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Disaggregation of passive microwave data and assimilation into distributed hydrological models:

Disaggregation of passive microwave data and assimilation into distributed hydrological models: The National Airborne Field Experiment (NAFE’05/06) Jetse Kalma et al., The University of Newcastle, Australia, Gilles Boulet , Patricia de Rosnay et al., CESBIO, France,

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Disaggregation of passive microwave data and assimilation into distributed hydrological models:

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  1. Disaggregation of passive microwave data and assimilation into distributed hydrological models: The National Airborne Field Experiment (NAFE’05/06) Jetse Kalma et al., The University of Newcastle, Australia, Gilles Boulet, Patricia de Rosnay et al., CESBIO, France, Jeffrey Walker et al., The University of Melbourne, Australia

  2. Concept • Fly at several altitudes over catchments whose size is of the order of one SMOS/AMSR pixel, • Leading to microwave datasets at different resolutions, • Taking the advantage of intensive surface soil moisture measurement campains as well as a long term automatic ground monitoring…

  3. Objectives Development and test of: • soil moisture retrieval algorithms from airborne passive microwave data at several nested scales, with emphasis on several aspects (AMSR/SMOS, different vegetation covers, multiangle flights, dew, topography) • downscaling strategies for retrieval of surface soil moisture at paddock scale • assimilation strategies of the disaggregated surface soil moisture product at local scale into a coupled land surface/hydrology model and performance assessment using continuous streamflow and soil moisture data at several locations throughout the catchment

  4. The NAFE catchments • 2 australian catchments: • Goulburn river / November 2005 • Yanco and Kyemba Creek / November 2006 • Strong climate variability (from subhumid to semiarid)

  5. Vegetation and soils Mostly black clays + sandstones Open woodlands (south half + northern ridges), crops (barley, wheat, oats, lucern), native and improved grass

  6. Weather stations (4) Streamflow gauges (7) Soil moisture stations (20) Automatic measurements + • Dew sensors • TIR sensors • Started in 2002 • Run until end of 2007

  7. 1 km 500m 250m 62.5m PLMRFlights PLMR resolutions

  8. 1 month flights schedule

  9. surface soil moisture meas. campaign GIS + GPS 5 cm capacitive probe

  10. Nested grids surface SM measurements

  11. PLMR Data @ 62.5 m resolution 02/11/2005 04/11/2005

  12. Disagregation strategy • Airborne brightness temperatures will be averaged over the whole catchment to produce SMOS-like data • Then paddock-scale surface SM will be derived using both approaches: • Deterministic approach: based on energy balance and radiative transfer model inversions and projections (Merlin et al., 2005) • Stochastic approach: based on internal variability per land use type (Faivre et al., 1996)

  13. Modelling strategy ICARE + radiative transfer schemes NDVI TIR TBh, TBv Soil-Vegetation-Atmosphere + Radiative Transfer models Vertical fluxes inputs = climate etc outputs = vertical fluxes coupling coupling Hydrological model Lateral redistribution input = infiltration outputs = runoff + Saturation zones dynamics TOPMODEL+KINEROS models

  14. Data Assimilation strategy • inversed airborne SM at paddock scale will be assimilated in the coupled hydrological model • its impact on streamflow and root zone SM prediction will be assessed using the network of automatic stations • the same work will be carried out for the disaggregated surface SM products • since the automatic ground monitoring will still be available in 2007, this work can be carried out for SMOS real data even if ground surface SM campaigns are not scheduled beyond 2006

  15. Further information • Contacts • Jetse.Kalma@newcastle.edu.au • Gilles.Boulet@cesbio.cnes.fr • j.walker@unimelb.edu.au

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