Implementing the Water Asset Accounts (WAA) over the EEA area

1. Implementing the Water Asset Accounts (WAA) over the EEA area Lessons learnt from “broad-brush” and “refined” implementation. Key challenges for data collection Philippe Crouzet EEA

2. The EEA • EEA’s mission is “to support sustainable development and to help achieve significant and measurable improvement in Europe’s environment, through the provision of timely, targeted, relevant and reliable information to policy-making agents and the public” • Permanent conceptual framework: DPSIR • Prominent production framework (for hydrosystems): • Legal framework for water: WFD, its daughter directives and non-repelled directives and the assessment of their effectiveness (e.g. BP 2012) • Environmental Accounts (in 2010, becoming “international interim statistical standard”, to be finalised in 2012) • A dual regulatory framework: EIONET (the European information network) and SEIS (*), in its exploratory and building phase

3. The EEA area of intervention Country groupings EEA member countries European Neighbourhood Policy ENP South ENP East Strategic Partnership Central Asia Strategy for a new partnership for Central Asia • EEA 32 • Albania, Bosnia & Herzegovina, Croatia, FYR of Macedonia, Kosovo, Montenegro, Serbia, Monaco • Algeria, Egypt, Israel, Jordan, Lebanon, Libya, Morocco, Palestinian Authority, Syria, Tunisia • Armenia, Azerbaijan, Belarus, Georgia, Moldova, Ukraine • Russian Federation • Kazakhstan, Kyrgyzstan, Uzbekistan, Turkmenistan, Tajikistan

4. Are time 1 and 2 consistent vs. stock assessment? Do gains compensate for losses? Can gain substitute to losses? Has the quality of the stock been maintained? Accounting conceptual model applied to water assets accounts and data issues Gain in stock e.g. by storage Data Time unit DataSpatial unit Data content issue Loss of stock e.g. by usage

5. Why developing accounts at the EEA level? • Water is key issue for: • Its availability proper, to serve domestic uses, industry, agriculture • As support to aquatic ecosystems and associated services (including fish ), • Energy production (hydropower, cooling) • Water resources may be hampered by CC, especially where scarcity already exists, • All policies demand balancing environment – economy – sustainability: • the “new green deal” asks for relevant and comparable indicators, • WFD effectiveness assessment has to be contextualised, • The SEEA/W (*) framework provides the conceptual and reporting tool to contribute achieving these goals.

6. Accounts and data acquisition strategy • The SEEA (system of Environmental and Economic accounting) was first developed to cope with existing data at statistical offices, • Deep analysis of the segment of SEEA applied to water (SEEAW methodology) demonstrated that sound implementation in the EEA area required seasonal and sub-basin approach to output comparable and useful water balance and accounts tables providing sensible indicators nevertheless fully endorsing the methodological principles of SEEAW (e.g. SNA compatible nomenclature, input –output tables, satellite and hybrid accounts, etc.) • For the EEA, the SEEA framework is deeply embedded into the integrated assessment and is one tool to support policy effectiveness assessment; hence it is a key driver of data acquisition strategy for the years to come

7. The SEEAW components: mimicking the hydrological cycle and human uses

8. The SEEAW components: mimicking the hydrological cycle and human uses • The scope of WAA (water assets accounts) is to compute top system and the exchanges inside top system and between top system and the uses as in bottom system. • The economic exchanges between uses (e.g. industry sells water to agriculture) are beyond our current scope • Key issues are defining proper ”territories of reference”, their interconnections and populate with reliable and relevant data

9. EEA implementation strategy • Implementing the accounts require three classes of ingredients: • A calculable reference system in which natural water exchanges can be modelled and in which the appropriate “territories of references” are defined and used as aggregates; • ECRINS was developed on this purpose from 2009 onwards, • A computation platform capable of handling data, modelling surrogate data when and where data is missing and assemble all heterogeneous data sources and output under the demanded SEEAW format; • The Nopolu platform (already used at Ifen under Eurostat subsidy) was selected and upgraded to this end • Having appropriate data categories, disaggregated at the appropriate time and space resolution. • Ad hoc data collection has been developed, tested and gaps largely analysed. • Testing the implementation is being carried out, from the end of 2008, under a 4 years development: • Test the calculations over a small catchment (the Ebro) and improve the three classes accordingly, • Test the application of the model on larger areas and check the appropriateness of the reference system and analyse data gaps, • Improve the reference system, analyse the results and propose new data collection strategy • Once done, implement for systematic production, ensure capacity building for the regular WA production. • Point II above is achieved and point III started to be undertaken.

