Presentation on theme: "Water cycle data and information needs : examples from the EU-FP7 «ACQWA» Project Martin Beniston Institute for Environmental Sciences University of Geneva,"— Presentation transcript:
Water cycle data and information needs : examples from the EU-FP7 «ACQWA» Project Martin Beniston Institute for Environmental Sciences University of Geneva, Switzerland GEOSS-IPCC Workshop, Assessing Climate Impacts on the Quantity and Quality of Water
Mountains as a source of more than half the worlds 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 km 2 ; 16 million inhabitants Swiss segment: 10,100 km million inhabitants Climate Glaciers Snow Vegetation Environmental Controls Tourism Energy Agriculture Economic Controls Runoff Extremes Geomorphic
Overview of ACQWA project components Climate Ice/GlacierSnowBiosphere Hydrology MODELS
Changes in seasonal temperatures (at 2,500 m asl) Beniston, 2006: Geophysical Research Letters 15 WinterSpringSummerAutumn Temperature [°C] Beniston, 2004: Climatic Change and Impacts, Springer
Changes in seasonal precipitation Beniston, 2006: Geophysical Research Letters WinterSpringSummerAutumn Precipitation change 2071/2100 vs 1961/1990 [%]
Shifts in snow volume according to altitude Total volume [10 9 m 3 ] Altitude [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 Courtesy: Max Maisch University of Zurich, Switzerland 2050? +3°C?
Possible future discharge by 2100 (m 3 /s, River Rhone) Beniston, 2010: Journal of Hydrology JFMAMJJASOND Average monthly discharge [m 3 /s]
Alleviating rivalries between economic sectors? Climatic change Water resources TourismAgricultureMining Conflict mitigation through improved water governance? Energy
Overview of ACQWA project components AdaptationGovernance POLICY TourismAgricultureEnergy IMPACTS Extremes Climate Ice/GlacierSnowBiosphere Hydrology MODELS ChileKyrgyzstan CASE- STUDIES An analogy today for the Alps of tomorrow? Possible opportunities during the 21st Century?
Data problems specific to the ACQWA project n Compatibility and transferability of socio-economic and demographic data for models requiring spatially-explicit data n Access to sensitive data in IWRM research, primarily water deviation as well as storage-pumping data and production schemes from hydropower companies n Access to hydrological and meteorological data in the Po, Aconcagua and Tien-Shan catchments (very restricted access, non-availability of digital data, little literature) n Groundwater data for spatially-explicit modelling
Outcomes of a recent ACQWA-sponsored workshop on data and science gaps (Riederalp, Switzerland, January 12-15, 2011) n About 25 different EU water&climate-related projects represented n Primary foci: u Identification of gaps in data and scientific information that can pose problems for the completion of major research projects u Possible solutions to alleviate such problems
Identification of problem areas - 1 n Partial inconsistency between physical and socio- economic data and models u For example, data on water uses may not be available at the temporal and spatial detail required by hydrologic models. u Hydrological information is often based on basins whereas economic (and social) data is administration regions. u Thus economic and physical data are often incompatible, because collected by different entities for different purposes. n Interactions between water policies and policies in other major sectors: u 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 n Measurements of total discharge (time variation or peak) and flood velocity across river and flood plain during extreme events are rare n 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. u This high density of data is not generally available to support research studies. n Water quality information is sparse u Sediments (bed load; suspended); biota (pathogens; parasites). u The remobilisation of polluted sediments in extreme floods as an important mechanism in contaminant transport is poorly known
Possible solutions n Future research should address: u building compatible data sets and the conversion process between different data formats u developing toolboxes for upscaling, downscaling and bias correcting data n 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… n Are policy makers able/willing to exploit all available information produced by the scientific community? n 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 n Increased awareness about the future of water resources in a given region to provide support to policies n Integration of inputs from stakeholders at both river basin and trans-boundary levels to attain adaptation goals n Information on projections and revision of water management plans, inter alia for the IPCC and UN-ISDR n Web-based tools to support water scenario development processes
Many thanks for your attention GEOSS-IPCC Workshop, Assessing Climate Impacts on the Quantity and Quality of Water