Water intensity of crop production

Indicator Specification
Indicator codes: WAT 006
Created 26 Apr 2017 Published 21 Dec 2017 Last modified 21 Dec 2017
24 min read
The water intensity of crop production is defined as the volume of water input (irrigation plus soil moisture in cubic meters; m 3 ) for one unit of GVA (in euros or PPS) generated from the production of all crop types, adjusted for subsidies. The lower the value of the indicator, the better the water intensity. It is a relative measure of the pressure of the economy (NACE activities A1.1 and A1.2) on water resources.

Assessment versions

Published (reviewed and quality assured)


Justification for indicator selection

Water is generally abundant is Europe, although long-term climate and hydrological assessments — including on population dynamics — indicate an acceleration in water scarcity across Europe. The agricultural sector is still one of the major users of water resources in Europe, accounting for approximately 60 % of total annual water abstraction. In southern Europe, this figure reaches more than 80 % in the summer months (EEA, 2017).

With more than 10 % of European territory under permanent water scarcity conditions, the high demand for water resources for agriculture — especially during the spring and summer months — constitutes a major pressure on European water bodies. Projections on climate change impacts indicate a rapid intensification of water scarcity in southern Europe and the expansion of its impacts to northern regions and mountainous areas. Therefore, the availability of water to all sectors, including agriculture, may decline even further (Zal et al. 2017).

Europe needs to improve the productivity and resource efficiency of its economic sectors, including agriculture (EC, 2011). In practice, this means producing more from less, using resources more sustainably and minimising impacts on the environment (EEA, 2016). In the context of crop production, this means that less water must be abstracted for crop growth for every unit of GVA generated.

This indicator measures total water input to crops (measured as the volume of water) against the GVA generated from crops (measured in euros or PPS). As the indicator compares the resource intensity of water with the GVA of crops, its primary objective is to support the assessment of the pressure crop production exerts on water resources and the sustainability of resource use in crop production (UNDESA, 2007).

Scientific references

Indicator definition

The water intensity of crop production is defined as the volume of water input (irrigation plus soil moisture in cubic meters; m3) for one unit of GVA (in euros or PPS) generated from the production of all crop types, adjusted for subsidies. The lower the value of the indicator, the better the water intensity. It is a relative measure of the pressure of the economy (NACE activities A1.1 and A1.2) on water resources.


Two different units can be used for the economic variable: 
m3 per EUR for exploring trends across time within the same country
mper PPS for comparing different countries from the same geographical region within the same year [1]

[1] The purchasing power standard (PPS) unit is used by Eurostat as a common currency for the European region that accounts for differences in the purchasing power in the 28 Member States and other European countries included in the assessments (e.g. European Free Trade Association (EFTA) countries, candidate countries and potential candidate countries). Theoretically, one PPS can buy the same amount of goods and services in each country. The adjustment for price level differences is implemented using the purchasing power parities (PPPs). Thus, PPPs can be interpreted as the exchange rate of the PPS against the euro.

Policy context and targets

Context description

Since 2007, the European Commission has recognised the challenges of water scarcity and drought, adopting a policy document (EC, 2007) followed by a number of policy reviews in subsequent years. More recently, the Commission also developed a policy supporting water reuse (EC, 2016) in the context of a circular economy. In this context, the European Environment Agency (EEA) implemented an indicator on water exploitation (the water exploitation index plus - WEI+) (EEA, 2017), which supports the implementation of policies on water scarcity and resource efficiency.

In addition, water has become part of the Resource Efficiency Roadmap, which was adopted by the Commission in 2011. This includes a clear target of keeping water abstraction below 20 % of available renewable water resources (EC, 2011). To achieve this requires substantial improvements with regard to water demand, including for crop production, which accounts for the highest proportion of agricultural water use. This strategic approach also makes up one of the key targets of the Seventh Environment Action Programme, which aims to turn the EU into a resource-efficient, green and competitive low-carbon economy.

A similar indicator concept has also been proposed by the United Nations to measure water use intensity by economic activity as a proxy for sustainable development (UNDESA, 2007). 




