Monitoring of water level variations of
inundation areas within the Pantanal Wetland
Denise Dettmering, Christian Schwatke, Anne Braakmann-Folgmann, and Eva Börgens
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM)
email: [email protected]
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Motivation
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• Monitoring of water levels is essential for various applications, such as water resource management, disaster monitoring, …
• Monitoring of water levels in remote areas is difficult.
Satellite Altimetry is able to provide water level estimations on a global scale without ground access.
However, the temporal resolution is limited to some days or month depending on the satellite‘s orbit. The orbit also defines the spatial resolution.
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• Number of freely available in-situ gauging stations is declining since 1980.
• Station distribution is inhomogeneous.
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Satellite Altimetry – Measurement Principle
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water level =
satellite height – (corrected) range
WL = hsat - ralt
Ellipsoid
orbit
water surface
ralt
hsat
WL
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Challenges of Inland Altimetry
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Inundation areas are even more challenging than lakes and rivers due to irregular water coverage
• Altimeter footprint covers not only water but also land areas.
• This leads to land contamination of the radar echos (waveforms).
Combination of different altimeter missions in order to improve temporal and spatial resolution
Special data pre-processing necessary (retracking)
Rigorous outlier detection helpful
typical ocean returns land-contaminated returns
• Small waters and extreme events may be missed due to data resolution
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Study area: Pantanal
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Pantanal national park: about 15 000 km²
One of the largest wetlands worldwide; located in central South America
56.4 – 58° W
16.4 – 18° S
Landsat, April 2003
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Landscape
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http://ulab.cca.edu/wp-content/uploads/2012/10/pantanal-ponds1.jpg http://pompei-hotels.com/travel-and-architecture-design/Aerial-View-Of-Floodlands-In-Pantanal.jpg
http://www.unique-national-parks.com/uploads/O6/Xg/O6XgsYad6Rq2Ff_RIecV9A/Pantanal-floods.jpg http://gezimanya.com/sites/default/files/lokasyonResimleri/pantanal-a-maior-area-alagada-do-mundo.jpg
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Data Coverage
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56.4 – 58° W
16.4 – 18° S
Envisat (2002-2010)
Saral (2013-2015) repeats every 35 days
TOPEX (1992-2002)
Jason-1 (2002-2009) Jason-2 (2008-2015)
repeats every 10 days
• Separation of the area in small grid cells (0.1 by 0.1 degree)
106 out of 256 grid cells (~42%)
some are not usable due to topography: land or mountains
• Only part of the grid cells are covered by satellite observations
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Sample time series
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Grid cell: ID 504
longitude: 303.25°, latitude: -17.35°
Rio Sao Lourenco
Pass#37 of TOPEX/Jason-1/Jason-2
mean water level: 107.898 ± 0.518 m
mean formal error: 6.6 cm
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Validation
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Blue: altimetry
Green: in-situ (shifted)
RMSE: 27.2 cm R=0.9424
Offset=97m
Grid cell: ID 504
longitude: 303.25°, latitude: -17.35°
Rio Sao Lourenco
Pass#37 of TOPEX/Jason-1/Jason-2
In-situ gauging station within the grid cell (about 3 km from the center)
data from ANA*; starting mid 2005
* Agencia National de Aguas (http://ana.gov.br)
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Animation of water level variations
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Water level time series [m] 2008 – 2015
(mean value per time series subtracted)
no data for Envisat/Saral between Oct. 2010 and March 2013
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Fitting of annual signal - 3 examples
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Fitting an harmonic signal with fixed annual frequency in each time series
Clear annual period with
regular amplitude R = 0.9336
R = 0.8938
Clear annual period with
changing amplitude
R = 0.5154
Annual behavior hardly detectable;
only occasional flooding
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Fitting of annual signal - correlations
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correlation R between signal and annual fit
Annual signal is able to represent the signal for most parts of the area
Fitting an harmonic signal with fixed annual frequency in each time series
#106 grid cells covered by observations in the central part of the Pantanal national park
#82 grid cells with correlation coefficient R.>.0.7 (77%)
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Amplitude and Phases of annual signal
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estimated amplitudes [m] month of maximum water level
March
Feb.
April
May
June
June
June
June
June
82 grid cells in the central part of the Pantanal national park
only signals with correlation coefficient R > 0.7
Rio Paraguay
Rio Canabu Rio Sao Lourenco
Larger amplitudes in rivers and its surroundings
Shift of the water maximum from north to south
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Conclusions
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• Satellite Altimetry provides reliable water level time series for wetlands and can help to monitor remote areas in ungauged basins.
• Absolut physical heights with dm-accuracy are available for a maximum time period of more than 20 years (depending on satellite mission).
• Due to the sparse spatial resolution a complete acquisition/coverage of the Pantanal region is not possible
• Most of the area show clear annual signals with maximal amplitude of about 1.5 m.
• The month of maximum amplitude varies between March (North-East) and June (South-West).
• Water level time series from satellite altimetry for different inland water bodies are available via DAHITI.
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DAHITI
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• DGFI-TUM provides water level time series for inland water bodies via web interface
• Database for Hydrological Time Series of Inland Water (DAHITI)
• Easy access to about 260 inland water targets (lakes and rivers)
http://dahiti.dgfi.tum.de
