multi-satellite remote sensing of global surface water extent and volume change. fabrice papa (1),...
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Multi-Satellite Remote Sensing of Global Surface Water Extent and Volume Change.
Fabrice PAPA (1), Catherine PRIGENT (2), William B. ROSSOW (1),Elaine MATTHEWS (3), Andreas GUNTNER (4), Frederic FRAPPART (5) et al (6).
(1) NOAA-CREST-CCNY, New York, USA(2) LERMA-Observatoire de Paris, Paris, France(3) NASA-GISS, New York, USA(4) GFZ, Postdam, Germany(5) CESBIO, Toulouse, France(6) LSCE, Paris/ IRD, Brasilia/ LEGOS, Toulouse/ UCI, Irvine ….
Mail to: [email protected] [email protected]
Continental Surface Waters and their Roles
They play a crucial role in the global biochemical and hydrological cycles
The largest methane source (~ 20-40%), a powerful greenhouse gas The only CH4 source dominated by short-term climate variations
Important compartment of continental water storage, regulate the local river hydrology Part of the fresh water input in the ocean via river discharges Sources for recharching ground water supplies. Role in present sea level rise? Surface Water extent and storageis crucial to measureHowever: incomplete knowledge of seasonal and inter-annual variability at regional to global scales
What before SWOT?
We are currently trying to develop new methods which match with SWOT goals:
1) Multi-year global dataset of surface water extent using multi-satellite methods
2) Dataset of surface water volume change combining multi-satellite methods
First for specific area: Rio Negro, Ganges…
But with an ultimate goal to do so at global scale
Applications: - dynamic of surface water extent, roles in the water/energy cycle - evaluation of hydrological models/ input for hydrological models - methane emissions studies
Applications: - large scale hydrology, decomposition of GRACE components - contribution of continental water to sea level rise
1) Global surface water extent dynamic
1) Global surface water extent from multi-satellite method
Dynamic of surface water extent at global scale
Merging of satellite data with different wavelengths (surface classification, NN, vegetation)
Passive microwaveSSM/I emissivities at 19, 37 GHz, H and V polarizations
Active microwaveERS scatterometer backscattering coefficient at 5.25 GHz
Visible and near infraredAVHRR NDVI (visible and near-infrared reflectances)
[Prigent et al, 2001; Prigent et al, 2007Papa et al., 2006, 2007,2008]
Mean fractional surface water extent at annual maximum
Data mapped on equal-area grid with 0.25°x0.25° resolution at equator (773 km²)
Monthly resolution for 1993-2004 (soon 5 days)
and at least extended to 2012 and longer
%
Global and zonal temporal variations of inundated surfaces extent
Dynamic of surface water extent at global scale
Need of validation, comparison, evaluation of these results
Global results: maximum extent: ~6.7 million km², strong seasonal cycle and inter-annual variability
Deseasonalized anomalies: decrease of surface water extent especially over the Tropics
Surface water extent at global scale: the Amazon case study
SAR estimates(100m)
Multi-Satellites derived estimates(~25 km)
Good agreement between the SAR-derived estimates and the Multi-Satellites derived estimates
Some differences at higher and lower stage for small and large extents (<10%; >90%)
[Prigent et al, 2007, JGR]
But comparison only for 2 months in 1995-1996.
SWOT will provide direct comparisons over longer period and different environments
GPCC rain
Surface water extent
In-Situ River discharge
Surface water extent
River height from altimeter
In-situ river level height
Now with current altimeters and in-situ gauges, evaluation is possible only for few points over the Amazon. SWOT will provide more data to compare with and with much more details.
Surface water extent at global scale: the Amazon basin case study
Only 1 point of discharge available to us
Over the Tropics, comparison with the trend in the density of population 1990-2005 for coastal regions
South Mexico
Madras, India
Hanoi, Vietnam
Trend in surface water extent
Trend in the population density
Good spatial agreement between the decrease in SW extent and the increasein the density of population (this has been checked for other locations), at leastfrom 1990 to 2005
Surface water extent, the coastal regions case
The SWOT high spatial resolution will help better understand in details what we are currently observing on the coast at ~25km Interval
Global Surface water extent dynamic: high demand from the “methane” community
Wetlands are the bigger contributorsto the interannual variability in methane emissions
Since 1999, compensation between an increase in anthropogenic emission and a decrease in CH4 emissions from wetlands
CH4 emissions from wetlandsestimated from multi-sat. method
SWOT will help characterizing wetland dynamics for CH4 model emission
Bousquet et al, Nature, 2006
2) Surface water volume change
Surface water volume change
Using the surface water extent dataset to get surface water volume change
Surface water extent
GPCC rain
WGHM surface storage
GRACE total storage
Amazon basin
2003 2004 2005
-2
-1
0
1
2
3
Precipitation (GPCC)
Inundation area extentfrom multi-satellite approach
WGHM simulated surface storage
GRACE total water storage
Surface water volume change
Good agreement between GRACE, SWE, WGHM, altimeter river height
Test area Rio Negro basin (700 000 km²) for altimetry-based approach
Altimeter track (T/P)In situ gauge
stationAltimeter station
Surface water volume change
1) Surface water volumesby combination of inundation extent with water levels from altimetry
Surface water storage
17
Inundation map Bilinear interpolation
Water levels from Topex/Poseidon and ENVISAT RA-2 and in situ gauges data
Surface water volumesWater level maps
[Frappart et al., JGR, 2008]
2) Surface water volumesby combination of inundation extent with topographic data
Surface water storage
Surface water storage change: Rio Negro basin case study
Mean seasonal amplitudeof water storage change
DEMAlti.
WGHM
GRACE
When developed at global scale, this approachcould be an opportunity to evaluate SWOT products at regional/global scale
We could also construct 2 decades of surfacewater volume to complete backward the SWOTmeasurements
Surface water volume changefrom multi-sat/alti is ~ 38%of Grace total storage
Given what we are observing at large scale with the “crude” 25 km interval samplingsurface water extent dataset, SWOT will provide opportunities to better understand:
Why SWOT would be great:
Why surface water extent is declining at global scale and especially over the Tropics, at least from 1993 to 2005
The decrease in coastal regions thanks to its high resolution
The interannual variability in methane emissions (and trends?)
The up-coming surface water volume change at global scale will provide a dataset to compare with SWOT measurements at least at the large scale.