The use of remote sensing-derived water surface data for hydraulic model calibration

Domeneghetti, Alessio; Tarpanelli, Angelica; Brocca, Luca; Barbetta, Silvia; Castellarin, Attilio; Brath, Armando

doi:10.1016/j.rse.2014.04.007

Cited by 103 publications

(95 citation statements)

References 58 publications

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“…Moreover, applications of data from the wide-swath drifting orbit mission Surface Water Ocean Topography (SWOT) have been considered (for example Biancamaria et al, 2011aor Yoon et al, 2012, however only with synthetically generated data: the SWOT mission is ex-pected to be launched in 2020 (NASA, 2016). Calibration of hydrodynamic model parameters has been explored as well: Domeneghetti et al (2014) calibrated channel roughness for a part of the Po River using multi-year Envisat and ERS-2 altimetry data. Their work relied on the availability of cross-section surveys.…”

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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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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“…Integration of SAR data with models is an established technique for reducing uncertainty in model predictions, as it updates/calibrates the model states/parameters with observed data (e.g. Andreadis et al, 2007;Biancamaria et al, 2011b;Domeneghetti et al, 2014;Giustarini et al, 2011;Garcia-Pintado et al, 2013Hostache et al, 2009;Matgen et al, 2010;Mason et al, 2009Mason et al, , 2012Montanari et al, 2009;Tarpanelli et al, 2013;Yan et al, 2014), with the aim of improving flood forecasts. Naturally, calibration of these hydraulic models is essential for accurate results, and calibration studies to date have largely focused on roughness.…”

Section: Introductionmentioning

confidence: 99%

Calibration of channel depth and friction parameters in the LISFLOOD-FP hydraulic model using medium-resolution SAR data and identifiability techniques

Wood

Hostache

Neal

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. Single satellite synthetic aperture radar (SAR) data are now regularly used to estimate hydraulic model parameters such as channel roughness, depth and water slope. However, despite channel geometry being critical to the application of hydraulic models and poorly known a priori, it is not frequently the object of calibration. This paper presents a unique method to simultaneously calibrate the bankfull channel depth and channel roughness parameters within a 2-D LISFLOOD-FP hydraulic model using an archive of moderate-resolution (150 m) ENVISAT satellite SAR-derived flood extent maps and a binary performance measure for a 30 × 50 km domain covering the confluence of the rivers Severn and Avon in the UK. The unknown channel parameters are located by a novel technique utilising the information content and dynamic identifiability analysis (DY-NIA) (Wagener et al., 2003) of single and combinations of SAR flood extent maps to find the optimum satellite images for model calibration. Highest information content is found in those SAR flood maps acquired near the peak of the flood hydrograph, and improves when more images are combined. We found that model sensitivity to variation in channel depth is greater than for channel roughness and a successful calibration for depth could only be obtained when channel roughness values were confined to a plausible range. The calibrated reach-average channel depth was within 0.9 m (16 % error) of the equivalent value determined from river crosssection survey data, demonstrating that a series of moderateresolution SAR data can be used to successfully calibrate the depth parameters of a 2-D hydraulic model.

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“…To bridge this gap, multiple sources of information can be used, such as the existing reports or the historical flood extent maps, as an alternative approach to reconstruct an accurate representation of reality (Chau and Lee, 1991;Mark et al, 2014). Although satellite imagery was used for delineating flood extents and calibrating model parameters to simulate fluvial events (Di Baldassarre et al, 2009;Domeneghetti et al, 2014;Horritt, 2000;Mason et al, 2009;Matgen et al, 2004;Oberstadler et al, 1997), it is not feasible to implement such an approach for short-lived pluvial events. In another study, dendrogeomorphic evidence (i.e., scars on 5 trees) was used as benchmarks in roughness calibration (Ballesteros et al, 2011).…”

Section: Introductionmentioning

confidence: 99%