No specific target or threshold has been set for this indicator. However, several European policies address sustainable development and resource efficiency, i.e. the Roadmap to a Resource Efficient Europe (EC, 2011), the Seventh Environment Action Programme (EC, 2014), the Circular Economy Package ('Closing the loop: An EU action plan for the circular economy'; EC, 2015) and the Common Agricultural Policy (CAP) Pillar 1 and Pillar 2.

Related policy documents

  • Addressing the challenge of water scarcity and droughts in the European Union
    EC (2007). Communication from the Commission to the Council and the European Parliament, Addressing the challenge of water scarcity and droughts in the European Union. Brussels, 18.07.07, COM(2007)414 final.
  • Guidelines on Integrating Water Reuse into Water Planning and Management in the context of the WFD
    Common Implementation Strategy for the Water Framework Directive.
  • Resource efficiency in Europe — Policies and approaches in 31 EEA member and cooperating countries
    This report provides an overview of resource efficiency policies and instruments in 31 member and cooperating countries of the European Environment Agency network (Eionet). A detailed survey was conducted during the first half of 2011 to collect, analyse and disseminate information about national experiences in developing and implementing resource efficiency policies, and to facilitate sharing of experiences and good practice. The report reviews national approaches to resource efficiency and explores similarities and differences in policies, strategies, indicators and targets, policy drivers and institutional setup and information gaps. It concludes with some EEA considerations for future policies on resource efficiency which could be considered in developing future resource efficiency policies at the EU and country levels. The analysis is illustrated with short examples of policy initiatives in the countries, described in more detail in the country profile documents available below.

Key policy question

What is the water intensity of crop production in Europe?

Specific policy question

Is the water intensity of crop production improving in Europe?


Methodology for indicator calculation

  • Water intensity of crop production is expressed as the volume of water input (irrigation plus soil moisture in cubic meters; m3) for one unit of GVA (in euros or PPS) generated from the production of all crop types, adjusted for subsidies. 
  •  Water input to crops is expressed as the total volume of water (in m3) per country per year made available to crops by either natural or artificial means. It can be calculated as follows:

 Water input to crops (m3) = irrigation abstraction(FSW) + irrigation abstraction(FGW) + irrigation abstraction(NFW) + soil moisture in growing season


  • irrigation abstraction(FSW) is the water abstraction for irrigation purposes from fresh surface water sources;
  • irrigation abstraction(FGW) is the water abstraction for irrigation purposes from fresh groundwater sources;
  • irrigation abstraction(NFW) is the water abstraction for irrigation purposes from non-freshwater sources, including treated saline, brackish or reclaimed water;
  • soil moisture in growing season is the water that is retained in the soil profile of arable land and permanent crops (or UAA excluding permanent grassland and kitchen gardens) during the growing season (assumed to be April-September); it is a fraction of the total amount of rainwater, excluding runoff, evaporation and deep percolation, and represents the amount of water that may be used by crops to cover their water requirements.

Irrigation abstraction(FSW) and irrigation abstraction(FGW) can be calculated using the Eurostat data set 'water abstraction for agriculture-irrigation (source: fresh surface and groundwater)'. Irrigation abstraction(NFW) can be calculated using the Eurostat data sets 'water abstraction for agriculture-irrigation (source: desalinated water)', 'water abstraction for agriculture-irrigation (source: reused water)' and 'water abstraction for agriculture-irrigation (source: non-fresh water sources, not reported elsewhere)'. Water abstraction is expressed in terms of annual volume (million m³ per year). Data are collected for each Member State of the EU, for EU candidate countries and for EFTA Member States at country level. The data are updated every two or three years and come from a variety of sources, including regional or local authorities, environmental administrations and industry. The most recent data are from 2013 or 2014. Data gaps may be filled using similar data sets included under WISE SoE — Water Quantity (WISE-3), AQUASTAT and KNOEMA.

Soil moisture in the growing season can be calculated using the results of the EEA indicator 'Soil moisture' (LSI 007). Soil water content has been estimated using the soil water balance model for European Water Accounting (swbEWA) and the results have been validated using in situ soil moisture measurements at different locations across Europe (Kurnik et al., 2014). The modelled results have been aggregated for the utilised agricultural areas, which are categorised as 'arable land' and 'permanent crops'. Aggregation is carried out per country and for the growing season (indicatively: April-September), assuming an indicative soil depth of 2 m.

