water cycle data and information needs : examples from the eu-fp7 «acqwa» project martin beniston...
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Water cycle data and information needs :examples from the EU-FP7 «ACQWA» Project
Martin BenistonInstitute for Environmental Sciences
University of Geneva, Switzerland
GEOSS-IPCC Workshop, 02.02.2011
Assessing Climate Impacts on the Quantity and Quality of Water
Mountains as a source of more than half the world’s rivers
Upstream-downstream links
Rhone Basin>15 million
Rhine Basin>50 million
Po Basin>15 million
Danube Basin>200 million
The Rhone River catchment
95,000 km2; 16 million inhabitants
Swiss segment: 10,100 km2
1.2 million inhabitants
Climate
Glaciers Snow
Vegetation
Environmental Controls
Tourism
Energy
Agriculture
Economic Controls
Runoff
ExtremesGeomorphic
Overview of ACQWA project components
Climate
Ice/Glacier Snow Biosphere
Hydrology
MODELS
Changes in seasonal temperatures (at 2,500 m asl)
Beniston, 2006:Geophysical Research Letters
15
Winter Spring Summer Autumn
Te
mp
era
ture
[°C
] 10
5
0
-5
Ben
iston, 2004: Clim
atic C
hange and Im
pacts, S
pringer
1961-1990
2071-2100
Changes in seasonal precipitation
Beniston, 2006:Geophysical Research Letters
-40.0
-30.0
-20.0
-10.0
0.0
10.0
20.0
30.0
40.0
Winter Spring Summer Autumn
Pre
cip
ita
tio
n c
ha
ng
e2
071
/21
00
vs
19
61/1
99
0 [
%]
Shifts in snow volume according to altitude
500
1000
1500
2000
2500
3000
3500
4000
4500
0 10 20 30 40 50 60
Total volume [109 m3]
Alt
itu
de
[m
]
Beniston et al., 2003:Theor. and Appl. Clim.
Almost total loss
40-60%loss
Slight increase
+4°C
2000
Glacier retreat:Tschierva Glacier, Engadine
Cou
rtes
y: M
ax M
aisc
hU
nive
rsity
of
Zur
ich,
Sw
itzer
land
2050?+3°C?
Possible future discharge by 2100(m3/s, River Rhone)
Be
nis
ton
, 20
10
: Jo
urn
al o
f Hy
dro
log
y
0
50
100
150
200
250
300
350
400
J F M A M J J A S O N D
Ave
rag
e m
on
thly
dis
ch
arg
e [m
3/s
]
1961-1990
2071-2100
Overview of ACQWA project components
Tourism AgricultureEnergyIMPACTS Extremes
Climate
Ice/Glacier Snow Biosphere
Hydrology
MODELS
Alleviating rivalries between economic sectors?
Climaticchange
Waterresources
Tourism Agriculture Mining
Conflict mitigation through improvedwater governance?
Energy
Overview of ACQWA project components
Adaptation GovernancePOLICY
Tourism AgricultureEnergyIMPACTS Extremes
Climate
Ice/Glacier Snow Biosphere
Hydrology
MODELS
Chile KyrgyzstanCASE-STUDIES An analogy today
for the Alps of tomorrow?Possible opportunities
during the 21st Century?
Data problems specific to the ACQWA project
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 ofproblem areas - 1
Partial inconsistency between physical and socio-economic data and models 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 ofproblem 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: 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 ofscientific results beyond IPCC
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
Many thanks for your attention
www.unige.ch/climate
GEOSS-IPCC Workshop, 02.02.2011
Assessing Climate Impacts on the Quantity and Quality of Water