should stay below 20 % of available renewable freshwater resources’. European-scale estimations of water scarcity are likely to shadow large local differences and would thus be misleading. Instead, estimations of the proportional area affected by water scarcity conditions (either seasonally or throughout an entire year) may better capture the actual level of water stress on the continental scale.
Regarding WEI+ thresholds, it is important that agreement is reached on how to delineate non-stressed and stressed areas. Raskin et al. (1997) suggested that a WEI value of more than 20 % should be used to indicate water scarcity, whereas a value of more than 40 % would indicate severe water scarcity. These thresholds are commonly used in scientific studies (Alcamo et al., 2000). Smakhtin et al. (2004) suggested that a 60 % withdrawal from the annual total runoff would cause environmental water stress. Similarly, the Food and Agriculture Organization of the United Nations (FAO) applies a value of above 25 % of water abstraction as an indication of water stress and of above 75 % as an indication of serious water scarcity (FAO, 2017). Since no formally agreed thresholds are available for assessing water stress conditions across Europe, in the current assessment, the 20 % WEI+ threshold proposed by Raskin at al. (1997) is considered to distinguish stressed from non-stressed areas, while a value of 40 % is used as the highest threshold for mapping purposes.
The WEI+ is an advanced version of the water exploitation index. It is geo-referenced and developed for use on a seasonal scale. It also takes into account water abstraction (gross) and return (net abstraction) to reflect water use.
In 2011, a technical working group, developed under the Water Framework Directive Common Implementation Strategy, proposed the implementation of a regionalised WEI+. This differed from the previous approach by enabling the WEI+ to depict more seasonal and regional aspects of water stress conditions across Europe (See Conceptual model of WEI+ computation). This proposal was approved by the Water Directors in 2012 as one of the awareness-raising indicators.
The regionalised WEI+ is calculated according to the following formula:
WEI+ = (abstractions - returns)/renewable freshwater resources.
Renewable freshwater resources are calculated as 'ExIn + P - Eta ± ΔS' for natural and semi-natural areas, and as 'outflow + (abstraction - return) ± ΔS' for densely populated areas.
Where:
ExIn = external inflow
P = precipitation
ETa = actual evapotranspiration
ΔS = change in storage (lakes and reservoirs)
outflow = outflow to downstream/sea.
It is assumed that there are no pristine or semi-natural river basin districts or sub-basins in Europe. Therefore, the formula 'outflow + (abstraction - return) - ΔS' is used to estimate renewable water resources.
Climatic data were obtained from the EEA Climatic Database, which was developed based on the ENSEMBLES Observation (E-OBS) Dataset (Haylock et al., 2008). The State of the Environment database was used to validate the aggregation of the E-OBS data to the catchment scale.
Streamflow data have been extracted from the EEA Waterbase — Water Quantity database. This database does not have sufficient spatial and temporal coverage yet. In order to fill the gaps, Joint Research Centre (JRC) LISFLOOD data (Burek et al., 2013) have been integrated into the streamflow data. The streamflow data cover Europe, in a homogeneous way, for the years 1990-2015 on a monthly scale.
Once the data series are complete, the flow linearisation calculation is implemented, followed by a water asset accounts calculation, which is done in order to fill the data for the parameters requested for the estimation of renewable water resources. The computations are implemented at different scales independently, from sub-basin scale to river basin district scale.
Overall, annually reported data are available for water abstraction by source (surface water and groundwater) and water abstraction by sector with temporal and spatial gaps. Gap-filling methods are applied to obtained harmonised time series.
No data are available at the European scale on 'Return'. Urban waste water treatment plant data, the European Pollutant Release and Transfer Register (E-PRTR) database, Eurostat population data, JRC data on the crop coefficient of water consumption, satellite observed phenology data have been used as proxy to quantify the water demand and water use by different economic sectors. Eurostat tourism data (Eurostat, 2013) and data on industry in production have been used to estimate the actual water abstraction and return on a monthly scale. Where available, state of the environment and Eurostat data on water availability and water use have also been used at aggregated scales for further validation purposes.