The utilised agricultural area categorised as 'arable land' or 'permanent crops' is available in Eurostat's Crop statistics. It is expressed annually in terms of area (ha per year). Data are collected by each Member State of the EU, EFTA/EEA countries (except Lichtenstein, which is exempt from the data transmission obligation), candidate countries and potential candidate countries at country level. The data are updated every year and come from the National Statistical Institutes. For all countries, the most recent data come from 2016.  

Gross value added (GVA) of crop production is presented in basic prices[1] per country per year (in € or PPS; values at constant prices[2]), adjusted for crop subsidies). This is an approximate measure of the net economic value generated by the producer exclusively from the production of all crop types, which best captures the revenues and the costs accrued by the producer. It can be calculated as follows:

  • crop GVA at basic prices = crop output – crop intermediate consumption – taxes + crop subsidies
  • crop GVA at basic prices, adjusted for subsidies = crop GVA at basic prices – crop subsidies


  • Crop output is the value of crop production at basic prices (in EUR or PPS; values at constant prices), per country per year. It can be calculated using the data set 'production value at basic price', which is available in Eurostat's 'Economic Accounts for Agriculture'. Crop output is expressed in terms of economic value on an annual timescale (EUR million or PPS per year). Data are collected for each Member State of the EU, for EU candidate countries and for EFTA members at country level. The data are updated every year and come from the national statistics institutes or national ministries of agriculture. For all countries, the most recent data are from 2016. Crop output is an aggregate of all crops and does not distinguish between crop categories. The values are expressed as basic prices, thus deductible taxes (e.g. value added tax (VAT)) or non-deductible per-unit taxes are excluded and subsidies are included.
  • Crop intermediate consumption is the value of intermediate costs at basic prices relevant for crop production (in EUR or PPS; values at constant prices), per country and year. It can be calculated using a proxy of existing Eurostat data sets, which are found under 'Economic Accounts for Agriculture'. Eurostat provides the 'intermediate costs for agricultural output at basic prices' as an aggregate, without separating into sub-categories, for the crop output, the animal output, the animal product processing, etc. However, a detailed list of intermediate cost types is provided ('seeds and planting stock,' 'energy; lubricants,' 'veterinary expenses', etc.), which allows those cost types considered to be closely associated with crop output to be isolated. There are two types of intermediate cost, which can be exclusively (or mostly) associated with crop production: 'seeds and planting stock' and 'plant protection products, herbicides, insecticides and pesticides'. In addition, several other types of intermediate cost can be shared between crop output and other types of agricultural output. In these cases, the share of the crop output in the value of the intermediate cost type was approximated. 'Fertilisers and soil improvers' are relevant for both crop output and animal output (but not for other components of the agricultural output). Therefore, the proportion of crop output relative to crop plus animal output was used to apportion a share of the figures to crop output. This was calculated by comparing the total crop output figures from 2002-2014 to the total crop plus animal output figures from 2002-2014. 'Energy; lubricants' are relevant for all types of agricultural output; therefore, the relative proportion of crop output to total agricultural output was used to apportion a share of the figures to crop output. This was calculated by comparing total crop output figures from 2002-2014 with total agricultural output figures from 2002-2014. None of the remaining intermediate cost types listed in Eurostat's Economic Accounts for Agriculture were considered to be associated with crop output, because they do not relate to crop farming, but rather to animal breeding or animal product processing or services, etc. Crop intermediate consumption is expressed in terms of economic value on an annual timescale (EUR million or PPS per year). The data sets used in the proxy are collected for each Member State of the EU, for EU candidate countries and for EFTA members at the country level. The data sets are updated every year and come from the national statistics institutes or the national ministries of agriculture. For all countries, the most recent data sets are from 2016. Approximating crop intermediate consumption was already ambitious for this indicator, so breaking it down into crop types was not even attempted. The values are expressed as basic prices, thus deductible taxes (e.g. VAT) or non-deductible per-unit taxes are excluded and subsidies are included.
  • Crop subsidies include EU or national payments to crop farms, per country per year. It can be calculated using a proxy of existing FADN data sets. 'Total Subsidies — excluding on investments (SE605)' accounts for subsidies on current operations linked to production, not including payments for investments or payments for cessation of farming activities. 'Gross Farm Income (SE410)' is the rough equivalent of crop GVA at micro-economic level, accounting for output minus intermediate consumption plus the balance of taxes and subsidies. In micro-economic terms, the share (%) of 'Total Subsidies — excluding on investments' out of gross farm income constitutes a rough equivalent of the share of crop subsidies out of crop GVA at macro-economic level. Therefore, once this share is calculated, the crop GVA may be discounted in order to derive the crop GVA, adjusted for crop subsidies. The crop farms considered to calculate both variables are those classified under the TF8 (Type of Farm) classification system as: TF = 1. Field crops; 2. Horticulture; 3. Wine; and 4. Other permanent crops. The data sets used in the proxy are collected by national liaison agencies (or by bodies nominated by them) under the guidance of national FADN committees for each Member State of the EU. The data sets are updated every year using a survey, which covers those agricultural holdings that could be considered commercial due to their size. For all countries, the most recent data sets come from 2013.