10. Catchment statistical unit Defining the S.U. on the pilot Ebro catchment

11. The high differences between reaches demonstrates the need for considering river segment as SU >200 m3/s <2 m3/s Water assets cartographic outputs on the Ebro pilot catchment • The most important feature of the EEA approach is that data to be accounted is computed at systematic and constant analytical unit: the Functional elementary catchment • Each value is rather uncertain, but allows any further aggregation (in next implementations, NUTs are set) and uniform processing facility

12. Sample outputs from the Ebro catchment • SEEAW output tables are: • Assets tables • Exchange tables (what resources feeds which other resource) • Water uses (which resource feed which use and what are the returns) • Key lessons learnt: • Method to compute rainfall / effective rainfall not sustainable, • Need to revise the reference system • Data hierarchy

13. Essential: cannot be modelled stratified stratified stratified Linear Replaceable: can be modelled from other variable Point Data categorisation & hierarchy Surfacic

14. Practical implementation of ad hoc data collection for the refined approach Define accurately statistical units

15. Some examples of data sources for “refined” • Substitution • River segment is statistical unit: discharge per segment computed with hydrological model from numerous gauging stations • Reservoir changes in stock replaced by inflow /outflow from river segment modelling, • Domestic abstractions missing: replaced by population per FEC (surfacic statistical unit) times volume per capita, • Essential • Rainfall and evaporation taken from MARS instead of national data sets, (surfacic) • Energy plants from Platts data sets (point) • Agricultural water needs from JRC (surfacic) • Gaps • Industry (point) • Domestic transfers (point /linear) • River run-off in large part of Europe at gauging stations (point)

16. The refined application • Data collection under a ‘SEIS-like’ approach for AT, PT, FR, UK, NL, DK, ES resulted in setting 4,114 gauging stations populated with 41,181,315 daily discharges aggregated into 1,468,329 monthly averages allowing extrapolation of discharges at the river segment for several years. • CH and IE to be integrated soon • Area limited only by river run-off * basin coverage, • This allowed processing Denmark, but not Austria (related basins not documented), • Environmental data collection largely out of priority data flows, • Expecting 2009-2010 revised water uses data collection to improve the computations,

17. Overall data consistency • Water balance is driven by: Rainfall-Evaporation • And is checked vs. outflow to the sea These three data sets are built from totally independent sources

18. Water soil balance issues • Soil is the central compartment; its monthly assessment requires: • Actual evaporation, applied to current stock • Field capacity and retro-modelling • Field capacity under production (ETC from Soil DC)

19. Spatial modelling Individual modelling Detailed data Stratified approach: urban water supply example • The abstracted volume is proportional to population whereas the data collection effort is driven by number of cities • Only large abstractions need precise location and source for volumes • Athens, or London get their water from far away, in different watersheds, changing their water cycle (abstraction and return in different basins / ‘territories of reference’)

20. Stratified approach: putting to work • The principle of stratified approach applies to all categories of water users, with different modalities. • Cities to be dealt with in junction with IUME, • Industry to be dealt with using e-PRTR as seed, • Energy production to be dealt with starting with the Platts permanently updated inventory, • Returns by SWWTP to be dealt with using the UWW Directive reporting • All point sources to be addressed MUST be in parallel entered in the reference systems, with the accurate topological relationships (work undergoing with ETC/LUSI)

21. How refining data collection processes to meet WAA requirements? • Spatial seamless systems are currently exploited; coarse resolution and differences in coverage are issues to analyse. • Reference system update requires special approach to countries (new reservoirs, large aqueducts). 2nd point in next ECRINS version, in Inspire compliant way. • Monitored data (typically river discharge, aquifer levels and for some reservoir reserve): towards systematic data collection of respectively daily/monthly values. The most disaggregated data both: • Ensures multi-purpose use (many different statistics needed to meet new objectives set by the MB), • Minimizes country burden (aggregates at Agency’s level) Urgent progresses to make under SEIS, • Non monitored point systems, typically water abstractions / uses: stratified approach and systematic exploiting of legal submissions.

22. Thank you for your attention

23. Practical application • Processing together the FEC (ECRINS), EuCitiesTowns and population density provides calculable proxies: • Density inside EuCitiesTowns is groups 1 and 2 • Density-density inside EuCitiesTowns per FEC= group3 • EuCitiesTowns apportioned per FEC provide additional information

24. Source: FAO The problem with this source is that it presents only an area where irrigation could be done per cell (5’*5’). This gives a certain potential, to model with crops Assumptions to be carried out in the accounting computation. • Source: JRC. • The problem with this source is twin: • It does not cover EEA area, • It does not have seasonal values • By contrast it expresses a demand, stated by actual uses and should floor the abstractions • Assumptions to be carried out in the accounting computation. For refined computation, in the absence of other source, apportionment of JRC source (as volume per 10*10km cell) was used after apportioning per sub-basin, which is the smaller aggregation level (sub-basins are apportionment of RBDs). Secondary assumption were made to share surface /GW and seasonalise.