Once water asset accounts are implemented according to the United Nations System of Environmental Accounting Framework for Water (2012), the necessary parameters for calculating water use and renewable freshwater water resources are harvested.
Following this, bar and pie charts are produced, together with static and dynamic maps.
For each parameter of water abstraction, return and renewable freshwater resources, primarily data from the Waterbase — Water Quantity database have been used. Eurostat, OECD and Aquastat (FAO) databases have also been used to fill the gaps in the data sets. Furthermore, the statistical office websites of all European countries have each been visited not only once but several times to get the most up-to-date data from these national open sources. Despite this, some gaps still needed to be filled by applying certain statistical or geospatial methodologies (See reference data sources for gap filling and modulation coefficients).
LISFLOOD data from the JRC have been used to gap fill the streamflow data set (See reference data sources for gap filling and modulation coefficients). The spatial reference data for the WEI+ are the European Catchments and Rivers Network System (Ecrins) data (250-m vector resolution). Ecrins is a vector spatial data set, while LISFLOOD data are in 5-km raster format. In order to fill the gaps in the streamflow data, centroids of the LISFLOOD raster have been identified as fictitious (virtual) stations. The topological definition of the drainage network in Ecrins has been used to match the most relevant and nearest fictitious LISFLOOD stations with EEA-Eionet stations and the Ecrins river network. After this, the locations of stations between Eionet and LISFLOOD stations were compared and overlapping stations were selected for gap filling. For the remaining stations, the following criteria were adhered to: fictitious stations had to be located within the same catchment as the Eionet station and have the same main river segment; in addition, both stations had to show a strong correlation.
A substantial amount of gap filling has been performed in the data on water abstraction for irrigation. First, a mean factor between utilised agricultural areas and irrigated areas has been used to fill the gaps in the data on irrigated areas. Then, a multiannual mean factor of water density (m3/ha) in irrigated areas per country has been used to fill the gaps in the data on water abstraction for irrigation.
The gaps in the data on water abstraction for manufacturing and construction have been filled by using Eurostat data on production in industry (Eurostat [sts_inpr_a]) and the E-PRTR database with the methodologies in the best available techniques reference document (BREF) to convert the production level into the volume of water.
Reported data on water abstraction and water use do not have sufficient spatial or temporal coverage. Therefore, estimates based on country coefficients are required to assess water use. First, water abstraction values are calculated and, second, these values are compared with the production level in industry and in relation to tourist movements in order to approximate actual water use for a given time resolution. This approach cannot be used to assess the variations (i.e. the resource efficiency) in water use within the time series.
Spatial data on lakes and reservoirs are incomplete. On the other hand, as reference volumes for reservoirs, lakes and groundwater aquifers are not available, the water balance can be quantified as only a relative change, and not the actual volume of water. This masks the actual volume of water stored in, and abstracted from, reservoirs. Thus, the impact of the residence time, between water storage and use, in reservoirs is unknown.
The sectoral use of water does not always reflect the relative importance of the sectors to the economy of a given country. It is, rather, an indicator that describes which sectors environmental measures should focus on in order to enhance the protection of the environment. A number of iterative computations based on identified proxies are applied to different data sets, i.e. urban waste water treatment plant data, E-PRTR data, Eurostat population data, JRC data on the crop coefficient of water consumption and satellite-observed phenology data have been used as proxies to quantify the water demand and water use by different economic sectors. This creates a high level of uncertainty in the quantification of water return from the economic sectors, thus also leads to uncertainty with regard to the 'water use' component.
In order to distribute population data across Europe, the Geostat 2011 grid data set from Eurostat was used. Then, further aggregations were performed in the spatial dimension to give the sub-basin and functional river basin district scales of Ecrins spatial reference data. The population within the time frame of one calendar year is regarded as stable. Variations are taken into account only for the annual scale. Deviations from officially reported data are expected because of the nature of the methodological steps followed.