If data are not available for any of the following variables; a)water abstraction, b)soil moisture, c)gross value added, d)subsidies on crops, then the calculation of water intensity of crop production was not conducted for the same country and for the same year.


[1] Basic price is the amount receivable by the producer from the purchaser for a unit of a product minus any tax (e.g. VAT) on the product plus any subsidy on the product:

basic price = market price – (VAT + non-deductible per unit taxes) + subsidies

[2] Constant prices assume that a value (e.g. GDP, GVA) is expressed in the price terms of a base period (normally a year). In this case, the values of crop output for both 2010 and 2013 are calculated using the 2010 prices as a reference.  

Methodology for gap filling

  • The data on water abstraction for irrigation purposes from fresh surface water and groundwater sources have many spatial and temporal gaps. Data for the following countries were gap filled as follows: Latvia (2005) taken as equal to 0, Hungary (2007) taken as equal to Hungary (2006); Hungary (2010) taken as equal to Hungary (2011); Greece (2010) taken as equal to Greece (2011); Portugal (2010) taken as equal to Portugal (2009); and Spain (2013), Denmark (2013), Netherlands (2013) and United Kingdom (2013) taken as equal to Spain (2012), Denmark (2012), Netherlands (2012) and United Kingdom (2012), respectively. Improvements in reporting will allow data gaps to be reduced in the future.
  • Water abstraction for irrigation purposes from non-fresh water sources (or any of its components) is taken as equal to 0 if not reported.

Methodology references


Methodology uncertainty

  • Because of the general nature of the irrigation abstraction data, which measure the volume of water that is abstracted for irrigation purposes in the agricultural sector, the indicator may not capture the added value of rainwater and irrigation that accrues for animal outputs (e.g. to grow grass or feed for animals). Accordingly, agricultural holdings that irrigate more to produce feed for their livestock will appear to have relatively high water intensities, as the indicator does not include contributions to GVA from animal outputs (it captures only crop GVA). Given the available data, it remains unclear how to deal with this issue.
  • It is not clear if the combined use of dual irrigation/drainage systems (i.e. draining in wet seasons, submerged irrigation in dry seasons by raising water tables in rivers or groundwater), which is practised in some countries, such as Poland and the Netherlands, is actually quantified and accounted for. This may lower the accuracy of the estimation of irrigation volumes.
  • The calculations of 'gross farm income' and 'total subsidies excluding on investments' do not include crop farms that produce crops in combination with dairy/meat. Excluding this category introduces uncertainty. However, including it is also problematic if the proportion that relates to dairy/meat production is not excluded.
  • The methodology that was used to estimate the soil moisture per country is based on EEA modelling work for European water accounting and further aggregations to capture the suitable temporal and spatial scales. Modelling is a simplistic representation of reality, which introduces a number of systematic or random errors. The aggregation techniques are built on assumptions that may insert distortions of the national values of soil moisture. For example, the growing season is considered unique for all countries and crops, using a generic period between April and September. In addition, the depth of the root zone has been taken as equal to 2 m, whereas this variable is known to vary.
  • If 'soil moisture in growing season' is not included in the 'water input to crops', then the water that corresponds to the reported crop GVA will not cover both rain-fed and irrigated conditions. Separating crop GVA into two portions, one for 'irrigated growth' and one for 'rain-fed growth' would be ideal, but, despite efforts, it has been very difficult to do this because of conceptual issues and the lack of specific country data on irrigated and non-irrigated yields. Two options have been tested for developing a partitioning coefficient. The first option used the ratio of irrigated area to UAA, whereas the second option used the ratio of the volume of irrigation water to the total volume of crop water. However, both options created distortions and introduced high degrees of uncertainty. Therefore, it was decided that the best option was to calculate the water input to crops, including the soil moisture in the growing season, to reduce this kind of uncertainty.
  • Because of the gaps in the irrigation abstraction data, the indicator is calculated for specific, non-consecutive years. This causes uncertainty because of the climate variability from year to year. Soil moisture and irrigation abstractions for irrigation purposes are known to differ between wet and dry years. However, a correlation is expected between them (i.e. when the former increases, the latter should decrease). Consequently, some parallel work may be needed to interpret the indicator results in the context of wet/dry seasons. The production of longer time series for the indicator is expected to partly neutralise the impact of climate on its interpretation. In addition, by using the sum of soil moisture and irrigation water in the indicator, the uncertainty due to climate variability is reduced. Whereas these two components are very sensitive to climatic conditions, their aggregation (i.e. total water input to crops) is less sensitive on an annual scale, because it is related to the total crop water needs.
  • The calculation of the crop GVA required the attribution of a proportion of the agricultural intermediate costs (i.e. the total sector costs) to the crop output level. The method that was developed (i.e. by attributing a proportion of the costs based on the relative size of the crop output to either the agricultural industry or the crop plus animal output, as appropriate) is a fair simplification, but it is expected to increase the uncertainty of the indicator results.
  • Total subsidies excluding on investments as a proportion of gross farm income is an estimation using micro-economic variables. Using the same proportion for apportioning crop subsidies and crop GVA, which are macro-economic variables, introduces uncertainties in the calculations.

