Transcript 8c_ETC_water Assessment of the reported on water abstraction

Test Data Exchange 2008
Assessment of the reported data
on Water Abstractions
Maggie Kossida
George Papoutsoglou
ETC/W
Thematic Workshop 'Water Quantity and Use'
10-11 October 2007, EEA, Copenhagen
National Technical University of Athens-NTUA
Main purpose of the Water Abstraction data request
 provide representative periodic assessments of the status & trends in
the freshwater abstractions
 support the development of WS&D indicators
 broader assessment of specific water-related issues in the relevant
conceptual ecosystem frameworks
 assess the impact of specific sectors, driving forces & responses
Key policy questions:
Is the abstraction rate of water sustainable ?
Is the use of water by sectors sustainable ?
Current EU picture
Water abstraction for irrigation
45000
40000
1990
2005
35000
mio. m3
30000
25000
20000
15000
10000
5000
0
Eastern (central Western (central
and northern)
and northern)
Western
(southern)
Need for more
detailed and less
aggregated data
Water use by sector
Test Data Exchange 2008_Requested Data
Data assessment_Water Abstractions
t = total
s = sectoral (PWS, Tourism, Agriculture, Industry, Thermoelectric Power, Mining, Fish
farms, Others)
* data not provided but can be calculated from the monthly and annual
Data assessment_Water Abstraction
Response: 16 countries
SPATIAL RESOLUTION
minimum reported scale
Regional Level
RBD
RB
Admin.
9
2
1
Country Level
4
SPATIAL DISTRIBUTION WITHIN EU
Southern
Western
Eastern
2
6
8
TEMPORAL RESOLUTION
minimum reported scale
Monthly
Annual
2
14
TEMPORAL DISTRIBUTION
reference year of reported data
2007
2006
2005
2004
3
7
5
1
Data were also provided in additional information in
the form of tables or graphs from 2 countries (one set
for 1994-2004, and another for 2005)
1 country also reported mean 4-8year values
(1995,1999-2003)
Overall assessment
Water Abstractions data are also shown to be available @
regional RBD level.
temporal resolution: data availability on monthly/seasonal
scale is more restricted
this could be related to the national collection procedure 
feedback from the counties on the process
Added Value of the disaggregated data
Annual averages do not depict seasonality which is important
Country level averages do not depict spatial variability and trends
Water balance + water use = water budget
Changes in the water budget of a RB /RBD
can demonstrate how human activities, (e.g. drainage, irrigation
systems, urbanization, land use change etc.) in one part of the hydrological
cycle may affect other aspects
Comparison of water budgets from different RBs/RBDs
can be used to integratedly address both water availability and
environmental issues
The following preliminary examples, based on the Test Data Exchange
2008, illustrate the importance of disaggregated data both in spatial and
temporal scale
Examples from the Test Data Exchange 2008
Water abstractions
Monthly Trends
per RB in SK
Danube (SK) monthly
trends in Freshwater
Abstractions
and the role of
Agriculture and
Industry
Depicting the Seasonality in Agricultural and Industrial water use in SK RBS
Water abstractions Monthly Trends in Shannon RBD, IRELAND
Further Steps

necessary technical clarifications, definition of terms for harmonization

timeliness and availability of the data in order to streamline the reporting
Cooperation between EEA and EUROSTAT (JQ) is already in process

A first QC check revealed uncertainty and inconsistency is some data sets. The
current data will be examined thoroughly and questions will be sent to the
countries for clarification

Water abstraction data are very important to support SoE assessments and
water scarcity and drought activities since they communicate important socioeconomic information indispensable for any work under the DPSIR
framework

Thus, EEA will also examine possibilities of seasonally disaggregating annual
abstraction data (using specific methodologies combined with water-use
coefficients (dependant on the availability of other types of data (e.g. sensus
data, land use date etc.), higher bias?
Thank you for your attention !