disaggregation of passive microwave data and assimilation into distributed hydrological models:
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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, - PowerPoint PPT PresentationTRANSCRIPT
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
National Airborne Field Experiment
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…
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
The NAFE catchments
• 2 australian catchments:– Goulburn river /
November 2005– Yanco and Kyemba
Creek / November 2006
• Strong climate variability (from subhumid to semiarid)
Vegetation and soils
Mostly black clays + sandstones
Open woodlands (south half + northern ridges), crops (barley, wheat, oats, lucern), native and improved grass
Automatic measurements
+• Dew sensors• TIR sensors• Started in 2002• Run until end of
2007
Weather stations (4)
Soil moisture stations (20)
Streamflow gauges (7)
0 50Km
NAFE05 Overview
Lake Glenbawn:PLMR calibration
Merriwa:Ground crew
KruiArea
MerriwaArea
Pembroke
Scone Airport:Air crew
Stanley
Illogan
Roscommon
Legend
NAFE operation base
SASMAS Site
NAFE focus farm
10000ft flight area
625ft flight area
2500ft flight area
5000ft flight area
Catchment boundary
Dales
Midlothian
Merriwa Park
Cullingral
1 km
500m
250m
62.5m
PLMRFlights
PLMR resolutions
Week 1Monday
Norhern GoulburnKrui AreaMerriwa Area
Week 2Monday
Norhern GoulburnKrui AreaMerriwa Area
Week 3Monday
Norhern GoulburnKrui AreaMerriwa Area
Week 4Monday
Norhern GoulburnKrui AreaMerriwa Area
625ft
Dew effect
Thursday
Tuesday
Tuesday Wednesday
Tuesday
Wednesday
Wednesday
ThursdayTuesday
Thursday Friday
Friday
10000ft
Wednesday Friday
Friday
Thursday
5000ft 2500ft
Multiangle 1 month flights schedule
surface soil moisture meas. campaign
5 cm capacitive probe
GIS + GPS
Legend
High resolution area
Ground sampling (500m)
Ground sampling (250m)
Ground sampling (125m)
Ground sampling (62.5m)
6.25m grid
12.5m grid
75m
150m1
50
m
Legend
High resolution area
Ground sampling (500m)
Ground sampling (250m)
Ground sampling (125m)
Ground sampling (62.5m)
Focus Farm
Legend
High resolution area
Ground sampling (500m)
Ground sampling (250m)
Ground sampling (125m)
Ground sampling (62.5m)
6.25m grid
12.5m grid
75m
150m1
50
m
Legend
High resolution area
Ground sampling (500m)
Ground sampling (250m)
Ground sampling (125m)
Ground sampling (62.5m)
Focus Farm
Nested grids surface SM measurements
PLMR Data @ 62.5 m resolution
02/11/2005
04/11/2005
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)
Modelling strategy
inputs = climate etcoutputs = vertical fluxes
coupling
NDVITIR
TBh, TBv
Verticalfluxes
Lateralredistribution
Hydrological model
input = infiltrationoutputs =runoff +Saturation zones dynamics
Soil-Vegetation-Atmosphere+ Radiative Transfer models
coupling
TOPMODEL+KINEROS models
ICARE + radiative transfer schemes
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
