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27 Jul 2011IGARSS 2011 - session WE2.T10 1 Benefits of satellite altimetry for transboundary basins S. Biancamaria 1,2, F. Hossain 3, D. P. Lettenmaier.

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Presentation on theme: "27 Jul 2011IGARSS 2011 - session WE2.T10 1 Benefits of satellite altimetry for transboundary basins S. Biancamaria 1,2, F. Hossain 3, D. P. Lettenmaier."— Presentation transcript:

1 27 Jul 2011IGARSS 2011 - session WE2.T10 1 Benefits of satellite altimetry for transboundary basins S. Biancamaria 1,2, F. Hossain 3, D. P. Lettenmaier 4, N. Pourthié 2 and C. Lion 1,2 1 LEGOS, Toulouse, France 2 CNES, Toulouse, France 3 CEE, Tennessee Tech University, Cookeville, TN, USA 4 CEE, University of Washington, Seattle, WA, USA

2 Transboundary basins 256 river basins are shared among 2 or more countries (Wolf et al., 1999) = 45% land surfaces 27 Jul 2011IGARSS 2011 - session WE2.T10 2

3 Outline 27 Jul 2011IGARSS 2011 - session WE2.T10 3 1.Forecasting Brahmaputra/Ganges water elevations using satellite altimetry 2.Monitoring Indus reservoirs with SWOT

4 Brahmaputra and Ganges basins Brahmaputra: drainage area=574,000km 2 ; population=30 Millions; unmanaged. Ganges: drainage area=1,065,000km 2 ; population=500 Millions; 34 dams/diversions. 27 Jul 2011IGARSS 2011 - session WE2.T10 4 Bangladesh

5 Issue 90% of water flowing in Bangladesh comes from India. No India/Bangladesh real time data sharing. Using in-situ measurements at its border -> forecast in Bangladesh only with 2 or 3 days lead time. Study purpose: Use satellite-based water elevation upstream in India to forecast water elevation at the gauge locations (India/Bangladesh border). 27 Jul 2011IGARSS 2011 - session WE2.T10 5

6 Data used: in-situ measurements 27 Jul 2011IGARSS 2011 - session WE2.T10 6

7 Data used: satellite altimetry Topex/Poseidon (T/P) satellite altimeter. Overlap with in-situ: January 2000/August 2002. Data downloaded from HYDROWEB: http://www.legos.obs-mip.fr/en/soa/hydrologie/hydroweb/ http://www.legos.obs-mip.fr/en/soa/hydrologie/hydroweb/ 27 Jul 2011IGARSS 2011 - session WE2.T10 7 242_1 166_1 014_1 116_2 T/P Virtual station Distance from gage Mean time between obs. 242_1550 km14 days 166_1250 km16 days Mean time between obs. Distance from gage T/P Virtual station 12 days1560 km116_2 22 days530 km014_1

8 Methodology 1/2 Compute the cross-correlation between upstream T/P and in-situ measurements: 27 Jul 2011IGARSS 2011 - session WE2.T10 8 Water level Correlation TimeLead time 00 0.6 with k=lead time k 0.8 k Upstream: h alti (t) Downstream; h insitu (t)

9 Methodology 2/2 Compute scatter plot in-situ measurements & T/P measurements k days earlier. Use linear fit to forecast water level at gauge location from T/P measurements. 27 Jul 2011IGARSS 2011 - session WE2.T10 9 h in-situ (t) 0 h alti (t-k) Linear fit of h insitu (t)=f[h alti (t-k)] Water level 0 Time h insitu (downstream) k day lead time forecast

10 Results on the Brahmaputra 5-day lead time Forecasts: 27 Jul 2011IGARSS 2011 - session WE2.T10 10 T/P virtual station 250 km upstream:T/P virtual station 550 km upstream: 5-day forecast RMSE ~ 0.5 m Brahmaputra water elevation 5 4 3 2 1 0 -2 -3 2000 2001 2002 Water elevation (m) Brahmaputra water elevation 5 4 3 2 1 0 -2 -3 2000 2001 2002 Water elevation (m) In-situ T/P forecast Legend:

