Coupling MODIS and Radar Altimetry Data for Discharge Estimation in Poorly Gauged River Basins

Tarpanelli, Angelica; Brocca, Luca; Barbetta, Silvia; Faruolo, Mariapia; Lacava, Teodosio

doi:10.1109/jstars.2014.2320582

Cited by 59 publications

(42 citation statements)

References 32 publications

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“…Still it has to be stressed that properties other than discharge and water level will not be represented realistically. Trigg et al (2009) had similar success with simplistic cross-section geometries: they introduced only marginal errors in water levels from a hydrodynamic model of the Amazon River when switching from surveyed cross sections to rectangular representations. However, for some rivers, it might be impossible to model the observed discharge-water-level relationships with such simplistic cross sections.…”

Section: Cross-section Calibrationmentioning

confidence: 92%

“…A good example for the focus of the hydrologic community on time series is the choice of Schwatke et al (2015) to merge satellite altimetry from missions with differing orbits into common virtual stations for their satellite altimetry database DAHITI. Another effort to obtain a densified altimetry dataset is the work by Tourian et al (2016): they merged multi-mission altimetry data over several rivers, linking the data between different virtual stations statistically and hydraulically, including data from CryoSat-2. The hydraulic link, however, is not a model but a simple time lag.…”

Section: Satellite Altimetry Over Riversmentioning

confidence: 99%

“…Other examples include other big rivers, such as the Mekong and Ob in the work of Birkinshaw et al (2014) where daily discharge data were estimated from Envisat and ERS-2 altimetry. A combination of MODIS data of river velocity and Envisat water levels was used by Tarpanelli et al (2015) to estimate discharge in the Po River. Becker et al (2014) used Envisat altimetry data to obtain a comprehensive dataset of water levels over the Congo Basin, a poorly gauged river system.…”

Section: Combining Satellite Altimetry With River Modelsmentioning

confidence: 99%

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Application of CryoSat-2 altimetry data for river analysis and modelling

Schneider¹,

Godiksen²,

Villadsen³

et al. 2016

Preprint

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Abstract. Availability of in situ river monitoring data, especially of data shared across boundaries, is decreasing, despite growing challenges for water resource management across the entire globe. This is especially valid for the case study of this work, the Brahmaputra basin in South Asia. Commonly, satellite altimeters are used in various ways to provide information about such river basins. Most missions provide virtual station time series of water levels at locations where their repeat orbits cross rivers. CryoSat-2 is equipped with a new type of altimeter, providing estimates of the actual ground location seen in the reflected signal. It also uses a drifting orbit, challenging conventional ways of processing altimetry data to river water levels and their incorporation in hydrologic-hydrodynamic models. However, CryoSat-2 altimetry data provides an unprecedentedly high spatial resolution. This paper suggests a procedure to i) filter CryoSat-2 observations over rivers to extract water level profiles along the river, and ii) use this information in combination with a hydrologic-hydrodynamic model to calibrate the simulated water levels at an accuracy that cannot be reached using information from globally available DEMs such as SRTM only. The filtering was done based on dynamic river masks extracted from Landsat imagery, providing high enough spatial and temporal resolution to map the braided river channels and their dynamic morphology. This allowed extraction of river water levels over previously unmonitored narrow stretches of the river. In the Assam Valley section of the Brahmaputra River, CryoSat-2 data and Envisat virtual station data were combined to calibrate water levels simulated by a 1D hydrodynamic model of the river. The hydrologic-hydrodynamic model used here is almost exclusively based on openly available remote sensing data and other global data sources providing an opportunity to achieve forecasts of both discharge and water levels in a poorly gauged river system.

