SWOT mission,
expectation for Tropical hydrology
Stéphane CALMANT & Frédérique SEYLER
Columbus, Ohio, 15-17 Sept 2008
Tropical basins: large (transboundary) braided rivers, changing beds with floodplains and wetlands
In practice, impossible to monitor by usual meansSWOT: catch every water body
1984 1991
1993
0 7 km
SWOT: full coverage mapping of changes in river course
Rivers change course with time…
Low waters
High waters
SWOT: inundated surfaces
Floodplain under forestHuge volume xLow velocity River discharge
2 km
Bonnet, M.P, et al. Floodplain hydrology in an Amazon floodplain lake (Lago Grande de Curuaí) Journal of Hydrology
Flood plain dynamics
44,5
55,5
66,5
77,5
88,5
99,510
10,511
11,5
0 10 20 30 40 50
varzea
mainstream
4
5
6
7
8
9
10
11
12
0 0,5 1 1,5 2 2,5
01/10/2005
18/06/2005
05/03/2005
19/11/2004
Flood peak
Flood fall
Flood increase
Low water
V MS
V= Varzea
MS= Main Stream
Floodplain vs main stem
Drawbacks of
conventional nadir altimetry
ENVISAT :hookingFor small rivers
SWOT: direct measurements
Leakage/hooking over temporarily islets
SWOT: no off-nadir ranges ?
025050075050
75
100
125
150
Distance from outlet (km)
Geo
id a
ltit
ud
of
zero
flo
w (
m)
Profile from national chart
Profile by sat altimetry
Caqueta River, Colombia
SWOT: High resolution of river altitude profile
FARCs Guerilla
VB
2.5 5.0 7.5 10.0
2490
4490
6490
8490
10490
H-z (m )
Dis
char
ge
(m3/
s)
Stage-discharge relationship: rating curve at virtual gauges
Leon, J.G., et al. Preliminary estimations of discharges in the Rio Negro basin by the flow routing model proGUM using altimetricspatial data. In revision
SWOT: will improve the time and space sampling frequency to input in the modelling schemes
Drawbacks of Gauges:
SWOT will provide Complementary information
Data of in situ gauges in international databases(exp Global Runoff Data Center)
Global Runoff Data Center
Date de fin des mesures●<1980●1980-1984●1985-1990●1990-1994●1995-2000●2000-2004●<2004
1900 2007
Number of active stations
1980
NEED FOR A RAPIDE, UNRESTRICTED DISTRIBUTION OF THE SWOT DATA
Which height variations?
Gauge is local
SWOT: cross bed slope variations
ANA: Hydrologic network optimization
CNPq –UFAM: Sediment transport models
CNPq – UnB: Floodplain processes and models
ELECTRONORTE: Balbina dam
CPRM : Extreme events management and prevision, underground water quality, fluvial geodynamics
Long Term
AMESD (African Monitoring of the Environment for Sustainable Development ): Congo-Oubangui-Sangha Basin management
Future:
ACTO - FFEM : Integrated and sustainable water management - AGIRE
Madeira dams project
SWOT will provide a full detection of the –now unmonitored- extent and level of each body in the complex river-wetland-inundated areas systems that are characteristic of tropical basins, without harming the temporal sampling, contrarily to conventional nadir altimetry.