Daily discharge estimation at ungauged river sites using remote sensing

Birkinshaw, Stephen; Moore, P. A.; Kilsby, C. G.; O’Donnell, Greg; Hardy, Andrew; Berry, P. A. M.

doi:10.1002/hyp.9647

Cited by 92 publications

(70 citation statements)

References 41 publications

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“…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.…”

Section: Combining Satellite Altimetry With River Modelsmentioning

confidence: 99%

“…This river mask was extracted from Landsat 7 and Landsat 8 NDVI imagery. Landsat imagery has been used repeatedly as a more finely resolved alternative to the global water masks discussed above: see for example the use with Envisat data over the Zambezi river by Michailovsky et al (2012), with Envisat and ERS-2 data over the Mekong and Ob rivers by Birkinshaw et al (2014), or the work by O'Loughlin et al (2013) using river widths, etc., extracted from Landsat NDVI imagery for a hydraulic characterization of the Congo River.…”

Section: Filtering Of Cryosat-2 Data -River Maskmentioning

confidence: 99%

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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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Section: Combining Satellite Altimetry With River Modelsmentioning

confidence: 99%

Section: Filtering Of Cryosat-2 Data -River Maskmentioning

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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“…Few studies dedicated to a thorough assessment of the radar altimetry over rivers, such as Ob, Mekong, Negro, Gange and Brahmaputra, even without comparisons with in situ gauges, have been published [7,[20][21][22][23][24][25]. The accuracy of altimeter water level time series over river and floodplains has been discussed in several previously published papers (i.e., [14,15,26]).…”

Section: Introductionmentioning

confidence: 99%

“…For example, Birkinshaw et al [25] found the water level corresponding to zero flow, inverting the empirical formula of Bjerklie et al [27] and assigning a discharge value obtained from another measured location on the same river on the basis of the catchment areas. In order to apply these empirical formulas relating the river discharge and different hydraulic variables, the involved coefficients have to be estimated a priori on the basis of a robust database of channel hydraulic information and discharge measurements [25,27]. Alternatively, Getirana et al [22] used modeled discharge from a distributed rainfall-runoff model to estimate the river bed depth and the discharge at the same time.…”

Section: Introductionmentioning

confidence: 99%

River Discharge Estimation by Using Altimetry Data and Simplified Flood Routing Modeling

et al. 2013

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A methodology to estimate the discharge along rivers, even poorly gauged ones, taking advantage of water level measurements derived from satellite altimetry is proposed. The procedure is based on the application of the Rating Curve Model (RCM), a simple method allowing for the estimation of the flow conditions in a river section using only water levels recorded at that site and the discharges observed at another upstream section. The European Remote-Sensing Satellite 2, ERS-2, and the Environmental Satellite, ENVISAT, altimetry data are used to provide time series of water levels needed for the application of RCM. In order to evaluate the usefulness of the approach, the results are compared with the ones obtained by applying an empirical formula that allows discharge estimation from remotely sensed hydraulic information. To test the proposed procedure, the 236 km-reach of the Po River is investigated, for which five in situ stations and four satellite tracks are available. Results show that RCM is able to appropriately represent the discharge, and its performance is better than the empirical formula, although this latter does not require upstream hydrometric data. Given its simple formal structure, the proposed approach can be conveniently utilized in ungauged sites where only the survey of the cross-section is needed.

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“…Encontraron que los flujos de salida calculados con el primero de ellos eran de alrededor del 65% (Contas) y 95% (Jaguaribe) más bajos que los calculados con ADP, subestimando el balance neto de agua en ambos sistemas. Por otro lado, el uso de métodos remotos para medir el nivel del agua, el ancho o la pendiente de un curso acuoso con el fin de determinar la descarga, genera considerable interés especialmente cuando las mediciones en el terreno no son posibles [24].…”

Section: Introductionunclassified