11 Results on the Ganges 27 Jul 2011IGARSS 2011 - session WE2.T10 11 10-day lead time forecast: T/P virtual station 530 km upstream: 5-day forecast RMSE ~ 0.6 m Ganges water elevation 6 4 2 0 -2 -4 2001 2001.42001.8 Water elevation (m) 10-day forecast RMSE ~ 0.9 m Ganges water elevation 6 4 2 0 -2 -4 2001 2001.42001.8 Water elevation (m) T/P virtual station 1560 km upstream: 5-day lead time forecast: In-situ T/P forecast Legend:

12 SWOT and the Brahmaputra/Ganges 27 Jul 2011IGARSS 2011 - session WE2.T10 12 SWOT = Water mask + water elevation (and river slope) with 2 or more observations per 22 days

13 Expected benefits from SWOT Higher precision on measurements -> better forecasts. More observations on the basin -> better time sampling. Water extent will improve inundation forecast: 27 Jul 2011IGARSS 2011 - session WE2.T10 13 Brahmaputra water elevation 5 4 3 2 1 0 -2 -3 2000 2001 2002 Water elevation (m) Brahmaputra water elevation Discharge (10 4 m 3.S -1 ) 7654321076543210 2000 2001 2002

14 Conclusion for Brahmaputra/Ganges Forecasting water elevation from nadir altimeters with lead time between 5 day and 10 day. Expected improvement from SWOT due to water elev. + extent, better accuracy, global observation. Fore more details: Biancamaria et al., GRL, 38, L11401, “Forecasting transboundary river water elevations from space” (June 2011). 27 Jul 2011IGARSS 2011 - session WE2.T10 14

15 Outline 27 Jul 2011IGARSS 2011 - session WE2.T10 15 1.Forecasting Brahmaputra/Ganges water elevations using satellite altimetry 2.Monitoring Indus reservoirs with SWOT

16 SWOT and world lakes/reservoirs 27 Jul 2011IGARSS 2011 - session WE2.T10 16 2 4 6 8 10 SWOT visits per repeat cycle 3 2.5 2 1.5 1 0.5 0 Surface area seen (10 6 km 2 )

17 Indus reservoirs 27 Jul 2011IGARSS 2011 - session WE2.T10 17 Indus basin=1.14x10 6 km 2, 53% to Pakistan, 34% to India. 2008 filling of Baglihar reservoir by India. 2009 construction of Kishenganga dam. -> Lack of information = difficulties in downstream water management

18 SWOT and Indus reservoirs 27 Jul 2011IGARSS 2011 - session WE2.T10 18 Reservoirs are seen between 2 to 3 times per 22 days

19 Baglihar dam 27 Jul 2011IGARSS 2011 - session WE2.T10 19 Baglihar dam: 450 MW Run-of-river type – Pondage volume = 37.5 x 10 6 m 3 – Full pondage level – dead storage level = 5 m -> Pondage area > 1 km 2 5 m 37.5x10 6 m 3 SWOT requirements on lakes and reservoirs = 10 cm error on 1 km 2 area. -> SWOT should be able to observe Baglihar dam

20 Baglihar dam 27 Jul 2011IGARSS 2011 - session WE2.T10 20 Reservoir in mountainous region = SWOT might be affected by layover. Layover=geometric distortion when radar beam reaches top of a tall feature before it reaches the base. Layover modeled by SARVisor for ALOS/PalSAR, 7° incidence angle (yellow=layover): Baglihar Ascending track:Descending track:

21 Kishenganga project 330 MW hydro-power plant. Layover modeled by SARVisor for ALOS/PalSAR, 7° incidence angle (yellow=layover): 27 Jul 2011IGARSS 2011 - session WE2.T10 21 Kishenganga Ascending track:Descending track: Kishenganga

22 Conclusion for Indus reservoirs 27 Jul 2011IGARSS 2011 - session WE2.T10 22 Hydro-electric reservoirs are needed to respond to the growing demand on electricity. Water management for downstream country is more difficult. Huge potential of SWOT to provide reservoir water volume changes Ongoing study to characterize layover on SWOT data and better quantifying SWOT accuracy and time sampling.

23 Thank you for your attention 27 Jul 2011IGARSS 2011 - session WE2.T10 23

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