The tourist data used were provided by Eurostat and relate to the nights spent per NUTS2 region, on the monthly scale, in accommodation establishments. Because of the aggregation/disaggregation steps followed, deviations from officially reported data are expected. The tourist population was included in the calculation as additional to the stable (local resident) population.
Where monthly data were not available, Eurostat tourist data (Eurostat, 2013), data on industry in production (Eurostat [sts_inpr_a]) and JRC satellite-observed phenology data were used to estimate the actual water abstraction and return on a monthly scale.
A validation of the results has been performed by comparing the estimates with reported data where feasible. Some contradictory results have been observed. For instance, the desalination of sea water is one of the methods used to meet the water demands of Cyprus, Malta and Spain. Based on this use of desalinated water, the actual WEI would be around 35-40 % for Malta. However, as desalinated water is not included in the computation of renewable freshwater resources, the WEI+ for Malta is around 100 %. Similarly, because of some technical issues with the reported data on streamflow, the WEI+ could not be computed for Cyprus. Therefore, the results for Cyprus were excluded from the overall assessment. The average WEI reported for Cyprus is 73.1 % for the years 2009-2013 under Water Framework Directive river basin management plan reporting.
A high degree of inconsistency between sub-basin and functional river basin district scales has been observed for the Guadiana river basin. The estimated WEI+ for Guadiana is 131 % for summer 2015, whereas the estimated WEI+ values for its sub-basins for the same period are as follows: 75 % for Upper Zancara, 41 % for Zujar and 48 % for Ardilla. This inconsistency seems to be related to the computations for the aggregation from sub-basin to functional river basin district for this basin. The value will be corrected once this technical problem has been solved.
Data are very sparse on some particular parameters of the WEI+. For instance, current streamflow data reported by the EEA member countries to the WISE SoE — Water Quantity database do not have sufficient temporal or spatial coverage to provide a strong enough basis for estimating renewable water resources for all of Europe. Such data are not available elsewhere at the European level either. Therefore, JRC LISFLOOD data are used intesively as surrogates (see availability on streamflow data).
Data on water abstraction by economic sectors have better spatial and temporal coverage. However, the representativeness of data for some sectors is also poor, such as the data on water abstraction for mining. In addition to the WISE SoE — Water Quantity database, intensive efforts to compile data from open data sources such as Eurostat, OECD, Aquastat (FAO) and national statistical offices have also been made (see share of surrogate data vs reported data on water abstraction).
Quantifying water exchanges between the environment and the economy is, conceptually, very complex. A complete quantification of the water flows from the environment to the economy and, at a later stage, back to the environment, requires detailed data collection and processing, which have not been done at the European level. Thus, reported data have to be used in combination with modelling to obtain data that can be used to quantify such water exchanges, with the purpose of developing a good approximation of 'ground truth'. However, the most challenging issue is related to water abstraction and water use data, as the water flow within the economy is quite difficult to monitor and assess given the current lack of data availability. Therefore, several interpolation, aggregation or disaggregation procedures have to be implemented at finer scales, with both reported and modelled data. Main consequences of data set uncertainty are the followings;
The Danube river basin is accounted for as a single district in Ecrins, so it aggregates a lot of regional and national information.
The water accounts and WEI+ results have been implemented in the EEA member and Western Balkan countries. However, regional data availability was an issue for some river basins (e.g. in Cyprus, the Jarft in Poland, North West and North Eastern river basins in the United Kingdom, the Kymijoki river basin in the Gulf of Finland, Gran Canarias of Spain and some Icelandic and Turkish river basins), which had to be removed from the assessment.
Because of the aggregation procedure used, slight differences exist between sub-basin and river basin district scales for total renewable water resources and water use.
Work specified here requires to be completed within 1 year from now.
Work specified here will require more than 1 year (from now) to be completed.
For references, please go to https://www.eea.europa.eu/data-and-maps/indicators/use-of-freshwater-resources-2 or scan the QR code.
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