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Section: Cross-section Calibrationmentioning

confidence: 92%

Section: Satellite Altimetry Over Riversmentioning

confidence: 99%

Section: Combining Satellite Altimetry With River Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Application of CryoSat-2 altimetry data for river analysis and modelling

Schneider¹,

Godiksen²,

Villadsen³

et al. 2016

Preprint

View full text Add to dashboard Cite

show abstract

Section: Combining Satellite Altimetry With River Modelsmentioning

confidence: 99%

Application of CryoSat-2 altimetry data for river analysis and modelling

Schneider

Godiksen

Villadsen

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Availability of in situ river monitoring data, especially of data shared across boundaries, is decreasing, despite growing challenges for water resource management across the entire globe. This is especially valid for the case study of this work, the Brahmaputra Basin in South Asia. Commonly, satellite altimeters are used in various ways to provide information about such river basins. Most missions provide virtual station time series of water levels at locations where their repeat orbits cross rivers. CryoSat-2 is equipped with a new type of altimeter, providing estimates of the actual ground location seen in the reflected signal. It also uses a drifting orbit, challenging conventional ways of processing altimetry data to river water levels and their incorporation in hydrologic-hydrodynamic models. However, CryoSat-2 altimetry data provides an unprecedentedly high spatial resolution. This paper suggests a procedure to (i) filter CryoSat-2 observations over rivers to extract water-level profiles along the river, and (ii) use this information in combination with a hydrologic-hydrodynamic model to fit the simulated water levels with an accuracy that cannot be reached using information from globally available digital elevation models (DEMs) such as from the Shuttle Radar Topography Mission (SRTM) only. The filtering was done based on dynamic river masks extracted from Landsat imagery, providing spatial and temporal resolutions high enough to map the braided river channels and their dynamic morphology. This allowed extraction of river water levels over previously unmonitored narrow stretches of the river. In the Assam Valley section of the Brahmaputra River, CryoSat-2 data and Envisat virtual station data were combined to calibrate cross sections in a 1-D hydrodynamic model of the river. The hydrologichydrodynamic model setup and calibration are almost exclusively based on openly available remote sensing data and other global data sources, ensuring transferability of the developed methods. They provide an opportunity to achieve forecasts of both discharge and water levels in a poorly gauged river system.

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“…Since the middle of the 1990's, satellite radar altimetry has been a successful technique for monitoring height variations of continental surface water, such as lakes and rivers (Morris and Gill 1994;Alsdorf et al 2001;Calmant et al 2008;Abarca-del-Rio et al 2012;Sima et al 2013;Yi et al 2013;Silva et al 2014;Pandey et al 2014;Tarpanelli et al 2015 and many others). The surface water level is measured within a terrestrial reference frame with repeatability varying from 10 to 35 days depending on the orbit cycle of the satellite.…”

mentioning

confidence: 99%

Lake Volume Monitoring from Space

Crétaux¹,

et al. 2016

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Lakes are integrators of environmental change occurring at both the regional and global scale. They present a wide range of behavior on a variety of timescales (cyclic and secular) depending on their morphology and climate conditions. Lakes play a crucial role in retaining and stocking water, and because of the significant global environmental changes occurring at several anthropocentric levels, the necessity to monitor all morphodynamic characteristics [e.g., water level, surface (water contour) and volume] has increased substantially. Satellite altimetry and imagery are now widely used together to calculate lake and reservoir water storage changes worldwide. However, strategies and algorithms to calculate these characteristics are not straightforward, and specific approaches need to be developed. We present a review of some of these methodologies by using lakes over the Tibetan Plateau to illustrate some critical aspects and issues (technical and scientific) linked to the observation of climate change impact on surface waters from remote sensing data. Many authors have measured water variation using the limited remote sensing measurements available over short time periods, even though the time series are probably too short to directly link these results with climate change. Indeed, there are many processes and factors, like the influence of lake morphology, that are beyond observation and are still uncertain. The time response for lakes to reach a new state of equilibrium is a key aspect that is often neglected in current literature. Observations over a long period of time, including maintaining a constellation of comprehensive and complementary satellite missions with service continuity over decades, are therefore necessary especially when the ground gauge network is too limited. In addition, the design of future satellite missions with new instrumental concepts (e.g., SAR, SARin, Ka band altimetry, Ka interferometry) will also be suitable for complete monitoring of continental waters.

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Coupling MODIS and Radar Altimetry Data for Discharge Estimation in Poorly Gauged River Basins

Cited by 59 publications

References 32 publications

Application of CryoSat-2 altimetry data for river analysis and modelling

Application of CryoSat-2 altimetry data for river analysis and modelling

Application of CryoSat-2 altimetry data for river analysis and modelling

Lake Volume Monitoring from Space

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