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Details of Grant 

EPSRC Reference: GR/S98634/01
Title: Hydraulic Modelling of Remote River Basins
Principal Investigator: Bates, Professor PD
Other Investigators:
Researcher Co-Investigators:
Project Partners:
University of California Los Angeles
Department: Geographical Sciences
Organisation: University of Bristol
Scheme: Overseas Travel Grants Pre-FEC
Starts: 11 June 2004 Ends: 10 September 2005 Value (£): 9,065
EPSRC Research Topic Classifications:
Coastal & Waterway Engineering
EPSRC Industrial Sector Classifications:
Water
Related Grants:
Panel History:  
Summary on Grant Application Form
Hydraulic modelling of flow in rivers is a key requirement for river basin management projects worldwide. However, most hydraulic models depend on access to to detailed and accurate data sets, particularly for topography and river flow to act as model boundary conditions. Such data availability is not the case for many overseas consulting projects, which may take place in remote basins or areas where there is sparse data coverage. An untried solution to this problem would be to parameterize hydraulic models using global data sets available in the public domain. Until recently such data has been of poor resolution and unsuitable for hydraulic modelling, but in 2000 a Space Shuttle mission (the SRTM) collected a new global DEM with sufficient resolution (-30m) and vertical accuracy (-5m rms error) for hydraulic modelling in large basins. However substantive research is required to develop models capable of using such data, to examine the accuracy of the derived data sets and to develop appropriate model-data assimilation techniques. Moreover, expertise in the SRTM does not currently exist in the UK. This proposal therefore seeks funds to collaborate with SRTM experts at the University of California Los Angeles in order to acquire essential knowledge of this new data set and undertake a feasibility study into the above research issues. Specifically, the feasibility study will extend the LISFLOOD-FP 2D hydraulic model for operation in global scale basins, develop techniques to optimally parameterise the LISFLOOD-FP model using SRTM data at large grid scales and validate the prototype model against available ground and space-borne hydrometric measurements for a single test site in the Amazon basin.
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Organisation Website: http://www.bris.ac.uk