Data sets uncertainty

  • The reported values under 'water abstraction for agriculture — irrigation' are identical to the values under 'water abstraction for agriculture' (Eurostat dataset: env_wat_abs) for Croatia, France, Malta, Slovenia and Turkey. This would imply that the agricultural sector in those countries extracts zero water for watering animals or other uses, which does not seem accurate.
  • A cross-checking of reporting for the 'irrigated areas at least once a year' under the Farm Structure Survey (FSS) (Eurostat dataset: ef_poirrig) and for the volumes under 'water abstraction for agriculture — irrigation' (Eurostat dataset: env_wat_abs) showed that Belgium reports zero irrigation for water abstraction for all available years, whereas non-zero irrigated areas are also reported for the same years. In addition, Finland and Latvia report irrigated areas that do not match the reported irrigation volumes. A further cross-check between WISE-3 and Eurostat reporting for irrigation abstraction revealed that there are significant differences in reported volumes for the following countries and years: Bulgaria (2013), the Netherlands (2010), Sweden (2010), Slovakia (2013) and the United Kingdom (2013).
  • Reported values of irrigation abstraction may not account for self-abstraction, which is a common practice in many areas, especially in southern Europe.
  • No data are available on desalinated water for irrigation purposes, whereas this practice seems to exist in some southern countries, e.g. in Spain, based on international literature (FAO, 2006).
  • Reclaimed water is a significant source of irrigation water in Cyprus and Spain, but the 2013 values are missing from their reporting. The same applies for the 2013 value for non-freshwater sources abstracted for irrigation in Spain. Because these water quantities are missing from the 2013 calculations, Cyprus and Spain may show inaccurately low water intensities.
  • The soil water balance model (swbEWA) has been found to overestimate soil water storage, especially for low soil depths near the surface.

