Transcript Les glaciers de la Suisse

Assessing Climate Impacts on the Quantity and Quality of Water
Water cycle data and information needs :
examples from the EU-FP7 «ACQWA» Project
Martin Beniston
Institute for Environmental Sciences
University of Geneva, Switzerland
[email protected]
GEOSS-IPCC Workshop, 02.02.2011
Mountains as a source of more
than half the world’s rivers
Upstream-downstream links
Rhine Basin
>50 million
Danube Basin
>200 million
Rhone Basin
>15 million
Po Basin
>15 million
The Rhone River catchment
95,000 km2; 16 million inhabitants
Swiss segment: 10,100 km2
1.2 million inhabitants
Environmental Controls
Economic Controls
Climate
Glaciers
Tourism
Snow
Vegetation
Geomorphic
Runoff
Extremes
Energy
Agriculture
Overview of ACQWA project
components
MODELS
Climate
Ice/Glacier
Snow
Hydrology
Biosphere
Beniston, 2006:
Geophysical Research Letters
Changes in seasonal
temperatures (at 2,500 m asl)
15
Temperature [°C]
10
2071-2100
5
0
-5
Winter
Spring
Summer
Autumn
Beniston, 2004: Climatic Change and Impacts, Springer
1961-1990
Beniston, 2006:
Geophysical Research Letters
Changes in seasonal
precipitation
Precipitation change
2071/2100 vs 1961/1990 [%]
40.0
30.0
20.0
10.0
0.0
-10.0
-20.0
-30.0
-40.0
Winter
Spring
Summer
Autumn
Shifts in snow volume according
to altitude
Beniston et al., 2003:
Theor. and Appl. Clim.
4500
Slight increase
Altitude [m]
4000
3500
3000
2500
40-60%
loss
+4°C
2000
1500
1000
Almost total loss
500
0
10
20
30
40
Total volume [109 m3]
50
60
Glacier retreat:
Tschierva Glacier, Engadine
Courtesy: Max Maisch
University of Zurich, Switzerland
2050?
2000
+3°C?
Possible future discharge by 2100
(m3/s, River Rhone)
400
1961-1990
300
250
200
2071-2100
150
100
50
0
J
F
M
A
M
J
J
A
S
O
N
D
Beniston, 2010: Journal of Hydrology
Average monthly discharge [m3/s]
350
Overview of ACQWA project
components
MODELS
Climate
Ice/Glacier
Snow
Biosphere
Hydrology
IMPACTS
Tourism
Energy
Agriculture
Extremes
Alleviating rivalries between
economic sectors?
Climatic
change
Tourism
Water
resources
Agriculture
Energy
Conflict mitigation through improved
water governance?
Mining
Overview of ACQWA project
components
MODELS
Climate
Ice/Glacier
Snow
Biosphere
Hydrology
IMPACTS
POLICY
CASESTUDIES
Tourism
Energy
Adaptation
Agriculture
Extremes
Governance
Chile
Kyrgyzstan
An analogy today
for the Alps of tomorrow?
Possible opportunities
during the 21st Century?
Data problems specific to the
ACQWA project

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Compatibility and transferability of socio-economic and
demographic data for models requiring spatially-explicit data
Access to sensitive data in IWRM research, primarily water
deviation as well as storage-pumping data and production
schemes from hydropower companies
Access to hydrological and meteorological data in the Po,
Aconcagua and Tien-Shan catchments (very restricted
access, non-availability of digital data, little literature)
Groundwater data for spatially-explicit modelling
Outcomes of a recent ACQWA-sponsored
workshop on data and science gaps
(Riederalp, Switzerland, January 12-15, 2011)


About 25 different EU water&climate-related
projects represented
Primary foci:
 Identification
of gaps in data and scientific
information that can pose problems for the
completion of major research projects
 Possible solutions to alleviate such problems
Identification of
problem areas - 1

Partial inconsistency between physical and socioeconomic data and models
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For example, data on water uses may not be available at the
temporal and spatial detail required by hydrologic models.
Hydrological information is often based on basins whereas
economic (and social) data is administration regions.
Thus economic and physical data are often incompatible,
because collected by different entities for different purposes.
Interactions between water policies and policies in other
major sectors:

For example, is water policy consistent with energy, agriculture,
and other industrial policies at the national and supra-national
levels?
Identification of
problem areas - 2


Measurements of total discharge (time variation or peak)
and flood velocity across river and flood plain during
extreme events are rare
Floods in urban areas are controlled by topography,
connectivity of the road network, sub-surface sewerage
system; flooding into properties depends upon the location
and dimension of potential entry points.


This high density of data is not generally available to support
research studies.
Water quality information is sparse


Sediments (bed load; suspended); biota (pathogens; parasites).
The remobilisation of polluted sediments in extreme floods as an
important mechanism in contaminant transport is poorly known
Possible solutions

Future research should address:

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
building compatible data sets and the conversion process
between different data formats
developing toolboxes for upscaling, downscaling and bias
correcting data
Establishment of a clearinghouse of relevant and
structured data, including meta-data, hosting not only
data from public and other services but also a
compilation of relevant data produced by EU-type
projects
Additional factors that need to
be considered…


Are policy makers able/willing to exploit all
available information produced by the scientific
community?
There is still a big gap between science available
and its use in policy – how can scientists
improve the flow of information?
Communication of
scientific results beyond IPCC

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Increased awareness about the future of water
resources in a given region to provide support to
policies
Integration of inputs from stakeholders at both
river basin and trans-boundary levels to attain
adaptation goals
Information on projections and revision of water
management plans, inter alia for the IPCC and
UN-ISDR
Web-based tools to support water scenario
development processes
Assessing Climate Impacts on the Quantity and Quality of Water
Many thanks for your attention
www.unige.ch/climate
[email protected]
GEOSS-IPCC Workshop, 02.02.2011