Rationale uncertainty

  • Using water abstraction data allows the capture of information on the total water that is withdrawn from the environment to make it available for crops. This includes information on water losses (e.g. leakages or evapotranspiration) during conveyance and the distribution of water from the source to the field via open canals or closed pipes, and on the on-field losses during the application of water (e.g. leakages, evapotranspiration or surface runoff) caused by the irrigation method/system (e.g. drip, sprinkler or surface irrigation) used. These losses are important aspects of water intensity, since countries that manage to keep these losses low are expected to abstract a lower proportion of water relative to their actual water need for growing crops. Therefore, the same gross value added from crops may be delivered with proportionally less water input. When constructing the indicator, using 'water use for irrigation' rather than 'water abstraction for irrigation' was considered; however, the data available from Eurostat were reported only once in 2010 (in the FSS) and the reporting of these data was not foreseen to be continued in the future. In addition, if water use for irrigation had been chosen, the differences in conveyance efficiency among European countries would be lost.
  • Water reuse is considered a practice that improves water intensity in the context of the economy because it prevents new abstractions from the environment and allows water to enter a new loop, where it may generate additional value before returning to the environment. However, in the context of this indicator, the use of reclaimed water for irrigation is treated as an abstraction by a separate source, because reclaimed water is actually abstracted from another sector (i.e. primarily the domestic sector) before being made available for irrigation. Therefore, it is not accounted for in irrigation abstraction(FSW), irrigation abstraction(FGW) or irrigation abstraction(NFW), even though its use generates value added from the crops it irrigates. On the contrary, water recycling at farm level represents water that is already accounted for in irrigation abstraction. To avoid double counting the same volume, this water is not included in estimates of total water input to crops. Since the same amount of water is used multiple times to create additional value, the impact of water recycling is taken into account indirectly through the increase of the value added from crops.
  • The economic variable of the indicator was selected from three options: crop output, GVA or net value added (NVA). Crop output was not selected because it does not account for intermediate costs of production, as GVA and NVA do. The indicator would be based on only revenues and not costs, thus being unable to exhibit the actual benefit of the economic activity for the industry/region/sector. Theoretically, it would be preferable to use NVA rather than GVA; however, the lack of complete data led to the selection of the latter. In addition, the selection of alternative aggregate macro-economic variables (e.g. gross domestic product (GDP)) would make the indicator less relevant for its intended purpose, because multiple external factors influence such variables.
  • The economic values of the indicator could be expressed as producer, market or basic prices. Basic prices was selected because of the availability of relevant data, which also enable the calculation of intermediate costs. In addition, an investigation of the country-level data shows that the difference between output valued using basic prices and producer prices was not large. Nevertheless, if per-unit subsidies or taxes change significantly, this would impact the indicator in a counterintuitive way (i.e. an increase in subsidies would decrease the apparent water intensity). This should be considered when interpreting the indicator results.
  • The economic values of the indicator could be expressed as constant or current prices. Constant prices are preferred for theoretical reasons, because they make interpreting the indicator more straightforward. Any increase in the GVA for a country can be interpreted as an increase in the quantity of output produced. If current prices were used, a change in the indicator could be as a result of a change in prices, and not necessarily be associated with a change in water intensity. In addition, constant price data are readily available.
  • The PPS unit adjusts euro values to reflect the actual buying power in different countries, thus accounting for the different amounts of goods and services a euro can buy in the different Member States of the EU. This is preferable for comparative assessments between countries, as relative differences in purchasing power are neutralised. It should be noted, though, that PPS does not specifically capture the purchasing power of European farmers. Therefore, the calculation of a special index covering the farmer’s basket would be preferable, but such data were not readily available during the construction of the indicator. Moreover, caution is needed when drawing conclusions from comparisons between countries, as the annual differences in GVA are affected by various agents: crop patterns, crop quality, soil fertility, crop production systems, water limitations, weather conditions, crop failures (e.g. because of frost, heat or insect attacks), etc. Comparisons between countries with significant structural differences may not be particularly instructive, whereas comparisons within the same geographical region may be more informative. Low water intensity of crop production values do not necessarily imply that the country is operating efficiently on all levels, but instead may be an indication that the baseline crop mix/production system is inherently of lower intensity. Further study is needed of the specific reasons for lower water intensities in some countries than in others.
  • The indicator is also calculated using unadjusted euro values, as these data were readily available. These results are produced to allow better comparisons across time within a single country, enabling the identification of trends. By using the unadjusted euro values, the previously mentioned discrepancy between the index used to produce the PPS values and a special index covering the farmer’s basket is neutralised. Changes in the relative purchasing power do not affect the interpretation of the indicator results, as no comparisons between countries are made.

Further work

Short term work

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

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

Nihat Zal


European Environment Agency (EEA)


Indicator code
WAT 006
Version id: 1

Frequency of updates

Updates are scheduled every 3 years


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

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Data references used

Data used

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